Animal Behaviour: Evolution and Mechanisms
Peter Kappeler (Ed.)
Animal Behaviour: Evolution and Mechanisms
123
Prof. Dr. Peter Kappeler University of Göttingen Dept. of Sociobiology/Anthropology & CRC Evolution of Social Behavior & German Primate Center Behavioral Ecology & Sociobiology Unit Kellnerweg 6 37077 Göttingen Germany
[email protected] ISBN 978-3-642-02623-2 e-ISBN 978-3-642-02624-9 DOI 10.1007/978-3-642-02624-9 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2010922317 c 2010 Springer-Verlag Berlin Heidelberg This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Typesetting: Data supplied by the author Cover Design: WMX Design GmbH, Heidelberg Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Preface
The study of animal behaviour has become one of the fastest growing biological disciplines in recent decades. This development can be easily inferred, for example, from the steady increase in the total number of publications on any aspect of animal behaviour, in particular also in journals with a more general readership (e.g. Nature, Proceedings of the Royal Society or Current Biology), the ever-increasing number of participants at international conferences (e.g. IEC or ISBE), and from the growing numbers of students choosing courses in this field. This development has several causes, of which I find three particularly compelling. First, it is increasingly being appreciated that behaviour is the crucial level at which an individual’s genotype and phenotype interface with the environment. Recognising behaviour as the main mechanism animals employ to ascertain their homeostasis, growth, survival and reproduction therefore provides a deep understanding of organismal integration and adaptation. Second, the astonishing success of the study of animal behaviour also has importantly to do with the intellectual flexibility and methodological inter-disciplinarity required for comprehensive analyses of behaviour. Today, students of behaviour are jacks-of-all-trades; importing, applying and improving methods from many neighbouring disciplines, such as molecular genetics, physiology or micro-electronics, as well as concepts and theories from less obvious sources, such as economics or sociology, for example. Finally, Charles Darwin’s theory of natural and sexual selection provide the study of animal behaviour with a powerful and firm theoretical framework that many closely-related disciplines (e.g. neurobiology) are lacking. This increase in the number of studies published in a growing number of ever more specialised journals and the application of new concepts, methods and technologies also has frustrating consequences, however. Except perhaps for a few exceptional colleagues, no one today is really able to develop and maintain an active research programme and to read all interesting and important publications and books that appear every month. We are increasingly forced to specialise and to restrict our attention to a few topics or taxa, despite a much larger intellectual curiosity. Most readers with a PhD will be familiar with these constraints set by increasing administrative loads, constantly changing teaching obligations as well as new types of
VI
Preface
expectations of our employers about our publication and grant acquisition records. This tendency to specialise backfires, however, when new generations of students need to be introduced comprehensively to all aspects of the study of animal behaviour, when they ask for background information to pursue their own personal curiosity, or when they ask great questions in a lecture course or seminar. One solution to this problem is to identify a useful introductory text or up-to-date review. In practice, however, textbooks tend to focus more on general principles than on current research, and reviews are typically written for specialists, and are, hence, of limited use if you want to keep abreast the literature in a broader field. A collection of authoritative reviews written by active leaders in their respective fields can fill this gap if they specifically address a non-specialist readership (i.e. not the closest peers), summarise and explain recent developments, and if they provide a forward-looking perspective for interested students as well as their closer colleagues. In 1978, John Krebs and Nick Davies began providing just this type of guidance for the then latest and fastest-growing field of animal behaviour: behavioural ecology. Their subsequent four edited volumes have informed and influenced several generations of students and academic mentors alike by providing a useful and stimulating basis for graduate seminars, a competent source of reference for non-specialists as well as a source of inspiration for newcomers and experts alike. The study of animal behaviour has made enormous leaps forward since the publication of the last Krebs and Davies volume in 1997 (Blackwell). Others have also sensed the void left by the non-continuation of their series (Danchin et al. 2008: ‘Behavioural Ecology’ Oxford University Press; Westneat and Fox 2010: ‘Evolutionary Behavioral Ecology’ Oxford University Press), but the field has become so wide that no single volume can do justice to the existing diversity of behavioural research projects any more. A recent trend among volumes of this kind appears to have been the concentration on a regional (i.e. either francophone or anglo-american) set of peers and their work; perhaps because they share certain preferred formats for teaching. The current volume attempts to fill a similar niche by featuring the state of the art in the study of animal behaviour in central continental Europe, where ethology has its deepest roots. In addition, because of space limitations, the contributions to this volume only represent a subset of current major research topics, but cover all recent international developments. For historical reasons, ethologist in German-speaking countries have mainly been interested in mechanisms, but the number of researchers embracing ultimate questions has been growing steadily. The title of this volume was therefore chosen to reflect this development. However, all authors were requested to address both ultimate and proxi-
Preface
VII
mate aspects in the presentation of their respective topics, and some chapters also deal with one or both of Tinbergen’s other questions. The contributions to this volume are organised into four broad sections. Note, however, that several chapters would also fit comfortably under a different header, as indicated by numerous cross-references among chapters. Communication and cognition continue to be central topics in the study of animal behaviour. In chapter 1, Martin Schaefer reviews evolutionary and functional aspects of visual communication. He emphasises the fact that visual signals not only play important roles in several functional domains of animals, but also in the communication between plants and animals. Using examples from both areas, he discusses models of signal design and evolution, concluding that environmental and other ecological factors need to be considered explicitly for a more comprehensive understanding of communication systems. Claudia Fichtel and Marta Manser deal with vocal communication in chapter 2. They focus on communication beyond the traditional senderreceiver paradigm and argue forcefully that bystanders also perceive vocal signals exchanged among members of social groups. This point is underscored by their review of empirical studies on audience effects and eavesdropping. Furthermore, group coordination provides a particular context, where individuals have to address several or all members of their social unit simultaneously, and where the traditional dyadic communication model fails. This review should therefore inspire much exciting new research on communication from a network perspective. In chapter 3, Dustin Penn and Joachim Frommen address kin recognition as a functionally important aspect of social and sexual behaviour. Following a much-needed conceptual clarification of the main concepts, they focus on the various mechanisms and signals involved in the recognition of kin. They also discuss central theoretical aspects in the evolution of kin recognition mechanisms as well as their genetic underpinnings and consequences. Their contribution concludes with a forward-looking perspective, identifying main problems and areas of kin recognition research requiring further work. In chapter 4, Mario Pahl, Jürgen Tautz and Shaowu Zhang use the honeybee as a model system to illustrate the fascinating sensory and cognitive abilities of animals with small nervous systems. They introduce the honeybee’s sensory world and summarise experimental work on their various cognitive abilities, including categorisation, rule learning and contextdependent learning. These sometimes stunning abilities provide instructive examples of how domain-specific cognitive faculties are linked to the specific ecological and social challenges these social insects face.
VIII
Preface
In the final chapter of this section, Kurt Kotrschal, Isabella Scheiber and Katharina Hirschenhauser use the highly-structured societies of greylag geese to provide a fascinating comparative perspective on social cognition. These geese show striking convergence in several fundamental features of their social systems with many mammals, including a femalebonded clan structure and elaborate patterns of mutual social support. Mates paired for life form the basic social units in this species and they exhibit stunning hormonal synchrony. They contribute to social stability through a particular pattern of social support that is reminiscent of some other vertebrate societies with individualised long-term relationships. Contributions to the second part revolve around the two central problems facing members of animal societies: conflict and cooperation. In chapter 6, Jürgen Heinze reviews sources of conflict and conflict resolution in social insect societies. Long regarded as harmonious superorganisms, societies of eusocial animals have only recently been recognised as harbouring internal strife as well. Using the queen-worker conflict about sex allocation and the struggle for dominance as examples, Heinze illustrates the sources and nature of such conflicts and reviews the behavioural mechanisms used to minimise or to resolve them. The important role played by inclusive fitness considerations in these conflicts highlights the interaction between ultimate and proximate factors in this context. In chapter 7, Judith Korb turns to cooperation with social insect societies as an evolutionary puzzle. Her review illuminates how relatedness and mechanisms that make cheating costly act in concert to minimise cheating and to stabilise cooperation. She goes on to show that similar mechanisms favour cooperation at other levels of biological organisation and advocates the use of a multilevel selection approach to study this and other evolutionary problems at all levels of the biological hierarchy. The subsequent chapter by Redouan Bshary is concerned with another extreme: cooperation among unrelated individuals. He introduces game theory as a particularly powerful and biologically satisfying approach to studying the problem of cooperation because it can explicitly deal with the many contingencies of real life. Using the well-studied example of marine cleaning mutualism between members of different species, he goes on to show how this approach is both necessary and useful in explaining cooperation. The tragedy of the commons provides another example where this approach might be fruitfully applied. In chapter 9, Gerald Kerth looks at group-decision making as a particular example of group-level cooperation that is potentially hampered by inter-individual conflict. How animals reconcile the potentially conflicting demands of group performance and individual interests has been subject to much recent modelling. A concise review of these models is combined
Preface
IX
with the results of empirical studies, including Kerth’s studies of Bechstein bat societies, to identify fundamental rules in animal groups of varying complexity and composition. The specific suggestions for future research in this field offered by Kerth will promote a more comprehensive approach towards studying group-decisions by incorporating additional intrinsic and social variables known to shape other aspects of social behaviour. In the final contribution to this section, Fritz Trillmich reviews the scope for cooperation and conflict in the context of parental care. Successful reproduction is often jeopardised by conflicts between mates, between parents and offspring, and among siblings. Using primarily examples from mammals, where some of these conflicts are particularly pronounced, Trillmich uses Tinbergen’s four questions to examine the nature and causes of these conflicts, the leeway for cooperation as well as the mechanisms modulating parental care. His chapter provides yet another example of the benefits of addressing a particular problem from all four perspectives, demonstrating in this case how consideration of all levels contributes to a much richer understanding of a complex problem. The third part of this volume revolves around problems of sex and reproduction. Chapter 11 by Wolf Blanckenhorn provides a broad opening perspective on these topics by outlining formal approaches to the study of sexual and natural selection, both in the wild and in the laboratory. He emphasises the benefits of using standardised selection measures in achieving a comprehensive picture of both proximate and ultimate explanations of a particular phenomenon. His illustration of how to obtain these measures from a variety of sources and how to use them in meta-analyses should facilitate and encourage a much wider use of this approach in the study of behaviour. Chapter 12 by Nils Anthes reminds most of us that sexual conflict and other sexual behaviours are not limited to the all too familiar separate-sex animals. In simultaneous hermaphrodites, male and female reproductive functions reside within the same body, providing an interesting twist for the study of sexual strategies. Anthes reviews a growing body of literature on hermaphrodites from an array of taxa that reveals fascinating evidence for the occurrence of mate choice, sexual conflict and post-copulatory selection in these animals. How hermaphrodites reconcile their intrinsic conflicts between their male and female function provides another prime example for organismal fine-tuning in face of fundamental problems, such as successful reproduction. Bart Kempenaers and Emmi Schlicht deal with an intuitively much more familiar problem in chapter 13: the optimisation of reproductive success through extra-pair behaviour in pair-living species. Focussing on a vast literature on birds, these authors first explore sources of variation in extra-
X
Preface
pair behaviour among species and populations. As extra-pair copulations in pair-living species constitute a puzzle for evolutionary biologists, they examine the associated potential costs and benefits from the perspectives of both sexes, identifying effects in the expected direction, i.e. males can increase offspring number and females offspring quality through extra-pair activities. Kempenaers and Schlicht also explore hitherto neglected aspects of extra-pair behaviour by illuminating its effects on the strength of sexual selection. In chapter 14, Bernhard Kraus and Robin Moritz focus on the polyandrous mating behaviour of social hymenoptera. The mating of hymenopteran queens with multiple males is of fundamental importance for these animals because of its genetic consequences for their societies where conflict and cooperation are so finely tuned to prevailing relatedness patterns. The authors review all major hypotheses proposed to explain the evolution of polyandry and subsequently explore the consequences of genetic variation for the social organisation of colonies. Using the honeybee as one of the best-studied model systems for these problems, they illustrate how genetic analyses have revolutionised our understanding of social insect societies. In chapter 15, Jutta Schneider and Lutz Frommhage provide an additional challenge to conventional sex roles by dissecting the mating strategies of male spiders that invest heavily in paternity enhancement with one (or very few) female(s), rather than trying to maximise access to many females. A small group of spiders is characterised by such exceptional males, and therefore provides an instructive example to reflect on traditional sex roles and any sex-specific rules that have emerged from studies of more ‘normal’ animals. The authors outline the fascinating diversity of mating strategies among spiders and explain how aspects of their genital morphology ultimately influence female (cannibalism) and male (monogyny) reproductive strategies. In the last chapter of this part, Wolfgang Goymann and Heribert Hofer use the theme of this volume to examine the relationships and interactions among mating systems, social behaviour and hormones. They show that testosterone is an important proximate factor involved in the regulation of different mating systems across species and that it also influences individual mating decisions in some species. Additional hormones (oxytocin and arginine vasopressin) are involved in pair-bond formation and the expression of different mating systems; in one particularly well-studied case, changes in one hormone receptor gene have been shown to elicit a cascade of massive changes in social behaviour. A key conclusion of this chapter resounds the title of this volume: proximate and ultimate aspects of a particular behavioural phenomenon are best studied in combination.
Preface
XI
Contributions to the final section of this volume deal with various aspects of behavioural variation. In chapter 17, Norbert Sachser and Sylvia Kaiser focus on the development of behavioural variation among and within individuals. First, they examine the role of genetic polymorphism and gene-environment interactions in generating individual variation in behavioural traits. In the second part of their chapter, Sachser and Kaiser summarise our current knowledge about the modulation of behavioural development by social factors. Focussing on mammals and proximate mechanisms, they show how the social environment of a pregnant female affects her offspring’s behaviour later in life, and how variation in social influences produces lasting effects on the behaviour of a developing individual throughout adolescence. As argued by the authors, such variability appears advantageous from an evolutionary perspective, as individuals are rapidly adapted to prevailing social environments. In chapter 18, Michael Taborsky and Jane Brockmann focus on alternative reproductive tactics as widespread and diverse adaptations in the struggle for successful reproduction that also represent a form of behavioural variation. They examine alternative reproductive tactics from the perspective of different allocation decisions in response to trade-offs in reproduction or life history optima. They summarise the known diversity of alternative reproductive tactics, describe the proximate mechanisms underlying them and discuss the evolutionary consequences of their coexistence. This phenomenon provides a compelling example for both the sensitivity of sexual selection towards exploiting any possibility for achieving reproductive success, as well as for the organismal integration required to build and sustain different prototypes of the same sex and species. In recent years, inter-individual variation in behaviour has received much attention. In chapter 19, Ralph Bergmüller reviews these new developments, detailing both, evolutionary and proximate aspects. He first provides a welcome discussion of terms, concepts and definitions before looking at the two sides of the animal personality coin: constraint and flexibility. This research topic also provides a good opportunity to illuminate the genetic bases of various behavioural traits, and Bergmüller summarises our current understanding of these and other proximate mechanisms. Consistent individual differences also provide a unique opportunity to study behavioural development as well as the fitness consequences of any differences. The author’s up-to-date summary of all these aspects provides useful orientation in a new and rapidly growing field of research, and it contains plenty of suggestions for interesting future research projects for those entering this field. Behavioural variation is not only rampant among individuals, but also among populations. In chapter 20, Carel van Schaik focuses on social
XII
Preface
learning as a ubiquitous mechanism contributing to this variation. He reviews and defines the various forms of social learning and analyses their social and cognitive preconditions. Social transmission of novel skills or behaviours can lead to cultural differentiation among populations of the same species, and van Schaik reviews the known examples of animal cultures in the second part of his chapter. His analysis indicates that animal cultures may be much more widespread, but the sophistication found in our own species remains unparalleled in nature. His chapter may well provide a basis for a much-needed general theory of animal culture. In the final chapter of this volume, Peter Kappeler and Cornelia Kraus provide an extensive overview of levels and causes of behavioural variability. They begin by reviewing the paradigm shifts that the study of behavioural variation has experienced since the early days of ethology. They go on to explore the different hierarchical levels of behavioural variation above the species level, within species, among individuals and within individuals over time and highlight the most important mechanisms constraining, maintaining or generating behavioural variability. One important conclusion emerging from this overview is that phylogenetic constraints on behaviour are surprisingly pervasive, even in species with higher cognitive abilities.
Acknowledgements I wish to thank a number of people for their contribution to this volume. First, the authors of the chapters of this volume have been extremely cooperative and disciplined. Because the importance of contributions to edited volumes cannot (easily) be assessed through ‘impact factors’, writing book chapters has gravitated towards the lower end of everyone’s professional priority list. However, the contributors to this volume have given this project top priority; having written and revised their chapters within just 8 months. In addition, most authors also peer-reviewed at least one other chapter. I thank all of them for making this project possible and for keeping it on schedule. I am equally grateful to the external experts who improved the quality of every single chapter with their constructive comments. Because reviewing a chapter for an obscure book project is even lower on anybody’s priority list, I want to sincerely thank the following colleagues for their professional altruism: Elizabeth Adkins-Regan, Theo Bakker, Tim Birkhead, Dan Blumstein, Jacobus Boomsma, Lars Chittka, James Curley, Melanie Dammhahn, Mark Elgar, Matthew Grober, Rachel Kendal, Eric Keverne, Peter Klopfer, Hannah Kokko, Rolf Kuemmerli,
Preface
XIII
Janet Leonard, Randolf Menzel, Nico Michiels, Doug Mock, Allen Moore, Bryan Neff, Kees van Oers, Carsten Schradin, Thomas Seeley, Dirk Semmann, Lotta Sundström, Zuleyma Tang-Martinez, David Westneat, Andrew Whiten and four anonymous referees. My sincere thanks are due to Stefanie Wolf, my editor at Springer Verlag, for her support of this project from the beginning, for her help with administrative matters, and for her patience and understanding. Finally, words are not enough to acknowledge the crucial role of Ulrike Walbaum in the production of this volume. She single-handedly formatted all texts, re-drew most figures and double-checked every single reference. Thank you Ulli – this book is really your ‘second baby’! Göttingen, January 2010
Peter Kappeler
Contents
Part I Communication and cognition Chapter 1 Visual communication: evolution, ecology, and functional mechanisms .......................................... 3 H. MARTIN SCHAEFER Chapter 2 Vocal communication in social groups...................................................... 29 CLAUDIA FICHTEL AND MARTA MANSER Chapter 3 Kin recognition: an overview of conceptual issues, mechanisms and evolutionary theory .................................................................................... 55 DUSTIN J. PENN AND JOACHIM G. FROMMEN Chapter 4 Honeybee cognition ................................................................................... 87 MARIO PAHL, JÜRGEN TAUTZ AND SHAOWU ZHANG Chapter 5 Individual performance in complex social systems: the greylag goose example....................................................................... 121 KURT KOTRSCHAL, ISABELLA B.R. SCHEIBER AND KATHARINA HIRSCHENHAUSER Part II Conflict and cooperation Chapter 6 Conflict and conflict resolution in social insects ..................................... 151 JÜRGEN HEINZE
XVI
Contents
Chapter 7 Social insects, major evolutionary transitions and multilevel selection .. 179 JUDITH KORB Chapter 8 Cooperation between unrelated individuals – a game theoretic approach ....................................................................... 213 REDOUAN BSHARY Chapter 9 Group decision-making in animal societies............................................. 241 GERALD KERTH Chapter 10 Parental care: adjustments to conflict and cooperation............................ 267 FRITZ TRILLMICH Part III Sex and reproduction Chapter 11 The quantitative study of sexual and natural selection in the wild and in the laboratory .............................................................. 301 WOLF BLANCKENHORN Chapter 12 Mate choice and reproductive conflict in simultaneous hermaphrodites ........................................................................................ 329 NILS ANTHES Chapter 13 Extra-pair behaviour ................................................................................ 359 BART KEMPENAERS AND EMMI SCHLICHT Chapter 14 Extreme polyandry in social Hymenoptera: evolutionary causes and consequences for colony organisation.............. 413 F. BERNHARD KRAUS AND ROBIN F.A. MORITZ
Contents
XVII
Chapter 15 Monogynous mating strategies in spiders................................................ 441 JUTTA SCHNEIDER AND LUTZ FROMHAGE Chapter 16 Mating systems, social behaviour and hormones .................................... 465 WOLFGANG GOYMANN AND HERIBERT HOFER Part IV Behavioural variation Chapter 17 The social modulation of behavioural development ................................ 505 NORBERT SACHSER AND SYLVIA KAISER Chapter 18 Alternative reproductive tactics and life history phenotypes................... 537 MICHAEL TABORSKY AND H. JANE BROCKMANN Chapter 19 Animal personality and behavioural syndromes...................................... 587 RALPH BERGMÜLLER Chapter 20 Social learning and culture in animals ..................................................... 623 CAREL P. VAN SCHAIK Chapter 21 Levels and mechanisms of behavioural variability.................................. 655 PETER M. KAPPELER AND CORNELIA KRAUS Index ........................................................................................................ 685
Contributors
NILS ANTHES Animal Evolutionary Ecology Institute for Evolution and Ecology University of Tübingen, D
[email protected] CLAUDIA FICHTEL Dept. of Behavioral Ecology and Sociobiology German Primate Center (DPZ) Göttingen, D
[email protected] RALPH BERGMÜLLER Eco-Ethologie University of Neuchâtel Neuchàtel, CH
[email protected] LUTZ FROMHAGE Group Behavioural Biology Biocenter Grindel University of Hamburg Hamburg, D
[email protected] WOLF BLANCKENHORN Institute of Evolutionary Biology and Environmental Studies University of Zürich-Irchel Zürich, CH
[email protected] H. JANE BROCKMANN Dept. of Biology University of Florida Gainesville, USA
[email protected] REDOUAN BSHARY Eco-Ethologie Institut de Biologie Université de Neuchâtel Neuchâtel, CH
[email protected] JOACHIM G. FROMMEN Konrad Lorenz Institute for Ethology Austrian Academy of Sciences Vienna, A
[email protected] WOLFGANG GOYMANN Dept. Behavioural Neurobiology MPI for Ornithology Seewiesen, D
[email protected] JÜRGEN HEINZE Institute of Zoology University of Regensburg, D
[email protected] XX
Contributors
KATHARINA HIRSCHENHAUSER Dept. Behavioural Neurobiology MPI for Ornithology Seewiesen, D
[email protected] HERIBERT HOFER Leibniz Institute for Zoo and Wildlife Research Berlin, D
[email protected] SYLVIA KAISER Dept. of Behavioural Biology University of Münster Münster, D
[email protected] JUDITH KORB Behavioral Biology University of Osnabrück Osnabrück, D
[email protected] KURT KOTRSCHAL Konrad Lorenz Research Station Grünau, A & Dept. of Behavioural Biology University of Wien, A
[email protected] F. BERNHARD KRAUS Molecular Ecology Institute of Biology University of Halle-Wittenberg Halle (Saale), D
[email protected] PETER M. KAPPELER Dept. of Behavioral Ecology and Sociobiology German Primate Center (DPZ) & Dept. for Sociobiology and Anthropology University of Göttingen Göttingen, D
[email protected] CORNELIA KRAUS Dept. for Sociobiology and Anthropology University of Göttingen Göttingen, D
[email protected] BART KEMPENAERS Dept. Behavioural Ecology and Evolutionary Genetics MPI for Ornithology Seewiesen, D
[email protected] MARTA MANSER Animal Behaviour Institute of Zoology University of Zürich Zürich, CH
[email protected] GERALD KERTH Animal Behaviour Institute of Zoology Zürich, CH
[email protected] ROBIN F.A. MORITZ Institute of Biology University of Halle-Wittenberg Halle (Saale), D
[email protected] Contributors
XXI
MARIO PAHL BEEgroup, Biocenter Würzburg University Würzburg, D
[email protected] JUTTA SCHNEIDER Group Behavioural Biology Biocenter Grindel University of Hamburg Hamburg, D
[email protected] DUSTIN J. PENN Konrad Lorenz Institute for Ethology Austrian Academy of Sciences Vienna, A
[email protected] MICHAEL TABORSKY Dept. Behavioural Ecology Institute of Zoology University of Bern Hinterkappelen, Bern, CH
[email protected] NORBERT SACHSER Dept. of Behavioural Biology University of Münster Münster, D
[email protected] JÜRGEN TAUTZ BEEgroup, Biocenter Würzburg University Würzburg, D
[email protected] H. MARTIN SCHAEFER Dept. of Animal Ecology and Evolutionary Biology University of Freiburg, D
[email protected] FRITZ TRILLMICH Behavioral Biology University of Bielefeld
[email protected] ISABELLA B.R. SCHEIBER Konrad Lorenz Research Station Grünau, A
[email protected] CAREL P. VAN SCHAIK Anthropological Institute and Museum University of Zürich Zürich, CH
[email protected] EMMI SCHLICHT Dept. Behavioural Ecology and Evolutionary Genetics MPI for Ornithology Seewiesen, D
[email protected] SHAOWU ZHANG Visual Sciences Group Research School of Biology Canberra ACT 2601, AU
[email protected] Part I Communication and cognition
Chapter 1
Visual communication: evolution, ecology, and functional mechanisms H. MARTIN SCHAEFER
ABSTRACT Throughout their lives, animals gather and weigh information to decide upon alternative states. Many of the decisions in social interactions, mate choice, and intrasexual competition rely upon information transfer in visual communication between senders and receivers. Furthermore, animals as well as plants also engage in interspecific visual communication such as warning displays and the attraction of mutualists. In the first part of this chapter, I discuss how the sensory and neuronal processes involved in detecting and recognising visual stimuli can influence the evolution of the design of informative visual traits. Based upon this functional understanding I review two models of signal evolution, sensory exploitation and sensory drive, in the second part of the chapter. The sensory exploitation model predicts that those signals evolve that are more efficient in stimulating the sensory or perceptual system of the receiver. The sensory drive model predicts that the sensory systems of animals, the signals they use, and their habitats are evolutionarily coupled. Finally, I discuss several case studies from plant-animal communication and sexual selection in birds to illustrate the point that many colours are strongly influenced by the environment. As such, there is a need to integrate ecology into the primarily evolutionary concept of communication theory in order to understand the evolutionary dynamics and diversity of communication systems.
1.1 Introduction Communication is ubiquitous and key to the organisation of behaviour. Cells communicate with each other, members of social groups communicate with each other, and members of different species often do the same. Communication is therefore widespread and occurs at different organisa-
4
H. Martin Schaefer
tional levels. It involves participants that differ widely in the tightness of their association. While there are many definitions of communication, most authors agree that communication involves the provisioning of information by a sender and the evaluation of this information in decision making by a receiver. We need to know then what information is. In a colloquial sense, information can be defined as the reduction in the uncertainty of the receiver about alternative conditions of the sender (see Shannon and Weaver 1949). Yet, it is often difficult to measure whether the trait of a sender used in communication actually reduces the uncertainty of the receiver. Communication is often manipulative, and there are clearly communication systems, such as camouflage, that do not reduce the uncertainty of the receiver. Here I adhere to the definition of communication by Dawkins and Krebs (1978), according to which communication is an action of a sender that influences the sensory system of a receiver so that the receiver changes its behaviour to the benefit of the sender. This definition circumvents the contentious issue of information. It states that by communicating, the sender tries to manipulate the receiver so that its behaviour increases the fitness of the sender. Clearly, communication can result in the transfer of information. In this case it is the transfer of private information that the senders has but the receivers is uncertain about. Despite this asymmetry in the control of information flux, the evolution of communication is essentially a coevolutionary process (Maynard Smith and Harper 1995). Note that this coevolutionary process can be one of antagonistic evolution, that is an arms race between senders and receivers. Yet, many authors maintain that communication, although often manipulative, benefits on average the senders and receivers of information (e.g., Maynard Smith and Harper 1995). Note the use of ‘on average’ in the previous sentence. Whereas senders almost always benefit from communication – otherwise they will be directly selected against and communication will not be evolutionarily stable – , there are cases in which receivers do not benefit, e.g., when they are exploited by the senders. Exploitation of communication is widespread; examples range from permanently rewardless flowers that exploit pollinators for their reproduction to bola spiders that chemically mimic the sex pheromone of their prey. Yet, if receivers do not benefit from responding on average to a given stimulus, they will stop doing so and thereby disrupt the communication system. Accordingly, if males did not obtain on average fitness benefits by responding to the female sex pheromone (one sender), the bola spider (second sender) could not exploit the inter-sexual communication system between the moths.
Visual communication: evolution, ecology, and functional mechanisms
5
The exploitation of pollinators by rewardless flowers and of male moths by bola spiders documents that communication often consists of several different senders and receivers. Thus, even intraspecific communication can involve different species, e.g., potential mates and predators that respond to the same signals and whose selection pressures shape the design of the signal. Even within a species, the sexes can represent different receivers. For example, a trade-off between epigamic signals to females and antagonist signals to males in the red-collared widowbird Euplectes ardens entails that the evolution of one signal is not independent from the evolution of the other signal (Andersson et al. 2002). Although it is conceivable that very specialised communication systems may only involve one sender and one receiver (e.g., chemical communication between mates that requires specific receptors), eavesdropping is common and the very nature of conspicuous communication makes it particularly prone to exploitation by predators. As such, many communication systems consist of multiple senders and receivers, whose relative abundance shapes the selective pressures on the design of communication. Although this network character of communication is increasingly acknowledged, communication has typically been viewed as a binary sender and receiver game. These binary games allow to elucidate fundamental properties of information transfer which can then be extended to more complex communication system and signalling networks at all levels of biological organisation (Skyrms 2009). Signals are the vehicles of communication. They are defined as morphological, physiological, or behavioural characteristics that are maintained by natural selection because they convey information to other organisms (Otte 1974). Otte’s definition is very useful even if we avoid the term ‘convey information to’ and use ‘manipulate other organisms’ instead. This definition is useful because it provides an evolutionary perspective that builds on the selective pressures that shape traits. The term signal is often defined more loosely as a trait that conveys information or that elicits a response in a receiver (Wiley 1994). However, traits may convey information without being primarily selected for that function (see BOX 1.1). For example, body size can reliably indicate the fighting ability of an individual without being selected for a role in communication (Maynard Smith and Harper 1995). Similarly, kestrels (Falco tinnunculus) detected vole scent marks in UV light but not in light without a UV component. Accordingly, they can use UV reflectance as visible cue that is a giveaway of the presence of voles in a given area (Viitala et al. 1995). Although informative, body size and UV reflectance in these examples are not signals because they are not selected to manipulate the opponents and kestrels, respectively.
6
H. Martin Schaefer BOX 1.1 Distinguishing between signals and cues can be challenging Even if a trait conveys information that alters the behaviour of a receiver to the benefit of both sender and receiver, it is not necessarily a signal. This is because the selective pressure of the receiver can feasibly be overridden by those of other selective agents, such as abiotic factors. This is a common theme in visual signals because pigments often fulfil multiple roles. For example, it is well known that melanins may protect against high irradiance and play a role in thermoregulation. The role of these non-communicative functions is not well understood, mainly because hypotheses on the adaptive value of non-communicative functions are not directly pitted against the hypothesis of an adaptive communicative role. This drawback leads to an underestimation of the complexity of communication systems. Plant-animal interactions provide a good example of the complexity of communication. Anthocyanins are plant pigments that impart red, blue, or black colouration to plant tissue. Anthocyanins are at the same time powerful dietary antioxidants that contribute to the health of consumers (Kong et al. 2003, Stinzig and Carle 2004). This is the main reason why there is considerable ongoing interest to increase the contents of bioactive anthocyanins, and more generally flavonoids and other plant phenols, in human nutrition. Surprisingly, however, the evolutionary ecology of anthocyanins, particularly in relation to plant-animal interactions has been a neglected research topic although anthocyanins are the major pigments in fruit and flower displays. Dark colouration in fruits is imparted by anthocyanins. Birds can thus visually evaluate the contents of anthocyanins as dietary antioxidants in fruits (Schaefer et al. 2008a). Owing to the necessary link between dark fruit colouration and anthocyanin contents, dark fruit colouration is best seen as an index of anthocyanin contents. The frugivorous blackcap (Sylvia atricapilla) selects artificial food according to its anthocyanin contents. Importantly, selecting food containing anthocyanins improves the humoral immune response of these birds (Catoni et al. 2008). Birds are thus apparently able to select fruits using their colour as a reliable signal of health benefits. They can thus attend to fruit colouration to increase their intake of flavonoids for self-medication (Catoni et al. 2008, Schaefer et al. 2008a). Conceivably, plants could increase their reproductive success by communicating antioxidant rewards to seed dispersers. If birds select fruits according to their health benefits and colours, the important evolutionary question is whether fruit colouration evolved as a signal to communicate these health benefits to seed dispersers. Examining fruit colour in the binary signalling game between plants and seed dispersers might suggest so because the health benefits of flavonoids occur not only in birds but more widely also in mammals. Yet, fruits are not only consumed by seed dispersers but also by fruit predators that consume fruit pulp without dispers-
Visual communication: evolution, ecology, and functional mechanisms
7
ing the seeds. Bacteria and fruit-rot fungi are actually the most ubiquitous fruit consumers that can have strong, detrimental effects on plant fitness (Janzen 1977, Cipollini and Stiles 1993). Importantly, high contents of anthocyanins strongly inhibited fungal growth in vitro and in damaged grapes reducing fungal growth by 95% (Schaefer et al. 2008b). Thus, the selective pressure of both mutualistic animals (seed dispersers) and antagonists (fruitrot fungi) are aligned to select for increased anthocyanin contents. Unless it is shown that selection for communication overrides selection for defence, anthocyanin contents is best thought of as a cue, not a signal.
In order to understand the evolution of communication it is important to differentiate between traits that are selected for their communicative role, i.e., signals, and those which are not. Traits that are not primarily selected for a communicative function and that can be informative are best viewed as cues (Otte 1974, Seeley 1989). Note my emphasis on the word primarily, a word that was missing in the previous definitions of cues. It is becoming increasingly clear that traits, including those used in communication, are shaped by multiple selective pressures (BOX 1.1). Pigments, for example, can function as signals and they are often concomitantly selected for their role in thermoregulation. It is therefore essential to evaluate the relative selective pressures acting on a given trait. I therefore conclude that signals are primarily selected for their communicative role and can thus evolve to manipulate the receiver, whereas the evolution of cues towards increasing manipulation is constrained because they are primarily selected for a non-communicative role. The kestrel example (above) testifies to the difficulties of distinguishing between cues and senders if distinct receivers attend to the same trait. Obviously, scent marks are very likely selected to communicate with other voles and thus represent signals. Their visual properties, however, have certainly not been selected to communicate to kestrels which therefore attend to cues when foraging on voles. Thus, if predators eavesdrop (‘cue in’) on sexually selected signals, these traits constitute signals to mates but cues to predators. Finally, a trait that is necessarily informative – e.g., if body size is an unfakeable indication of fighting ability – is best viewed as an index of a certain quality (Maynard Smith and Harper 1995). In the following, I will briefly review the sensory (Sect. 1.3) and neuronal basis (Sect. 1.4) for colour vision to show how animals’ visual sensitivities may influence the design of visual signals (Sect. 1.2). Based on this information, I evaluate key concepts in signal evolution in the following sections. Although most concepts that I discuss in this chapter also pertain more widely to communication in other sensory modalities, I will focus on
8
H. Martin Schaefer
the evolution and the proximate mechanisms underlying visual communication.
1.2 Visual sensitivities Most animals are able to extract information from visual traits using two different aspects, achromatic information, that is variation in brightness or the intensity of reflected light from a given surface, and chromatic information on colour. Variation in brightness is perceived on the scale of white to black and often referred to as luminance if analysed according to the sensory abilities of animals. Humans perceive saturation and hue as chromatic aspects of visual information. Saturation describes the colours’ similarity to a chromatically neutral shade such as grey (or white or black); colours that contain no or very little grey are deeply saturated, whereas a grey with a little tint of colour has a low saturation (see Kelber et al. 2003 for a thorough review). In contrast, hue defines colour differences that are related to colour categories, e.g., red, yellow, and green. While there is no evidence that animals perceive hue and saturation as humans do, there is some evidence that bumblebees have a perceptual dimension of saturation (Lunau et al. 1996). Furthermore, experiments on chickens show that they categorise colours and generalise across them (that is treating stimuli that can be differentiated as equivalent) in a way similar to humans (Jones et al. 2001). In order to extract colour information, an animal needs at least two distinct receptors that differ in their spectral sensitivities because this is a prerequisite to distinguish between colours that do not differ in brightness. Animals can thus be characterised according to the number of distinct receptors that are found in their retina and that are used for colour vision. They vary from monochromats, dichromats (many mammals), trichromats (primates, many insects), to tetrachromats (most fishes yet known, most birds and lizards, some insects; see Fig. 1.1). Importantly, behavioural experiments are required to assess the dimensionality of colour vision of a given animal. For example, mantis shrimps are exceptional in possessing 16 morphologically different photoreceptors, but the dimensionality of their colour vision is currently unknown and likely involves fewer dimensions (Marshall et al. 2007). Understanding the spectral sensitivities of animals allows modelling the initial steps of colour perception. In general, visual neurons may either sum photoreceptor signals (in achromatic vision), or compare them by some type of inhibitory interaction (in chromatic vision) to give the ratio
Visual communication: evolution, ecology, and functional mechanisms a
1.2
9
UV
1.0
Sensitivity
0.8 0.6 0.4 0.2 0.0
b
1.2
UV
1.0
Sensitivity
0.8 0.6 0.4 0.2 0.0 300
400
500
600
700
Wavelength [nm]
Fig. 1.1 The spectral sensitivities of animals differ. Birds are tetrachromatic, possessing four cone types that differ in spectral sensitivities (a), whereas many insects such as bees are trichromatic, possessing three different cone types (b). The normalised spectral sensitivities of the cones are illustrated by the white lines. Colour shade indicates colour variation as seen by human eyes except for the UV which humans do not perceive. Note that bees are less sensitive to red light than birds (see Sect. 1.3.2).
or difference of receptor signals (Kelber et al. 2003). It is important to acknowledge that colour perception is much more complicated than these first basic steps of neuronal coding that are currently estimated in visual modelling. In particular, colour is not only in the eye of the beholder, but
10
H. Martin Schaefer
involves higher cognitive processes. As yet, the cognitive component of signal evaluation is still a black box in most non-verbal animals and represents one of the most important frontiers in our current understanding of signal evolution; not only in visual communication but more widely in all sensory modalities (Chittka and Brockmann 2005). Despite these obvious limitations, the use of colour vision models is a powerful tool allowing for tests of specific predictions about the selective pressures upon signal design. This explains their increasingly widespread use to explain the design of communication in aposematism, sexual selection, camouflage, and interspecific interactions between mutualists or antagonists (e.g., Heiling et al. 2003, Cuthill et al. 2005, Endler et al. 2005, Darst et al. 2006, Schaefer et al. 2007).
1.3 Sensory selection on signal design 1.3.1 Conspicuousness Colour vision modelling enables us to examine the basic assumption of signal theory that signal receivers should select for signals that are more conspicuous and easier to detect. This assumption seems intuitively plausible and it has been supported by theoretical modelling (Schluter and Price 1993). However, there are few tests of this assumption under natural conditions (Schaefer et al. 2006, Cazetta et al. 2009). Such tests would be desirable because the relationship between detectability and fitness benefits is unlikely to be constant in distinct environments and communication systems. It can even vary within communication systems. For example, Cazetta et al. (2009) analysed whether fruit detection is a function of the detectability of different fruit colours. According to their preliminary evidence from four different colours, the relationship between detectability and fruit consumption is linear in low contrasting fruits and asymptotic in strongly contrasting fruits. Animals can show behavioural modifications that increase the conspicuousness of their sexually selected signals. Manakins – small, neotropical forest-dwelling birds – have a lek system where males congregate at traditional mating arenas to compete for females. Males of the golden-collared manakin (Manacus vitellinus) show a particular behaviour in that they clear the court in which they are displaying. Colour vision modelling revealed that the plumage patches used during courtship are more contrasting against the clear court than they are against the typical leaf litter of the forest floor (Uy and Endler 2004). The behavioural modification may thus act to increase the conspicuousness of males to females, particularly be-
Visual communication: evolution, ecology, and functional mechanisms
11
cause, apart from colour contrasts, clearing the court results in a less variable background that further enhances the transmission of visual signals. 1.3.2 Selection by multiple receivers A cornerstone of sexual selection theory is that sexual and natural selection are two opposing forces shaping animal traits. Indeed, Endler (1980) demonstrated in his seminal study that guppy pigmentation is mediated by a balance between sexual selection driving the evolution of colour signals towards maximized conspicuousness for conspecifics and natural selection selecting against conspicuous individuals. This is because both mates and predators respond more strongly to conspicuous, i.e., contrasting colours. Increased viability costs associated with increased signalling thus provide one possible mechanism to ensure the evolutionary stability of reliable information transfer. Private communication channels are one way to resolve the evolutionary trade-off between natural and sexual selection in animal colouration. Private communication channels occur if prey uses colour signals that are more conspicuous to conspecifics than they are to predators. Note the relative difference; private communication channels are not invisible to predators, predators are just less sensitive to them. A prerequisite for private communication channels is that prey and predators differ in their visual sensitivities. This situation is common because many predators belong to different taxonomic classes than their prey species. Even if prey and predators belong to the same class, they may have distinct visual abilities. For example, the spectral sensitivity of the short-wave receptor of songbirds is shifted towards the ultraviolet, whereas it is apparently shifted towards the violet part of the spectrum in hawks and crows (Ödeen and Hảstad 2003). This difference explains why, according to vision modelling, the plumage colours of European songbird species are more conspicuous to their conspecifics than to their avian predators (Håstad et al. 2005). Similarly, the UV ornamentation of male swordtails (Xiphorus spp.) increases their attractiveness to females but not to their predator, the Mexican tetra (Astyanax mexicanus), that is less sensitive to UV (Cummings et al. 2003). It remains unresolved, however, how widespread such private communication channels really are, mainly because the visual sensitivities of many species are not known and it is doubtful how well current visual models predict their visual abilities (Stevens and Cuthill 2007). Differences in sensory abilities are also important in interactions between multiple species that are ecologically more similar than predators and potential mates. Such interactions among multiple species are com-
12
H. Martin Schaefer
monly found in plant-animal interactions where plants interact with suites of mutualistic and antagonistic species. Differences in the visual abilities of animals may result in divergent selective pressures of these agents. For example, monkeyflowers (Mimulus spp.) are pollinated by trichromatic bees and tetrachromatic hummingbirds. Introgressing different flower colour alleles into near iso-genic lines of two Mimulus species, Bradshaw and Schemske (2003) showed that a shift in floral colour resulted in a concomitant change in pollinator spectrum (hummingbirds vs. bees) that could, in theory, be initiated by a single mutation. This is an extremely interesting example because the sensory ecology of pollinators predicts their reaction towards the floral colour shift. Pink flowers are pollinated by bumblebees which are not very sensitive to variation in the red part of the spectrum. Hummingbirds, however, are very sensitive to red and pollinate predominantly the red flowers. Thus, a single mutation can be adaptive, leading to premating isolation owing to differential attraction of pollinators. The magnitude of this single mutation is explicable by considering the sensory ecology of different signal receivers. This, in turn, allows for understanding the repeated evolution of pollination by hummingbirds from ancestral insect-pollinated species in the North American flora. The examples above document how natural selection upon both senders and the sensory systems of receivers shapes the design of signals. This effect is also visible on different time scales. On a developmental time scale, tadpoles develop different colours depending on the presence and type of predators (Touchon and Warkentin 2008). While the induced colour changes of tadpoles may have been adaptive, rendering them less conspicuous to the two types of predators (dragonfly larvae and fish), the adaptiveness has not been demonstrated in this study. The most rapid predator-induced colour changes occur in species like chameleons that change colour within milliseconds or seconds. Chameleons show adaptive, predator-specific colour change if faced with predators that differ in visual abilities. They show stronger background matching if faced with an avian predator of acute colour vision relative to a snake with less developed colour vision (Stuart-Fox et al. 2008).
1.4 Selection by lower neuronal processes Not only the spectral sensitivities of animals, but also their neuronal and cognitive processes have selected for the design of colour signals. Although neuronal processes involved in the detection of signals and their recognition form a continuum, I tentatively discriminate between higher
Visual communication: evolution, ecology, and functional mechanisms
13
and lower neuronal processes. The latter represent the first steps of neuronal coding of the output of receptor cells, whereas the former are involved in cognitive processes (see Sect. 1.5). Major advances in recent years have demonstrated that lower neuronal processes can shape the selective pressures that predators exert upon the design of camouflage traits. There are many forms of camouflage including background matching (where prey matches the background in colour, form and shape), disruptive colouration, and masquerade (where prey resembles an uninteresting specific item of the background such as a stick or a leaf; Fig. 1.2). Because these different camouflage techniques have been recently reviewed (e.g., Stevens 2007), I will focus here only upon the effects of neuronal coding. Disruptive colouration thwarts detection by sporting contrasting patterns on the body outline (Cott 1940, Merilaita 1998). These contrasting patterns are particularly effective in hindering detection of a prey by exploiting edge detection mechanisms in early visual processes (Stevens 2007). Edge detection mechanisms enhance the sensitivity of predators to contrasts because these are naturally associated with the boundaries of objects (Osorio and Srinivasan 1991). Contrasting marginal patterns that create false boundaries and mask the shape of the body can thereby conceal the body outline (Cuthill et al. 2005). Edge detection mechanisms are probably optimised for detecting targets against the heterogeneous background of natural scenes. For example, a background of leaves varies dramatically, that is over 3 log units, in brightness (Sumner and Mollon 2000, Regan et al. 2001). Variation in brightness is particularly pronounced if there is a mosaic of sunlit spots and shadows created by three-dimensional objects. Thus, many organisms apparently segregate images based upon such high-contrast borders. As a consequence, edge detection is mediated primarily by achromatic contrasts because achromatic variation typically exceeds, and is therefore more reliable than, variation in chromatic contrasts (Osorio et al. 1999). Conversely, chromatic contrasts are particularly valuable for identifying objects against an achromatically variable background such as foliage (see Sect. 1.6). Marginal markings in prey that create either chromatic or achromatic contrasts can yield effective disruptive colouration that camouflages its bearer (Schaefer and Stobbe 2006, Stevens et al. 2006). Interestingly, both studies working on artificial butterfly-like models revealed that disruptive colouration is effective, albeit less so, even if the colours do not match those of the background. However, two further studies showed with different patterns that increasing contrast to the background decreases the survival probabilities of disruptive prey (Stevens et al. 2008a, Stobbe and Schaefer 2008). Thus, the extent to which disruptive colouration enables
14 a
d
H. Martin Schaefer b
c
e
Fig. 1.2 Animals use different visual techniques of protective camouflage to evade predators. Toxic animals often defend themselves with highly contrasting colours (a), whereas undefended prey can evade predators by background matching like the amphibian in (b) or disruptive colouration that is characterised by contrasting marginal colour patterns that disrupt the body outline (c). Disruptive colouration is thus very different from the border profile enhancement seen in (d). Contrasting spots are another form of protective colouration (e). The traditional hypothesis is that they startle predators through eye mimicry but recent experiments revealed that they rather serve as protective colouration instead by diverting the attention of the predator away from the shape of the body (Stevens et al. 2008b).
the bearer to exploit a larger diversity of habitats than background matching is not well resolved and may depend on form and location of the contrasting patterns. The eyespots that many butterflies but also fish (and possibly birds such as pygmy owls) sport (Fig. 1.2) are another visual feature that is apparently selected by the design of receptive fields in the retina of predators. The traditional hypothesis is that such eye-like spots mimic the eyes of a larger animal and thereby startle potential predators. However, such circular, contrasting spots are highly effective in stimulating the centre-surround arrangement of visual fields in the retina of vertebrates (Stevens et al. 2007). Detailed experiments showed that large size and higher number of spots increase their protective value, irrespective of the level of resemblance to
Visual communication: evolution, ecology, and functional mechanisms
15
real eyes. Conspicuous patches of different shapes serve to camouflage prey probably by diverting the attention away from the shape of the body (Stevens et al. 2008b). Thus, neuronal perceptual mechanisms, rather than eye mimicry, seem to explain the design of wing and fin spots.
1.5 Selection by higher neuronal processes The higher neuronal circuitry involves cognitive processes which are often unknown and difficult to study in non-verbal animals (Chittka and Brockmann 2005). Unravelling the evolutionary significance of higher brain processes presents a particularly exciting research topic. These processes can influence selection upon colour patterns through various mechanisms. These include perceptual errors, shifts in preferences for stimuli that are caused by discrimination learning (peak-shift phenomena), attention limited by the rate of information processing, speed-accuracy trade-offs, and the retrieval and devaluation rate of memory properties (Dukas 2002, ten Cate and Rowe 2007, Chittka et al. 2009). The retrieval function of the memory is best studied in the context of foraging. For example, bees choose among floral colours depending on their experience with these colours 24 hours ago. The retrieval of colour memories in the honeybee thus follows a circadian rhythm that apparently matches the circadian rhythm of nectar and pollen production in flowers (Zhang et al. 2006, Prabhu and Cheng 2008). Bees thus possess a Zeitgedächtnis (time memory) allowing them to adaptively fine-tune their foraging behaviour to the peak availability of nectar associated with visual stimuli (see also Pahl et al. this volume). Associative learning can influence colour selection also at different time scales. Similar aged garden warblers (Sylvia borin) that were either handraised or caught as immatures in the wild differed in their ability to assess sugar rewards in foods independent of colour stimuli. Birds of both groups initially preferred red food over orange food. Although all birds were kept on the same diet for a period of seven months, wild-caught birds achieved higher sugar intakes when confronted with alternative foods of distinct sugar rewards whose colouration switched between experiments (Schaefer et al. 2008c). The higher nutrient intake occurred because wild-caught birds devaluated the colour information of preceding experiments more quickly. These experiments thus document that previous experience has long-lasting effects on food choice even in simple foraging situations where foods only vary in the single dimension of sugar contents. The examples of bees (above) and garden warblers both document that a better
16
H. Martin Schaefer
understanding of associative learning is needed for evaluating how animals respond to visual stimuli. In the following, I will examine two models of signal evolution that allow for a better understanding of the staggering diversity of visual signals that is inherent to almost every communication system from flowering plants on an Alpine meadow to the visual (and acoustical) diversification of epigamic signals in an avian rainforest community. Doing so allows us to amend the primarily evolutionary concept of signal theory with the ecology of the species involved.
1.6 Sensory trade-offs and sensory exploitation An exciting line of research suggests that the diversity of signals can, at least partly, be explained by distinct signalling strategies. In general, traits that convey information consist of a design (or efficacy) and a content component (Guilford and Dawkins 1991). The design component describes the proximate, sensory aspects of a trait discussed above, whereas a trait’s content describes the information (message) that it conveys (or not). Thus, signals could feasibly diverge to either maximise their conspicuousness (design component) or their reliability (content component). Modelling signal evolution in a binary sender receiver game where signals differed in efficacy and reliability yielded that – in theory – this trade-off could explain the diversity of signals because the efficacy component will vary according to environmental conditions (Schluter and Price 1993). Studying the plumage characteristics in three bird species, Andersson (2000) suggested that such trade-offs indeed occur in avian plumage. There is also supporting evidence from other signalling systems. Closely related toxic poison frogs differ in their warning colouration. Increasing either conspicuousness or toxicity affords equivalent avoidance by predators; suggesting that such alternative strategies of warning displays can explain the diversity of warning colouration (Darst and Cummings 2006). Similarly, the colours of fleshy fruits in a Venezuelan rainforest diverged along the dichotomy of either content- or efficacy-related colours. The most contrasting fruit colour (red), did not indicate the contents of fruit pulp, whereas chromatic variation in other fruit colours indicated the sugar, protein, and tannin contents of fruits (Schaefer and Schmidt 2004, Schmidt et al. 2004). An intriguing trade-off between relative detectability and relative nutritional returns also occurs in red and black fruit colours. Both colours are imparted by anthocyanins as plant pigments, and many fruits change pig-
Visual communication: evolution, ecology, and functional mechanisms
17
mentation from red to black during the ripening process owing to a quantitative change in anthocyanin contents (e.g., blackberries; see BOX 1.1). During fruit ripening, the appearance of red pigmentation is associated with low contents of anthocyanins, whereas the black pigmentation of ripe fruits is imparted by further accumulation of anthocyanins. The ripening of fruits entails thus a shift from a chromatic, red cue to a predominantly achromatic black one in the ripe fruit. This shift is important because it has dramatic consequences for the signal-noise ratio of fruits. As explained earlier, the background of most terrestrial scenes is highly heterogenic in brightness. Against such a background, it is very difficult to detect a primarily achromatic target, simply because it is concealed among background noise. These theoretical considerations predict that ripe fruits, which are made to be eaten by seed dispersers, are actually more difficult to detect than pre-ripe fruits. Indeed, fish crows (Corvus ossifragus) detected red fruits from a larger distance (60% increase) compared with similar sized black fruits (Schaefer et al. 2006). Given that birds strongly prefer feeding on the ripest fruits available (Schaefer and Schaefer 2006) delaying the maturation of red midripe fruits could be adaptive for plants because it increases the detectability of the entire fruit display. This is a strategy similar to the retention of pollinated flowers that increase the overall attractiveness of the plant for pollinators (Weiss 1991). The relatively lower detectability of ripe fruits is thus not explicable by a communicative function but rather by the defensive properties of anthocyanins in ripe fruits (see BOX 1.1). How can we envision the evolutionary stability of efficacy-related signals that provide little information? One important model is the sensory exploitation model that has been developed in the context of sexual selection, but that is equally applicable to other communication systems, such as plant-animal communication (Schaefer and Ruxton 2009). This model posits i) that female preferences for traits are explicable because certain traits are more effective in stimulating the female sensory systems, and ii) that traits are more likely to evolve that match pre-existing biases in the females sensory system (Basolo 1990, Ryan et al. 1990, Endler and Basolo 1998). Natural selection upon sensory systems maintains sensory biases. For example, four species of avian seed dispersers and pollinators have inherent preferences for contrasting fruit or flower displays, respectively, even if these are presented at close distance to the animals (Schmidt et al. 2004, Naug and Arathi 2007). However, it is not only the magnitude of contrast that influences foraging decisions. In a series of elegant experiments Lunau et al. (1996) demonstrated that the magnitude of contrasts explained the initial approach to artificial flowers (i.e., detection), but that
18 a
H. Martin Schaefer b
c
Fig. 1.3 Many orchids that do not provide nutritional rewards to pollinators are polymorphic in colour. The rare white morph of the unrewarding orchid Orchis mascula (a) is very attractive to pollinators. Interestingly, if white table tennis balls are positioned among the common purple morph (b), they are as efficient in attracting pollinators as the rare white morph even though they do not resemble flowers. The attraction of insects to white table tennis balls (c) provides a particular convincing example of how senders might exploit sensory biases of receivers (here pollinators) to forage on contrasting targets (Dormont et al. 2009; photos © Bertrand Schatz).
the actual floral colour influenced the decision whether or not to land on a given flower (i.e., a preference). Preferences for contrasting food sources are probably adaptive for pollinators and seed dispersers because fruits and flowers differ from their predominantly leafy green background in colour, scent and shape. Reacting to colour contrasts thus presents one important proximate mechanism for animals to locate and identify food resources. However, these preferences for contrasting colours can also be exploited by signallers. For example, permanently unrewarding flowers are often highly contrasting and thereby attractive for pollinators (Fig. 1.3). Indeed, the floral displays of nectarless flowers are often described as flamboyant, but the hypothesis that unrewarding flowers are characterised by more contrasting pigmentation than rewarding flowers has apparently not been tested. Thus, using an efficacyrelated signalling strategy may be evolutionarily stable because it exploits inherent biases of the sensory system of the receivers. Senders can exploit sensory biases of other animals or biases that occur when the sensory input is processed in the brain of an animal. The latter are thus biases that arise during information processing. There are several related models on signal evolution that can be distinguished according to their relative emphasis on the exploitation of sensory vs. higher brain proc-
Visual communication: evolution, ecology, and functional mechanisms
19
esses (Endler and Basolo 1998). Regardless of the origin of a bias, models on the exploitation of pre-existing biases allow to predict why certain signals evolve if they include an explicit phylogenetic approach. They can thus predict the sequence of events in signal evolution. For example, biases for larger size in mates are widespread in the animal kingdom potentially driving the evolution of larger-sized ornaments (Ryan and Keddy-Hector 1992, Rosenthal and Evans 1998). A prerequisite for the pre-existing biases model is thus to show that the preference for a trait is ancestral occurring in species lacking that trait, and that the trait is developed in the predicted direction in related species. This has been demonstrated in systems as diverse as acoustic communication in frogs and visual inspection of morphological traits in swordtail fishes (Xiphorus spp.) and short-tailed widowbirds (Euplectes axiliaris) (Basolo 1990, Ryan et al. 1990, Pryke and Andersson 2002). Thus, pre-existing biases are a powerful mechanism that may explain the evolution of acoustic and visual signals.
1.7 Sensory drive The sensory drive model is an ecological model to explain the diversity of signals. This model predicts that the sensory system of animals, their signals and signalling behaviour, and habitat choice have all been coupled over evolutionary times (Endler 1992). Since environmental differences affect the transmittance and perception of signals (the efficacy component), this model predicts geographical differences in signal perception and signalling behaviour. Elegant tests of how sensory constraints associated with predictable environmental differences drive signal evolution, and even speciation, are found in aquatic environments. In five closely related dichromatic fish species, habitat choice entails an inherent trade-off in colour and luminance detection that leads to differences in the spectral tuning of these fish. The trade-off is associated with water depth but primarily driven by variation in background colour and brightness. Species living in habitats with high variance in luminance evolved sensory systems and signals that favour chromatic detection (Cummings 2007). Sensory drive can result in strong divergent selection. For example, in Lake Victoria cichlid species, divergent selection along an environmental gradient of water clarity and depth-mediated light gradients drives divergent evolution of the visual system (opsin genes). In the lake there are related cichlid species pairs where males differ in having either a red or blue nuptial colouration. Although these fishes are geographically sympatric, they are better thought of as parapatric with adjoining depth ranges in the
20
H. Martin Schaefer
lake. The red species always occurs at greater mean water depth. Divergent selection upon the visual systems of these fishes evidenced by higher genetic variation at the opsin gene loci compared to that of neutral loci is leading to incipient speciation (Terai et al. 2006). The contrasting selection regimes lead to divergence in male breeding colouration and female preferences in this system, but also in sticklebacks (Boughman 2001). Importantly, several populations of cichlid species along the steep environmental gradient of water clarity are reproductively isolated, showing that sensory drive may lead to speciation even in the absence of strict geographic isolation (Terai et al. 2006, Seehausen et al. 2008). Evidence for sensory drive is also found in terrestrial communication systems. Mesic and xeric habitats differ in the quality of ambient light because they differ in the amount of light filtered by the vegetation (Endler 1993). Allopatric Anolis lizard populations from mesic and xeric habitats differ in dewlap colouration, a sexually selected signal, so that each population sports a colour that increases detectability in its specific habitat (Leal and Fleishman 2004). Environmental differences in the conspicuousness of an epigamic trait might likewise explain unidirectional introgression in the hybrid zone of golden-collared (Manacus vitellinus) and whitecollared (M. candei) manakins. Each species’ collar is better detectable in areas where both are allopatric, whereas in the hybrid zone the conspicuousness of the golden collar exceeds that of the white collar. These results suggest that sensory mechanisms can explain the unidirectional spread of yellow plumage across the hybrid zone as well as its slowed movement beyond it (Uy and Stein 2007).
1.8 Environmental influence on communication The examples above provide powerful evidence for how environmental differences may drive visual perception, signal evolution and, ultimately, speciation. Abiotic factors can accelerate population differentiation and sensory drive because pigments often fulfil dual roles in thermoregulation and communication. Visual traits can therefore be particularly prone to respond to environmental differences, which may partly explain the diversification of visual traits. Environmental determination of colour traits occurs in many communication systems, for example, avian plumage traits that are involved in mate choice (Hadfield et al. 2007, Norris et al. 2007). A large cross-fostering experiment by Hadfield and colleagues uncoupled genetic from environmental effects because some blue tit (Cyanistes caeruleus) chicks of each
Visual communication: evolution, ecology, and functional mechanisms
21
family were raised by their parents and others by foster parents. Heritability of the sexually selected ultraviolet/blue cap of the species and of the yellow, carotenoid-based breast feathers was low (h2 = 0.10 and 0.07, respectively). None of the traits indicated components of offspring fitness. This is an important study for evaluating alternative models of sexual selection because it shows that female blue tits were unlikely to obtain indirect benefits (through high quality offspring) by choosing among males based upon the colouration of these plumage traits. In the good gene model, females obtain indirect genetic benefits for their offspring by mating with the most ornamented male because ornaments can be costly handicaps and thereby indicate the genetic quality of their bearer (Zahavi 1975). The good gene model is often contrasted with models on direct benefits that females may accrue by mating with a partner that invests more in parental duties. The low heritability of and strong environmental influence on plumage traits in the blue tit do not support indirect models of sexual selection (Hadfield et al. 2006). Thus, these studies raise fundamental questions about the reliability of information transfer in communication and, more generally, about the common usage of inferring genetic patterns from phenotypic data. I will now examine two case studies of plant-animal interactions. These are informative for two reasons. The first study shows that environmental determination of visual traits does not necessarily compromise their reliability. The second study nicely summarises why the textbook wisdom that floral colours are an adaptation to communicating to biotic dispersal agents does not fully appreciate the evolutionary trajectories of communication. The colouration of the bracts in the infructescences of black elder (Sambucus nigra) is a good example of an environmentally driven communication system (Fig. 1.4). In forest gaps, individuals have red bracts, whereas the bracts remain green in individuals growing in forest shade. Bract colouration is a phenotypically plastic trait because individuals can sport both colour phenotypes if they receive direct sunlight on only one side. Red colouration often develops in plant tissue as a protection against excess sun light. Since individuals in gaps receive more light, they also produce sweeter fruits, forging a link between bract colouration and fruit quality. In this communication system, fruit quality is quantitatively indicated by the colour contrasts between bracts and the background; the higher the contrasts, the sweeter the fruits. Hence, red pedicels concomitantly increase the detectability and the reliability of information exchange in black elder. Blackcaps attend to bract colouration when consuming fruits and prefer fruits from red bracts. Yet, since bract colouration is an environmentally determined trait, it should be regarded as a cue until there is evidence
22
H. Martin Schaefer
Fig. 1.4 Fruit-eating blackcaps preferentially consume black elder fruits from infructescences with red pedicels (illustrated by the arrow) because red pedicel pigmentation is reliably associated with sweeter fruits.
that the selective pressure of seed dispersing birds overrides that of excess irradiance (Schaefer and Braun 2009). This study shows that environmental coupling of the design of a visual trait and of the content it indicates can lead to reliable, environmentally determined information transfer. Differences in flower colour are traditionally interpreted as an adaptation towards divergent selection by pollinators; an idea that can be traced to the late 18th century (Sprengel 1793). Spatial differentiation in the blue and white colour morph of Linanthus parryae has become a model system in evolutionary biology. The colour polymorphism in this species is caused by a single gene. The sole pollinator, a melyrid beetle, does apparently not differentiate between colour morphs. Applying his model of isolation by distance, Wright (1943) concluded that spatial differentiation in L. parryae was caused by random drift. Schemske and Bierzychudek (2007) studied
Visual communication: evolution, ecology, and functional mechanisms
23
genetic differentiation in this species. They found no differentiation in allozyme markers in populations with distinct floral colour. They therefore concluded that spatial differentiation in floral colour is explicable by natural selection, a conclusion supported because each morph fared best in transplant experiments in their local habitats. Thus, the colour polymorphism in this species is explicable by pleiotropy, i.e. by the multiple effects that a single gene has on distinct phenotypes (colour and local performance) and not by divergent selection upon communication to pollinators.
1.9 Conclusion Throughout the chapter, I have stressed the need to account for the functional mechanisms underlying visual communication in order to understand the evolutionary trajectories of visual communication. Today, researchers can build upon a quickly expanding knowledge on the sensory processes of signal reception that form the basis for the models of sensory exploitation and sensory drive. Both of these models on signal evolution have emphasised the role of sensory biases and have led to the increasing use of visual modelling in evolutionary and ecological studies. Incorporating the evolutionary significance of higher neuronal processes into current models on signal evolution represents one of the most important current challenges for a functional understanding of communication. Another current frontier is to address how the often significant environmental influence on visual traits alters their design and information content. Substantial environmental influence on signalling can destabilise communication systems that transmit information on the genetic quality of the signaller. A good example of such a communication system is provided by the model of indirect genetic benefits in sexual selection theory that underlies the paradigm of the handicap principle. In other communication systems, however, the linkage between phenotypic visual trait and phenotypic quality may be largely driven by the environment. Future studies are needed to test this conjecture as well as to assess how widely the handicap principle explains the evolutionary stability of communication systems.
Acknowledgements I thank Martin Stevens, Lars Chittka and Peter Kappeler for many very constructive comments and Bertrand Schatz for permission to use his photos in Fig. 1.3. All other photos © Veronika Schaefer and Martin Schaefer.
24
H. Martin Schaefer
References Andersson S (2000) Efficacy and content in avian colour signals. In: Espmark Y, Amundsen T, Rosenqvist G (eds) Animal Signals: Signalling and Signal Design in Animal Communication. Tapir Academic Press, Trondheim, Norway, pp 47-60 Andersson S, Pryke SR, Örnborg J, Lawes MJ, Andersson M (2002) Multiple receivers, multiple ornaments, and a trade-off between agonistic and epigamic signaling in a widowbird. Am Nat 160:683-691 Basolo AL (1990) Female preference predates the evolution of the sword in swordtail fish. Science 250:808-810 Boughman JW (2001) Divergent sexual selection enhances reproductive isolation in sticklebacks. Nature 411:944-948 Bradshaw HD Jr, Schemske DW (2003) Allele substitution at a flower colour locus produces a pollinator shift in monkeyflowers. Nature 426:176-178 Catoni C, Schaefer HM, Peters A (2008) Fruit for health: the effect of flavonoids on humoral immune response and food selection in a frugivorous bird. Funct Ecol 22:649-654 Cazetta E, Schaefer HM, Galetti M (2009) Why are fruits colorful? The relative importance of achromatic and chromatic contrasts for detection by birds. Evol Ecol 23:233-244 Chittka L, Brockmann A (2005) Perception space – the final frontier. PLOS Biol 3:e137, doi:10.1371/journal.pbio.0030137 Chittka L, Skorupski P, Raine NE (2009) Speed-accuracy tradeoffs in animal decision making. Trends Ecol Evol 24:400-407 Cipollini ML, Stiles EW (1993) Fruit rot, antifungal defense, and palatability of fleshy fruits for frugivorous birds. Ecology 74:751-762 Cott HB (1940) Adaptive Coloration in Animals. Methuen, London Cummings ME (2007) Sensory trade-offs predict signal divergence in surfperch. Evolution 61:530-545 Cummings ME, Rosenthal GG, Ryan MJ (2003) A private ultraviolet channel in visual communication. Proc R Soc Lond B 270:897-904 Cuthill IC, Stevens M, Sheppard J, Maddocks T, Párraga CA, Troscianko TS (2005) Disruptive coloration and background pattern matching. Nature 434:72-74 Darst CR, Cummings ME (2006) Predator learning favours mimicry of a lesstoxic model in poison frogs. Nature 440:208-211 Darst CR, Cummings ME, Cannatella DC (2006) A mechanism for diversity in warning signals: conspicuousness versus toxicity in poison frogs. Proc Natl Acad Sci USA 103:5852-5857 Dawkins R, Krebs JR (1978) Animal signals: information or manipulation. In: Krebs JR, Davies NB (eds) Behavioural Ecology: An Evolutionary Approach. Blackwell, Oxford, pp 282-309
Visual communication: evolution, ecology, and functional mechanisms
25
Dormont L, Delle-Vedove R, Bessière JM, Hossaert-McKey M, Schatz B (2009) Rare white-flowered morphs increase the reproductive success of common purple morphs in a food-deceptive orchid. New Phytol 185:300-310 Dukas R (2002) Behavioural and ecological consequences of limited attention. Philos Trans R Soc Lond B 357:1539-1547 Endler JA (1980) Natural selection on color patterns in Poecilia reticulata. Evolution 34:76-91 Endler JA (1992) Signals, signal conditions, and the direction of evolution. Am Nat 139:S125-S153 Endler JA (1993) The color of light in forests and its implications. Ecol Monogr 63:1-27 Endler JA, Basolo AL (1998) Sensory ecology, receiver biases and sexual selection. Trends Ecol Evol 13:415-420 Endler JA, Westcott DA, Madden JR, Robson T (2005) Animal visual systems and the evolution of color patterns: sensory processing illuminates signal evolution. Evolution 59:1795-1818 Guilford T, Dawkins MS (1991) Receiver psychology and the evolution of animal signals. Anim Behav 42:1-14 Hadfield JD, Burgess MD, Lord A, Phillimore AB, Clegg SM, Owens IPF (2006) Direct versus indirect sexual selection: genetic basis of colour, size and recruitment in a wild bird. Proc R Soc Lond B 273:1347-1353 Hadfield JD, Nutall A, Osorio D, Owens IPF (2007) Testing the phenotypic gambit: phenotypic, genetic and environmental correlations of colour. J Evol Biol 20:549-557 Håstad O, Victorsson J, Ödeen A (2005) Differences in color vision make passerines less conspicuous in the eyes of their predators. Proc Natl Acad Sci USA 102:6391-6394 Heiling AM, Herberstein ME, Chittka L (2003) Crab-spiders manipulate flower signals. Nature 421:334 Janzen DH (1977) Why fruits rot, seeds mold, and meat spoils. Am Nat 111:691713 Jones CD, Osorio D, Baddeley RJ (2001) Colour categorization by domestic chicks. Proc R Soc Lond B 268:2077-2084 Kelber A, Vorobyev M, Osorio D (2003) Animal colour vision – behavioural tests and physiological concepts. Biol Rev 78:81-118 Kong J-M, Chia L-S, Goh N-K, Chia T-F, Brouillard R (2003) Analysis and biological activities of anthocyanins. Phytochemistry 64:923-933 Leal M, Fleishman LJ (2004) Differences in visual signal design and detectability between allopatric populations of Anolis lizards. Am Nat 163:26-39 Lunau K, Wacht S, Chittka L (1996) Colour choices of naive bumble bees and their implications for colour perception. J Comp Physiol A 178:477-489 Marshall J, Cronin TW, Kleinlogel S (2007) Stomatopod eye structure and function: a review. Arthropod Struct Dev 36:420-448 Maynard Smith J, Harper DGC (1995) Animal signals: models and terminology. J Theor Biol 177:305-311
26
H. Martin Schaefer
Merilaita S (1998) Crypsis through disruptive coloration in an isopod. Proc R Soc Lond B 265:1059-1064 Naug D, Arathi HS (2007) Receiver bias for exaggerated signals in honeybees and its implications for the evolution of floral displays. Biol Lett 3:635-637 Norris DR, Marra PP, Kyser TK, Ratcliffe LM, Montgomerie RA (2007) Continent-wide variation in feather colour of a migratory songbird in relation to body condition and moulting locality. Biol Lett 3:16-19 Ödeen A, Hảstad O (2003) Complex distribution of avian color vision systems revealed by sequencing the SWS1 opsin from total DNA. Mol Biol Evol 20:855-861 Osorio D, Srinivasan MV (1991) Camouflage by edge enhancement in animal coloration patterns and its implications for visual mechanisms. Proc R Soc Lond B 244:81-85 Osorio D, Miklósi A, Gonda Z (1999) Visual ecology and perception of coloration patterns by domestic chicks. Evol Ecol 13:673-689 Otte D (1974) Effects and functions in the evolution of signaling systems. Annu Rev Ecol Syst 5:385-417 Prabhu C, Cheng K (2008) One day is all it takes: circadian modulation of the retrieval of colour memories in honeybees. Behav Ecol Sociobiol 63:11-22 Pryke SR, Andersson S (2002) A generalized female bias for long tails in a shorttailed widowbird. Proc R Soc Lond B 269:2141-2146 Regan BC, Julliot C, Simmen B, Viénot F, Charles-Dominique P, Mollon JD (2001) Fruits, foliage and the evolution of primate colour vision. Philos Trans R Soc Lond B 356:229-283 Rosenthal GG, Evans CS (1998) Female preference for swords in Xiphophorus helleri reflects a bias for large apparent size. Proc Natl Acad Sci USA 95:4431-4436 Ryan MJ, Keddy-Hector A (1992) Directional patterns of female mate choice and the role of sensory biases. Am Nat 139:S4-S35 Ryan MJ, Fox JH, Wilczynski W, Rand AS (1990) Sexual selection for sensory exploitation in the frog Physalaemus pustulosus. Nature 343:66-67 Schaefer HM, Braun J (2009) Reliable cues and signals of fruit quality are contingent on the habitat in black elder (Sambucus nigra). Ecology 90:1564-1573 Schaefer HM, Ruxton GD (2009) Deception in plants: mimicry or perceptual exploitation? Trends Ecol Evol 24:676-685 Schaefer HM, Schaefer V (2006) The fruits of selectivity: how birds forage on Goupia glabra fruits of different ripeness. J Ornithol 147:638-643 Schaefer HM, Schmidt V (2004) Detectability and content as opposing signal characteristics in fruits. Proc R Soc Lond B 271:S370-S373 Schaefer HM, Stobbe N (2006) Disruptive coloration provides camouflage independent of background matching. Proc R Soc Lond B 273:2427-2432 Schaefer HM, Levey DJ, Schaefer V, Avery ML (2006) The role of chromatic and achromatic signals for fruit detection by birds. Behav Ecol 17:784-789 Schaefer HM, Schaefer V, Vorobyev M (2007) Are fruit colors adapted to consumer vision and birds equally efficient in detecting colorful signals? Am Nat 169:S159-S169
Visual communication: evolution, ecology, and functional mechanisms
27
Schaefer HM, McGraw K, Catoni C (2008a) Birds use fruit colour as honest signal of dietary antioxidant rewards. Funct Ecol 22:303-310 Schaefer HM, Rentzsch M, Breuer M (2008b) Anthocyanins reduce fungal growth in fruits. Nat Prod Commun 3:1267-1272 Schaefer HM, Spitzer K, Bairlein F (2008c) Long-term effects of previous experience determine nutrient discrimination abilities in birds. Front Zool 5:4, doi:10.1186/1742-9994-5-4 Schemske DW, Bierzychudek P (2007) Spatial differentiation for flower color in the desert annual Linanthus parryae: was Wright right? Evolution 61:25282543 Schluter D, Price T (1993) Honesty, perception and population divergence in sexually selected traits. Proc R Soc Lond B 253:117-122 Schmidt V, Schaefer HM, Winkler H (2004) Conspicuousness, not colour as foraging cue in plant-animal interactions. Oikos 106:551-557 Seehausen O, Terai Y, Magalhaes IS, Carleton KL, Mrosso HDJ, Miyagi R, van der Sluijs I, Schneider MV, Maan ME, Tachida H, Imai H, Okada N (2008) Speciation through sensory drive in cichlid fish. Nature 455:620-626 Seeley TD (1989) The honey bee colony as a superorganism. Am Sci 77:546-553 Shannon CE, Weaver W (1949) The Mathematical Theory of Communication. University of Illinos Press, Urbana Skyrms B (2009) Evolution of signalling systems with multiple senders and receivers. Philos Trans R Soc Lond B 364:771-779 Sprengel CK (1793) Das entdeckte Geheimnis in der Natur im Bau und in der Befruchtung der Blumen. Weldon and Wesley, New York Stevens M (2007) Predator perception and the interrelation between different forms of protective coloration. Proc R Soc Lond B 274:1457-1464 Stevens M, Cuthill IC (2007) Hidden messages: are ultraviolet signals a special channel in avian communication? BioScience 57:501-507 Stevens M, Cuthill IC, Windsor AMM, Walker HJ (2006) Disruptive contrast in animal camouflage. Proc R Soc Lond B 273:2433-2438 Stevens M, Hopkins E, Hinde W, Adcock A, Connolly Y, Troscianko T, Cuthill IC (2007) Field experiments on the effectiveness of 'eyespots' as predator deterrents. Anim Behav 74:1215-1227 Stevens M, Graham J, Winney IS, Cantor A (2008a) Testing Thayer's hypothesis: can camouflage work by distraction? Biol Lett 4:648-650 Stevens M, Hardman CJ, Stubbins CL (2008b) Conspicuousness, not eye mimicry, makes ‘eyespots’ effective antipredator signals. Behav Ecol 19:525-531 Stinzig FC, Carle R (2004) Functional properties of anthocyanins and betalains in plants, food, and in human nutrition. Trends Food Sci Tech 15:19-38 Stobbe N, Schaefer HM (2008) Enhancement of chromatic contrast increases predation risk for striped butterflies. Proc R Soc Lond B 275:1535-1541 Stuart-Fox D, Moussalli A, Whiting MJ (2008) Predator-specific camouflage in chameleons. Biol Lett 4:326-329 Sumner P, Mollon JD (2000) Chromaticity as a signal of ripeness in fruits taken by primates. J Exp Biol 203:1987-2000
28
H. Martin Schaefer
ten Cate C, Rowe C (2007) Biases in signal evolution: learning makes a difference. Trends Ecol Evol 22:380-387 Terai Y, Seehausen O, Sasaki T, Takahashi K, Mizoiri S, Sugawara T, Sato T, Watanabe M, Konijnendijk N, Mrosso HDJ, Tachida H, Imai H, Shichida Y, Okada N (2006) Divergent selection on opsins drives incipient speciation in Lake Victoria cichlids. PLOS Biol 4:e433, doi:10.1371/journal.pbio.0040433 Touchon JC, Warkentin KM (2008) Fish and dragonfly nymph predators induce opposite shifts in color and morphology of tadpoles. Oikos 117:634-640 Uy JAC, Endler JA (2004) Modification of the visual background increases the conspicuousness of golden-collared manakin displays. Behav Ecol 15:10031010 Uy JAC, Stein AC (2007) Variable visual habitats may influence the spread of colourful plumage across an avian hybrid zone. J Evol Biol 20:1847-1858 Viitala J, Korpimäki E, Palokangas P, Koivula M (1995) Attraction of kestrels to vole scent marks visible in ultraviolet light. Nature 373:425-427 Weiss MR (1991) Floral colour changes as cues for pollinators. Nature 354:227229 Wiley RH (1994) Errors, exaggeration, and deception in animal communication. In: Real LA (ed) Behavioral Mechanisms in Evolutionary Ecology. University of Chicago Press, Chicago, pp 157-189 Wright S (1943) An analysis of local variability of flower color in Linanthus parryae. Genetics 28:139-156 Zahavi A (1975) Mate-selection – a selection for a handicap. J Theor Biol 53:204214 Zhang S, Schwarz S, Pahl M, Zhu H, Tautz J (2006) A honey bee knows what to do and when. J Exp Biol 209:4420-4428
Chapter 2
Vocal communication in social groups CLAUDIA FICHTEL AND MARTA MANSER
ABSTRACT Vocal communication plays a particularly important role in the regulation of social interactions and in the coordination of activities in many mammals and birds that are organised into social groups. Previous research on the function and evolution of vocal signals has mainly considered dyadic interactions of a signaller and its addressed receiver. However, in social groups it is likely that additional individuals attend to dyadic communication and that they use this information to their own benefit, sometimes at a cost to the signaller. To improve existing communication models, benefits and costs of vocal communication caused by bystanders must therefore also be considered. Here we discuss vocal communication in social groups and identify the effects of additional individuals on signalling interactions, concentrating on audience effects, eavesdropping and group coordination. First, a review of the existing literature reveals that the presence of an audience, i.e., additional individuals within the signalling range, clearly affects the outcome of communicative interactions, and that individuals modulate their signalling behaviour according to the presence of bystanders or a particular category of bystanders in a variety of contexts. Second, social knowledge acquired by eavesdropping on the communicative network within a group influences not only future actions, but can also provide individual benefits for eavesdroppers, whereas mutual eavesdropping can structure cooperation and alliance formation, and, hence, contribute to long-term group stability. Third, communicative networks also provide a means to facilitate the maintenance of group cohesion and decisionmaking processes. In conclusion, cost-benefit analyses at the level of dyadic interactions reveal clear differences with communication networks, where repeated interactions with multiple partners are considered. Future communication models and empirical studies should therefore consider the composition of the entire communication network as well as the effects of repeated interactions to fully understand signalling interactions in social groups.
30
Claudia Fichtel and Marta Manser
2.1. Introduction Communication is of central importance in the life of social animals. Due to their far-reaching effects on social relationships, survival and reproduction, communication systems are among the key research models to understand biological processes at the ultimate and proximate level. Animals communicate with each other using different sensory modalities (Bradbury and Vehrencamp 1998, Schaefer this volume, Penn and Frommen this volume); here we focus on acoustic signals. Communication in the broadest sense is defined as the interaction between a sender delivering a signal to a receiver attending to it and subsequently changing its behaviour (Bradbury and Vehrencamp 1998, Maynard Smith and Harper 2003). The three elements involved in communication – sender, signal and receiver – are connected by an optimising principle to make the signal as efficient as possible (Smith 1981, Bradbury and Vehrencamp 1998). Signals are ‘an act or structure that alters the behaviour of other organisms, because of that effect, and which is effective because the receiver’s response has also evolved’ (Maynard Smith and Harper 2003). In contrast, cues are ‘a feature of the world, animate or inanimate, that can be used by an animal as a guide to future action’ (Maynard Smith and Harper 2003). They are a by-product of an animal’s behaviour, such as body postures or noises inadvertently produced while eating, fleeing or mating, from which other individuals may in turn gain information about the specific context or traits of the sender. Cues are also given in the absence of receivers and are not selected for communication because they are inadvertently provided (Danchin et al. 2004). Both, signals and cues, provide information for recipients. Signal transmission has traditionally been viewed as a dyadic interaction between a sender and a receiver (Bradbury and Vehrencamp 1998). However, in social groups where multiple potential senders and receivers are present, communication occurs within a network consisting of many individuals (McGregor and Dabelsteen 1996, McGregor 2005). The fact that information is accessible to a broad audience (public information) allows individuals not only to gather information while observing communication between other individuals (social information) but also to acquire novel information by social learning (see van Schaik this volume). Social information can be gained by eavesdropping: an act in which third-party bystanders extract information from signalling interactions of others (McGregor and Dabelsteen 1996, McGregor 2005). Although the acquisition of social information is faster and achieved at lower costs than acquiring this information through individual experience, it bears the risk of ac-
Vocal communication in social groups
31
BOX 2.1 Definitions and terminology Audience or bystander: individual that is present, but does not take actively part in communicative interactions between others Audience effect: changes in the signalling behaviour caused by the presence of other individuals, of which the signaller is aware Communication: interaction between an individual (sender) delivering a signal to another individual (receiver) using it to make a decision Communication network: a set of interacting individuals within the signal range Cue: a feature of the world, animate or inanimate, that can be used by an animal as a guide to future action; not selected for communication Eavesdropping: the act of extracting information from signalling interactions between other individuals Information: property of a source – entity or a process – eliciting a reaction of a receiver in a biologically functional manner Interceptive eavesdropping: an individual benefits by intercepting signals intended for another individual, usually at a cost to a signaller Receiver: individual perceiving a signal or cue and likely altering its behaviour because of that Sender: individual producing a signal or a cue Signal: any act or structure that alters the behaviour of other organisms, which has been selected for communication Social eavesdropping: when individuals gather information on other individuals by attending to their signalling interaction (McGregor and Dabelsteen 1996, Bradbury and Vehrencamp 1998, Jablonka 2002, Maynard Smith and Harper 2003)
quiring false information (Laland 2004, Danchin et al. 2004, Dabelsteen 2005, Bonnie and Earley 2007). In addition, communication in stable social networks includes the potential for individuals to integrate information from past interactions into future actions, which in turn may have consequences for the costs and benefits of any given signalling action. Moreover, in stable social groups communication appears to facilitate the coordination of activities to achieve tasks that would not be possible were they to act alone (Sumpter and Brännström 2008). Acoustic communication is of special interest in studying communication networks because acoustic signals are typically loud, conspicuous and travel over long range and can hence be perceived by more individuals than the intended receiver. The production of acoustic signals is to a degree flexible and can be adjusted to the audience. Acoustic signals are used in a variety of contexts, including territorial defence, mating, parent-
32
Claudia Fichtel and Marta Manser
offspring interactions, predation, regulation of social interaction and coordination of group movements (Bradbury and Vehrencamp 1998); all contexts in which bystanders may gain important information for their future actions. Acoustic signals may convey basic information about the sender, such as its individual and group identity, age, sex, size, condition and motivational state, i.e. its tendency to react in a specific way (Hauser 1996, Bradbury and Vehrencamp 1998). Most of the time specific call types also seem to be related to the sender’s external context (reviewed in Manser 2009), such as contact calls while foraging, or travelling calls while moving (Boinski 1991). Moreover, some signals refer to specific attributes of objects or events in the external environment of the caller, as shown for food recruitment calls (Hauser 1998, Bugnyar et al. 2001, DiBitetti 2003, Gros-Louis 2004a) and functionally referential alarm calls in several primates (Seyfarth et al. 1980, Pereira and Macedonia 1991, Zuberbühler et al. 1999, Fichtel and Kappeler 2002), other mammals (Owings and Leger 1980, Slobodchikoff et al. 1991, Manser 2001, Manser et al. 2001) and birds (Evans et al. 1994, Griesser 2008). These signals function in a variety of ways to affect the behaviour of receivers. In territorial defence or mate attraction, signals are addressed at a broad class of receivers and may function to repel competitors and/or attract mates, respectively (Reby et al. 1999, Kitchen 2004, Catchpole and Slater 2008). In these situations, signal variation might be associated with the quality of the sender and signals from particular individuals are considered to be honest (Zahavi 1977, Zahavi and Zahavi 1997). Signals may also reflect variation in the affective state of the sender (Morton 1977, Marler 1992, Fichtel et al. 2001), and they may function to communicate what the sender is going to do next. In this chapter, we emphasise the role of communication networks in species living in stable social groups where individuals have many opportunities to monitor social interactions of several conspecifics simultaneously and repeatedly. In such groups, acoustic signals are usually also received by several individuals other than the addressed recipient, which in turn may have a direct impact on signalling interactions or their outcome. Moreover, communication interactions may have delayed and long-lasting influences on individual behaviour. We therefore focus on two related aspects; namely how the presence of other individuals influences the production of signals, and how additional receivers filter out the important information when they are not primarily addressed. Identifying the potential costs and benefits of the presence or influence of additional individuals as audience or eavesdroppers of a communicative act will help to illuminate to what extent these boundary conditions influence signalling behaviour. To this end, we first examine examples in which network members influ-
Vocal communication in social groups
33
ence the outcome of a signalling interaction (audience effect) and subsequently focus on situations in which others gain information by eavesdropping (social and interceptive eavesdropping). Third, we illustrate the use of signals that are explicitly addressed at several recipients and may facilitate group cohesion or decision-making processes. Finally, we discuss cost-benefit analyses of vocal communication within networks by the present models and suggest future directions for research that will enhance our understanding of animal societies in general.
2.2 Audience effects With the production of a signal, information is available to all individuals present within the signal range, and signallers often behave differently, depending on the presence and identity of others (Marler et al. 1986). This adjustment of behaviour, the so-called audience effect, requires that the caller is aware of the presence of specific receivers, and it indicates that signals are produced strategically, rather than involuntarily. Audience effects have first been described in chickens (Gallus gallus) emitting alarm and food calls. Cocks preferably emit food calls in the presence of hens, sometimes even when no food is available (Marler et al. 1986). Furthermore, both sexes emit terrestrial alarm calls, but males only emit aerial alarm calls when conspecifics are close by (Karakashian et al. 1988). A similar audience effect on callers has since been described in several other species (see below). Principally, we can distinguish between contexts, in which simply the presence of a receiver triggers calling, and contexts, in which bystanders attend to interactions between signallers and receivers (eavesdrop), and may gather information to make decisions about future actions. In contexts, in which the targeted receivers also act as audience, different categories have been identified. Signallers have been described to be affected in their call production by: i) the mere presence of a receiver; ii) the presence of a specific receiver category; or iii) the specific context the receiver finds itself in. The comparison between situations in which a signaller either emits a call when a receiver is present or not allows to test whether individuals have voluntary control over call production, or whether call production is an involuntary response to a specific context (Evans 1997). This question has mainly been investigated in the context of the production of alarm calls. Calls that are typically directed towards a predator and/or conspecifics, so-called mobbing calls, are emitted independent of whether an audience of conspecifics is nearby or not, whereas
34
Claudia Fichtel and Marta Manser
alarm calls emitted to warn group members are typically produced if a conspecific is nearby (Thomas langurs, Presbytis thomasis: Wich and Sterck 2003; yellow mongoose, Cynictis penicillata: Le Roux et al. 2008). Audience effects have also been described for interactions between species, where fork-tailed drongos (Dicrurus adsimilis) adjust their alarm call production when foraging with a group of pied babblers (Turdoides bicolour: Ridley et al. 2007). Not only the mere presence of a receiver influences the calling behaviour of animals, but also the identity or the behaviour of the audience. For example, in chickens, cocks adjust their production of alarm and food calls depending on the sex of conspecifics present (Marler et al. 1986). In Belding’s ground squirrels (Spermophilus belding), alarm calls are more likely emitted when close kin is nearby (Sherman 1977). In capuchin monkeys (Cebus capucinus), individuals finding food are more likely to emit calls when high-ranking individuals are close by than low-ranking ones (GrosLouis 2004b). Rumble vocalisations of elephants (Loxodonta africana) cause a decrease in the distance between individuals, and this effect is enhanced among highly affiliated social partners (Leighty et al. 2008). In banded mongoose (Mungos mungo), pups adjust their calling rate to the identity of their targeted providers (Bell 2008). Two recent studies suggested that callers also take the context or behaviour of their addressed audience into account and adjust calling accordingly. In blue monkeys (Cercopithecus mitis) males appear to take the level of danger experienced by the other group members into account when emitting alarm calls (Papworth et al. 2008). Similarly, Thomas langurs do not stop giving alarm calls when threatened by a predator until every single group members has responded with an alarm call, suggesting that they keep track of who has responded and who has not (Wich and de Vries 2006). Audience effects in triadic contexts involve the sender, a receiver and a bystander. In chimpanzees (Pan troglodytes), victims of aggression tend to modify the acoustic structure of their screams to exaggerate the situation, but only in the presence of individuals that are capable of intervening and supporting the caller (Slocombe and Zuberbühler 2007). Moreover, female chimpanzees are more likely to produce copulation calls in the presence of high-ranking males, but they are less likely to call when high-ranking females are nearby, suggesting that adjustment of calling rate may serve to reduce competition among females (Townsend et al. 2008). Avoidance of potential conflicts by adjusting call rate has also been suggested for nomadic male lions (Panthera leo), who benefit by roaring to enhance social ties with potential cooperators. However, in the presence of resident males they call less often, thereby concealing their own presence to avoid poten-
Vocal communication in social groups
35
tial costs of escalated conflicts by eavesdropping on resident males (Grinnell and McComb 2001). Although most studies on audience effects have dealt with the production of alarm and food calls, and some have focussed on aggressive interactions, the examples above show that these effects can occur in almost any context of communication. Furthermore, some recent studies revealed that not only the production of the signals, but also the response of receivers to these signals is affected by the presence of additional receivers. In rhesus macaques (Macaca mulatta), the outcome of mother-infant interactions was influenced by the potential risk of aggression posed by bystanders (see BOX 2.2, Semple et al. 2009). The likelihood of mothers allowing crying infants access to the nipple was higher in the presence of high-risk bystanders than during control situations or in the presence of low-risk bystanders. Finally, the presence of additional signallers can also influence a communicative act. The begging behaviour of nestlings in several bird species (Wright and Leonard 2002) and that of mammalian pups has been shown to be affected by siblings that either directly compete with each other and cause an increase in begging intensity (Price et al. 1996), or that cooperate and decrease begging intensity when others are present (Bell 2007). Therefore, in communication networks with more than just a single actor and reactor, both the production of signals and the response to them can be affected by presence of additional individuals. Audience effects on signal interactions have presumably evolved depending on the benefits and costs imposed on the signaller or intended receivers by the presence of bystanders. The examples above indicate that by taking the presence of bystanders, or of a particular category of bystanders, into account, individuals involved in signal interactions can benefit by either enhancing or inhibiting the production of signals. Contexts for enhancing signal production include the attraction of mates (Marler et al. 1986) or recruitment to food sources (Gros-Louis 2004b). Contexts for inhibiting signal production include aggressive interactions either within a group (e.g., infant crying in rhesus macaques), between groups (e.g., lions avoiding the attention of resident males), but also between species (e.g., killer whales, Orcinus orca, reducing vocal activity while hunting, see below). This perspective clearly shows the flexibility of animals in the production of acoustic signals, but also the necessity to consider communication within the existing social network, and not only as the sum of dyadic interactions, to understand the variation of signaller’s and receiver’s behaviour in similar contexts.
Claudia Fichtel and Marta Manser BOX 2.2 Audience affects the outcome of mother-infant interactions in rhesus macaques Research question: Infants in rhesus macaques (Macaca mulatta) cry to get access to their mother’s nipple. The question was whether crying is acoustically aversive, and therefore bystanders exhibit aggression towards the mother or the infant to stop the crying. It was predicted that mothers should respond more often to crying by allowing infant access to their nipples in the presence of potentially aggressive animals.
100
a)
Percentage of bouts in which access was given
Percentage of bouts in which access was given
Methods: 9 adult rhesus females that had dependent infants were observed in a free-ranging population on Cayo Santiago, Puerto Rico. All crying bouts of a focal mother’s infant were recorded and quantified for: i) the number and identity of bystanders within 2 m of the focal mother; ii) the occurrence of aggression towards the mother or the infant during the crying bout; iii) the type of aggression and the identity of the aggressive animal; iv) whether contact was made with the nipple. Each crying bout was then classified according to the presence of i) no bystanders; ii) low-risk bystanders; or iii) high-risk bystanders.
Percentage of bouts in which access was given
36
80 60 40 20 0
100
No bystanders
Low-risk bystanders
100
b)
80 60 40 20 0
No bystanders
High-risk bystanders
c)
80 60 40 20 0
Low-risk bystanders
High-risk bystanders
Fig. 2.1 a-c) Percentage of crying bouts in which mothers gave crying infants access to the nipple, depending on the presence and type of bystanders.
Vocal communication in social groups
37
Results: Crying was associated with increased aggression from bystanders towards mothers and infants. In particular high-risk bystanders affected the outcome of the crying bout more than low-risk bystanders (Fig. 2.1 a-c). Mothers were less likely to yield access to the nipples when no bystanders were present (39.4% of crying bouts), compared to situations when low-risk (53.5%) or at least one high-risk bystander (81.8%) were present. Conclusions: This study showed the influence of bystanders on a receiver, rather than on the signaller producing the call. It emphasises the point that the effect of additional receivers on all parties involved in a signalling interaction have to be considered to fully understand the social dynamics in group-living animals. (Semple et al. 2009)
2.3 Eavesdropping Eavesdropping is defined as the act of extracting information from signalling interactions between other individuals (McGregor and Dabelsteen 1996, McGregor 2005). Two classes of eavesdropping have been identified: social and interceptive eavesdropping (McGregor and Dabelsteen 1996, Peake 2005). Social eavesdropping occurs when individuals gather information on other individuals by attending to their signalling interaction. This form of eavesdropping has important consequences for individuals that interact regularly with several individuals and have the opportunity to monitor social and communicative interactions of other group members. In contrast, during interceptive eavesdropping, an individual benefits by intercepting signals intended for another individual, usually at a cost to the signaller. Predators and parasites commonly use interceptive eavesdropping to locate prey (Zuk and Kolluru 1998, Mougeot and Bretagnolle 2000, Bernal et al. 2007, Fichtel in press a), and competitors rely on it to oust rivals from a resource (Peake 2005). However, prey eavesdropping on vocalisations emitted by predators in turn resulted in adaptations of predators, such as transient killer whales (Orcinus orca), reducing their vocal activity while hunting on marine mammals, which have sensitive underwater hearing within the frequency range of killer whales (Deeke et al. 2005). Thus, the ability to eavesdrop and the knowledge that other species may eavesdrop (audience effect) provide a basis for the evolution of mutually fine-tuned behavioural adaptations.
38
Claudia Fichtel and Marta Manser
2.3.1 Social eavesdropping Eavesdropping plays an important role in assessing other individual’s quality in contexts such as territorial conflict or mating competition. By conducting playback experiments, it has been shown that male eavesdroppers modulate their agonistic decisions based on information obtained from listening to aggressive signalling interactions between unfamiliar males (Naguib and Todt 1997, Naguib et al. 1999, Peake et al. 2001, Mennill and Ratcliffe 2004a, Paz-y-Mino et al. 2004), where eavesdropping males usually respond more aggressively to the perceived winner (Naguib and Todt 1997, Naguib et al. 1999, Peake et al. 2001, Mennill and Ratcliffe 2004b, McGregor 2005). Females also use information transmitted during malemale aggressive interactions to assess the suitability of future males, and they prefer to mate with the winner of an observed contest (Otter et al. 1999, Menill et al. 2002, McGregor 2005). In social groups, eavesdropping is important in the acquisition of social knowledge that influences the formation of strategic alliances. Individuals of social groups form long-lasting stable relationships based on kinship, dominance or temporary affiliation (e.g., friendships in primates) of unrelated individuals (Krause and Ruxton 2002, Kotrschal et al. this volume). In order to compete successfully within such groups, it is advantageous for individuals to recognise who outranks whom, who is closely bonded to whom, and who is likely to be allied to whom. The ability to adopt a third party’s perspective and to discriminate among social relationships that exist among others would seem to be of great selective benefit (Cheney and Seyfarth 2005). Experiments revealed that primates attend extensively to vocalisations in social interactions among other group members. For example, in chacma baboons (Papio hamadryas ursinus), dominant individuals produce threat-grunts and subordinates screams during aggressive interactions. Mimicking such fights with playback experiments, Cheney and colleagues (1995) demonstrated not only that baboons pay attention to these vocal interactions, but also that simulated rank reversals elicited more attention than sequences that were consistent with the dominance hierarchy, indicating that bystanders keep track of the dominance hierarchy by regularly monitoring vocal interactions of group members. Bergman and colleagues (2003) additionally showed that baboons are able of evaluating aggressive vocal interactions not only on the basis of rank but also kinship (see BOX 2.3). Moreover, eavesdropping on conflicts involving kin enhances the opportunity to support relatives in these conflicts, which in turn may have long-term consequences on relative’s dominance rank (Engh et al. 2009). Thus, eavesdropping may have played an important proximate
Vocal communication in social groups
39
role in the evolution of alliance formation and cooperation (Cheney and Seyfarth 2005, Covas et al. 2007, Bshary this volume). Eavesdropping on vocal utterances of group members allows individuals not only to gather information by listening to dyadic interactions but also by combining information gained from vocalisations of individuals that do not directly interact with each other. In baboons, dominant males monopolise matings by forming consortships with oestrous females that are characterised by mate guarding and close proximity. Baboons usually produce grunts when travelling and foraging and females produce copulation calls while mating. Crockford and colleagues (2007) mimicked a temporal separation of the consorting male and its respective female by broadcasting the consort male’s grunts from one speaker and the female’s copulation calls from another speaker 40 m apart, simulating that she is copulating with another male. Lower-ranking males that were tested with this playback experiment approached the speaker with the female calls more often than after control trials, indicating that eavesdropping on other’s vocalisation might be one strategy by which male baboons achieve sneaky matings. In other species with stable social networks, such as African elephants, social knowledge seems to provide fitness benefits for receivers. African elephants live in complex fission-fusion societies comprising different matrilineal family units led by the oldest female. Playback experiments with contact calls revealed that adult females are familiar with calls of around 100 other individuals in the population, being able to discriminate between calls on the basis of how often they associate with the caller (McComb et al. 2000). However, families differ in how good they are in this task. Linking reproductive success of the family unit with the discriminatory ability of the oldest females revealed that families with older matriarchs have higher reproductive success, some of which might be attributable to superior social knowledge (McComb et al. 2001, McComb and Reby 2005). These examples illustrate that social knowledge acquired by eavesdropping on the communicative network within a group can provide fitness benefits on eavesdroppers. Mutual eavesdropping can structure cooperation and alliance formation, and, hence, contribute to long-term group stability. Moreover, at the community level, eavesdropping has important consequences for the evolution of anti-predator strategies. Some species eavesdrop on other prey’s alarm calls. Such heterospecific alarm call recognition occurs between taxa and is usually characterised by mutual recognition of both species’ alarm calls. Heterospecific recogniton of alarm calls has been demonstrated in many social birds and mammals, but also in a non-vocal reptile, the Galápagos marine iguana (Amblyrhynchos cristatus), or non- social species such as Gunther’s dik-dik (Madoqua
40
Claudia Fichtel and Marta Manser BOX 2.3 Hierarchical classification by rank and kinship in baboons Research question: Groups of chacma baboons (Papio hamadryas ursinus) are composed of a number of different matrilines arranged in a stable, linear dominance hierarchy in which all female members of one matriline outrank or are outranked by all female members of another matriline. Ranks are typically stable, often for 20 or more years, but when they do change entire families rise in rank over others. The question was whether baboons are able to evaluate rank and kinship of aggressively interacting females simultaneously, and whether they recognise that some rank reversals may have greater social importance than others. Methods: A1 - A2 - A3 B1 - B2 - B3 C1 - C2 - C3
Fig. 2.2 Schematic illustration of three matrilines, each including three females. Matriline/family A is high-ranking, B middle and C is low-ranking. Within families, female 1 is high, 2 middle, and 3 is low-ranking.
Playback experiments were designed to mimic a fight between two females. During aggressive interactions dominant females produce threat-grunts whereas subordinate females produce screams (A1 threat-grunts => A3 screams). To simulate a rank reversal threat-grunts and screams of different ranking females were broadcast from a hidden loudspeaker in an inconsistent order (A3 threat-grunts => A1 screams). 19 adult females living in the Okavango Delta in Botswana (all of known matrilineal kinship) were tested with 3 different playback trials: (1) (2) (3)
within family rank reversal (A3 threat-grunts => A1 screams) between family rank reversal (B3 threat-grunts => A1 screams) no-reversal control consistent with the rank order (A1 threat-grunts => A3 screams)
Based on video-recordings, the time females spent looking towards the speaker was measured.
Results: Individuals spent more time looking towards the speaker after the presentation of betweenfamily rank reversals than after within-family rank reversals or the control. Time spent looking towards the speaker did not differ after the presentation of within-family rank reversal and the control, however (Fig. 2.3).
Duration of looking [sec]
Vocal communication in social groups
41
5 4 3 2 1 0
Between family
Within family
No reversal control
Conclusions: Baboons are able to classify others simultaneously according to both individual rank and kinship. The selective pressures imposed by complex societies may therefore have favoured cognitive skills that allow monitoring rank reversals by eavesdropping on aggressive interactions of group members. (Bergman et al. 2003)
guentheri; Seyfarth and Cheney 1990, Shriner 1998, Fichtel 2004, Vitousek et al. 2007, Magrath et al. 2007, Lea et al. 2008, Müller and Manser 2008). In addition, in mixed-species associations, in which groups of different species regularly travel and forage together, eavesdropping on the other’s species alarm calls provides mutual benefits. Because mixedspecies groups often consist of species that preferentially use different habitat strata, each species benefits by the complementary sensitivity in predator detection (Fichtel in press b) and extended foraging niches (Gautier-Hion et al. 1983, McGraw and Bshary 2002, Wolters and Zuberbühler 2003). Thus, the ability to eavesdrop is one of the prerequisites for the formation of mixed-species associations.
2.4 Group cohesion and group coordination Living in groups has many benefits but also generates conflicts due to individual differences in needs depending on age, sex or social status (Alexander 1974, Bertram 1978, van Schaik 1983, Zemel and Lubin 1995). To maintain group cohesion and social stability despite these conflicts, individuals need to synchronise and coordinate their activities such as foraging, resting, social interactions and collective movements (Conradt and Roper 2003, 2007, Rands et al. 2003, Kerth et al. 2006, Kerth this volume). In the context of maintaining group cohesion and coordination, many animals produce vocal signals (Boinski and Garber 2000, Radford
42
Claudia Fichtel and Marta Manser
2004, Trillmich et al. 2004). These calls have usually been labelled as contact calls and are widespread among social mammals and birds. Contact calls may serve as a ‘location marker’ to announce the caller’s spatial position and to regulate spacing between group members, but also to signal group identity. These calls are usually given at high rates when groups move or forage and appear to be addressed at a group of targets; however, in some cases the same calls are also addressed at specific targets. Many social species produce contact calls when travelling, foraging and resting (Struhsaker 1967, Boinski 1993, Rendall et al. 2000, Radford 2004, Trillmich et al. 2004, Koda et al. 2008). For example, group-living pied babblers regularly produce so-called chucks while foraging to maintain cohesion, but also to regulate spacing of potential foraging competitors (Radford and Ridley 2006). Contact calls appear to be addressed at a class of targets and in many primate species, such as chacma baboons or Japanese macaques (Macaca fuscata), call rate increases when the risk of becoming separated from the group is increased (Rendall et al. 2000, Koda et al. 2008). From the sender’s perspective these calls appear to signal the senders’ location. However, from the receiver’s perspective, their function is less well understood, and contact calls may modulate the receiver’s tendency to approach or to avoid individuals. Thus, contact calls appear to have an important function within the signalling network of a group in the maintenance of cohesion, but the proximate mechanism driving the contact function are not entirely clear. In contrast, the function of the same type of contact calls seems to vary when they are addressed at a specific target. Many primates, such as baboons or macaques, produce contact calls when approaching other individuals, and the likelihood of a subsequent peaceful interaction is higher when approaches are accompanied by a contact call. During social interactions, contact calls seem to communicate the intention to behave peacefully towards others and may function as generic commitments conveying information about what animals will do next (Bauers 1983, Masataka 1989, Cheney et al. 1995, Rendall et al. 2000, Silk et al. 2000, Silk 2001). Thus, according to the audience, i.e. a group of targets or specific targets, the function of contact calls varies in some species from maintaining group cohesion to regulating social interactions. In addition, many species produce vocalisations to indicate their readiness to travel or to initiate group movements (reviewed by Boinski 2000). So-called travel calls (Boinski 1991) have been described in birds and mammals but mainly in primates (reviewed in Fichtel et al. in press). For example, group-living birds, such as green woodhoopoes (Phoeniculus purpureus) and domestic geese (Anser domesticus), or primates, such as squirrel and capuchin monkeys, use specific calls to initiate group move-
Vocal communication in social groups
43
ments and to recruit group members (Boinski 1993, Radford 2004). Some species also combine visual and acoustic displays to initiate movements, Barbary macaques (Macaca sylvanus) shake twigs or drum on dead wood (Mehlmann 1996), and elephants produce a specific rumble-call in combination with ear flagging (Poole et al. 1988). However, some species do not produce a specific travel call to initiate movements, but exchange contact calls during the decision-making processes before the group’s departure. For example, Guinea baboons (Papio papio) exchange contact barks to coordinate themselves before the group splits up into subgroups or fusions again (Byrne 1981). Verreaux’s sifakas (Propithecus verreauxi) do not produce a specific travel call to initiate movements, but contact calls before leaping off, suggesting that these are involved in the decision-making process of the group’s departure (Trillmich et al. 2004). Thus, the use of vocal signals that are directed at a broad audience and used to initiate and coordinate group movements seems to be widespread in group-living animals and might be an important mechanism of decision-making processes of movements (see also Kerth this volume). However, detailed empirical data on information transfer by acoustic signals driving decision-making processes are rare and represent a promising future research area in communication networks. Within a signalling network, animals can also benefit from coordinated activity via passive transfer of cue-based information of acoustic signals produced as a by-product of other behaviours. For example, rough-toothed dolphin (Steno bredanensis) subgroups often synchronise their swimming behaviour in order to save energy caused by positive hydrodynamic effects. During synchronised swimming, usually only one group member produces echo-locating signals and the other members are silent to avoid ambiguous echo scenery, thereby eavesdropping on the signalling individual, which may lead to further energy savings (Götz et al. 2006). Moreover, lesser bulldog bats (Noctilia albiventris) produce echo-locating calls when prey has been detected and is being attacked. Playback experiments revealed that these inadvertently produced cues attract other group members, facilitating social foraging and potentially more efficient exploitation of patchily distributed food resources (Dechmann et al. 2009). Moreover, inadvertently produced cues may also serve as alarm signals. In crested pigeons (Ocyphaps lophotes), which have modified flight feathers that cause a distinct whistle when flying off, it has been shown that other group members use these cues as alarm signals (Hingee and Magrath 2009). Thus, these examples illustrate that the production of acoustic signals or cues provides public information for group members, which in turn may facilitate group cohesion and coordination of activities.
44
Claudia Fichtel and Marta Manser
2.5 Costs-benefit analyses of signalling networks in social groups Communication evolves due to direct or indirect benefits to the signaller and receiver by the production of a signal, with the net gain potentially differing between them. The fact that senders adjust their calling behaviour depending on receivers acting as audience or eavesdroppers, suggests that uncontrolled signalling induces costs. It also indicates that to understand the evolution of communication we do not only have to consider a dyadic interaction between a sender and a receiver, but also the network of additional animals exposed to the signal’s transmission. The costs and benefits of adjusting signalling may be more affected in the production of costly rather than cheap signals and when the variation between receivers is large (Searcy and Nowicki 2005). In social groups, where a sender is likely to be surrounded by individuals differing in status, age, sex, reproductive stage or condition, the variation of the net gain to adjust signalling will depend on the size and heterogeneity of the group. Furthermore, the likelihood of interacting repeatedly with the same individuals is high, which can affect the ESS in signalling behaviour compared to one-time interactions (Silk et al. 2000). Cost-benefit analyses and theoretical models focusing on dyadic actor-reactor situations (e.g. Johnstone 1998) are thus unlikely to reflect the full complexity of communication in group-living species, where multiple senders and receivers interact repeatedly with each other. The early models of communication considering only dyadic one-time interactions between a single signaller and a receiver may explain the basic underlying mechanisms. However, more recent models in which the influence of additional individuals and repeated interactions on signalling interactions has been considered in specific contexts indicated that these factors can influence the outcome importantly. For example, in the context of begging, it has been shown that the presence of other individuals, in this case siblings, can affect the begging behaviour and cause different ESS in calling behaviour, depending on whether multiple signallers compete with each other (Godfray 1995) or cooperate (Johnstone 2004) while addressing the same receiver(s). For low-cost signals that have been suggested to evolve only when the benefits to both the signaller and the receiver are similar, a game-theoretical model that allowed individuals to interact repeatedly, revealed that low-cost signals can also evolve when conflicts of interests exists between sender and listener (Silk et al. 2000). Sumpter and Brännström (2008) suggested that costly signalling can evolve through synergy. By communicating within a network the group becomes more effective than the sum of their parts (see BOX 2.4). In addition, theoretical
Vocal communication in social groups BOX 2.4 Mechanistic model of foraging: synergy effect due to communication Research question: Foraging success and colony size correlate in cliff swallows (Petrochelidon pyrrhonota, Fig. 2.4; Brown and Brown 1996). Both, the amount of food collected by the parents per foraging trip and the frequency of trips increased with colony size. When these factors were combined, they appeared to add up to a linear increase in per capita success with colony size. The question, therefore, is why foraging success increases with colony size? Fig. 2.4 The amount of food collected per parent cliff swallow increases with colony size.
Amount of food collected per foraging trip [g]
1.0 66
0.8 0.6
27 43
15 37
9 31
0.4
3
0.2 1
10
100
1000
10000
Colony size
Model: General framework of the mechanism of how a group of communicating foragers finds a food source. A group of n individuals consists of x individuals that are informed about the location of the food source. This also means that x is a measure of group productivity, because it is the number of successful foragers at any point, and x/n equals per capita success because it represents the proportion of informed individuals in the group. The rate per individual of finding the feeder is given by the function f(x). The rate per individual of losing the food source is given by g(x). Both functions f and g differ depending on the recruitment mechanism used by the modeled species. Therefore the rate of change of the number of individuals going to the feeder is:
dx f ( x)(n x) g ( x) x dt Solving
→
(t denotes time)
f ( x*)(n x*) g ( x*) x *
(x* is the equilibrium, or long-term, number of individuals going to the feeder). The change of this equilibrium with n determines how foraging efficiency changes with group size.
45
46
Claudia Fichtel and Marta Manser Conclusions: If we assume that social communication increases the rate at which individuals find the food source, then f(x*) increases and g(x*) decreases. As a direct consequence, each individual will profit from signalling about the food location as the feedback loop increases the total gain more than the summed benefits, and this effect may explain the pattern found in cliff swallows. (Sumpter and Brännström 2008)
models including multiple senders and receivers suggest that the main function of signalling networks is to facilitate collective action, and to guide group decisions that lead to coordinated action (Skyrms 2009). The different empirical studies reporting effects of additional individuals within the active signal range on signalling behaviour clearly emphasise the fact that variation in the composition of communication networks needs to be considered in cost-benefit analyses. However, existing theoretical models have only integrated additional senders and receivers to a limited extent. This may have two reasons: first, communication networks have only been recently emphasised (McGregor and Dabelsteen 1996), and secondly, dynamic analyses including multiple senders and receivers or repeated interactions result in complex signalling games that are mathematically challenging (Skyrms 2009). In addition, empirical studies that not only identify the dyadic interactions, but also describe the outcome of them in relation to the network and repeated interactions are still missing. For example, the benefits of attracting others by advertising a food source and partially sacrificing the caller’s own share (Gyger et al. 1986, Hauser and Marler 1993, Evans et al. 1994, Wilkinson and Boughman 1998, Di Bitetti 2003, Gros-Louis 2004b) have been intensely debated. Food callers may benefit by increasing their inclusive fitness, or decreasing predation risk or reciprocation (Elgar 1986, Heinrich and Marzluff 1991, Wilkinson and Boughman 1998). However, Sumpter and Brännström (2008) suggested that by communicating within a network, animals can increase their rate of finding food and costly signalling can evolve through synergy, where the gain for the group members by communicating with each other becomes more than the sum of their parts. Furthermore, the example of baboons, which use their memory of recent interactions to make inferences about whether a call is being directed at themselves or at some other individual (Engh et al. 2006), indicates the need to investigate signalling behaviour as a function of repeated interactions. Thus, the composition of the communication network and the repeated use of signals, as well as coordinated activities in social groups, clearly influence when and how they are used, in addition to the factors identified to affect dyadic interactions.
Vocal communication in social groups
47
2.6 Conclusions and outlook for future studies Vocal communication in social groups does not only include dyadic signalling interactions, but is affected by the presence of additional individuals within the signal range. To understand the function and evolution of specific signals, we therefore have to consider the entire communication network. Such an approach may reveal that benefits and costs must not be constant, but instead reflect non-linear functions of group size and composition. This insight furthers a better understanding of why different forms of social communication evolved in different types of groups (Sumpter and Brännström 2008). Adopting this perspective also allows the formulation of empirically testable predictions. Without knowing the mechanism of communication and how they depend upon the number, identity or quality of interacting individuals, we cannot predict whether or not a particular form of communication will evolve. It is important to measure the benefit function in a wide range of contexts, considering different group sizes and different group compositions (homogenous versus heterogeneous). Together with models that include multiple interacting individuals, we will be able to identify which factors and interactions drive the evolution of variation in vocal communication in social groups. Moreover, more empirical studies are required to identify the effects of social communication within the networks and to compare the outcomes of dyadic interactions without any bystanders to multiple interactions among several or all group members. The comparison of signalling behaviour in small groups versus large groups on group decision-making processes and the function of contact calls will permit identification of the effect of the presence of multiple individuals. Furthermore, eavesdropping and its influence on future actions have only been investigated in a few contexts and species, but it is likely to affect the dynamics of social groups extensively. Determining whether it is simply the number of individuals involved in a signalling interaction or their identity will also contribute to our understanding of communication in social groups.
Acknowledgements We thank Peter Kappeler for the invitation to contribute to this book. Additionally,we are grateful to Dan Blumstein, Peter Kappeler, Martin Schaefer and Robert Seyfarth for helpful comments on an earlier version or parts of this chapter.
48
Claudia Fichtel and Marta Manser
References Alexander RD (1974) The evolution of social behavior. Annu Rev Ecol Syst 5:325-383 Bauers KA (1993) A functional analysis of staccato grunt vocalizations in the stumptailed macaque (Macaca arctoides). Ethology 94:147-161 Bell MBV (2007) Cooperative begging in banded mongoose pups. Curr Biol 17:717-721 Bell MBV (2008) Receiver identity modifies begging intensity independent of need in banded mongoose (Mungos mungo) pups. Behav Ecol 19:1087-1094 Bergman TJ, Beehner JC, Cheney DL, Seyfarth RM (2003) Hierarchical classification by rank and kinship in baboons. Science 302:1234-1236 Bernal XE, Page RA, Rand AS, Ryan MJ (2007) Cues for eavesdroppers: do frog calls indicate prey density and quality? Am Nat 169:409-415 Bertram BCR (1978) Living in groups: predators and prey. In: Krebs JR, Davies NB (eds) Behavioural Ecology: An Evolutionary Approach. Blackwell, Oxford, pp 64-96 Boinski S (1991) The coordination of spatial position: a field study of the vocal behaviour of adult female squirrel monkeys. Anim Behav 41:89-102 Boinski S (1993) Vocal coordination of troop movement among white-faced capuchin monkeys, Cebus capucinus. Am J Primatol 30:85-100 Boinski S (2000) Social manipulation within and between troops mediates primate group movement. In: Boinski S, Garber PA (eds) On the Move: How and Why Animals Travel in Groups. University of Chicago Press, Chicago, pp 421-469 Boinski S, Garber PA (2000) On the Move: How and Why Animals Travel in Groups. University of Chicago Press, Chicago Bonnie KE, Earley RL (2007) Expanding the scope for social information use. Anim Behav 74:171-181 Bradbury JW, Vehrencamp SL (1998) Principles of Animal Communication. Sinauer Associates, Sunderland/MA Bugnyar T, Kijne M, Kortschal K (2001) Food calling in ravens: are yells referential signals? Anim Behav 61:949-958 Byrne RW (1981) Distance vocalizations of Guinea baboons (Papio papio): an analysis of function. Behaviour 78:283-312 Catchpole CK, Slater PJB (2008) Birdsong: Biological Themes and Variations. University of Chicago Press, Chicago Cheney DL, Seyfarth RM (2005) Social complexity and the information acquired during eavesdropping by primates and other animals. In: McGregor PK (ed) Animal Communication Networks. Cambridge University Press, Cambridge, pp 583-603 Cheney DL, Seyfarth RM, Silk JB (1995) The responses of female baboons (Papio cynocephalus ursinus) to anomalous social interactions: evidence for causal reasoning? J Comp Psychol 109:134-141
Vocal communication in social groups
49
Conradt L, Roper TJ (2003) Group decision-making in animals. Nature 421:155158 Conradt L, Roper TJ (2007) Democracy in animals: the evolution of shared group decisions. Proc R Soc Lond B 274:2317-2326 Covas R, McGregor PK, Doutrelant C (2007) Cooperation and communication networks. Behav Proc 76:149-151 Crockford C, Wittig RM, Seyfarth RM, Cheney DL (2007) Baboons eavesdrop to deduce mating opportunities. Anim Behav 73:885-890 Dabelsteen T (2005) Public, private or anonymous? Facilitating and countering eavesdropping. In: McGregor PK (ed) Animal Communication Networks. Cambridge University Press, Cambridge, pp 38-62 Danchin E, Giraldeau L-A, Valone TJ, Wagner RH (2004) Public information: from nosy neighbors to cultural evolution. Science 305:487-491 Dechmann DKN, Heucke SL, Giuggioli L, Safi K, Voigt CC, Wikelski M (2009) Experimental evidence for group hunting via eavesdropping in echolocating bats. Proc R Soc Lond B 276:2721-2728 Deecke VB, Ford JKB, Slater PJB (2005) The vocal behaviour of mammal-eating killer whales: communicating with costly calls. Anim Behav 69:395-405 DiBitetti MS (2003) Food-associated call of tufted capuchin monkeys (Cebus apella nigritus) are functionally referential signals. Behaviour 140:565-592 Elgar MA (1986) House sparrows establish foraging flocks by giving chirrup calls if the resources are divisible. Anim Behav 34:169-174 Engh AL, Hoffmeier RR, Cheney DL, Seyfarth RM (2006) Who, me? Can baboons infer the target of vocalizations? Anim Behav 71:381-387 Engh AL, Hoffmeier RR, Seyfarth RM, Cheney DL (2009) O brother, where art thou? The varying influence of older siblings in rank acquisition by female baboons. Behav Ecol Sociobiol 64:97-104 Evans CS (1997) Referential signals. In: Owings DH, Beacher MD, Thompson NS (eds) Perspectives of Ethology. Plenum Press, New York, pp 99-143 Evans CS, Evans L, Marler P (1993) On the meaning of alarm calls: functional reference in an avian vocal system. Anim Behav 46:23-38 Fichtel C (2004) Reciprocal recognition in sifaka (Propithecus verreauxi verreauxi) and redfronted lemur (Eulemur fulvus rufus) alarm calls. Anim Cogn 7:45-52 Fichtel C (in press a) Costs of alarm calling: lemur alarm calls attract fossas. Lemur News Fichtel C (in press b) Predation on primates. In: Mitani JC, Call J, Kappeler PM, Palombit R, Silk J (eds) The Evolution of Primate Societies. University of Chicago Press, Chicago Fichtel C, Kappeler PM (2002) Anti-predator behavior of group-living Malagasy primates: mixed evidence for a referential alarm call system. Behav Ecol Sociobiol 51:262-275 Fichtel C, Hammerschmidt K, Jürgens J (2001) On the vocal expression of emotion. A multi-parametric analysis of different states of aversion in the squirrel monkey. Behaviour 138:97-116
50
Claudia Fichtel and Marta Manser
Fichtel C, Pyritz LW, Kappeler PM (in press) Coordination of group movements in non-human primates. In: Boos M, Kolbe M, Ellwart S, Kappeler PM (eds) Coordination in Human and Non-human Primate Groups. Springer, Heidelberg Gautier-Hion A, Quris R, Gautier J-P (1983) Monospecific vs polyspecific life: a comparative study of foraging and antipredatory tactics in a community of Cercopithecus monkeys. Behav Ecol Sociobiol 12:325-335 Godfray HCJ (1995) Signaling of need between parents and young: parentoffspring conflict and sibling rivalry. Am Nat 146:1-24 Götz T, Verfuss UK, Schnitzler H-U (2006) ‘Eavesdropping’ in wild roughtoothed dolphins (Steno bredanensis)? Biol Lett 2:5-7 Griesser M (2008) Referential calls signal predator behavior in a group-living bird species. Curr Biol 18:69-73 Grinnell J, McComb K (2001) Roaring and social communication in African lions: the limitations imposed by listeners. Anim Behav 62:93-98 Gros-Louis J (2004a) The function of food-associated calls in white-faced capuchin monkeys, Cebus capucinus, from the perspective of the signaller. Anim Behav 67:431-440 Gros-Louis J (2004b) Responses of white-faced capuchins (Cebus capucinus) to naturalistic and experimentally presented food-associated calls. J Comp Psychol 118:396-402 Gyger M, Karakashian SJ, Marler P (1986) Avian alarm calling: is there an audience effect? Anim Behav 34:1570-1572 Hauser MD (1996) The Evolution of Communication. Bradford/MIT Press, Cambridge Hauser MD (1998) Functional referents and acoustic similarity: field playback experiments with rhesus monkeys. Anim Behav 55:1647-1658 Hauser MD, Marler P (1993) Food-associated calls in rhesus macaques (Macaca mulatta). II. Costs and benefits of call production and suppression. Behav Ecol 4:206-212 Heinrich B, Marzluff JM (1991) Do common ravens yell because they want to attract others? Behav Ecol Sociobiol 28:13-21 Hingee M, Magrath R (2009) Flights of fear: a mechanical wing whistle sounds the alarm in a flocking bird. Proc R Soc Lond B 276:4173-4179 Jablonka E (2002) Information: its interpretation, its inheritance, and its sharing. Philos Sci 69:578-605 Johnstone RA (1998) Efficacy and honesty in communication between relatives. Am Nat 152:45-58 Johnstone RA (2004) Begging and sibling competition: how should offspring respond to their rivals? Am Nat 163:388-406 Karakashian SJ, Gyger M, Marler P (1988) Audience effect on alarm calling in chickens (Gallus gallus). J Comp Psychol 102:129-135 Kerth G, Ebert C, Schmidtke C (2006) Group decision making in fission-fusion societies: evidence from two-field experiments in Bechstein’s bats. Proc R Soc Lond B 273:2785-2790
Vocal communication in social groups
51
Kitchen DM (2004) Alpha male black howler monkey responses to loud calls: effect of numeric odds, male companion behaviour and reproductive investment. Anim Behav 67:125-139 Koda H, Shimooka Y, Suguira H (2008) Effects of caller activity and habitat visibility on contact call rate of wild Japanese macaques (Macaca fuscata). Am J Primatol 70:1055-1063 Krause J, Ruxton GD (2002) Living in Groups. Oxford University Press, Oxford Laland KN (2004) Social learning strategies. Learn Behav 32:4-14 Lea AJ, Barrera JP, Tom LM, Blumstein DT (2008) Heterospecific eavesdropping in a nonsocial species. Behav Ecol 19:1041-1046 Leighty KA, Soltis J, Wesolek CM, Savage A (2008) Rumble vocalizations mediate interpartner distance in African elephants, Loxodonta africana. Anim Behav 76:1601-1608 Le Roux A, Cherry MI, Manser MB (2008) The audience effect in a facultatively social mammal, the yellow mongoose, Cynictis penicillata. Anim Behav 75:943-949 Magrath RD, Pitcher BJ, Gardner JL (2007) A mutual understanding? Interspecific responses by birds to each other’s aerial alarm calls. Behav Ecol 18:944-951 Manser MB (2001) The acoustic structure of suricates’ alarm calls varies with predator type and the level of response urgency. Proc R Soc Lond B 268:2315-2324 Manser MB (2009) The generation of functionally referential and motivational vocal signals in mammals. In: Brudzynsky SM (ed) Handbook of Mammalian Vocalization. Elsevier, New York, pp 479-488 Manser MB, Bell MB, Fletcher LB (2001) The information that receivers extract from alarm calls in suricates. Proc R Soc Lond B 268:2485-2491 Marler P (1992) Functions of arousal and emotion in primate communication: a semiotic approach. In: Nishida T, McGrew WS, Marler P, Pickford M, de Waal FBM (eds) Topics in Primatology. Vol 1: Human Origins. University of Tokyo Press, Tokyo, pp 225-233 Marler P, Dufty A, Pickert R (1986) Vocal communication in the domestic chicken. II. Is a sender sensitive to the presence and nature of a receiver? Anim Behav 34:194-198 Masataka N (1989) Motivational referents of contact calls in Japanese macaques. Ethology 80:265-273 Maynard Smith J, Harper D (2003) Animal Signals. Oxford University Press, Oxford McComb K, Reby D (2005) Vocal communication networks in large terrestrial mammals. In: McGregor P (ed) Animal communication networks. Cambridge University Press, Cambridge, pp 372-389 McComb K, Moss C, Sayialel S, Baker L (2000) Unusually extensive networks of vocal recognition in African elephants. Anim Behav 59:1103-1109 McComb K, Moss C, Durant SM, Baker L, Sayialel S (2001) Matriarchs as respositories of social knowledge in African elephants. Science 292:491-494
52
Claudia Fichtel and Marta Manser
McGraw WS, Bshary R (2002) Association of terrestrial mangabeys (Cercocebus atys) with arboreal monkeys: experimental evidence for the effects of reduced ground predator pressure on habitat use. Int J Primatol 23:311-325 McGregor PK (2005) Animal Communication Networks. Cambridge University Press, Cambridge McGregor PK, Dabelsteen T (1996) Communication networks. In: Kroodsma DE, Miller EH (eds) Ecology and Evolution of Acoustic Communication in Birds. Cornell University Press, Ithaca/NY, pp 409-425 Mehlman PT (1996) Branch shaking and related displays in wild Barbary macaques. In: Fa JE, Lindburg DG (eds) Evolution and Ecology of Macaque Societies. Cambridge University Press, Cambridge, pp 503-526 Mennill DJ, Ratcliffe LM (2004a) Do male black-capped chickadees eavesdrop on song contests? A multi-speaker playback experiment. Behaviour 141:125-139 Mennill DJ, Ratcliffe LM (2004b) Overlapping and matching in song contests of black-capped chickadees. Anim Behav 67:441-450 Mennill DJ, Ratcliffe LM, Boag PT (2002) Female eavesdropping on male song contests in songbirds. Science 296:873 Morton ES (1977) On the occurrence and significance of motivation-structural rules in some bird and mammal sounds. Am Nat 111:855-869 Mougeot F, Bretagnolle V (2000) Predation as a cost of sexual communication in nocturnal seabirds: an experimental approach using acoustic signals. Anim Behav 60:647-656 Müller CA, Manser MB (2008) The information banded mongooses extract from heterospecific alarms. Anim Behav 75:897-904 Naguib M, Todt D (1997) Effects of dyadic vocal interactions on other conspecific receivers in nightingales. Anim Behav 54:1535-1543 Naguib M, Fichtel C, Todt D (1999) Nightingales respond more strongly to vocal leaders of simulated dyadic interactions. Proc R Soc Lond B 266:537-542 Otter K, Mcgregor PK, Terry AMR, Burford FRL, Peake TM, Dabelsteen T (1999) Do female great tits (Parus major) assess males by eavesdropping? A field study using interactive song playback. Proc R Soc Lond B 266:13051309 Owings DH, Leger DW (1980) Chatter vocalizations of California ground squirrels: predator-social-role specificity. Z Tierpsychol 54:163-184 Papworth S, Böse A-S, Barker J, Schel AM, Zuberbühler K (2008) Male blue monkeys alarm call in response to danger experienced by others. Biol Lett 4:472-475 Paz-y-Miño G, Bond AB, Kamill AC, Balda RP (2004) Pinyon jays use transitive inference to predict social dominance. Nature 430:778-781 Peake TM (2005) Eavesdropping in communication networks. In: McGregor PK (ed) Animal Communication Networks. Cambridge University Press, Cambridge, pp 13-37 Peake TM, Terry AMR, McGregor PK, Dablesteen T (2001) Male great tits eavesdrop on simulated male-to-male vocal interactions. Proc R Soc Lond B 268:1183-1187
Vocal communication in social groups
53
Pereira ME, Macedonia JM (1991) Ringtailed lemur anti-predator calls denote predator class, not response urgency. Anim Behav 41:543-544 Poole JH, Payne K, Langbauer WR Jr, Moss CJ (1988) The social contexts of some very low frequency calls of African elephants. Behav Ecol Sociobiol 22:385-392 Price K, Harvey H, Ydenberg R (1996) Begging tactics of nestling yellow-headed blackbirds, Xanthocephalus xanthocephalus, in relation to need. Anim Behav 51:421-435 Radford AN (2004) Vocal coordination of group movement by green woodhoopoes (Phoeniculus purpureus). Ethology 110:11-20 Radford AN, Ridley AR (2006) Recruitment calling: a novel form of extended parental care in an altricial species. Cur Biol 16:1700-1704 Rands SA, Cowlishaw G, Pettifor RA, Rowcliffe JM, Johnstone RA (2003) Spontaneous emergence of leaders and followers in foraging pairs. Nature 423:432-434 Reby D, Cargnelutti B, Hewison AJM (1999) Contexts and possible functions of barking in roe deer. Anim Behav 57:1121-1128 Rendall D, Cheney DL, Seyfarth RM (2000) Proximate factors mediating ‘contact’ calls in adult female baboons (Papio cynocephalus ursinus) and their infants. J Comp Psychol 114:36-46 Ridley AR, Child MF, Bell MBV (2007) Interspecific audience effects on the alarm-calling behaviour of a kleptoparasitic bird. Biol Lett 3:589-591 Searcy WA, Nowicki S (2005) The Evolution of Animal Communication: Reliability and Deception in Signalling Systems. Princeton University Press, Princeton Semple S, Gerald MS, Suggs DN (2009) Bystanders affect the outcome of motherinfant interactions in rhesus macaques. Proc R Soc Lond B 276:2257-2262 Seyfarth RM, Cheney DL (1990) The assessment by vervet monkeys of their own and another species’ alarm calls. Anim Behav 40:754-764 Seyfarth RM, Cheney DL, Marler P (1980) Vervet monkey alarm calls: semantic communication in a free-ranging primate. Anim Behav 28:1070-1094 Sherman PW (1977) Nepotism and the evolution of alarm calls. Science 197:1246-1253 Shriner WM (1998) Yellow-bellied marmot and golden-mantled ground squirrel responses to heterospecific alarm calls. Anim Behav 55:529-536 Silk JB (2001) Grunts, girneys, and good intentions: the origins of strategic commitment in nonhuman primates. In: Nesse R (ed) Evolution and the Capacity for Commitment. Russell Sage Press, New York, pp 138-157 Silk JB, Kaldor E, Boyd R (2000) Cheap talk when interests conflict. Anim Behav 59:423-432 Skyrms B (2009) Evolution of signalling systems with multiple senders and receivers. Philos Trans R Soc Lond B 364:771-779 Slobodchikoff CN, Kiriazis J, Fischer C, Creef E (1991) Semantic information distinguishing individual predators in the alarm calls of Gunnison’s prairie dogs. Anim Behav 42:713-719
54
Claudia Fichtel and Marta Manser
Slocombe KE, Zuberbühler K (2007) Chimpanzees modify recruitment screams as a function of audience composition. Proc Natl Acad Sci USA 104:1722817233 Smith WJ (1981) Referents of animal communication. Anim Behav 29:1273-1275 Struhsaker TT (1967) Auditory communication among vervet monkeys (Cercopithecus aethiops). In: Altmann SA (ed) Social Communication among Primates. University of Chicago Press, Chicago, pp 281-384 Sumpter DJT, Brännström A (2008) Synergy in social communication. In: d’Ettore P, Hughes DP (eds) Sociobiology of Communication: An Interdisciplinary Perspective. Oxford University Press, Oxford, pp 191-208 Townsend SW, Deschner T, Zuberbühler K (2008) Female chimpanzees use copulation calls flexibly to prevent social competition. PLoS ONE 3:e243, doi:10.1371/journal.pone.0002431 Trillmich J, Fichtel C, Kappeler PM (2004) Coordination of group movements in wild Verreaux’s sifakas (Propithecus verreauxi). Behaviour 141:1103-1120 van Schaik CP (1983) Why are diurnal primates living in groups? Behaviour 87:120-144 Vitousek MN, Adelman JS, Gregory NC, St Clair JJH (2007) Heterospecific alarm call recognition in a non-vocal reptile. Biol Lett 3:632-634 Wich SA, de Vries H (2006) Male monkeys remember which group members have given alarm calls. Proc R Soc Lond B 273:735-740 Wich SA, Sterck EHM (2003) Possible audience effect in Thomas langurs (primates; Presbytis thomasi): an experimental study on male loud calls in response to a tiger model. Am J Primatol 60:155-159 Wilkinson GS, Boughman JW (1998) Social calls coordinate foraging in greater spear-nosed bats. Anim Behav 55:337-350 Wolters S, Zuberbühler K (2003) Mixed-species associations of Diana and Campbell’s monkeys: the costs and benefits of a forest phenomenon. Behaviour 140:371-385 Wright J, Leonard ML (2002) The Evolution of Begging: Competition, Cooperation and Communication. Kluwer, Dordrecht Zahavi A (1977) The cost of honesty (further remarks on the handicap principle). J Theor Biol 67:603-605 Zahavi A, Zahavi A (1997) The Handicap Principle: A Missing Piece of Darwin’s Puzzle. Oxford University Press, New York Zemel A, Lubin Y (1995) Inter-group competition and stable group sizes. Anim Behav 50:485-488 Zuberbühler K (2008) Audience effects. Curr Biol 18:R189-R190 Zuberbühler K, Cheney DL, Seyfarth RM (1999) Conceptual semantics in a nonhuman primate. J Comp Psychol 113:33-42 Zuk M, Kolluru GR (1998) Exploitation of sexual signals by predators and parasitoids. Q Rev Biol 73:415-438
Chapter 3
Kin recognition: an overview of conceptual issues, mechanisms and evolutionary theory DUSTIN J. PENN AND JOACHIM G. FROMMEN
‘all good kumrads you can tell by their altruistic smell.’ (e.e. cummings)
ABSTRACT Kin recognition (KR) is the ability to identify or distinguish kin from nonkin, and it is thought to be an important driving force in the evolution of social and sexual behaviour. Here, we provide an introduction to KR, including an overview of the main debates, the underlying mechanisms and evolutionary analyses. First, we examine the many evolving definitions for KR, as these have caused some confusion and debate. We explain why retaining both broad and narrow definitions can be instructive for thinking about the problem. Second, we provide examples of the different types of KR from empirical studies, ranging from the use of spatial cues to selfinspection and green-beard genes. We also suggest a classification scheme of the different mechanisms based on whether they are considered to be KR in the broad or in the narrow sense. Third, we consider the key components necessary for most or all KR mechanisms, and explain why the central problem for any recognition mechanism is to balance the risk of acceptance versus rejection errors. Fourth, we summarise theoretical analyses addressing the evolution of nepotism through kin recognition, and the maintenance of genetic polymorphisms controlling KR. Fifth, we examine evolutionary analyses of apparent KR failures, errors, and mistakes. Finally, we suggest some of the main challenges that need to be addressed in future KR research.
56
Dustin J. Penn and Joachim G. Frommen
3.1 Introduction Individuals in many social species behave altruistically, and in extreme cases may even sacrifice their own reproduction for the group, as with eusocial insects. To explain the remarkable altruism found in some species, W.D. Hamilton (1964) suggested his theory of inclusive fitness which clarifies the conditions under which altruism is expected to evolve: ‘The social behaviour of a species evolves in such a way that in each distinct behaviour-evoking situation the individual will seem to value his neighbors’ fitness against his own according to the coefficients of relationship appropriate to that situation’ (p. 19). This principle, known as Hamilton’s rule, shows that genetic relatedness is one of the keys to understanding altruism. This insight provided an important new theoretical approach to studying cooperation and other social behaviours (genes’-eye view of evolution; Dawkins 1976), and inspired the development of sociobiology (Wilson 1975). Inclusive fitness theory is arguably one of the most important advance in our understanding of natural selection since the modern evolutionary synthesis (Griffin and West 2002). Hamilton (1964) also suggested that when selection favours helping kin, mechanisms may evolve that allow individuals to discriminate kin from non-kin. Further, he (1964:25) proposed a thought experiment in which a gene evolves that enables ‘the perception of the presence of like genes in other individuals’ and it also helps other individuals carrying the genes, and in this way, it helps copies of itself. He acknowledged that such a ‘super gene’, or what is now known as a green-beard gene (Dawkins 1976), is highly improbable, but nevertheless it is instructive for obtaining insights into how altruism evolves. Hamilton’s ideas sparked much interest in testing whether and how animals recognise kin (see Holmes 2004) and the role that kin recognition (KR) plays in cooperation, inbreeding avoidance, and other kin biases (BOX 3.1). Before Hamilton, KR research had previously focused on parent-offspring recognition, whereas inclusive fitness theory broadened interest in social interactions among collateral kin (e.g., siblings, nieces, nephews, aunts and uncles). Subsequent work has shown that organisms in a wide variety of taxa – from single-celled organisms to humans – are able to distinguish kin from non-kin (e.g., Fletcher and Michener 1987, Waldman et al. 1988, Hepper 1991a). KR may also influence the behaviour of gametes, the haploid phase of the life cycle (i.e., sperm-egg and sperm-sperm interactions; Moore and Moore 2002), and fetal-placental interactions (Haig 1996, Summers and Crespi 2005).
Kin recognition: conceptual issues, mechanisms and evolutionary theory
57
BOX 3.1 Kin biases occur with and without kin recognition There are many ways that organisms treat kin differentially from non-kin. Such kin biases can be developmental, physiological, or behavioural responses and may include either helping or avoiding kin. Many species display parental care, which can enhance offspring fitness under certain conditions (see Trillmich this volume). Furthermore, conditional helping for kin is common, and such nepotism results in kin selection. An extreme case of altruistic helping is the evolution of sterile workers in eusocial insects (Hughes et al. 2008). Kin biases also include kin aggregations and discriminating admittance to social groups. In addition to helping kin, some species avoid competition with kin (West et al. 2002), or show conditional aggression toward non-kin (cannibalism and infanticide) (Pfennig et al. 1993, Manica 2002). Many species show inbreeding avoidance, which most likely functions to avoid the deleterious consequences of inbreeding (inbreeding depression) (Crnokrak and Roff 1999). However, more studies are needed to determine whether natural selection favours intermediate levels of outbreeding due to harmful consequences of extreme outbreeding (optimal outbreeding). Kin biases do not require KR, however. For example, sex-biased dispersal may function to avoid inbreeding, and it does not require an ability to distinguish kin versus non-kin. It has been suggested that kin biases that do not involve KR should be called ancillary kin bias (Halpin 1991, Tang-Martinez 2001) or non-discriminatory kin bias (Barnard et al. 1991). However, the term ancillary implies a bias of secondary importance, which is not the case, and non-discriminatory kin bias may be confusing since non-discriminatory implies no bias (see BOX 3.2). We suggest that such biases might instead be referred to as kin biases without kin recognition.
The trouble is that kin recognition research has been plagued with terminological, conceptual, and methodological issues, including debates over the meaning of the term kin recognition (Waldman et al. 1988, Gamboa et al. 1991). These debates came to a head when Grafen (1990) evaluated the field, and made several controversial objections. He argued that there is a paucity of evidence for ‘true kin recognition’, which he defined as systems ‘whose use and function is to assess the kinship of conspecifics’. Grafen concluded that there was only one convincing example of true kin recognition (i.e., Grosberg and Quinn 1986) because previous studies failed to rule out possible artifacts or incidental biases arising from individual, group, and species recognition abilities. Nevertheless, Grafen described a verbal model for how a true kin recognition system might evolve and maintain itself. His paper triggered a flurry of criticism
58
Dustin J. Penn and Joachim G. Frommen
(Blaustein et al. 1991, Byers and Bekoff 1991, Stuart 1991) and replies (Barnard et al. 1991, Grafen 1991a,b,c). There is still no consensus over these issues, even after 20 years, though there have been many important advances. In this chapter, we provide an overview of kin recognition, and focus particularly on the following issues. First, we consider the various definitions for KR (and kin discrimination), and the terminological debates that have created much controversy and confusion. Second, we examine the proximate mechanisms controlling KR, and we suggest a novel classification of the mechanisms. Third, we consider how KR evolves, and summarise results from theoretical analyses aimed to understand the origins and maintenance of nepotism through KR. Fourth, we summarise evolutionary ideas proposed to explain apparent KR failures. Finally, we suggest some of the central problems that need to be addressed in future research on KR.
3.2 What is kin recognition? Sorting out terminological confusion Determining whether animals recognise their kin or not depends on how one defines kin recognition. In the broad sense, kin recognition refers to the ability to identify, distinguish or classify kin from non-kin, regardless of the mechanism or evolutionary functions (descriptive definition). However, the problem is that there are several other definitions (Table 3.1). For example, kin recognition is also defined as the ability to distinguish and the differential treatment of kin versus non-kin (Sherman and Holmes 1985, Waldman 1987). This operational definition is practical, but it muddles two potentially distinct processes, recognition – which is a proximate mechanism – versus kin-biased actions (Byers and Bekoff 1986). Recognition does not necessarily lead to differential responses toward kin, ‘just as recognising a fruit as an orange does not necessarily lead us to eating it’ (Barnard 1991), and kin biases are not necessarily due to kin recognition (see BOX 3.1). The problem is that different researchers use different definitions, not only for kin recognition (KR), but also for kin discrimination (KD) and kin bias (KB), sometimes even in the same paper. Therefore, it is useful to examine how these terms cause confusion (BOX 3.2). To try to reduce the ambiguity and confusion, some researchers propose using more strict or narrow definitions for KR (Table 3.1). However, the problem is that few seem to agree on a definition, and which definition a researcher uses depends upon whether they emphasise a particular mechanism, adaptive function, or evolutionary history. For example, some sug-
Kin recognition: conceptual issues, mechanisms and evolutionary theory
59
Table 3.1. Evolving definitions for kin recognition (KR). 1. Descriptive = ability to identify or distinguish kin versus non-kin, regardless of mechanisms or functions 2. Operational = ‘…differential treatment of conspecifics differing in genetic relatedness’ (Sherman and Holmes 1985; considered ‘KB’ here) 3. Mechanistic = ability to distinguish kin versus non-kin using genetic similarity or any cues that are correlated with kinship (Holmes 2004) = ‘the process by which individuals assess the genetic relatedness of conspecifics to themselves or others based on their perception of traits expressed by or associated with these individuals’ (Waldman et al. 1988) = ability to distinguish kin versus non-kin among conspecifics, including familiarity, but excluding spatial and temporal cues (Halpin 1991, TangMartinez 2001) = unobservable neural process of classifying individuals as kin (Byers and Bekoff 1986, Barnard 1991, Tang-Martinez 2001) = ability to distinguish and respond differentially to kin (Hepper 1991a; called ‘KD’ here) 4. Cognitive Mechanism = ‘the (externally, at least) unobservable neural process of classing individuals as kin’ (Barnard 1991, Barnard et al. 1991, Tang-Martinez 2001, Griffin and West 2002) 5. Adaptive Function = any mechanism that functions to recognise kin, regardless of the underlying mechanisms 6. Mechanism and Adaptive Function = ability to distinguish genetic similarity in conspecifics, which currently functions for this purpose (so-called true kin recognition; Grafen 1990) 7. Mechanism, Origins and Adaptive Function = ability to distinguish kin versus non-kin among conspecifics that originally evolved and currently functions for this purpose (Tang-Martinez 2001)
gest restricting the term KR to particular mechanisms, such as direct recognition of conspecific phenotypes (Halpin 1991, Tang-Martinez 2001), neural and cognitive mechanisms (Barnard 1991, Tang-Martinez 2001), or the ability to detect genetic similarity (Grafen 1990). Narrowly defining
60
Dustin J. Penn and Joachim G. Frommen BOX 3.2 Coming to terms with kin recognition, kin discrimination, and kin bias There are several definitions for kin recognition (KR), kin discrimination (KD), and kin biases (KB), which cause much confusion and debate. The word recognition refers to the ability to recall and identify someone from past experience or knowledge (from the Latin recognoscere, or to know again). Thus, Halpin (1986) suggested that strictly speaking this term should only be used for the ability to identify or distinguish familiar or previously known individuals, as the recognition of a stranger is ‘a logical impossibility’. Halpin points out that recognition is often used synonymously with discrimination (from the Latin discriminare or to divide), and suggests that discrimination is a preferable term for the ability to distinguish individual conspecifics. The problem, however, is that the word discrimination has three different definitions in English: (1) perceptive abilities to distinguish or make fine distinctions; (2) biased treatment of individuals based on their membership to a group; (3) or both. This ambiguity explains why KD is defined in different ways: (1) the ability to distinguish kin from non-kin (which we call KR); (2) differential treatment of kin versus non-kin (which we call KB, but it is also used as an operational definition for KR; Hepper 1991b); (3) both an ability to distinguish and differential treatment of kin versus non-kin. i.e., some use all three interchangeably (Holmes and Sherman 1983); (4) kin biases due to KR (Barnard 1991, Barnard et al. 1991). It is little wonder that KD causes so much confusion, especially since authors often slip back and forth among the common usages. The figure below summarises the relationships between the various definitions and terms, and how we define them in this paper (also see the Glossary). (1) The ability to identify or distinguish kin versus non-kin = KR (but also called KD)
(4)
(2) differential treatment of kin versus non-kin = KB (but also called KR, KD)
(3) the ability to distinguish and the differential treatment of kin versus non-kin KR and KB = KD (4) differential treatment of kin versus non-kin due to the ability to distinguish them KB based on KR = KD
KR based on a particular mechanism is unnecessarily restrictive, however. Restricting KR to mechanisms that rely on individual phenotypic cues, for example, might rule out other interesting possibilities, such as KR based on extended phenotypes (e.g., acquired commensal microbes or the shape of a birds’ nest, etc.). Limiting KR to cognitive or neural mechanisms ex-
Kin recognition: conceptual issues, mechanisms and evolutionary theory
61
cludes bacteria, plants, unicellular social amoebae, and colonial marine invertebrates (unless cognition is broadly defined to include these taxa). Restricting KR to genetic similarity detection (Grafen 1990) could unnecessarily define the topic out of existence. Also, in many circumstances, environmentally determined cues may provide even better indicators of kinship than genetic ones (Gamboa et al. 1991). As Hamilton (1975) pointed out, ‘kinship should be considered just one way of getting this positive regression of genotype in the recipient, and that it is this positive regression that is vitally necessary for altruism’. If a species has evolved parent, offspring, or sibling recognition, then it is difficult to understand why such behaviours should not be considered KR (after all, offspring are kin) just because they use mechanisms other then genetic similarity detection. Grafen (1990) also proposed that the term KR should be restricted to mechanisms that specifically function to recognise kin. Testing the consequences of KR is necessary to distinguish between adaptive versus incidental KR. However, some ethologists caution against labeling behaviours by their presumed functions or proximate causes, as these assumptions may later turn out to be incorrect (and a behaviour may have more than one function), and instead recommend using descriptive terms. Tang-Martinez (2001) goes further and proposes reserving the term KR only for mechanisms that originally evolved as well as currently function to recognise kin. This idea follows from the suggestion that the term adaptation should be reserved for traits that are shaped by natural selection for their current role, and the term exaptation for traits that originally evolved for something other (Gould and Vrba 1982). However, history-laden definitions for adaptation are impractical and misleading for several reasons (Reeve and Sherman 2001). For example, it is impossible to discern where an adaptation ends and an exaptation begins. How much of the current function of a trait must differ from its original role for it to be considered to be an exaptation? Adaptations generally evolve by modifying or coopting existing traits, and therefore, all traits are exaptations if we go back far enough in time. So, while more work is needed on the functions (Blaustein et al. 1991) and phylogenetic origins of KR (Crampton and Hurst 1994), there are practical reasons to advocate descriptive over mechanistic, functional or history-laden definitions. To demonstrate KR, some researchers insist that in addition to showing an ability to distinguish kin versus non-kin, one must also work out the mechanism (though there is no consensus about which mechanism, as we address further in the next section), its adaptive functions, and its evolutionary origins. This is hardly practical. A number of definitions for KR have been proposed, and there are advantages in retaining both broad and
62
Dustin J. Penn and Joachim G. Frommen
narrow definitions (as is the case for many terms in biology, such as heritability). We suggest that strict definitions of KR should be treated as hypotheses about the underlying mechanisms and functions. It is instructive to note that similar terminological problems plagued the study of social learning, as Galef (1976) pointed out over 30 years ago: ‘Some investigators prefer purely descriptive terms even though these can obscure differences in the mechanisms underlying surface similarities in behavioural interaction.… Others utilise terminology reflecting hypothesised underlying mechanisms mediating observed behavioural interaction…, and there are those who employ operationally defined categories…’. He lamented that the explosion of new definitions and labels has added nothing to our understanding of the mechanisms or the adaptive functions for social learning. This is probably why Hamilton (1975) suggested that ‘it seems on the whole preferable to retain a more flexible use of terms’.
3.3 Proximate mechanisms: how do organisms recognise kin? In this section, we provide an overview and examples of the various mechanisms through which organisms identify or distinguish kin versus non-kin. We also suggest a classification scheme for these mechanisms based on the broad and narrow definitions for KR. Then, we consider a general model describing the key components that are thought to comprise all or most KR mechanisms. 3.3.1 Types of kin recognition mechanisms There are several different mechanisms that enable animals to distinguish kin versus non-kin, and several classifications of KR mechanisms have been proposed. The most widely cited scheme (e.g., Sherman and Holmes 1985, Waldman 1987) proposes four categories: (1) recognition alleles; (2) familiarity (associative learning); (3) phenotype matching; and (4) spatially-based mechanisms. These categories are criticised because they are not based on consistent criteria, and some mechanisms (2 and 4) are not considered to be KR by researchers who reject the broad definition for KR. The alternative proposals, however, are rather complicated (Barnard et al. 1991, Tang-Martinez 2001) or too simple (e.g., it has been suggested to exclude spatially-based mechanisms, and combine the rest into two categories, recognition alleles and learning; Barnard et al. 1991, Tang-Martinez
Kin recognition: conceptual issues, mechanisms and evolutionary theory
63
Table 3.2. Kin recognition mechanisms can be classified according the types of cues used and matching rules (i.e., the referents used for recognition). Shading shows broad and more narrow definitions. 1. Contextual cues R uses spatial, temporal, and state-dependent cues 2. Phenotypic cues A. Direct familiarity R compares S at time 1 to S at time 2 (e.g., associative learning of individually-distinctive cues) B. Without direct familiarity (i) Indirect familiarity R compares S to K (e.g., associative learning of familial-distinctive cues) (ii) Self inspection R compares S with R (e.g., compare individually-distinctive cues through habituation/dishabituation) (iii) Green-beard genes R compares S with R (no prior experience necessary) R = receiver making the evaluation, S = sender being evaluated, and K = likely kin to R
2001). Thus, the proposed classifications of KR mechanisms vary depending upon how researchers define kin recognition. Therefore, we propose a classification of the types of KR based on broad or narrow-sense definitions (Table 3.2). We first examine examples of KR in the broad-sense (spatially-based mechanisms and familiarity), and then in the narrow-sense (indirect familiarity, self-inspection, and green-beard genes). Another distinction used for classifying KR mechanisms is based on the types of cues, which can be divided into two categories: indirect, contextual cues versus direct, phenotypic cues (Waldman 1988). Since direct, phenotypic cues are further divided into direct versus indirect familiarity (see below; Wyatt 2003), we only use the terms direct and indirect for this later distinction. 3.3.1.1 Contextual cues (spatial, temporal and other nonphenotypic mechanisms) Many species rely on spatial, temporal, or other contextual cues to distinguish kin versus non-kin (see Table 3.3). For example, many birds, mam-
64
Dustin J. Penn and Joachim G. Frommen
mals and fish rely on location to recognise offspring, and use the rule: ‘any young in my nest are mine’. For example, male house mice (Mus musculus) normally kill pups, but after mating with a female, they no longer attack her pups (Elwood and Ostermeyer 1984). They thus use mating as a contextual cue to assess the probability of being related to the pups (statemediated recognition). Female moorhens (Gallinula chloropus) destroy any eggs they find in their nest if they have not begun to lay eggs, and they apparently use their knowledge of their own egg-laying to bias investment into their own offspring (McRae 1996). Such decision rules are not necessarily all-or-none. In dunnocks (Prunella modularis), males allocate parental care based on the amount of sexual access they had to a mate, which correlates with offspring paternity (Davies et al. 1992, Hartley et al. 1995). Some contextual cues may be easily exploited by cheaters, but there may be no cheat-proof mechanisms. Extreme examples are birds that care for a Table 3.3 Kin recognition (KR) has been found in a wide variety of species, and these are some arbitrarily chosen examples from different taxa. Taxa
Species
Behaviour
Reference
1. Contextual cues Burying beetles (Necrophorus vespilloides)
Mothers kill larvae that hatch too early to be own young
Müller and Eggert 1990
Birds
Bank swallows (Riparia riparia)
Treat all chicks in their nest as their own, as long as chicks are younger than 14 days
Beecher et al. 1981
2. Phenotypic cues a. Direct familiarity Predatory mites (Phytoseiulus persimilis)
Cannibalise non-kin and unfamiliar kin, but not familiar kin
Schausberger 2007
Birds
Barnacle geese (Branta leucopsis)
Breed near sister, but only when they were born in the same year
van der Jeugd et al. 2002
Mammals
Barbary macaques (Macaca sylvanus)
Avoid mating with individuals with whom they were familiarised during early life
Kuester et al. 1994
Broad sense KR
Insects
Broadest sense KR
Insects
Kin recognition: conceptual issues, mechanisms and evolutionary theory
Broadest sense KR
b. Without direct familiarity (i) Indirect familiarity Prefer to shoal with unfamiliar kin, based on learning of sibling’s cues
Frommen et al. 2007a,b
Fishes
Pelvicachromis taeniatus
Both sexes prefer familiar as well as unfamiliar kin as mates
Thünken et al. 2007a,b
Mammals
House mice (Mus musculus)
Males avoid mating with females carrying MHC genes of the family with which they are reared
Yamazaki et al. 1988
(ii) Self inspection Plants
Sea rockets (Cakile edentula)
Grow additional roots when share soil with non-kin
Dudley and File 2007
Birds
Peafowl (Pavo cristatus)
Peacocks, raised with non-kin, lek with relatives
Petrie et al. 1999
Amphibians
Clawed frogs (Xenopus leavis)
Preferred to group with siblings with which they shared MHC haplotypes to those with no MHC haplotypes in common
Villinger and Waldman 2008
Prefer forming chimeras with related cells
Queller et al. 2003
Broad sense KR
Three-spined stickleback (Gasterosteus aculeatus)
Narrow sense KR
Fishes
65
(iii) Green-beard genes Social amoebae
Dictyostelium purpureum
cuckoo’s chick in their nest. Furthermore, contextual cues may not allow recognising kin outside the respective context. Because conspecific phenotypic cues are not involved, and mistakes are possible, some researchers argue that species that utilise contextual mechanisms do so because they lack the ability to recognise kin (Barnard et al. 1991, Tang-Martinez 2001). Indeed, classifying contextual cues as KR seems an odd use of the term recognition, but perhaps such cues are commonly utilised in most other types of recognition systems. Contextual mechanisms are KR in the broadest sense of the term, and some may instead prefer to consider them as kin bias without kin recognition (see BOX 3.1).
66
Dustin J. Penn and Joachim G. Frommen
3.3.1.2 Phenotypic cues Some suggest that the term KR should be restricted for mechanisms that rely on direct cues from conspecifics, including chemical, acoustic, visual, behavioural or other phenotypes (Barnard et al. 1991, Tang-Martinez 2001). These may be features of individuals or groups (e.g., colony odours). The first type of phenotypic recognition we address is another example of KR in the broad sense. A. Direct familiarity (also called ‘prior association’) There is a great deal of evidence that animals rely on direct familiarity to recognise kin (e.g., Table 3.3). This mechanism can be found in many species where young stay together during the first days of their life. Here, the phenotypes of individuals who are kin – or likely to be kin – are individually learned, classified and later on treated as related or not. Close kin are often more familiar than non-kin, and a wide variety of species use previous association to recognise kin (e.g., Westermarck 1891, Porter et al. 1981, Dewsbury 1982, Holmes and Sherman 1982). They follow a rule: treat familiar individuals as kin because they are likely to be kin. Individuals may become classified as kin if they become familiar at particularly sensitive times during ontogeny. For example, humans and other mammals negatively imprint on individuals with which they are reared, and subsequently avoid mating as adults. They follow the rule: avoid mating with individuals I grow up with in my family. This so-called Westermarck effect was the first mechanism discovered to control kin discrimination in humans (BOX 3.3). Tang-Martinez (2001) suggests that kin biases based on familiarity should be regarded as individual rather than kin recognition. These are not mutually exclusive alternatives, however, and it seems moot to debate whether to call such behaviours kin biases based on individual recognition or kin recognition based on individual familiarity. As familiarity is not considered to be KR by some researchers (but instead, it is seen as something that must be controlled to test KR), we consider it to be KR in the broad sense. Regardless, determining how animals distinguish kin versus non-kin among unfamiliar individuals is clearly one of the more challenging problems in this field. There are at least two types of mechanisms that do not require familiarity, and we consider these to be KR in the narrow sense.
Kin recognition: conceptual issues, mechanisms and evolutionary theory
67
BOX 3.3 Kin recognition in Homo sapiens
In his autobiography, Hamilton (1996) commented that he ‘did not anticipate the degree of relevance to humans that the findings eventually proved to have’. However, he surely realised that incest avoidance is a topic that has puzzled thinkers since ancient times (Porter 1991). Like other animals, humans show kin biases in a wide array of contexts, including incest avoidance, parental care, and cooperative behaviour. The mechanisms they use are multifarious, too. Maybe the best known is direct familiarity (also known as the Westermarck effect). Westermarck (1981) described that small children are negatively imprinted on their age mates, avoiding them as partners when reaching adulthood. Similar results were found by Lieberman et al. (2007) who showed that kinship is estimated by the perinatal association of the proposed sibling with the individual’s genetic mother as well as through the duration of time siblings live together. Many studies show that human offspring are able to recognise their mothers through volatile scent cues, and vice versa (Porter 1991). There is suggestive evidence that humans are also capable of recognising unfamiliar kin as well, and self-reference may play a role. For example, DeBruine (2002) found people trust a stranger’s face more when it has been morphed with their own than when it was left unchanged. Familiarity was ruled out by using morphs of celebrities; only selfresemblance mattered. The use of self-reference in human KR was further supported by a study that found that dizygotic as well as monozygotic twins preferred pictures of faces that were merged with their own over faces that were merged with the face of the twin (Bressan and Zucchi 2009). B. Without direct familiarity (1) Indirect familiarity (also called ‘phenotype matching’) Individuals can potentially recognise kin even among unfamiliar individuals by comparing the phenotypes of putative kin with those of known (familiar) kin: individuals who resemble their own kin are treated as related. There are examples of this KR mechanism in many species in which the young stay together during the first days of their life (Table 3.3). For example, in brood-caring fish, fry have ample opportunities to learn cues (e.g., smell) of their siblings or parents before they leave the nest or cave. Later on in life they use these cues to
68
Dustin J. Penn and Joachim G. Frommen
recognise not only their nest mates, but also relatives raised in other broods. This mechanism not only allows recognising unfamiliar siblings, but also more distantly related kin like half-siblings or cousins (see BOX 3.4). Its weakness is that in species with close contact between kin and non-kin during maturation (e.g., in colonial species) or with high amount of stolen fertilisations, individuals may learn the BOX 3.4 MHC genes: candidate genetic loci for kin recognition cues The genes of the major histocompatibility complex (MHC) are a multigene family of highly polymorphic loci that control immunological self/nonself recognition, and are suspected to play a role in KR (Brown and Eklund 1994). MHC genes influence odour and mating preferences in a variety of species, including mice, humans, fish, and frogs (Yamazaki et al. 1988, Penn and Potts 1998, Milinski 2006). MHC-dependent mating preferences may function to increase or optimise offspring MHC-heterozygosity (e.g., Penn and Potts 1998, Penn et al. 2002), avoid inbreeding, or both (Penn 2002). Female mice prefer to nest communally with sisters, or MHC-identical individuals when sisters are unavailable (Manning et al. 1992). Also, female mice are more likely to retrieve pups if the pups are MHC-identical to the dam (Yamazaki et al. 2000). It is unclear how MHC genes influence odour, though several candidate volatiles have been identified (Willse et al. 2005, 2006, Novotny et al. 2007), and MHC-derived peptides have been shown to be detected through the vomeronasal organ (Leinders-Zufall et al. 2004). Interestingly, house mice avoid mating with individuals carrying MHC genes that are identical to the foster family with which they are reared (familial imprinting; Yamazaki et al. 1988, Penn and Potts 1998). This behaviour may provide a more effective mechanism for avoiding sib matings than self-inspection. For example, consider the MHC-genotypes of closely related mice, shown below (most individuals are heterozygous since MHC genes are polymorphic). If ac relies entirely on self-inspection, she will risk mating with 0.25 of her siblings (bd) and 0.5 of her half-siblings (de and df). In contrast, by using familial imprinting, ac can avoid mating with all full-siblings (bc, ad, bd), all half-siblings (ce, cf, de, df), and half of all cousins (Penn and Potts 1999). By imprinting on a variety of phenotypic cues of family members, this may provide a highly effective mechanism to avoid inbreeding (i.e., indirect familiarity). ab
ac
bc
cd
ad
ef
bd
ce
cf
de
df
Kin recognition: conceptual issues, mechanisms and evolutionary theory
69
cues of relatives as well as non-relatives and treat all individuals bearing these cues similarly. This mechanism is often called phenotype matching, and is seen categorically distinct from familiarity, but the crucial difference is that with phenotype matching the animal learns self- or familial- rather than individually-distinctive cues (Porter 1988, Barnard et al. 1991, Tang-Martinez 2001). (2) Self-inspection (also called ‘self-referent phenotype matching’ and the ‘armpit effect’) It has been suggested that to recognise kin, animals might inspect their own scent, voice or other phenotypic cues and compare how well they match with other individuals, and use the similarity to recognise kin (armpit effect, Dawkins 1976). There are some, though still surprisingly few candidates for KR through self-inspection (Table 3.3), and these are often found in unicellular organisms, fungi and plants, rather than animals (reviewed in Tsutsui 2004; Table 3.3). Mateo and Johnston (2000) reported evidence for self-referent phenotype matching in golden hamsters (Mesocricetus auratus). However, their study is criticised for several reasons, e.g., not ruling out post-partum and earlylife familiarisation with close kin through fetal olfaction (e.g., Heth and Todrank 2001, Mateo and Johnston 2001, Hare et al. 2002, Mateo and Johnston 2003). Self-inspection may evolve when the opportunity to learn relative’s cues is limited or unreliable due to a lack of family members to use for comparison, or due to the presence of unrelated individuals in the same nest or burrow. Self-inspection is often viewed as categorically distinct from other learning mechanisms, yet it is arguably a type of phenotype matching, in which the cues used for comparison are not learned from conspecifics but from self. Self-inspection might also be considered to be a type of familiarity (associative learning) (though if it involves habituation to one’s own cues, this is non-associative rather than associative learning). Oddly, self-reference matching is widely considered a form of genetic KR in the strict sense (recognition alleles, see below) even though genetically determined cues may or may not be involved. A problem with the self-inspection hypothesis is that it is unclear how it might be empirically distinguished from green-beard effects. (3) Green-beard genes (also called ‘recognition alleles’, and ‘genetic kin recognition’) As mentioned in the introduction, when speculating on how animals might evolve mechanisms to recognise their kin, Hamilton (1964) postulated the evolution of a super gene that is able to recognise and help copies of itself in other individuals (Haig 1996), and this model be-
70
Dustin J. Penn and Joachim G. Frommen
came known as a green-beard gene (Dawkins 1976, 1982). A greenbeard gene helps copies of itself by encoding three traits: (1) influencing the expression of a rare phenotypic trait, such as a green beard; (2) enabling individuals to recognise the trait in others; and (3) acting altruistically towards individuals carrying the trait (or antagonistically towards individuals that do not). In other words, the same gene influences all these traits simultaneously through pleiotropy. Green-beard effects may be controlled by single or multiple loci. If their effects are controlled by multiple loci, this might be considered a genetic KR system (Grafen 1990). The distinction between green-beard effects and other types of genetic KR mechanisms is fuzzy in theoretical models (Rousset and Roze 2007). Green-beard genes are often dismissed as being far-fetched; even Hamilton recognised that it is unlikely that a single gene could ever influence all these traits. Some argue that green-beard genes are unlikely because they are genetic outlaws, as they help individuals bearing similar cues who are sometimes unrelated, this leads to intragenomic conflicts, which favours the evolution of suppressor genes (the parliament of the genome; Alexander and Borgia 1978, Helantera and Bargum 2007). Others argue that green-beard genes are not necessarily outlaws, as the rest of the genome will reap any benefits obtained by a green-beard gene (Ridley and Grafen 1981). The first report for a green-beard gene was found in a study on spiteful behaviour in fire ants (Solenopsis invicta; Keller and Ross 1998), though these findings have been challenged (Vander Meer and Alonso 2002). Subsequently, several candidate green-beard effects have been reported, including cooperation among budding yeast (Smukalla et al. 2008), social amoeba (Queller et al. 2003) and lizards (Sinervo et al. 2006), parent-offspring recognition at the placenta (Haig 1996, Summers and Crespi 2005), altruistic sperm pairing (Moore and Moore 2002), and self-incompatibility loci in plants (reviewed in Tsutsui 2004). As mentioned above, the main problem with the green-beard gene hypothesis is empirically distinguishing it from self-inspection: it requires eliminating all phenotypic cues that an organism could obtain about its own phenotypic cues, which seems difficult if not impossible. Therefore, many evolutionary researchers combine them together into tag-based kin recognition (e.g., Axelrod et al. 2004, Antal et al. 2009), as we will see in the next section. In summary, there is much evidence that many species can distinguish kin and non-kin, and some evidence to support all of the proposed mechanisms. Furthermore, the various types of KR mechanisms are not mutually exclusive, as they may be used by different individu-
Kin recognition: conceptual issues, mechanisms and evolutionary theory
71
als within a species, or they may change during development, age, or an individuals’ condition or context (Neff and Sherman 2002, Mateo 2004). 3.3.2 Key components of KR mechanisms Even though there are several types of KR mechanisms, it has been suggested that all KR systems must have several key components or design features to enable individuals to recognise and respond differentially to kin (e.g., Sherman and Holmes 1985, Waldman 1987; Fig. 3.1). From this perspective, KR is not a single system, but rather a device or contraption with many components. First, KR requires a sender that produces kinship cues (also known as markers, labels, signatures, and tags), which are phenotypic traits produced by the organism, such as chemical, visual, or acoustic signatures, that provide information about kinship. Kinship cues must be highly variable among individuals – and also consistent or developmentally stable within each individual, and the variability of cues must be genetic or correlated with genetic relatedness (e.g., see BOX 3.4). KR cues may function specifically to indicate relatedness, or more likely they are produced incidentally, with no special function for communicating relatedness. For example, Todrank and Heth (2003) suggest that animals produce odour signals (which are usually a blend of compounds or ‘signature mixtures’ sensu Wyatt 2003) that have a wide range of functions, from individual to kin to species recognition. The broadest definition of KR, as we have seen, also includes indirect spatial, temporal or other contextual cues associated with kinship, as well as direct phenotypic cues, though these would not be an example of kin communication (see below). Second, recognition begins with sensory detection (or perception) of kinship cues, such as through olfaction, visual, hearing, or tactile mechanisms by receivers (also called discriminators). Usually, only one type of sensory modality is studied, though a combination may be involved (multimodal processing. Next, recognition requires a phenotype matching mechanism: a hypothetical device that compares a sender’s cues to a template, an internal model or representation of cues from self or other referent, and evaluates the similarity between them, as necessary for classification (Lacy and Sherman 1983). A template may be learned from self (selfinspection) or from other referents, even though phenotype matching is often seen as categorically distinct from self-inspection. Recognition errors occur due to excess over-lap in cues, and one of the central problems for KR systems is to optimise the risk of acceptance errors (Type I or false
72
Dustin J. Penn and Joachim G. Frommen
Sender: (1) Cues Display chemical, visual, acoustic information e.g., scent marking
Contextual information (e.g., spatial cues)
Receiver: (2) Recognition Perception (sensory detection) e.g., olfaction Phenotypic matching e.g., self-inspection
(3) Decision-rules / Heuristics e.g., avoid similar smelling mates
Receiver’s physiological state and ecological context
(4) Action e.g., inbreeding avoidance
Fig. 3.1 Kin recognition (or kinship communication) involves several key components, from (1) the production of cues by senders to (2) recognition, (3) decisions, and (4) actions by receivers. Recognition per se includes cue detection and phenotypic matching, which are used for making decisions regarding actions. Spatial, temporal, and other contextual cues may be used, at least for KR in the broadest sense. Self-inspection (shown above) and indirect familiarity are examples of KR mechanisms in the narrow sense. Decision rules involve acceptance thresholds and simple rules-of-thumb that enable receivers to evaluate the likely relatedness of conspecifics. Decisions may also integrate contextual information about the receivers’ own age, condition, physiological state, and ecological constraints to weigh the perceived costs and benefits (adapted from Sherman and Holmes 1985, Waldman et al. 1988; mice drawn by Shawn Meagher).
positives), due to accepting ‘undesirable recipients’, with rejection errors (Type II or false negatives), due to rejecting ‘desirable recipients’ (Reeve 1989, Beecher 1991, Sherman et al. 1997).
Kin recognition: conceptual issues, mechanisms and evolutionary theory
73
Third, after recognition, receivers use this information for making decisions, which are cognitive or other information processing devices that control behavioural and other responses (or store the information into memory). Adaptive decisions also integrate contextual information about the receivers’ internal state or motivation, and other relevant information. For example, plains spadefoot toad tadpoles (Spea bombifrons) cannibalise other tadpoles and they eat more non-kin than kin, except for when they are very hungry; then they become indiscriminate (Pfennig et al. 1993). The importance of the context-dependence of acceptance thresholds should not be underestimated. Fourth, receivers’ decisions enable them to take the appropriate action, which may be developmental, physiological or behavioural responses that result in differential treatment of kin (e.g., Liebert and Starks 2004). For example, this occurs when a mother rejects a foreign offspring because she detects that it has previously been licked or labeled by another female. Actions can be all-or-none, such as when there is a critical threshold above which all senders are accepted and below which they are rejected. However, whether receivers take action or not depends on the relative rates of interaction with and the fitness consequences of accepting and rejecting desirable and undesirable recipients (Reeve 1989). As we will see later, recognition does not necessarily lead to discrimination if, for example, the perceived costs outweigh the benefits. This summary of KR components differs somewhat from previous versions (Sherman and Holmes 1985, Waldman 1987). For example, we do not consider cues and actions as components of recognition per se, even though cues are necessary for recognition to occur. We divide recognition and decision-rules into separate components, because they may be mechanistically distinct. Referring to all these steps as components of recognition overlooks the communication aspects of the system, and particularly selection on the sender’s cues (Beecher 1991). Therefore, this model is more accurately described as components of kinship communication rather than a KR system, and communication is not necessarily honest. This is an important point for evolutionary analyses of KR, which we address in the next sections.
3.4 Evolutionary analyses of kin recognition KR research has always been grounded on evolutionary analyses of social behaviour, and particularly Hamilton’s ideas about nepotism (see Holmes 2004). In this section, we provide an overview of theoretical analyses that
74
Dustin J. Penn and Joachim G. Frommen
have aimed to understand how KR recognition evolves, and in particular, how natural selection maintains the diversity of genes controlling KR (in the narrow sense). These analyses have only considered the evolution of KR in mediating cooperation (nepotism) so far, and not inbreeding avoidance or other kin biases, and they have only examined self-inspection (or green-beard effects), and not considered indirect familiarity. 3.4.1 Evolutionary origins and maintenance of genetic kin recognition It has been difficult to understand how KR might evolve and be maintained by natural selection. Crozier (1986) made the first mathematical model of the evolution of KR by examining its role in nepotism, and he concluded that it is unstable, and inevitably drives itself to extinction. He found that individuals bearing common phenotypic cues (markers) have more opportunities to find and engage in cooperative activities than those bearing rare markers, and therefore, they gain greater fitness. The common markers become even more common over time, and eventually all individuals have the same marker. Once a marker no longer provides an indicator of kinship, there is no benefit to KR. In short, rare alleles will be at a disadvantage in finding cooperators, which eliminates the marker diversity, and any benefits of KR. Nevertheless, Crozier (1987) suggested that genetic variation in KR cues might be maintained by piggy backing on other loci under balancing selection, such as inbreeding avoidance, parentoffspring recognition, individual recognition, or a completely different source of selection, such as parasites. Grafen (1990) pointed out that Crozier’s model assumed that social interactions are always beneficial as there are no cheats (social parasites that display a marker and exploit other’s cooperation), and therefore, there is no benefit to limiting interactions to kin. Rare markers provide better indicators of kinship, which would favour greater altruism among individuals carrying rare markers. He concluded that ‘cheating maintains genetic polymorphisms at the matching locus because common alleles are hit harder when cheating arises, because they are too trusting’. On the other hand, if the marker and conditional helping evolve independently, then cheaters, displaying the correct marker without providing help, might undermine the system. Axelrod et al. (2004) conducted a simulation in which heritable cues of relatedness, which they called tags, can coevolve with discrimination and other strategies based on these indicators. They found that conditional or discriminating altruism can be maintained in a stable equilibrium.
Kin recognition: conceptual issues, mechanisms and evolutionary theory
75
Jansen and van Baalen (2006) made a similar simulation based on a recognisable cue (coloured beards) to study the evolutionary dynamics of beard colour polymorphism (beard chromodynamics). They found that complete linkage between the matching and conditional helping loci leads to highly unstable dynamics, and to the rapid loss of tag variation (beard colours). However, when they allowed low recombination, beard colour and conditional helping were maintained at intermediate frequency in the population. This is in contrast to the assumption that tight coupling (pleiotropy or close linkage) is necessary for green-beard effects. Thus, it appears that cooperative genes must continuously change their tags to avoid exploitation by defectors or social parasites, much like red queen dynamics in host-parasite interactions. Rousset and Roze (2007) constructed a model using two-loci that control matching and helping, and they examined how various rates of recombination and dispersal (spatial population structure) affect the maintenance of polymorphisms. They found that selection usually eliminates KR and helping due to the benefits for common markers, just as Crozier (1986) found. Yet, when they reduced dispersal and recombination between the matching and helping loci, the polymorphisms were maintained: rare markers benefit from greater levels of helping, just as Grafen (1990) suggested. Increasing mutation rates help to maintain polymorphisms at both loci, as mutations supply new alleles into the system as they go extinct, but this still requires restrictive conditions. Perhaps the most interesting finding is that adding an extrinsic selective advantage for rare alleles, such as negative-frequency dependent selection from parasites, effectively maintains KR and conditional helping (Gardner and West 2007), as Crozier (1986) also suggested. More recently, Antal et al. (2009) used an analytical approach to model the evolution of conditional cooperation based on tag-based recognition of phenotypic similarity (green-beard or self-referent effects). Unlike previous models, they found that the evolution of cooperation does not require spatial structure. They also found that cooperation is more likely to evolve if the strategy mutation rate is controlled by one or few genes, and the phenotypic tags are encoded by many loci. In summary, nepotism mediated by KR may be prone to drive itself to extinction, but not always. It can be maintained under certain conditions, namely linkage between loci and subdivided population structure, and from extrinsic sources of balancing selection – such as from parasites. Its red queen dynamic nature suggests that its occurrence will vary over time and space, i.e., among populations and even within populations of the same species. We should expect genetic KR driven nepotism to be found in species with low dispersal and recombination. Evolutionary analyses
76
Dustin J. Penn and Joachim G. Frommen
help explain why MHC genes, which control immunological recognition of parasites, are also implicated in KR (Gardner and West 2007; BOX 3.3). Although these models suggest that nepotism through genetic KR is unlikely to evolve without spatial structure or other restrictive conditions, a recent analysis suggests otherwise (Antal et al. 2009). 3.4.2 Apparent kin recognition failures There are many examples in which animals do not seem to recognise their kin, even when it would seem to be in their interest to do so. For example, when male birds are cuckolded, they do not eject the extra-pair offspring from the nest. It is instructive to consider apparent KR failures (Beecher 1991, Sherman et al. 1997), and the evolutionary hypotheses to explain them. First, KR (or KB) may not occur because the costs of discrimination outweigh the benefits. There are surely potential tradeoffs for any kinbiased behaviours, so that the optimal response may sometimes require taking no action or discrimination, which might be mistaken as a recognition failure. For example, it has been suggested that the benefits of rejecting extra-pair offspring by male birds may not be worth the costs of making recognition mistakes, and erroneously killing their own offspring (Kempenaers and Sheldon 1996). There may be other costs for males that discriminate against extra-pair offspring, such as risk of desertion by their mate. It is instructive to consider that the body’s immune system functions to recognise parasites; however, a lack of immune responses to a parasite is not necessarily due to a recognition failure. Mounting an immune response can help resolve an infection, but it also has costs, especially in case of autoimmunity and other forms of immunopathology. Since immune recognition has detrimental side-effects, selection sometimes favours immune tolerance to infection. Similarly, just as selection favours optimal immunity and tolerance rather than maximal responsiveness, we should expect kin discrimination responses to be optimised to balance the potential fitness costs and benefits. This decision problem faced by receivers has been studied in several theoretical models (Reeve 1989, Beecher 1991), but it has not been empirically tested to our knowledge. Second, KR may not occur because signalers are under selection to conceal their identity to potential receivers (anti-recognition hypothesis) (Beecher 1991). For example, fathers may not recognise their own offspring because in species with high rates of extra-pair paternity, offspring may be favoured to conceal their identity so that they do not resemble their genetic fathers (also called neonatal identify deception) (Beecher 1991,
Kin recognition: conceptual issues, mechanisms and evolutionary theory
77
Pagel 1997). Most analyses assume that signalers honestly signal their identity, even if only inadvertently, and do not consider the possibility that individuals evolve mechanisms to disguise themselves. Yet, one theoretical analysis shows that selection can favour concealment over a wide range of conditions (Johnstone 1997). Moreover, it shows that kin discrimination will not evolve just because it benefits receivers: it depends on whether honest signature cues are also beneficial to signalers. This is called the communication problem, as it involves the evolution of the sender’s cues, as well as the receiver’s KR abilities (Johnstone 1997). Similarly, the failure of the immune system to recognise invading pathogens is sometimes due to pathogens evolving mechanisms to escape immune recognition. Interestingly, such deception games may be required for selection to maintain cooperation through KR (Grafen 1990), as we previously discussed. Finally, a failure to recognise kin may be maladaptive due to insufficient time to evolve and adapt to new environmental conditions (evolutionary lag-time hypothesis; see Dawkins 1982), or as we have seen, selection from kin-biased behaviours eroding the genetic polymorphisms required to maintain itself (Crozier 1987). Such maladaptive ideas are hypotheses of last resort however, as testing requires ruling out the functional hypotheses.
3.5 Conclusions and future directions Many species have the ability to distinguish kin from non-kin, which may function to facilitate helping kin, avoiding inbreeding, or other kin-biased behaviours. Determing whether a species utilises KR or not depends on how one defines this term, and there is much debate over how to define it. It might be useful to replace the term KR with KD or perhaps kin detection, kin identification, or kinship communication, though these alternatives have their own problems. We suggest that it is useful to retain broad definitions for KR, and treat the strict definitions as hypotheses about the mechanisms and functions. There is also much debate about how to classify the various types of KR mechanisms, and as a pragmatic approach, we suggest classifying the mechanisms according to whether they fit the broad or narrow-sense definitions of KR. Finally, recent theoretical studies are helping to explain the evolution of nepotism through KR, as well as apparent KR mistakes, errors and failures.
78
Dustin J. Penn and Joachim G. Frommen
There are still many unresolved problems regarding KR, and here, we suggest a few ideas for future research on both mechanistic and evolutionary questions: (1) The proximate mechanisms through which KR affects KB’s are unclear, and more work is needed here. Efforts to find candidate genetic loci controlling KR could narrow the search by focusing on linked loci that are highly polymorphic, and control immune recognition to pathogens and parasites, and not only MHC genes (BOX 3.4). (2) The adaptive functions of KR are not well understood (Blaustein et al. 1991). KD is thought to increase the indirect fitness of the individual through cooperation; however, experimental evidence for this hypothesis is still scarce, opening ample opportunities for future studies. (3) It has been suggested that somatic incompatibility (or allorecognition) systems of colonial organisms might function for KR, and that these have multiple phylogenetic origins (Crampton and Hurst 1994). These ideas deserve further analyses. (4) It is often assumed that a species has either evolved KR or not, and when different studies report mixed results the positive evidence is treated with scepticism. Yet, theoretical models predict much intraspecific variation in KR abilities within and among populations, as well as dynamic changes over time and according to the varying ecological constrains. For example, the report of green-beard genes in fire ants (Keller and Ross 1998) was not supported in a different study (Vander Meer and Alonso 2002) perhaps due to geographic variation (also see Liebert and Starks 2004). Future studies should examine such variability, and also how mechanisms may change during development, age, condition or context (Neff and Sherman 2002, Mateo 2004). (5) There are several models on the evolution of genetic KR, but what are the conditions in which natural selection favours the evolution of KR through familiarity, indirect familiarity and other types of learning? (6) Theoretical analyses of the evolution of KR are restricted to the evolution of conditional helping (nepotism), and future models need to consider inbreeding avoidance and other potential benefits (and preferences for mating with kin to increase inclusive fitness benefits).
Kin recognition: conceptual issues, mechanisms and evolutionary theory
GLOSSARY Green-beard gene: a postulated gene that simultaneously influences the development of a characteristic phenotype (cue), the ability to recognise this cue, and also helping conspecifics bearing this cue or label (or harming those who do not). Genetic relatedness: estimated as the proportion of genes shared, or the probability of alleles at a randomly chosen locus, between two individuals being shared due to common descent (Sewall Wright’s coefficient of relationship r). There is no absolute measure of relatedness among individuals, as it is relative to the population mean, which can result in negative relatedness. Thus, relatedness is not simply a measurement of genetic similarity between individuals, as it depends on the population structure (Griffin and West 2002). Heuristics: simple rules-of-thumb for detection, recognition, making classifications or other decisions that are efficient and accurate under most circumstances, even though they can also lead to errors. These appear to be used in all KR mechanisms. Inclusive fitness: an individual’s own reproductive success (conventional fitness) plus its effects on the reproductive success of its relatives, each one weighed by the coefficient of relatedness (Dawkins 1982). Kin: individuals that are genetically related due to common descent (e.g., offspring, siblings, cousins, etc.). Kinship: a special case of genetic similarity in which the probability of individuals sharing an allele at a particular locus depends upon their distance in a path of common descent (Grafen 1990). Kin bias (KB): differential treatment of kin versus non-kin, which may be due to kin recognition or not (Barnard 1991). Kin discrimination (KD): in the broad sence, the ability to distinguish (KR) and the differential treatment (KB) of kin versus non-kin. In the narrow sense, KB due to KR (Barnard 1991). Kin recognition (KR): in the broad sense, the ability to identify, distinguish and classify kin versus non-kin, though there are several narrow versions (see Table 3.1). We use the term in this broad sense, unless otherwise indicated. Kin selection: natural selection due to interactions among kin, such as nepotistic helping behaviours. There are several common misunderstandings about kin selection (see Dawkins 1979), which is why Hamilton disliked this term. Nepotism: a form of conditional helping, in which altruism is provided to close kin (parental care is a special case of nepotism). This behaviour is often referred to as kin selection. Recognition alleles: in the broad sense, genes that control KR (or at least the production of cues and ability to recognise kinship cues). In the literature this term is used for green-beard genes, self-inspection, or both.
79
80
Dustin J. Penn and Joachim G. Frommen
Acknowledgements We are very grateful to Z. Tang-Martinez, who offered particularly thoughtful comments on the manuscript. We thank A. Hettyey, T. Thünken, S.A. Baldauf, S.M. Zala, an anonymous referee, as well as many students for their helpful comments on earlier versions, S. Meagher for the illustrations of mice’ and R. Hengsberger for assistance with editing figures and tables. Finally, we thank P.M. Kappeler for editing the volume and inviting us to write a chapter.
References Alexander RD, Borgia G (1978) Group selection, altruism, and the levels of organization of life. Annu Rev Ecol Syst 9:449-474 Antal T, Ohtsuki H, Wakeley J, Taylor PD, Nowak MA (2009) Evolution of cooperation by phenotypic similarity. Proc Natl Acad Sci USA 106:8597-8600 Axelrod R, Hammond RA, Grafen A (2004) Altruism via kin-selection strategies that rely on arbitrary tags with which they coevolve. Evolution 58:1833-1838 Barnard CJ (1991) Kinship and social behavior: the trouble with relatives. Trends Ecol Evol 6:310-312 Barnard CJ, Hurst JL, Aldhous P (1991) Of mice and kin: the functional significance of kin bias in social behavior. Biol Rev 66:379-430 Beecher MD (1991) Success and failures of parent-offspring recognition in animals. In: Hepper PG (ed) Kin Recognition. Cambridge University Press, Cambridge, pp 95-124 Beecher MD, Beecher IM, Hahn S (1981) Parent-offspring recognition in bank swallows (Riparia riparia). II. Development and acoustic basis. Anim Behav 29:95-101 Blaustein AR, Bekoff M, Byers JA, Daniels TJ (1991) Kin recognition in vertebrates: what do we really know about adaptive value? Anim Behav 41:10791083 Bressan P, Zucchi G (2009) Human kin recognition is self-rather than familyreferential. Biol Lett 5:336-338 Brown JL, Eklund A (1994) Kin recognition and the major histocompatibility complex: an integrative review. Am Nat 143:435-461 Byers JA, Bekoff M (1986) What does ‘kin recognition’ mean? Ethology 72:342345 Byers JA, Bekoff M (1991) Development, the conveniently forgotten variable in ‘true kin recognition’. Anim Behav 41:1088-1090 Clarke FM, Faulkes CG (1999) Kin discrimination and female mate choice in the naked mole-rat Heterocephalus glaber. Proc R Soc Lond B 266:1995-2002 Crampton WGR, Hurst LD (1994) True kin recognition, in the form of somatic incompatibility, has multiple independent origins. Anim Behav 47:230-234
Kin recognition: conceptual issues, mechanisms and evolutionary theory
81
Crnokrak P, Roff DA (1999) Inbreeding depression in the wild. Heredity 83:260270 Crozier RH (1986) Genetic clonal recognition abilities in marine invertebrates must be maintained by selection for something else. Evolution 40:1100-1101 Crozier RH (1987) Genetic aspects of kin recognition: concepts, models, and synthesis. In: Fletcher DJC, Michener CD (eds) Kin Recognition in Animals. Wiley, New York, pp 55-73 Davies NB, Hatchwell BJ, Robson T, Burke T (1992) Paternity and parental effort in dunnocks Prunella modularis how good are male chick-feeding rules. Anim Behav 43:729-745 Dawkins R (1976) The Selfish Gene. Oxford University Press, New York Dawkins R (1979) Twelve misunderstandings of kin selection. Z Tierpsychol 51:184-200 Dawkins R (1982) The Extended Phenotype: the Gene as the Unit of Selection. WH Freeman, Oxford DeBruine LM (2002) Facial resemblance enhances trust. Proc R Soc Lond B 269:1307-1312 Dewsbury DA (1982) Avoidance of incestuous breeding between siblings in two species of Peromyscus mice. Biol Behav 7:157-169 Dudley SA, File AL (2007) Kin recognition in an annual plant. Biol Lett 3:435438 Elwood RW, Ostermeyer MC (1984) Does copulation inhibit infanticide in male rodents? Anim Behav 32:293-294 Fletcher DJC, Michener CD (1987) Kin Recognition in Animals. John Wiley, New York Frommen JG, Luz C, Bakker TCM (2007a) Kin discrimination in sticklebacks is mediated by social learning rather than innate recognition. Ethology 113:276282 Frommen JG, Mehlis M, Brendler C, Bakker TCM (2007b) Shoaling decisions in three-spined sticklebacks (Gasterosteus aculeatus) – familiarity, kinship and inbreeding. Behav Ecol Sociobiol 61:533-539 Galef BG Jr (1976) Social transmission of acquired behavior: a discussion of tradition and social learning in vertebrates. Adv Stud Behav 6:77-100 Gamboa GJ, Reeve HK, Holmes WG (1991) Conceptual issues and methodology in kin-ecognition research: a critical discussion. Ethology 88:109-127 Gardner A, West SA (2007) Social evolution: the decline and fall of genetic kin recognition. Curr Biol 17:R810-R812 Gould SJ, Vrba ES (1982) Exaptation – a missing term in the science of form. Paleobiology 8:4-15 Grafen A (1990) Do animals really recognise kin? Anim Behav 39:42-54 Grafen A (1991a) Kin vision? A reply to Stuart. Anim Behav 41:1095-1096 Grafen A (1991b) A reply to Blaustein et al. Anim Behav 41:1085-1087 Grafen A (1991c) A reply to Byers and Bekoff. Anim Behav 41:1091-1092 Griffin AS, West SA (2002) Kin selection: fact and fiction. Trends Ecol Evol 17:15-21
82
Dustin J. Penn and Joachim G. Frommen
Grosberg RK, Quinn JF (1986) The genetic control and consequences of kin recognition by larvae of a colonial marine invertebrate. Nature 322:456-459 Haig D (1996) Gestational drive and the green-bearded placenta. Proc Natl Acad Sci USA 93:6547-6551 Halpin ZT (1986) Individual odors among mammals: origins and functions. Adv Stud Behav 16:39-70 Halpin ZT (1991) Kin recognition cues of vertebrates. In: Hepper PG (ed) Kin Recognition. Cambridge University Press, Cambridge, pp 220-258 Hamilton WD (1964) The genetical evolution of social behaviour I. J Theor Biol 7:1-16 Hamilton WD (1975) Innate social aptitudes of man: an approachfrom evolutionary genetics. In: Fox R (ed) ASA Studies 4: Biosocial Anthropology. Malaby Press, London, pp 133-153 Hamilton WD (1996) Narrow Roads of Gene Land. WH Freeman, Oxford Hare JF, Sealy SG, Underwood TJ, Ellison KS, Stewart RLM (2002) Evidence of self-referent phenotype matching revisited: airing out the armpit effect. Anim Cogn 6:65-68 Hartley IR, Davies NB, Hatchwell BJ, Desrochers A, Nebel D, Burke T (1995) The polygynandrous mating system of the alpine accentor, Prunella collaris. II. Multiple paternity and parental effort. Anim Behav 49:789-803 Helanterä H, Bargum K (2007) Pedigree relatedness, not greenbeard genes, explains eusociality. Oikos 116:217-220 Hepper PG (1991a) Kin Recognition. Cambridge University Press, Cambridge Hepper PG (1991b) Recognizing kin: ontogeny and classification. In: Hepper PG (ed) Kin Recognition. Cambridge University Press, Cambridge, pp 259-288 Heth G, Todrank J (2001) Self referencing in hamsters: comment from Heth and Todrank. Trends Ecol Evol 16:74 Holmes WG (2004) The early history of Hamiltonian-based research on kin recognition. Ann Zool Fennici 41:691-711 Holmes WG, Sherman PW (1982) The ontogeny of kin recognition in two species of ground squirrels. Am Zool 22:491-517 Holmes WG, Sherman PW (1983) Kin recognition in animals. Am Sci 71:46-55 Hughes WOH, Oldroyd BP, Beekman M, Ratnieks FLW (2008) Ancestral monogamy shows kin selection is key to the evolution of eusociality. Science 320:1213-1216 Jansen VAA, van Baalen M (2006) Altruism through beard chromodynamics. Nature 440:663-666 Johnstone RA (1997) Recognition and the evolution of distinctive signatures: when does it pay to reveal identity? Proc R Soc Lond B 264:1547-1553 Keller L, Ross KG (1998) Selfish genes: a green beard in the red fire ant. Nature 394:573-575 Kempenaers B, Sheldon BC (1996) Why do male birds not discriminate between their own and extra-pair offspring? Anim Behav 51:1165-1173 Kuester J, Paul A, Arnemann J (1994) Kinship, familiarity and mating avoidance in Barbary macaques, Macaca sylvanus. Anim Behav 48:1183-1194
Kin recognition: conceptual issues, mechanisms and evolutionary theory
83
Lacy RC, Sherman PW (1983) Kin recognition by phenotype matching. Am Nat 121:489-512 Leinders-Zufall T, Brennan P, Widmayer P, Chandramani P, Maul-Pavicic A, Jager M, Li X-H, Breer H, Zufall F, Boehm T (2004) MHC class I peptides as chemosensory signals in the vomeronasal organ. Science 306:1033-1037 Lieberman D, Tooby J, Cosmides L (2007) The architecture of human kin detection. Nature 445:727-731 Liebert AE, Starks PT (2004) The action component of recognition systems: a focus on the response. Ann Zool Fennici 41:747-764 Manica A (2002) Filial cannibalism in teleost fish. Biol Rev 77:261-277 Manning CJ, Wakeland EK, Potts WK (1992) Communal nesting patterns in mice implicate MHC genes in kin recognition. Nature 360:581-583 Mateo JM (2004) Recognition systems and biological organization: the perception component of social recognition. Ann Zool Fennici 41:729-745 Mateo JM, Johnston RE (2000) Kin recognition and the ‘armpit effect’: evidence of self-referent phenotype matching. Proc R Soc Lond B 267:695-700 Mateo JM, Johnston RE (2001) Self referencing in hamsters: reply from Hauber and Sherman. Trends Ecol Evol 16:74-75 Mateo JM, Johnston RE (2003) Kin recognition by self-referent phenotype matching: weighing the evidence. Anim Cogn 6:73-76 McRae SB (1996) Family values: costs and benefits of communal nesting in the moorhen. Anim Behav 52:225-245 Milinski M (2006) The major histocompatibility complex, sexual selection, and mate choice. Annu Rev Ecol Evol Syst 37:159-186 Moore T, Moore HD (2002) Marsupial sperm pairing: a case of ‘sticky’ green beards? Trends Ecol Evol 17:112-113 Müller JK, Eggert A-K (1990) Time-dependent shifts between infanticidal and parental behavior in female burying beetles: a mechanism of indirect motheroffspring recognition. Behav Ecol Sociobiol 27:11-16 Neff BD, Sherman PW (2002) Decision making and recognition mechanisms. Proc R Soc Lond B 269:1435-1441 Novotny MV, Soini HA, Koyama S, Wiesler D, Bruce KE, Penn DJ (2007) Chemical identification of MHC-influenced volatile compounds in mouse urine. I: quantitative proportions of major chemosignals. J Chem Ecol 33:417434 Pagel M (1997) Desperately concealing father: a theory of parent-infant resemblance. Anim Behav 53:973-981 Penn DJ (2002) The scent of genetic compatibility: sexual selection and the major histocompatibility complex. Ethology 108:1-21 Penn DJ, Potts WK (1998) MHC-disassortative mating preferences reversed by cross-fostering. Proc R Soc Lond B 265:1299-1306 Penn DJ, Potts WK (1999) The evolution of mating preferences and major histocompatibility complex genes. Am Nat 153:145-164 Penn DJ, Damjanovich K, Potts WK (2002) MHC heterozygosity confers a selective advantage against multiple-strain infections. Proc Natl Acad Sci USA 99:11260-11264
84
Dustin J. Penn and Joachim G. Frommen
Petrie M, Krupa A, Burke T (1999) Peacocks lek with relatives even in the absence of social and environmental cues. Nature 401:155-157 Pfennig DW, Reeve HK, Sherman PW (1993) Kin recognition and cannibalism in spadefoot toad tadpoles. Anim Behav 46:87-94 Porter RH (1988) The ontogeny of sibling recognition in rodents: superfamily Muroidea. Behav Gen 18:483-494 Porter RH (1991) Mutual mother-infant recognition in humans. In: Hepper PG (ed) Kin Recognition. Cambridge University Press, Cambridge, pp 413-432 Porter RH, Tepper VJ, White DM (1981) Experimental influence on the development of huddling preferences and ‘sibling’ recognition in spiny mice. Dev Psychobiol 14:375-382 Queller DC, Ponte E, Bozzaro S, Strassmann JE (2003) Single-gene greenbeard effects in the social amoeba Dictyostelium discoideum. Science 299:105-106 Reeve HK (1989) The evolution of conspecific acceptance thresholds. Am Nat 133:407-435 Reeve HK, Sherman PW (2001) Optimality and phylogeny: a critique of current thought. In: Orzack SH, Sober E (eds) Adaptationism and Optimality. Oxford University Press, Oxford, pp. 64-113 Ridley M, Grafen A (1981) Are green beard genes outlaws? Anim Behav 29:954955 Rousset F, Roze D (2007) Constraints on the origin and maintenance of genetic kin recognition. Evolution 61:2320-2330 Schausberger P (2007) Kin recognition by juvenile predatory mites: prior association or phenotype matching? Behav Ecol Sociobiol 62:119-125 Sherman PW, Holmes WG (1985) Kin recognition: issues and evidence. In: Hölldobler B, Lindauer M (eds) Experimental Behavioral Ecology and Sociobiology. Gustav Fischer-Verlag, Stuttgart, pp 437-460 Sherman PW, Reeve HK, Pfennig DW (1997) Recognition systems. In: Krebs JR, Davies NB (eds) Behavioural Ecology: An Evolutionary Approach. Blackwell, Oxford, pp 69-98 Sinervo B, Chaine A, Clobert J, Calsbeek R, Hazard L, Lancaster L, McAdam AG, Alonzo S, Corrigan G, Hochberg ME (2006) Self-recognition, color signals, and cycles of greenbeard mutualism and altruism. Proc Natl Acad Sci USA 103:7372-7377 Smukalla S, Caldara M, Pochet N, Beauvais A, Guadagnini S, Yan C, Vinces MD, Jansen A, Prevost MC, Latge J-P, Fink GR, Foster KR, Verstrepen KJ (2008) FLO1 is a variable green beard gene that drives biofilm-like cooperation in budding yeast. Cell 135:726-737 Stuart RJ (1991) Kin recognition as a functional concept. Anim Behav 41:10931094 Summers K, Crespi B (2005) Cadherins in maternal-foetal interactions: red queen with a green beard? Proc R Soc Lond B 272:643-649 Tang-Martinez Z (2001) The mechanisms of kin discrimination and the evolution of kin recognition in vertebrates: a critical re-evaluation. Behav Proc 53:21-40 Thünken T, Bakker TCM, Baldauf SA, Kullmann H (2007a) Active inbreeding in a cichlid fish and its adaptive significance. Curr Biol 17:225-229
Kin recognition: conceptual issues, mechanisms and evolutionary theory
85
Thünken T, Bakker TCM, Baldauf SA, Kullmann H (2007b) Direct familiarity does not alter mating preference for sisters in male Pelvicachromis taeniatus (Cichlidae). Ethology 113:1107-1112 Todrank J, Heth G (2003) Odor-genes covariance and genetic relatedness assessments: rethinking odor-based ‘recognition’ mechanisms in rodents. Adv Stud Behav 32:77-130 Tsutsui ND (2004) Scents of self: the expression component of self/nonself recognition systems. Ann Zool Fennici 41:713-727 van der Jeugd HP, van der Veen IT, Larsson K (2002) Kin clustering in barnacle geese: familiarity or phenotype matching? Behav Ecol 13:786-790 Vander Meer RK, Alonso LE (2002) Queen primer pheromone affects conspecific fire ant (Solenopsis invicta) aggression. Behav Ecol Sociobiol 51:122-130 Villinger J, Waldman B (2008) Self-referent MHC type matching in frog tadpoles. Proc R Soc Lond B 275:1225-1230 Waldman B (1987) Mechanisms of kin recognition. J Theor Biol 128:159-185 Waldman B (1988) The ecology of kin recognition. Annu Rev Ecol Syst 19:543571 Waldman B, Frumhoff PC, Sherman PW (1988) Problems of kin recognition. Trends Ecol Evol 3:8-13 West SA, Pen I, Griffin AS (2002) Cooperation and competition between relatives. Science 296:72-75 Westermarck EA (1891) The History of Human Marriage. Macmillian, London Willse A, Belcher AM, Preti G, Wahl JH, Thresher M, Yang P, Yamazaki K, Beauchamp GK (2005) Identification of major histocompatibility complexregulated body odorants by statistical analysis of a comparative gas chromatography/mass spectrometry experiment. Anal Chem 77:2348-2361 Willse A, Kwak J, Yamazaki K, Preti G, Wahl JH, Beauchamp GK (2006) Individual odortypes: interaction of MHC and background genes. Immunogenetics 58:967-982 Wilson EO (1975) Sociobiology: The New Synthesis. Havard University Press, Cambridge/MA Wyatt TD (2003) Pheromones and Animal Behaviour: Communication by Smell and Taste. Cambridge University Press, Cambridge Yamazaki K, Beauchamp GK, Kupniewski D, Bard J, Thomas L, Boyse EA (1988) Familial imprinting determines H-2 selective mating preferences. Science 240:1331-1332 Yamazaki K, Beauchamp GK, Curran M, Bard J, Boyse EA (2000) Parentprogeny recognition as a function of MHC odortype identity. Proc Natl Acad Sci USA 97:10500-10502
Chapter 4
Honeybee cognition MARIO PAHL, JÜRGEN TAUTZ AND SHAOWU ZHANG
ABSTRACT Behavioural research on honeybees has shown that bees are not the simple, hardwired creatures they were once believed to be. Bees display perceptual and ‘cognitive’ abilities that are rich, complex and flexible. In this chapter, we begin a review of these abilities with a brief introduction of the bee’s sensory equipment. Next, we describe several experimental approaches to bee behaviour. As this review is not intended to be exhaustive, we focus on behavioural experiments on free-flying honeybees. The studies described here investigate complex forms of learning and navigation, and mark important steps in understanding the processes underlying the bee’s remarkable behaviours.
4.1 Introduction Animals are constantly exposed to a stream of sensory information that must be successfully harnessed to improve their chances of survival and reproduction. The way in which animals go about doing this, i.e. the mechanisms by which animals acquire, process, store, and act on information from the environment (Shettleworth 1998; see also Giurfa 2003), can be termed cognition. This chapter focuses on the latter part of this sequence of events, namely the manner in which animals respond to information in the environment through observable behaviours, such as foraging, navigation, mate recognition and other forms of decision making. We begin by outlining the reasons why the honeybee (Apis mellifera) is eminently suited for such investigations into animal cognition. We then describe the sensory world of the honeybee, as this background information is highly relevant to the types of behaviour that this insect can produce. The bulk of the chapter presents the results of research on the impressive behavioural repertoire of honeybees in relation to the sensory information
88
Mario Pahl, Jürgen Tautz and Shaowu Zhang
available to them, under both laboratory and natural conditions, focusing on more recent behavioural studies that demonstrate that these insects also possess cognitive abilities that were once only ascribed to vertebrates. We also decided to concentrate on studies that have made use of free-flying bees, as they go further towards simulating situations that match the behaviour of bees in nature. Naturally, we recognise the important and fascinating contributions made by studies using tethered bees in experimental paradigms like the proboscis extension reflex (such as Bitterman et al. 1983, Maleszka and Helliwell 2001, Giurfa and Malun 2004), but an indepth review of these studies is beyond the scope of the current chapter.
4.2 Why study honeybees? Studies of animal cognition have traditionally focused on vertebrates like rats, monkeys and birds, i.e. animals that possess relatively large brains and are evolutionarily not too distant from humans. A bee brain, on the other hand, contains less than a million neurons (Witthöft 1967), about five orders of magnitude less than a human brain with an estimated 100 billion neurons (Williams and Herrup 1988). However, it would be a mistake to assume that higher neuron numbers and larger brains are a prerequisite for complex learning, which is defined as any learning other than simple associative or Pavlovian learning and operant conditioning (Giurfa 2003). Many of the experimental paradigms and behavioural assays developed for vertebrates have now been adapted to insects. One example is the delayed match-to-sample (DMTS) paradigm, which was independently developed in 1959 by Blough and Konorski for pigeons, and later used to study memory in honeybees (see Sect. 4.4.1; Blough 1959, Konorski 1959). Honeybees are social insects with a sophisticated system of division of labour, in which each bee flexibly carries out different tasks, depending on its age and the colony’s needs. Arranged in the order of occurrence, these are: cell cleaning, capping the brood, caring for the brood, serving in the queen’s court, receiving nectar, production of honey, removal of detritus, pollen packing, comb building, ventilation, entrance guarding and foraging. They fly fast and with precision, navigate large distances to food sources, communicate those food locations and potential new nest sites using a symbolic dance language, and efficiently manipulate different flowers to extract nectar and pollen (von Frisch 1967, Seeley 1995). This lifestyle makes honeybees highly suitable organisms for studying the principles of learning, memory and navigation. When trained to fly into a Y-maze to memorise one of two opposing stimuli, a bee can learn a new
Honeybee cognition
89
odour during just a few rewarded visits to a food source, a new colour in about 5 visits, a new pattern in about half a day (after 20-30 visits), and a new route to a food source in only 3-4 visits (Zhang 2006). The underlying navigational skills that make this behaviour possible require efficient information processing and storage mechanisms which, in turn, allow bees to display perceptual and ‘cognitive’ abilities that are surprisingly rich, complex and flexible (Menzel and Mueller 1996, Srinivasan et al. 1998, Collett and Collett 2002, Giurfa 2003, Zhang and Srinivasan 2004a,b).
4.3 The honeybee’s sensory world As the acquisition of useful information from the outside world is the first step in our cognitive sequence of events defined above, it is pertinent to consider the two main sensory systems of the honeybee – the eyes and the antennae. Most of the honeybee brain is devoted to processing the sensory input from these structures (Brandt et al. 2005), and it follows that vision and olfaction play critically important roles in honeybee cognition. These two systems are briefly described below. 4.3.1 The compound eye The honeybee’s compound eyes cover a large part of the head, and consist of approximately 6,000 ommatidia each (Tautz 2008). Compound eyes have, compared to human lens eyes, a low visual acuity, because each ommatidium contributes 1 pixel to the picture the bee perceives (in contrast to a single complete picture on the retina formed by a lens). Thus, a bee has to inspect a flower closely to be able to see its exact shape. The bee’s temporal resolution, however, is extremely high, and well suited for fast flight maneuvers (Srinivasan et al. 1999). Bees have trichromatic vision provided by UV, blue and green receptors (Menzel and Blakers 1976), which shift their visual spectrum into the shorter wavelengths, compared to human colour vision. This means that honeybees cannot see red (which appears black to them), but they can see UV light. The short wavelength UV receptor is also involved in perceiving linearly polarised light (Rossel and Wehner 1986). Because many blossoms carry UV-reflecting patterns on the petals, this information can be used to discriminate flowers (Chittka et al. 1994). The green receptor is, apart from colour vision, used for edgeand movement detection (Lehrer et al. 1990), including distance estimation by optic flow (Chittka and Tautz 2003).
90
Mario Pahl, Jürgen Tautz and Shaowu Zhang
4.3.2 The antennae Olfaction is important for navigation, foraging and social behaviours in the hive. Floral scents guide honeybees to profitable flowers to forage on, and they can amplify the spatial memories of those locations. Once a scent is associated with a food location, re-encountering this scent inside the hive (for example from a returning forager who has been foraging on the same flower species) is enough to trigger the navigational memories, and make the bee revisit the food site (Johnson and Wenner 1966, Reinhard et al. 2004a). Inside the hive, the queen pheromone prevents worker bees from laying eggs and rearing other queens, as long as the active queen is young and healthy. Nurse bees can distinguish between queen and worker eggs based on their scent, and destroy eggs from other worker bees (see Ratnieks and Wenseleers 2008, Tautz 2008, and Heinze this volume for details on worker policing). Since each hive has its own special bouquet of hydrocarbons on the bees’ cuticulae, they can easily distinguish between their nestmates and foreign bees. The 60,000 olfactory receptor cells on the antennae are able to discriminate a nearly unlimited number of odours (Vareschi 1971). Interestingly, the sensillae are concentrated on the right antenna, and bees respond to odours better when they are trained on their right antenna. This kind of functional lateralisation is a phenomenon well known in humans and other vertebrates, and has recently been shown in the honeybee as well (Letzkus et al. 2006).
4.4 Experimental approaches The visual and olfactory capabilities mentioned above make the honeybee a flexible model organism for the study of cognition and behaviour, one that can be subjected to a variety of experimental techniques, both in the laboratory and in the field. Some of the more widely used techniques are described below. 4.4.1 Learning in maze experiments Bees can be easily trained to forage at artificial sucrose feeders, even several kilometres from the hive (von Frisch 1967). Each visiting bee can be individually marked, and its behaviour can then be observed at the feeder and inside the hive (for example in Collett and Baron 1994). Experiments such as this are very useful in identifying and separating out the many fac-
Honeybee cognition a
b
Matching stimuli
A’
91
B’
Baffle
Sample stimulus A d
% Correct decisions
100
A
B
A’
B’
75
50 1
2
3
4
Training block
5
6
Probability of response
c
1.0 P 0.5
0.0
U
P
6
7
U 1
2
3
4
5
Trial
8
Fig. 4.1 a. Delayed match-to-sample (DMTS) setup in a Y-maze. In order to get a reward, the bee has to look at the sample stimulus A, store it in working memory, and recall it when deciding for one of the two matching stimuli A’ or B’. The baffle prevents the bee from seeing both sample and matching stimulus at the same time. A’ leads to a reward in this example. b. Proboscis extension response (PER) in harnessed bees. Touching the antennae with sucrose solution (US) elicits proboscis extension in naive bees, while an odour does not. Bees are conditioned to associate an odour (CS) with a sucrose reward (US). The odour alone leads to proboscis extension in the trained bee. c. Learning curve of a DMTS experiment. * denotes a choice level significantly different from random choice. Adapted from Gross et al. (2009). d. Learning curve of a PER experiment. Probability of response to the CS in a group of subjects given paired training (P) and in a group given unpaired training (U) followed by paired training (U → P). Adapted with permission from Bitterman et al. (1983). See text for details. Pictures in b courtesy of Helga R. Heilmann, BEEgroup.
tors that honeybees have to take into account when, for instance, embarking on a foraging trip to a food source. Artificial feeders can also be placed behind a stimulus at the end of a maze (Fig. 4.1a), in which the bee has to make one or more decisions for a visual stimulus or odour to gain access to
92
Mario Pahl, Jürgen Tautz and Shaowu Zhang
the feeder. The maze can be simply Y-shaped, when a single discrimination task is to be performed (for example, Srinivasan and Lehrer 1988), or more complex, when the bee is trained to navigate an extensive maze according to symbolic cues or rules (see Sect. 4.5.2). A widely used setup to investigate the principles of learning and working memory is the delayed match-to-sample (DMTS) paradigm. Established in more traditional animals models in cognitive studies, such as monkeys (Damato et al. 1985), dolphins (Herman and Gordon 1974) and pigeons (Roberts 1972), it proved extremely useful in honeybee research as well. In most DMTS experiments, the animal is presented with a sample stimulus A, followed by a delay, and is then presented with two matching stimuli, A’ and B’. In order to receive a reward, the animal has to memorise the sample stimulus, and after a short delay (e.g. 5 sec), choose the matching stimulus identical to the sample; A’ in this case. If B is the sample stimulus, the animal has to choose matching stimulus B’ to receive a reward (Fig. 4.1a, c). The animal then has to show the ability to transfer the learned matching ability to novel stimuli, which it has not encountered during the training phase. Both long-term and working memory are required to successfully complete this task – long-term memory for the matching rule, and working memory for the sample pattern to be matched on each visit to the maze. 4.4.2 Navigation in tagged free-flying honeybees While it is relatively easy to observe marked honeybees at an artificial feeder or at the hive, it is nearly impossible to study the behaviour of honeybees in mid-flight with the naked eye. Human observation can also only be carried out for a few hours at a time, which makes it difficult to gauge the behaviour of large numbers of foragers over a long study period, such as days or weeks. It is precisely to overcome such difficulties that some researchers have turned to miniature signaling devices that can be attached to the thorax of individual bees, thereby allowing their behaviour to be monitored automatically. One such technique involves the use of harmonic radar, with which the exact trajectories of individuals can be monitored over short periods of time. This technique has proven valuable in studies of honeybee navigation, particularly in the investigation of homing mechanisms (Menzel et al. 2005, Reynolds et al. 2007). More recently, radio frequency ID (or RFID) tags have also been used to study foraging behaviour in honeybees (Streit et al. 2003, Fuchs et al. 2006). Each tag is coded with an individual ID which is logged by a receiver every time a tagged honeybee passes near it. This technology seems
Honeybee cognition
93
ideally suited for investigating various problems, such as the effect of the weather or the visual landscape on honeybee homing and foraging abilities. 4.4.3 Classical conditioning in harnessed bees Classical conditioning is a form of associative learning that was first demonstrated in dogs by Ivan Pavlov. In this experimental paradigm, the bee is harnessed in a tube so that the antennae and mouth parts can move freely (Fig. 4.1b). When the antennae are touched with a sucrose solution (unconditioned stimulus, US), the bee extends its proboscis to drink the sucrose. Simple, non-associative forms of learning, such as habituation and sensitisation, can be studied in this way. Odourants do not elicit this reaction in untrained animals. However, when an odour (conditioned stimulus, CS) is presented just a few seconds before the sucrose, the bee forms an association between the US and the CS (forward pairing), and the odourant (CS) alone can elicit the PER in the next test (Bitterman et al. 1983, see Fig. 4.1d for a learning curve). So far, this is purely associative learning, and no higher processing is required. However, honeybees can not only be trained to perform elementary distinctions involving a rewarded (A+) and an unrewarded odour (B–, where + and – represent rewarded and non-rewarded stimuli, respectively). They can solve configural learning tasks as well, where pure elementary associations are insufficient to succeed. In a biconditional discrimination experiment, involving four odours A, B, C and D, bees could be trained to react to only two binary combinations of four odours (AB+, CD+) but not to the other combinations (AC–, BD–, see Hellstern et al. 1995). Although the reward frequency during the training for each stimulus was equal, the bees formed configural associations, enabling them to react appropriately to the odour combinations. Honeybees can solve positive patterning tasks as well, where the animals learn to react to the combination of two odours (AB+), but not to the single odours (A–, B–). The same is true for negative patterning (AB–, A+, B+, see Deisig et al. 2001). The PER setup is an excellent method to bring advanced learning and memory processes into a laboratory situation. The harnessed bee setup also enables scientists to apply electrophysiological and optophysiological techniques in vivo (Giurfa 2007), while the bee is behaving in a PER experiment, to trace memory and learning to brain areas and individual neurons. However, as stated earlier, the remainder of this chapter will be devoted to studies involving free-flying bees.
94
Mario Pahl, Jürgen Tautz and Shaowu Zhang
4.5 Cognitive mechanisms underlying behaviour All animals must make decisions throughout their lives when interacting with their surroundings, and the honeybee is no exception. Decisionmaking is necessary inside the hive, when, for instance, following a waggle dance, and outside the hive, when locating a food source, actively foraging at the food source, or returning to the hive. We will therefore discuss in this section studies on three important mechanisms that inform decisionmaking in honeybees, as evidenced by behaviour observed in free-flying animals. 4.5.1 Categorisation When honeybees are foraging, they need to remember routes to and from different food sources. There can be little doubt that they use some kind of neural ‘snapshot’ to remember and recognise landscapes and landmarks on these routes (Collett and Cartwright 1983, Judd and Collett 1998). However, it is hard to believe that the bee’s brain is capable of storing so many different images of the environment in its restricted memory. Categorisation is an information processing strategy in which objects or events are grouped together into categories, so that a similar response can be made to all members of the category (Keller and Schoenfeld 1950, Troje et al. 1999). Thus, an organism is not restricted to respond only to stimuli it has already encountered, but it can develop a set of appropriate reactions to all stimuli that match certain criteria (Wasserman 1993). Since categorisation is the basis for any identification and classification task, it has enormous biological relevance, particularly for a foraging honeybee. It would be especially interesting to know the extent to which invertebrates are able to employ this ability in spite of their miniature central nervous systems (see Prete 2004 for some examples). 4.5.1.1 Learning pattern properties The lifestyle of honeybees requires them to remember a number of different patterns, such as the shape of the hive, shapes of nectar-bearing flowers, and shapes of prominent landmarks. Thus, one would expect that honeybees have evolved a way to compress image information and to extract the general identifying features of a pattern, such as its shape, orientation, symmetry, colour and size. Indeed, honeybees have been shown to be able to extract orientation (van Hateren et al. 1990), radial and circular symmetry (Horridge and Zhang 1995) as well as bilateral symmetry, including the
Honeybee cognition
95
orientation axis (Giurfa et al. 1996, Horridge 1996), of visual patterns, and to learn these features to solve decision-making tasks. Other characteristics of objects, such as colour and size, can be extracted and memorised as well, without having to store the entire image (Horridge et al. 1992, Ronacher 1992). Recently, using differential conditioning in free-flying bees, Dyer et al. (2005) have shown that honeybees are even capable to discriminate between, and recognise images of, human faces. 4.5.1.2 Categorisation of natural objects In 2004, Zhang and colleagues investigated whether bees can categorise similar natural images together. They trained bees in a multiple choice maze (Fig. 4.2a, b) to distinguish between four different types of natural scenes, and to group them into four distinct categories: Category F consisted of images of flowers that were star-shaped and of different colours; Category f comprised images of flowers that were nearly circular in shape and of different colours; Category P consisted of images of plant stems of various shapes; and Category L was composed of images of landscapes (Fig. 4.2c). Within each category, individual images differed in details of shape, texture, and sometimes colour. Bees were trained in a multiple choice maze in a DMTS task, in which they were shown a picture as a sample stimulus in the entrance chamber (C1). To continue through the maze, they had to fly through a small hole in the middle of the sample picture to enter chamber two (C2). The back wall of C2 was transparent, with a 3-cm hole in its centre. The small aperture restricted the bees’ flight speed, and the transparent wall allowed them to see four additional pictures (or comparison stimuli) on the rear wall of chamber three (C3, see Fig. 4.2a, b). During training, the sample stimuli and the four comparison stimuli were all from Group 1. Groups 1-4 each consisted of one unique example of each of the four categories; all of them are shown in Fig. 4.2c. If the bee chose the correct test stimulus in C3, she received a reward of sugar solution from a feeder that was placed in the reward box behind that stimulus, by landing on and crawling through a tube in the centre of the stimulus (Fig. 4.2). In transfer tests, Zhang et al. investigated whether the trained bees could match a sample stimulus from one group to a stimulus of the same category from a different group. They had to, for example, match the yellow star-shaped flower F1 in group 1 to the blue star-shaped flower F3 in group 3 (Fig. 4.2c and 4.3b). In these tests, the sample was always a stimulus from Group 1, but the comparison stimuli were from Group 2, 3 or 4 (Fig. 4.2c). The bees performed very well in these transfer tests. In fact, in each case, the bees showed a clear and significant preference for the test stimu-
96
Mario Pahl, Jürgen Tautz and Shaowu Zhang a) Lateral view
b) Frontal view
R1,2 C1
C2
C3 R3,4
1
2
3
4
20 cm
c) Stimuli Group 1 F1
f1
P1
L1
F2
f2
P2
L2
F3
f3
P3
L3
F4
f4
P4
L4
Group 2
Group 3
Group 4
Fig. 4.2 The multiple choice maze in the categorisation experiment. a shows the multiple choice maze in lateral view. b shows a frontal view of the choice area and the arrangement of stimuli. c illustrates all the training (group 1) and testing (groups 2-4) stimuli. Adapted with permission from Zhang et al. (2004).
lus that belonged to the same category as the sample (Fig. 4.3a, b). Particularly noteworthy is the transfer test using Group 4, in which the comparison stimuli were entirely novel (Fig. 4.3c, Group 4). These stimuli had never been used in the training phase, or in the learning tests or transfer tests. Again, the bees performed very well at chosing the test stimulus that was in the same category as the sample (Fig. 4.3c).
Honeybee cognition
***
n =10 bees
*** ***
***
***
***
n =10 bees
* ***
n =10 bees
***
***
n =10 bees
***
***
n =10 bees
n =10 bees
*** *
*
*
**
n =10 bees
***
* ***
*
***
n =10 bees
***
***
n =10 bees
***
***
n =10 bees
***
* ***
***
***
97
***
* ***
n =10 bees
***
*** ** ***
n =10 bees
***
***
Fig. 4.3 Results of the categorisation experiment. These transfer tests examined the ability of bees to categorise sample stimuli from group 1, to test stimuli of the same category in (A) group 2, (B) group 3 and (C) the novel group 4. For each group, the bars show the relative preferences for the four test stimuli when the sample was F1, f1, P1 or L1, as shown underneath the abscissa. In each panel, N denotes the number of bees that were tested in each experiment. Asterisks denote statistically significant differences from the random choice level of 25% (broken horizontal lines). ***P < 0.001; **P < 0.01; *P < 0.05. Black asterisks refer to levels significantly greater than 25%, and red asterisks to levels significantly lower than 25%. O denotes P > 0.05. Values are means ± S.E.M. In each case, the bees chose the test stimulus that belonged to the same category as the sample. Adapted with permission from Zhang et al. (2004).
98
Mario Pahl, Jürgen Tautz and Shaowu Zhang
The results of the transfer tests with novel stimuli (Fig. 4.3c) show that the bees performed very well at chosing the novel test stimulus that was in the same category as the sample. The honeybees exhibited the same response to novel stimuli that differed greatly in their individual, low-level features. That is, bees treat these highly variable stimuli as equivalent. These findings suggest that the honeybee possesses an ability to group similar visual stimuli into categories, similar to that of vertebrates (Zhang et al. 2004). 4.5.2 Rule learning The ability to learn general rules for dealing with often-encountered situations is adaptive for an animal, as it would remove the need to repeatedly assess every situation and try out new strategies each time. This is particularly true for situations where the appropriate response can be determined by attending to real or abstract cues, and is followed up by an application of a learned set of behaviours. Honeybees are good candidates for the study of the acquisition of abstract rules; after all, the waggle dance is the most complex abstract communication systems in the animal kingdom outside human language. Several studies have shown that honeybees can not only learn visual and olfactory stimuli as signals that indicate a particular action to be performed, but that they can also be trained to learn other abstract rules that are specific to particular experimental situations. 4.5.2.1 Learning principles of symbolic matching In 2001, Giurfa and colleagues showed that honeybees are capable of learning the concept of ‘sameness’ in a DMTS task, and the concept of ‘difference’ in a delayed non-matching task (DNMTS). The bees were trained in a Y-maze as shown in Fig. 4.1a. In one experiment, a group of bees was trained to match gratings: when the sample was a horizontal grating, the bees had to choose the horizontal comparison stimulus to get a reward; if the sample was a vertical grating, it had to choose the vertical stimulus. The position of the comparison stimuli was interchanged regularly to prevent the bees from simply learning to fly to the left or right. The bees learned this task well. The trained group was then tested on their ability to transfer their learned rules to colours. When a yellow sample was presented, they had to choose the yellow comparison stimulus, and when blue was presented as a sample, they had to choose blue. The bees were able to immediately solve the new task, although they had never encountered colours during their training.
Honeybee cognition
99
Honeybees can also learn to match odours in the same setup. Furthermore, bees trained to match odours can immediately transfer the learned matching ability to colours, showing that the concept of ‘matching’ can be transferred even across sensory modalities. Finally, bees can learn the concept of ‘difference’ as well, when they are trained to choose the nonmatching stimulus rather than the matching one. These tasks involve working memory, when the bee has to remember the sample stimulus during the short delay, and long-term memory, where the general rule ‘choose the matching pattern similar to the sample at the entrance’ is stored. A more complex variant of this paradigm is the symbolic delayed match-to-sample (SDMTS) task. Here, the sample and matching stimuli are never identical; the correct choice is either arbitrarily designed by the experimenter (i.e. if the sample is blue, choose the horizontal grating as matching stimulus, and if the sample is yellow, choose the vertical grating, see Zhang et al. 1999), or share a symbolic feature, e.g. number of items presented, and the animal has to extract the common number to get a reward (see Gross et al. 2009 and Sect. 4.5.2). Why would honeybees have evolved the ability to solve such tasks? Considering their foraging behaviour, we find that honeybees are often required to match memorised images to actual scenes. Collett and Wehner suggested that, when travelling repeatedly between a food source and the hive, foraging insects use a series of visual snapshots acquired en route to find their way. By comparing the stored image to the actual scene, the insect is able to ascertain whether it is on the right path to its goal (Collett and Kelber 1988, Wehner et al. 1990, 1996, Judd and Collett 1998). When bees forage at a meadow with many different flowers, they visit several blossoms of the same plant species before they reach their nectar load of ~50 mg and head home. Flower constancy is beneficial not only for the plants, ensuring pollination by pollen of the same species, but also for the bees, who become more efficient when learning to handle the same type of blossom repeatedly (Chittka et al. 1999). It also allows a bee to learn that a particular plant species produces nectar at a particular time of day. Thus, matching their memorised representation of a profitable species several times on a foraging trip improves foraging efficiency (see also Sect. 4.5.1). 4.5.2.2 Visual working memory in decision making In 2005, Zhang and colleagues set out to investigate the role of working memory in decision making in honeybees. They used a modified version of a Y-maze (shown in Fig. 4.4) with a long tunnel attached in front of the decision chamber, so that the distance between the sample and the matching stimuli (d1 in Fig. 4.4) could be varied between 25 and 575 cm. A
100
Mario Pahl, Jürgen Tautz and Shaowu Zhang
0.9
d2
0.8
Entrance
d1 A’
Choice frequency
B’
Sample A/B
R
0.7 A
B
A’
B’
0.6 0.5 0.4
y = 0.48e 0
2.5
-0.53t
+ 0.50
2
r = 0.999
5.0 7.5 Delay [sec]
10.0
12.5
Fig. 4.4 Maze setup, visual stimuli and results of the working memory experiment. The bee flies through the entrance into the tunnel (d2), and encounters sample A or B. Then it travels distance d1 between the sample and the decision chamber (1st circle). Here, it makes a decision between stimuli A’ and B’ to get a reward (R). B’ is rewarded in this example. The choice frequency drops to random level (dashed line) at a delay of 8.68 sec (d1 = 475 cm). Adapted with permission from Zhang et al. (2005).
longer distance between the sample and the decision chamber means a longer flight time for the bee, and thus the delay time could be varied between 1.24 ± 0.1 sec at 25 cm and 11.41 ± 1.69 sec at 575 cm. They trained the bees with a set of blue gratings oriented 45º (A) and 135º (B) from the horizontal (Fig. 4.4). During training, the distance between the sample pattern and the choice chamber was 25 cm. When the bees’ choice frequency for the correct pattern reached a plateau at 75 ± 3%, tests with greater distances and thus longer delay times were carried out. The results show that a visual pattern can be kept in working memory for about 8 sec; longer delays lead to random choices in the DMTS task (dashed line in Fig. 4.4). The information stored in working memory decays exponentially as a function of time (see Fig. 4.4 for equation). There is a surprising symmetry to Chittka’s findings on the memory dynamics for flower choice in bumblebees. He and his colleagues found that the flower constancy was excellent at intervisit intervals of up to 2 sec, dropped to half-maximum accuracy at 3-4 sec, and had decayed completely at 9 sec (Chittka et al. 1997, 1999). Zhang et al. also found that, when the DMTS task involves two samples (one relevant, the other irrelevant), bees can be trained to learn to use the relevant sample to perform the task if the relevant sample is always at a fixed position, or the relevant sample always has the same place in the sequence of presentation (always first or always second). Bees that have learned to use the relevant sample and to ignore the irrelevant sample can generalise this learning, and apply it to novel sets of sample and compari-
Honeybee cognition
101
son stimuli that they have not previously encountered. The findings point to a remarkably robust, and yet plastic working memory in the honeybee (Zhang et al. 2005). 4.5.2.3 Number-based visual generalisation The numerical abilities of many vertebrate species such as raccoons (Davis 1984), dolphins (Kilian et al. 2003), monkeys (Brannon and Terrace 2000), songbirds (Hunt et al. 2008) and even salamanders (Uller et al. 2003), have been investigated in the scientific literature. However, there are few convincing accounts of invertebrate numerical competence. Honeybees, by virtue of their other impressive cognitive feats, are a prime candidate for investigations of this topic. In a recent experiment, Gross et al. (2009) used the DMTS paradigm to test the limits of the honeybees’ ability to match two visual patterns solely on the basis of the shared number of elements in the two patterns. A group of about 20 bees was trained in a modified Ymaze apparatus to perform a basic DMTS task (Fig. 4.1a). After the bees had learned the DMTS rule with an accuracy of about 70% correct decisions, as shown in the learning curve in Fig. 4.1c, they were tested on novel sets of visual stimuli containing 2 and 3 blue dots in random configurations. The bees solved this task with an average accuracy of 74%, providing a first hint that the bees may be using the element number as a cue to solve the task (Fig. 4.5a). The bees were then tested whether they could transfer the rule ‘match the number of items’ to a totally new set of stimuli. Once again, the bees were able to convincingly match the sample and choice patterns, even when they contained two versus three yellow stars, or lemons (Fig. 4.5b). Then, an additional level of abstraction was introduced by making the elements of the sample and choice patterns different. Now, the bees encountered a sample pattern of three blue dots, for instance, which they had to match to a choice pattern composed of three yellow lemons, again in random configurations. Here, too, the bees performed remarkably well, using the number of items to identify the rewarded pattern (Fig. 4.5c). Next, a test was performed to investigate if the bees could transfer their ability to discriminate between two and three, to arrays of three and four items, the latter being a value they had not previously encountered. The bees could successfully carry out a three-to-three match, when the competing stimulus contained four elements. However, they were not able to consistently do a four-to-four match (Fig. 4.5d). Thus, there seemed to be a limit to their ability to extrapolate to higher numerosities: their performance in discriminating four versus five, five versus six and four versus six was also not above chance in all tests (Fig. 4.5e-g). Control experiments confirmed
102
Mario Pahl, Jürgen Tautz and Shaowu Zhang
a Choice n = 19 n = 17 pattern 1.00 Choice frequency
***
***
b
***
n = 25
***
***
n = 18
c
***
n = 16
***
***
n = 17
d
***
0.75 0.50 0.25
0.00 Sample pattern
Choice frequency
e Choice n = 15 pattern 1.00
n = 15
f
n = 12
n = 12
g
n = 14
n = 13
0.75 0.50 0.25
0.00 Sample pattern
Fig. 4.5 Results of the numerosity discrimination experiment. Shown are the transfer tests with various pattern configurations. The pattern below each pair of bars is the sample and that above each bar is the choice pattern; the y-axis gives the choice frequency. The data present the pooled first choices (from each foraging trip) of individual bees. a The configuration of dots on the sample and choice patterns is randomised. b The blue dot patterns in A are replaced with yellow stars, to see if bees can transfer their matching ability to different, unknown stimuli. c The sample and choice patterns are composed of two different elements. d-f Bees trained to discriminate between two and three are tested on patterns with d three and four elements, e four and five elements, f five and six elements, g four and six elements. n = number of bees per condition. Error bars show standard errors. ***denotes statistically significant difference at p < 0.001, **denotes p < 0.01, *denotes p < 0.05 and O denotes p > 0.05. Adapted with permission from Gross et al. (2009).
Honeybee cognition
103
that the bees were not using cues such as scent, the colour or the exact configuration of the visual elements, the combined area or edge length of the elements, or illusory contours formed by the elements (see Gross et al. 2009 for details). An estimation of relative numerical quantity could be extremely useful to foraging honeybees: combining information about the degree of stomach distension along with the number of flowers visited on a foraging trip could provide bees with an index of the profitability of a food source. Honeybees can recognise images of complex natural scenes (Dyer et al. 2008), and may be able to use them as potential landmarks. The number of landmarks encountered on a foraging trip, or found near the hive, could be useful in navigation (Chittka and Geiger 1995, Skorupski and Chittka 2006, Dacke and Srinivasan 2008). Number generalisation could also help in estimations of the number of blossoms on a branch and/or, the number of bees on a blossom, thereby allowing a forager to decide whether to forage at that location or whether to search for a new one. 4.5.2.4 Negotiating a complex maze The classical model animals in vertebrate cognition research, i.e. rats, mice and pigeons (Pick and Yanai 1983, Dale 1988) have often been tested for the ability to learn navigating complex mazes. Apart from the numerous studies using Y-maze setups, few studies exist that investigate the ability of invertebrates to negotiate complex mazes, where more than one or two correct decisions are required to reach the reward. In 1996, Zhang et al. conducted a study investigating the ability of honeybees to fly through a variety of complex mazes in search of a sugar reward in the presence or absence of a number of visual cues. Each maze consisted of a 4x5 matrix of identical cubic boxes with a hole in the centre of each side wall. The experimenters created different paths through the maze by leaving some holes open and blocking others, so that the bees had to fly through a sequence of 9-14 boxes, including 3-5 decision boxes, to reach the reward (Fig. 4.6a, c). To exclude the possible role of external landmarks, the position and orientation of the maze were changed regularly. The experimenters also swapped the position of all boxes before each test to exclude possible olfactory cues left by the bees in training. a) Negotiating a maze by following a colour cue. In the first series of experiments, the bees’ ability to fly through a maze following a colour cue was tested. The cue in this case was a 4x4-cm green mark placed under the correct exit hole in each decision box. After the initial training, in which a feeder was moved step by step along the correct path in the first three
104
Mario Pahl, Jürgen Tautz and Shaowu Zhang
a
b
Reward 18
19
20
13
14
15
16
9
10
11
12
5
6
7
8
1
2
3
4
80 Test 1
Frequency [%]
17
60 40
0
C1
C2
C3
Category
d
Reward 17
18
19
20
13
14
15
16
9
10
11
12
5
6
7
8
1
2
3
4
20
Entrance
0
Colour mark Correct path Incorrect path
Control
20
Entrance c
Test 2
Test 3
Frequency [%]
80
Test 4
Test 5
C4
Control
60 40
C1
C2
Category
C3
C4
Right turn Left turn Decision boxes on correct path
Fig. 4.6 Learning to negotiate complex mazes using visual cues. a shows the maze setup in series 1. The green colour marks indicate the correct path. b shows the results of series 1. In test 1, the bees are following the trained route. In test 2, the maze is reconfigured and the bees have to follow the green patches on a novel route. Control bees were tested in a maze without colour cues. c shows the maze setup in series 2. Colours indicate the direction of turn. d shows the results of series 2. Test 3 shows the results for the trained route. In tests 4 and 5, the maze was rearranged, and the bees are using the learnt turning rules in a novel route. Adapted with permission from Zhang et al. (1996).
boxes, it was placed in the last box. During this initial training, the bees had the chance to learn that the green patch indicated the correct exit hole. After each bee had visited the feeder in the last box at least once, it was placed in the feeder cage behind the last box.
Honeybee cognition
105
Immediately thereafter, each individual bee’s performance was tested. Performance was scored in 4 categories (C1-C4). C1 included flights in which the bee made no mistake and flew directly to the goal, in the flights in C2, the bee turned back and retraced her path one or more times but stayed on the correct path, C3 contained flights in which the bee made one or more mistakes but still arrived at the goal, and the bees in C4 did not reach the goal at all within 5 minutes. The bees that had learned to follow the colour mark in the first three boxes were immediately able to follow the same cue through the whole maze (Test 1 in Fig. 4.6b). When the maze was rearranged and the path changed, the bees were still able to follow the cue to the goal (Test 2 in Fig. 4.6b). This means that the bees could generalise the sign tracking rule they had learned in the first maze, and used it successfully to fly through a new maze. Their performance in Test 1 and 2 was significantly better than a control group of bees with the same training in an unmarked maze with an unfamiliar route to the goal. b) Negotiating a maze by learning a symbolic cue. Can bees learn to negotiate a maze by using symbolic cues as well? To address this question, Zhang et al. trained bees in the same way as above. In this new maze, a left or right turn in the decision boxes was indicated by a colour cue at the back of the box (Fig. 4.6c). Thus, the correct exit was not directly indicated by a colour mark, but the colours were symbols signaling the direction of turn. Blue indicated a right turn, and green indicated a left turn. The bees learned this task as well, as shown in Fig. 4.6d, Test 3. Again, the bees were able to transfer the learned symbolic rules to new maze configurations, and followed novel paths to the goal (Fig. 4.6d, Tests 4 and 5). The performance in all tests was as high as in the previous experiment, and significantly better than the control group. When Zhang et al. trained bees in a third experiment, in a maze where no cues were given, the bees did not learn the route on their own. They had to be trained stepwise along the entire path, but still performed significantly better than the control group. Thus, bees can be taught to negotiate a maze, if the training is done in a series of simple steps. Learning was fastest when the bees were given a set of rules which they can follow, and they learned symbolic cues just as rapidly as direct cues. The bees also demonstrated the ability to transfer the learned rules to novel but analogous contingencies in the spatial and the chromatic domain (Zhang et al. 1996).
106
Mario Pahl, Jürgen Tautz and Shaowu Zhang
4.5.3 Context-dependent learning Contextual cues are dependent on the environment and the situation. They can facilitate memory retrieval, when the context in which the memory was encoded is replicated. Thus, context cues help to carve up the world into distinct regions, and help animals to cope with possible confusions (Colborn et al. 1999, Fauria et al. 2002, Cheng 2005, Dale et al. 2005). Honeybees are able to flexibly change their preference for a visual pattern according to the context in which a task is carried out (Zhang et al. 2006). Two recent studies have demonstrated the simultaneous use of up to three contextual cues in the honeybee. They investigated whether the task at hand (foraging or homing), the location (different foraging areas), and the time of day (morning or afternoon), could be utilised as contextual cues by bees. 4.5.3.1 Task and time as contextual cues In this study, Zhang et al. investigated the effect of time of day (morning or afternoon), task (foraging and homing), as well as both parameters simultaneously, as contextual cues in modulating bees’ preference for a visual pattern. Bees were trained to visit an artificial feeder in a Y-maze (like Fig. 4.1a but without the sample pattern), where they had to make a foraging decision between visual stimulus A and B to get a reward. After feeding, the bees returned to their hive, which had two entrances. Each carried a visual stimulus, A and B, and only one entrance was open at a time. Here, the bees had to choose the correct visual stimulus to gain access to the hive and unload the sugar water they had foraged in the maze. We carried out three series of experiments to investigate these interactions. In the first series of experiments, the bees were trained to choose A at the feeder and at the hive in the morning. In the afternoon, following a midday break, they had to choose B at the feeder and at the hive. During the breaks (midday and night), the maze was closed, and the visual stimuli were removed from the hive, and both entrances were open. The bees could easily learn this task and preferred A in the morning and B in the afternoon, respectively. The results indicate that bees can reverse their preference following midday breaks, as well as overnight breaks, at the feeder and at the hive. Time acted as a contextual cue in this experiment. For the second series of experiments, a new group of honeybees was trained to choose stimulus A at the feeder, and B at the hive. The bees could learn this task as well, switching their preference in just a few minutes, depending on whether they were going out to forage or were returning to the hive. The task at hand was acting as context cue in this case.
Honeybee cognition Feeder side
107
Hive side
Choice frequency for stimulus A
1.00
A
A
n = 15
0.75
n = 15 n = 15
n = 13 0.50
0.25
0.00
n = 14
n = 14 n = 15
n = 15 Training 5
7
9
11
Training 13
Time of day
15
17
Training 7
9
11
Training 13
15
17
19
Time of day
Fig. 4.7 Task as contextual cue. Results of experimental series 3 at the feeder and the maze. The visual patterns were black/white horizontal vs. vertical gratings at the feeder and at the hive. The horizontal grating at the feeder and the vertical grating at the hive were the rewarded patterns in the morning, whereas the vertical grating at the feeder and the horizontal grating at the hive were rewarded in the afternoon. Choice frequencies for the horizontal grating are given. Results show that the trained bees significantly reverse their pattern preference at the feeder and at the hive entrance following midday breaks, as well as overnight breaks. There is a significantly different pattern preference at the feeder and at the hive entrance within each testing period. The modulation of the average choice frequency, with reference to the horizontal grating, could be approximated very well by a sinusoidal curve with a frequency of 0.52, i.e. a period of 12 h. The phase of the sinusoidal curve at the hive was shifted 180° with reference to the feeder. *** denotes p < 0.001. See text for further details. Adapted with permission from Zhang et al. (2006).
The third series of experiments was the most demanding one for the experimental bees. Results are shown in Fig. 4.7. A new group of foragers was trained to choose stimulus A in the maze and stimulus B at the hive in the morning. The same bees then had to choose stimulus B at the feeder and A at the hive in the afternoon to be rewarded. Stimulus A was a horizontal black and white grating, and B was a vertical grating. They solved this task as well, demonstrating that trained bees can reverse their pattern preference at the feeder and at the hive entrance depending on the time of day, and at the same time reverse their preference between foraging and homing, and choose opposite patterns at the feeder and at the hive. The training thus imposed a learnt pattern preference on the bees’ daily cir-
108
Mario Pahl, Jürgen Tautz and Shaowu Zhang
cadian rhythm (Fig. 4.7). This study demonstrates that forager bees possess a sophisticated memory and are able to remember tasks within a temporal context. Honeybees can thus ‘plan’ their activities in time and space, and use context to determine which action to perform and when (Zhang et al. 2006). 4.5.3.2 Time of day and location as contextual cues In one context cue study, Pahl and colleagues investigated how the colour, shape and location of patterns could be memorised within a time frame. Bees were trained to visit two Y-mazes, one of which presented yellow vertical (rewarded) versus horizontal (non-rewarded) gratings at one site in the morning, while another presented blue horizontal (rewarded) versus vertical (non-rewarded) gratings at another site in the afternoon. The bees learned the correct decisions in the two mazes easily. They also had no problems solving transfer tests in the learning mazes, in which the colour cues of the visual patterns were removed, but the location cue, the orientation of the visual patterns and the temporal cue still existed. Now, in order to remove the location cue, the two training mazes were removed and a single maze constructed in a neutral location between the previous mazes, where the bees had never received any training. Three kinds of transfer tests were performed, each in the morning and in the afternoon, in the novel maze (Fig. 4.8). In test 1, the location cue was removed, but other contextual cues, i.e. the colour and orientation of the visual patterns, as well as the temporal cue, still existed. The bees could immediately solve the task at the new location (Fig. 4.8a). In test 2, the location cue and the orientation cue of the visual patterns were removed, but the colour cue and temporal cue still existed. Here, the bees preferred the yellow grating in the morning and the blue grating in the afternoon (Fig. 4.8b). In test 3, the location cue and the colour cue of the visual patterns were removed, but the orientation cue and the temporal cue still existed. Now, the bees preferred the vertical black grating in the morning and the horizontal black grating in the afternoon. The results of this experiment revealed that honeybees can recall their memory of the rewarded visual patterns by using spatial and temporal information, separately and simultaneously. In the learning tests, the bees reached an average performance (morning and afternoon sessions taken together) of 83% correct choices. Setting this as a baseline, we can compare the difficulty of the transfer tests, and thus determine the relative importance of the different cues for the bees. In the transfer tests in the neutral location, the bees reached their best average performance of 91% in experiment 2, the colour discrimination task (Fig. 4.8b). The performance in this transfer test was even better than
Honeybee cognition
a
Choice frequency for stimulus
1.00
b
n = 18
n=9
morning
afternoon
109
c
n = 19
n = 11
n = 12
n = 13
0.75
0.50
0.25
0.00
morning afternoon
morning afternoon
Fig. 4.8 Time as contextual cue. Results of the transfer tests in the neutral location. a Test 1 with yellow and blue training patterns. The bees preferred the yellow vertical stimulus in the morning, and the blue horizontal stimulus in the afternoon. b Test 2 with yellow and blue patterns in the same orientation. The bees preferred the yellow stimulus in the morning, and the blue stimulus in the afternoon. c Test 3 with black patterns. The bees preferred the vertical grating in the morning, and the horizontal grating in the afternoon. n denotes number of individual bees in each test; bars are means ± S.E.M.. Adapted with permission from Pahl et al. (2007).
that of the learning tests, regardless of the missing location and pattern orientation cues. Thus, colour seems to be the most important visual cue for honeybee choice behaviour. These findings are consistent with previous reports that honeybees learn a new colour after about five visits, whereas they require 20–30 visits to learn a pattern (Zhang and Srinivasan 1994). Using the training patterns at maze C in transfer test 1, the bees performed about the same as in the training mazes. Here, the only missing cue was the maze location. This cue seems to have had almost no effect on the bees’ choice performance in small scale navigation, when other contextual cues were available. Pattern colour, shape and the time of day were enough to allow a baseline level of performance at a new location. When the colour cue and the location cue were both taken out in test 3, the bees’ average performance was reduced to 72% (Fig. 4.8c). These results indicate that the shape cue is more difficult for the bees to use than the colour cue. Pattern orientation or, in nature, the shape of different flowers, is thus more important than location for the bees’ choice behaviour once they
110
Mario Pahl, Jürgen Tautz and Shaowu Zhang
have reached their feeding site. The bees clearly used the former to distinguish between the patterns in all experiments except the colour discrimination task, where pattern shape was unavailable. Applying these findings to the natural situation, the colour and shape of flowers are the most important visual cues used by bees to choose between different flower species. When visiting different feeding sites, or different patches of flowers, they can recall their memory of the most rewarding species in conjunction with the time of day, and thus find the most profitable food source even at a new location. Recently, Prabhu and Cheng showed that honeybees trained on colours for only one day can also use temporal information in decision making. This indicates that bees might have a natural tendency towards inferring a circadian pattern on unclear reward situations (Prabhu and Cheng 2008a). They also found that, when similar training is conducted with odours, bees prefer only the odour that was most recently associated with a reward (Prabhu and Cheng 2008b). Thus, bees have two ways to assess the reward probability when encountering a novel situation, which may produce conflicting interests. However, in a forager bee’s natural foraging environment, colour and scent are seldom experienced separately from each other. More experiments are required to examine how the bees’ circadian preference pattern is modulated when color and scent are coupled. The bees’ ability to integrate elements of circadian time, place and visual stimuli is akin to episodic-like memory (Clayton and Dickinson 1998) and we have therefore named this kind of memory ‘circadian timed episodic-like memory’ (Pahl et al. 2007). 4.5.3.3 Associative learning and recall In humans, a smell or a sound can easily trigger a vivid memory of an associated event in the past, even when it involves a different sensory modality and the episode occurred a long time ago. When the smell of sunscreen reminds us of a day at the beach during last summer, our brain displays a cross-modal associative recall; it links a scent to a visual scene and a location. In 1998, Srinivasan and co-workers could show that honeybees link sights to smells, and thus show that insect brains are capable of crossmodal associative recall as well (Srinivasan et al. 1998, Zhang et al. 1999). When foraging, cross-modal associative recall could facilitate the search for a food source in honeybees. For example, the scent of lavender could initiate a search for blue flowers (Zhang 2006), and canola scent could lead to a preference for yellow blossoms. So far, the data show that honeybees could potentially use cross-modal recall, but do bees actually use it in everyday foraging in a natural envi-
Honeybee cognition
111
ronment? To investigate this question, Reinhard and colleagues designed an experiment to test whether floral scents can induce recall of navigational and visual memories in a natural foraging terrain (Reinhard et al. 2004a,b). They trained individually marked bees to forage at several scented sugar feeders at different outdoor locations, each 50 m from the hive. In the first experiment, feeder one carried rose scent, and feeder two carried lemon scent. After two days of training, the bees were tested by replacing the feeders with empty, unscented jars. Then, for eight minutes each, rose and lemon scents were alternately blown into the hive by a small fan. During each scent blowing interval, the experimenters noted the number of marked bees arriving at each test feeder. The foragers leaving the hive during the rose scent interval showed a significant preference for the feeder that was previously rose-scented and vice versa. Repeating the experiment with different scent combinations, such as rose and almond or lemon and almond, led to similar results. The injected scent triggered navigational memories previously acquired during the training. Foraging for nectar and pollen is crucial for the survival of the hive. Foraging bees cover a huge area of potential foraging sites, and when a single forager finds a particularly rewarding site, it needs to convey the information to its nestmates. In his classic studies, von Frisch (1967) reported the famous honeybee dance language, in which foragers communicate distance and direction of a food source to each other, in order to recruit more foragers to a rewarding site. A recent study has even hinted at the possibility that two different bee species, Apis cerana cerana and Apis mellifera ligustica, can understand each other’s dances (Su et al. 2008). This study demonstrates an additional mechanism that could be used by bees to recruit large numbers of bees to a good food source. The scent of the returning bee, as well as the taste of the nectar brought to the hive, can trigger navigational, visual or olfactory memories in other experienced bees, and facilitate recruitment to and utilisation of the food source. 4.5.4 Other cognitive mechanisms used in navigation To properly service the needs of their colony, forager bees need to accurately locate profitable food sources, and efficiently transport nectar and pollen back to the hive. The mechanisms by which bees achieve this are numerous, and we are only beginning to obtain an in-depth understanding of these processes. It has long been known that the polarisation pattern on the sky provides bees compass information, even when the sun is hidden by clouds (von Frisch 1967, also see Wehner 2001 for a recent review). In both ants and
112
Mario Pahl, Jürgen Tautz and Shaowu Zhang
honeybees, this information can be combined with odometric information about angular and linear movements – the path integration mechanism – which provides the animal with information about its current position relative to the point of departure (Wehner 2003). Honeybees also use landmarks in their visual environment to find a location where they have previously foraged (Gould 1987, Collett and Kelber 1988). The memory of a landmark, which indicates the location of a food source, is stored in the context of the journey to that food source, i.e. along with its expected distance from the hive (Cartwright and Collett 1983), and also with other landmarks that immediately precede the flight target (Chittka et al. 1995a). The use of multiple landmarks to break a journey into several segments also has the effect of increasing the accuracy of navigation across long distances (Srinivasan et al. 1997). However, as honeybees can forage in both novel and familiar terrain, it should come as no surprise that they can use their path integration and landmark-based navigation systems flexibly: Chittka and colleagues have shown that when foraging by familiar landmarks, honeybees are able to suppress their path integration system, even when those landmarks are displaced. When forced to forage in a novel location without learnt landmarks, they use path integration to navigate back to the hive (Chittka et al. 1995b). Honeybees can store at least two different sets of visual stimuli as landmarks that have the potential to trigger memories of two different foraging routes (Zhang et al. 1999). These associative groupings of landmarks can also be used flexibly, as encountering any one stimulus out of the group can facilitate the recall of the other stimuli. The advantage of such a system would be the following: if a forager, who is attempting to retrace a learnt route indicated by a set of landmarks, becomes somehow disoriented, she could still potentially re-orient herself with respect to the route as long as she encounters any one of those landmarks while searching, regardless of its place in the learnt sequence of landmarks. The distance from the hive to a food source can also be precisely estimated by honeybees, using the phenomenon of optic flow, which is the movement of the image of an animal’s surroundings, as detected by its eyes, as the animal changes position. Two experiments have demonstrated that it is such image motion that tells a bee how far it has travelled, in both naturalistic (Esch and Burns 1995) and controlled (Srinivasan et al. 2000) situations. In the first study, it was shown that honeybees that flew from a hive to a feeder, both placed on the roofs of tall buildings, underestimated their distance travelled, as indicated by their waggle dances. This was because flying at a great height reduces the amount of optic flow produced by the image of the ground. In the second experiment, bees that were made to fly into a narrow tunnel with black and white vertical stripes on its walls
Honeybee cognition
113
(to produce maximum image motion), signaled large distances in their dances, even though they had only flown about 12 metres. Here, the reverse happened: the narrow tunnel amplified the optic flow registered by the bees’ eyes, leading them to overestimate the distance travelled. Finally, there has been some debate in the literature concerning the use of map-based strategies in navigation by honeybees, as opposed to the simpler, route learning mechanisms (e.g. with the help of landmarks) discussed above. Using harmonic radar, Menzel et al. found that displaced bees were able to set a new course at this arbitrary point, and choose to fly to at least two locations (an artificial feeder or the hive) from there. This result is suggestive of a map-like organisation of spatial memory in navigating honeybees (Menzel et al. 2005). Recently, however, Wray et al. (2008) demonstrated that potential foragers inside the hive will not reject dances that advertise food resources in improbable locations, such as the middle of a lake – argueing against the possibility that bees possess a spatial map of the hive’s surroundings. In another study, bees fitted with RFID transmitters, and released at distant locations up to 11 km away, where they would probably never have foraged, were recorded as having returned to the hive, sometimes after as long as 48 hours (Pahl et al. in prep.). However, the rate and speed at which bees returned to the hive was strongly affected by the direction in which the bees were released. This indicates that bees make use of either prominent landmarks or landscape features to successfully navigate in some locations around the hive, but are greatly challenged when displaced to new locations.
4.6 Conclusions Successful foraging is crucial for the survival of a honeybee colony, and foragers act as its sensory units. Honeybees constantly integrate environmental information, in order to maximise individual foraging efficiency, and also adjust their behaviour according to the colony’s needs (Seeley 1995). 100 million years of co-evolution with angiosperm plants (Hu et al. 2008) have resulted in sensory systems that are well-adapted to this task. The studies reviewed here show a rich repertoire of adaptive behaviours, some of which were earlier believed to be restricted to bigger-brained animals. Many of the results cannot be explained by simple associative or operant learning, and thus demonstrate that complex learning is possible even in small brains. Honeybees face complex choices inside and outside the hive, and the studies discussed in this chapter illuminate some of the mechanisms involved in their decision making.
114
Mario Pahl, Jürgen Tautz and Shaowu Zhang
We showed that honeybees are capable of forming and using categories, in which objects can be grouped together. A honeybee is thus able to use a similar response to all stimuli that match one category, and it does not have to learn an appropriate response for each new stimulus. In experimental setups, honeybees are able to categorise the shared features of artificial patterns, as well as those of natural objects. Rules help honeybees to cope with often recurring situations, e.g. repeatedly visiting the same plant for foraging. They can learn to use visual and olfactory stimuli as an indicator of what to do next; in a complex maze setup, they learn abstract rules in order to successfully navigate the maze. In a DMTS setup, honeybees quickly learn the delayed-matching rule, which requires not only long-term memory to remember the rule itself, but also short-term memory to recall the sample pattern after the delay. Context learning is another way to flexibly cope with motivational and environmental changes. During the outbound foraging flight to a food source, the foraging bee has to recall a different route memory than on the inbound homing flight. The different tasks at hand, ‘foraging’ and ‘homing’, set the memories in different contexts, thus avoiding confusion. When plant species differ in their peak nectar secretion times, the time of day can separate the competing plants into different contexts. Thus, honeybees learn to visit one profitable plant in the morning, and a different one in the afternoon. Such a circadian-timed episodic-like memory allows honeybees to remember tasks within a temporal context, and to ‘plan’ their foraging trips most efficiently. Cross-modal associative recall can motivate experienced forager bees inside the hive to fly out and search for a particular flower, whose scent is borne by the bee advertising that food source through a waggle dance. This highly adaptive mechanism leads to faster recruitment to profitable food sources, and thus enhances the hive’s competitiveness. Honeybees navigate successfully over several kilometres when collecting different resources, and when swarming to a new nest site. Through the dance language, the foraging bees communicate the direction and distance of those locations to their hive mates. Honeybees accomplish the impressive task of finding such food sources with the help of their polarisation compass, a path integration system and local and global landmark memories. There is currently mixed evidence in favour of a map-like spatial memory in honeybees. Further experiments are needed to investigate this controversial question. Throughout this chapter, we have presented research that demonstrates that honeybees are not the simple reflexive automata that they were once assumed to be. The cognitive capabilities of an animal seem to be largely
Honeybee cognition
115
governed by what it needs to pursue its lifestyle, and not by the presence or absence of a backbone.
Acknowledgements We are grateful for Aung Si’s valuable help with the manuscript, and for Peter Kappeler’s constructive comments on an earlier version. MP is supported by a grant of the German Excellence Initiative to the Graduate School of Life Sciences, University of Würzburg.
References Bitterman ME, Menzel R, Fietz A, Schäfer S (1983) Classical conditioning of proboscis extension in honeybees (Apis mellifera). J Comp Psychol 97:107119 Blough DS (1959) Delayed matching in the pigeon. J Exp Anal Behav 2:151-160 Brandt R, Rohlfing T, Rybak J, Krofczik S, Maye A, Westerhoff M, Hege H-C, Menzel R (2005) Three-dimensional average-shape atlas of the honeybee brain and its applications. J Comp Neurol 492:1-19 Brannon EM, Terrace HS (2000) Representation of the numerosities 1-9 by rhesus macaques (Macaca mulatta). J Exp Psychol Anim Behav Process 26:31-49 Cartwright BA, Collett TS (1983) Landmark learning in bees – experiments and models. J Comp Physiol A 151:521-543 Cheng K (2005) Context cues eliminate retroactive interference effects in honeybees (Apis mellifera). J Exp Biol 208:1019-1024 Chittka L, Geiger K (1995) Can honey bees count landmarks? Anim Behav 49:159-164 Chittka L, Tautz J (2003) The spectral input to honeybee visual odometry. J Exp Biol 206:2393-2397 Chittka L, Shmida A, Troje N, Menzel R (1994) Ultraviolet as a component of flower reflections, and the colour perception of hymenoptera. Vision Res 34:1489-1508 Chittka L, Geiger K, Kunze J (1995a) The influences of landmarks on distance estimation of honey bees. Anim Behav 50:23-31 Chittka L, Kunze J, Shipman C, Buchmann SL (1995b) The significance of landmarks for path integration in homing honeybee foragers. Naturwissenschaften 82:341-343 Chittka L, Gumbert A, Kunze J (1997) Foraging dynamics of bumble bees: correlates of movements within and between plant species. Behav Ecol 8:239-249 Chittka L, Thomson JD, Waser NM (1999) Flower constancy, insect psychology, and plant evolution. Naturwissenschaften 86:361-377
116
Mario Pahl, Jürgen Tautz and Shaowu Zhang
Clayton NS, Dickinson A (1998) Episodic-like memory during cache recovery by scrub jays. Nature 395:272-274 Colborn M, Ahmad-Annuar A, Fauria K, Collett TS (1999) Contextual modulation of visuomotor associations in bumble-bees (Bombus terrestris). Proc R Soc Lond B 266:2413-2418 Collett TS, Baron J (1994) Biological compasses and the coordinate frame of landmark memories in honeybees. Nature 368:137-140 Collett TS, Cartwright BA (1983) Eidetic images in insects: their role in navigation. Trends Neurosci 6:101-105 Collett TS, Collett M (2002) Memory use in insect visual navigation. Nat Rev Neurosci 3:542-552 Collett TS, Kelber A (1988) The retrieval of visuo-spatial memories by honeybees. J Comp Physiol A 163:145-150 Dacke M, Srinivasan MV (2008) Evidence for counting in insects. Anim Cogn 11:683-689 Dale RH (1988) Spacial memory in pigeons on a four-arm radial maze. Can J Psychol 42:78-83 Dale K, Harland DP, Manning-Jones A, Collett TS (2005) Weak and strong priming cues in bumblebee contextual learning. J Exp Psychol 208:65-74 D’Amato MR, Salmon DP, Colombo M (1985) Extent and limits of the matching concept in monkeys (Cebus apella). J Exp Psychol Anim Behav Process 11:35-51 Davis H (1984) Discrimination of the number three by a raccoon (Procyon lotor). Anim Learn Behav 12:409-413 Deisig N, Lachnit H, Giurfa M, Hellstern F (2001) Configural olfactory learning in honeybees: negative and positive patterning discrimination. Learn Mem 8:70-78 Dyer AG, Neumeyer C, Chittka L (2005) Honeybee (Apis mellifera) vision can discriminate between and recognise images of human faces. J Exp Biol 208:4709-4714 Dyer AG, Rosa MGP, Reser DH (2008) Honeybees can recognise images of complex natural scenes for use as potential landmarks. J Exp Biol 211:1180-1186 Esch HE, Burns JE (1995) Honeybees use optic flow to measure the distance to a food source. Naturwissenschaften 82:38-40 Fauria K, Dale K, Colborn M, Collett TS (2002) Learning speed and contextual isolation in bumblebees. J Exp Biol 205:1009-1018 Fuchs S, Kralj J, Tautz J (2006) Radio frequency identification tags (RFID) for monitoring of worker bees infested with Varroa destructor or with Nosema apis at the hive entrance. Apidologie 37:643-645 Giurfa M (2003) Cognitive neuroethology: dissecting non-elemental learning in a honeybee brain. Curr Opin Neurobiol 13:726-735 Giurfa M (2007) Behavioral and neural analysis of associative learning in the honeybee: a taste from the magic well. J Comp Physiol A 193:801-824 Giurfa M, Malun D (2004) Associative mechanosensory conditioning of the proboscis extension reflex in honeybees. Learn Mem 11:294-302
Honeybee cognition
117
Giurfa M, Eichmann B, Menzel R (1996) Symmetry perception in an insect. Nature 382:458-461 Giurfa M, Zhang SW, Jenett A, Menzel R, Srinivasan MV (2001) The concepts of ‘sameness’ and ‘difference’ in an insect. Nature 410:930-933 Gould JL (1987) Honey bees store learned flower-landing behaviour according to the time of day. Anim Behav 35:1579-1581 Gross HJ, Pahl M, Si A, Zhu H, Tautz J, Zhang SW (2009) Number-based visual generalisation in the honeybee. PLoS ONE 4:e4263, doi:10.1371/journal.pone.0004263 Hellstern F, Wüstenberg D, Hammer M (1995) Contextual learning in honeybees under laboratory conditions. In: Elsner N, Menzel R (eds) Learning and Memory. Proceedings of the 23rd Göttingen Neurobiology Conference. Vol. I. Thieme Verlag, Stuttgart, abstract 30 Herman LM, Gordon JA (1974) Auditory delayed matching in the bottlenose dolphin. J Exp Anal Behav 21:19-26 Horridge GA (1996) The honeybee (Apis mellifera) detects bilateral symmetry and discriminates its axis. J Insect Physiol 42:755-764 Horridge GA, Zhang SW (1995) Pattern vision in honeybees (Apis mellifera): flower-like patterns with no predominant orientation. J Insect Physiol 41:681688 Horridge GA, Zhang SW, Lehrer M (1992) Bees can combine range and visual angle to estimate absolute size. Philos Trans R Soc Lond B 337:49-57 Hu S, Dilcher DL, Jarzen DM, Taylor DW (2008) Early steps of angiospermpollinator coevolution. Proc Natl Acad Sci USA 105:240-245 Hunt S, Low J, Burns KC (2008) Adaptive numerical competency in a foodhoarding songbird. Proc R Soc Lond B 275:2373-2379 Johnson DL, Wenner AM (1966) A relationship between conditioning and communication in honey bees. Anim Behav 14:261-265 Judd SPD, Collett TS (1998) Multiple stored views and landmark guidance in ants. Nature 392:710-714 Keller FS, Schoenfeld WN (1950) Principles of Psychology. Appleton-CenturyCrofts, New York Kilian A, Yaman S, von Fersen L, Güntürkün O (2003) A bottlenose dolphin discriminates visual stimuli differing in numerosity. Learni Behav 31:133-142 Konorski J (1959) A new method of physiological investigation of recent memory in animals. Bull Acad Pol Sci Biol 7:115-117 Lehrer M, Srinivasan MV, Zhang SW (1990) Visual edge detection in the honeybee and its chromatic properties. Proc R Soc Lond B 238:321-330 Letzkus P, Ribi WA, Wood JT, Zhu H, Zhang SW, Srinivasan MV (2006) Lateralization of olfaction in the honeybee Apis mellifera. Curr Biol 16:1471-1476 Maleszka R, Helliwell P (2001) Effect of juvenile hormone on short-term olfactory memory in young honeybees (Apis mellifera). Horm Behav 40:403-408 Menzel R, Blakers M (1976) Colour receptors in the bee eye – morphology and spectral sensitivity. J Comp Physiol A 108:11-13 Menzel R, Mueller U (1996) Learning and memory in honeybees: from behavior to neural substrates. Annu Rev Neurosci 19:379-404
118
Mario Pahl, Jürgen Tautz and Shaowu Zhang
Menzel R, Greggers U, Smith A, Berger S, Brandt R, Brunke S, Bundrock G, Hülse S, Plümpe T, Schaupp F, Schüttler E, Stach S, Stindt J, Stollhoff N, Watzl S (2005) Honey bees navigate according to a map-like spatial memory. Proc Natl Acad Sci USA 102:3040-3045 Pahl M, Zhu H, Pix W, Tautz J, Zhang SW (2007) Circadian timed episodic-like memory – a bee knows what to do when, and also where. J Exp Biol 210:3559-3567 Pick CG, Yanai J (1983) Eight arm maze for mice. Int J Neurosci 21:63-66 Prabhu C, Cheng K (2008a) One day is all it takes: circadian modulation of the retrieval of colour memories in honeybees. Behav Ecol Sociobiol 63:11-22 Prabhu C, Cheng K (2008b) Recency preference of odour memory retrieval in honeybees. Behav Ecol Sociobiol 63:23-32 Prete FR (2004) Complex Worlds from Simpler Nervous Systems. MIT Press, Cambridge/MA Ratnieks FLW, Wenseleers T (2008) Altruism in insect societies and beyond: voluntary or enforced? Trends Ecol Evol 23:45-52 Reinhard J, Srinivasan MV, Guez D, Zhang SW (2004a) Floral scents induce recall of navigational and visual memories in honeybees. J Exp Biol 207:43714381 Reinhard J, Srinivasan MV, Zhang SW (2004b) Olfaction: scent-triggered navigation in honeybees. Nature 427:411 Reynolds AM, Smith AD, Reynolds DR, Carreck NL, Osborne JL (2007) Honeybees perform optimal scale-free searching flights when attempting to locate a food source. J Exp Biol 210:3763-3770 Roberts WA (1972) Short-term memory in pigeon: effects of repetition and spacing. J Exp Psychol 94:74-83 Ronacher B (1992) Pattern-recognition in honeybees: multidimensional-scaling reveals a city-block metric. Vision Res 32:1837-1843 Rossel S, Wehner R (1986) Polarization vision in bees. Nature 323:128-131 Seeley TD (1995) The Wisdom of the Hive. The Social Physiology of Honey Bee Colonies. Harvard University Press, Cambridge/MA Shettleworth SJ (1998) Cognition, Evolution, and Behavior. Oxford University Press, New York Skorupski P, Chittka L (2006) Animal cognition: an insect’s sense of time? Curr Biol 16:R851-R853 Srinivasan MV, Lehrer M (1988) Spatial acuity of honeybee vision and its spectral properties. J Comp Physiol A 162:159-172 Srinivasan MV, Zhang SW, Bidwell NJ (1997) Visually mediated odometry in honeybees. J Exp Biol 200:2513-2522 Srinivasan MV, Zhang SW, Zhu H (1998) Honeybees link sights to smells. Nature 396:637-638 Srinivasan MV, Poteser M, Kral K (1999) Motion detection in insect orientation and navigation. Vision Res 39:2749-2766 Srinivasan MV, Zhang SW, Altwein M, Tautz J (2000) Honeybee navigation: nature and calibration of the ‘odometer’. Science 287:851-853
Honeybee cognition
119
Streit S, Bock F, Pirk CWW, Tautz J (2003) Automatic life-long monitoring of individual insect behaviour now possible. Zoology 106:169-171 Su S, Cai F, Si A, Zhang SW, Tautz J, Chen S (2008) East learns from West: Asiatic honeybees can understand dance language of European honeybees. PLoS ONE 3:e2365. doi:10.1371/journal.pone.0002365 Tautz J (2008) The Buzz about Bees: Biology of a Superorganism. Springer, Berlin Troje NF, Huber L, Loidolt M, Aust U, Fieder M (1999) Categorical learning in pigeons: the role of texture and shape in complex static stimuli. Vision Res 39:353-366 Uller C, Jaeger R, Guidry G, Martin C (2003) Salamanders (Plethodon cinereus) go for more: rudiments of number in an amphibian. Anim Cogn 6:105-112 van Hateren JH, Srinivasan MV, Wait PB (1990) Pattern recognition in bees: orientation discrimination. J Comp Physiol A 167:649-654 Vareschi E (1971) Duftunterscheidung bei der Honigbiene – Einzelzell-Ableitungen und Verhaltensreaktionen. Z Vergl Physiol 75:143-173 von Frisch K (1967) The Dance Language and Orientation of Bees. Harvard University Press, Cambridge/MA Wasserman EA (1993) Comparative cognition: beginning the second century of the study of animal intelligence. Psychol Bull 113:211-228 Wehner R (2001) Polarization vision – a uniform sensory capacity? J Exp Biol 204:2589-2596 Wehner R (2003) Desert ant navigation: how miniature brains solve complex tasks. J Comp Physiol A 189:579-588 Wehner R, Bleuler S, Nievergelt C, Shah D (1990) Bees navigate by using vectors and routes rather than maps. Naturwissenschaften 77:479-482 Wehner R, Michel B, Antonsen P (1996) Visual navigation in insects: coupling of egocentric and geocentric information. J Exp Biol 199:129-140 Williams RW, Herrup K (1988) The control of neuron number. Annu Rev Neurosci 11:423-453 Witthöft W (1967) Absolute Anzahl und Verteilung der Zellen im Hirn der Honigbiene. Zoomorphology 61:160-184 Wray MK, Klein BA, Mattila HR, Seeley TD (2008) Honeybees do not reject dances for ‘implausible’ locations: reconsidering the evidence for cognitive maps in insects. Anim Behav 76:261-269 Zhang SW (2006) Learning of abstract concepts and rules by the honeybee. Int J Comp Psychol 19:318-341 Zhang SW, Srinivasan MV (1994) Prior experience enhances pattern discrimination in insect vision. Nature 368:330-332 Zhang SW, Srinivasan MV (2004a) Exploration of cognitive capacity in honeybees: higher functions emerge from a small brain. In: Prete FR (ed) Complex Worlds from Simpler Nervous Systems. MIT Press, Cambridge/MA, pp 41-74 Zhang SW, Srinivasan MV (2004b) Visual Perception and Cognition in Honeybees. In: Chalupa LM, Werner JS (eds) The Visual Neurosciences. MIT Press, Cambridge/MA, pp 1501-1513
120
Mario Pahl, Jürgen Tautz and Shaowu Zhang
Zhang SW, Bartsch K, Srinivasan MV (1996) Maze learning by honeybees. Neurobiol Learn Mem 66:267-282 Zhang SW, Lehrer M, Srinivasan MV (1999) Honeybee memory: navigation by associative grouping and recall of visual stimuli. Neurobiol Learn Mem 72:180-201 Zhang SW, Srinivasan MV, Zhu H, Wong J (2004) Grouping of visual objects by honeybees. J Exp Biol 207:3289-3298 Zhang SW, Bock F, Si A, Tautz J, Srinivasan MV (2005) Visual working memory in decision making by honey bees. Proc Natl Acad Sci USA 102:5250-5255 Zhang SW, Schwarz S, Pahl M, Zhu H, Tautz J (2006) Honeybee memory: a honeybee knows what to do and when. J Exp Biol 209:4420-4428
Chapter 5
Individual performance in complex social systems: the greylag goose example KURT KOTRSCHAL, ISABELLA B.R. SCHEIBER AND KATHARINA HIRSCHENHAUSER
ABSTRACT Convergent social structures can be found in taxa that split a long time ago, for example more than 230 Mio years ago as in the case of mammals and birds. Such convergence is explained by common selection regimes, as all social systems are shaped by sex-specific tactics and strategies to optimise their reproductive success. In addition, the major social mechanisms, brain and physiology, are highly conserved throughout the vertebrates. Manoeuvring social contexts tends to be energetically costly and, hence, favours efficient decision-making. Therefore, at least in vertebrates, complex social systems generally select for social cognition. As an example for social convergence between mammals and birds, we introduce the surprisingly complex social system of greylag geese, featuring components such as a female-bonded clan structure, long parent-offspring relationships, as well as elaborate and highly functional patterns of mutual social support. Our results show that partners in reproductively successful goose pairs are in hormonal synchrony and provide social support to each other. We suggest that social support may be a major structuring principle of other social systems with long-term individualized and valuable partnerships as well. In general, individual performance in social systems is determined by the interplay between proximate mechanisms and ultimate functions.
122
Kurt Kotrschal, Isabella B.R. Scheiber and Katharina Hirschenhauser
5.1 Introduction: being social is the default setting in mammals and birds Vertebrate bodies, physiologies and minds are shaped by individual relationships with others. Being social may be useful, rewarding, disastrous, pleasant or intimidating, but it is certainly unavoidable in most species. Therefore, individuals and species cannot be understood via their adaptations to the physical and ecological environments alone, but their social dimension needs to be considered as well. In contrast to simple groups, such as aggregations that coordinate in space and time (Krause and Ruxton 2002), many social systems are relatively complex, i.e. individuals live with a partner and/or a group permanently or seasonally, and they engage in specific, valuable and durable relationships. In fact, the essence of all social life is to optimise one’s own fitness whilst keeping one’s own social web intact (Fig. 5.1). This insight points at the importance of the individual styles of stress coping and conflict behaviour (Aureli and de Waal 2000, Aureli et al. 2002, Koolhaas et al. 2007) for sociality. At least in homoeothermic vertebrates, sociality is probably the default option. This assumption is supported by a number of structures and mechanisms, which feature prominently in vertebrate brain and physiology (Fig. 5.2), including the ‘social behaviour network’ (Goodson 2005, McGregor 2005), bonding mechanisms (Curley and Keverne 2005, Goodson et al. 2009), basic emotional systems (Panksepp 1998, 2005) and the two stress
Cognition and emotionality
Individual social performance and fitness Social context / embedding
Coping with social stress
Fig. 5.1 Schematic representation of the major interacting faculties relevant for individual decision making and fitness in complex social systems: Individual stress coping is determined by individual behavioural phenotype (including emotionality), social embedding and social experiences past. This simple model is also applicable for ontogeny, particularly epigenetics.
Individual performance in complex social systems
123
Brain
Genetic background
NCl
Maternal effects Parenting style
SAA
HPA
PC
Stress systems
Adrenals
Cardiovascular system
Fig. 5.2 Diagram of some of the components of a ‘common social toolbox’ contributing to explain some of the parallels in social organisation between birds, such as geese, and mammals. Brain and major peripheral elements are shown that are involved in homoeothermic vertebrate social behaviour, mediating social bonding/attachment, social support, as well as basic emotional systems. The ‘socio-sexual diencephalic and tegmental network’ (Goodson 2005; horizontal hatching) governs the ‘instinctive’ social behaviour, which is controlled by the prefrontal cortex (PC) in mammals and by the posterior forebrain caudolateral nidopallium (NCl) in birds. These brain systems communicate tightly with the two stress axes, the hypothalamo-pituitary axis (HPA; pituitary in black, adrenal cortex vertically hatched) and the sympathico-adrenergic axis (SAA, adrenal core dotted). The setpoints regulating the interactions of these systems are shaped during ontogeny by genetic background, maternal effects, parenting styles and ongoing social interactions, thereby, social styles may be epigenetically passed on over generations.
coping systems, which were conservatively maintained over evolutionary times, the fast sympathetico-adrenomedullary (SAS) and slow hypothalamic-pituitary-adrenocortical (HPA) stress axes (Sapolsky 1992, von Holst 1998, Summers 2002). In fact, the greatest modulation of these (anti-)stress systems generally occurs in social contexts (DeVries et al. 2003, McEwen and Wingfield 2003, Wascher et al. 2008a,b). Since the groundbreaking work of Hamilton (1964) and Wilson (1975), biologists have begun to incorporate dynamic social components into their concepts. Essential input was provided by experimental psychologists and
124
Kurt Kotrschal, Isabella B.R. Scheiber and Katharina Hirschenhauser
primatologists (de Waal 1982, Byrne and Whiten 1988, Whiten and Byrne 1997). Social behaviour is difficult to deal with scientifically, not the least because individual behaviour in a social net depends on what others do, or even on their mere presence (McGregor 2005). Moreover, social behaviour, social embedding and social experience feed back onto the brain structures and physiological mechanisms involved, contributing to individual phenotypic plasticity (Fig. 5.2). Emotional arousal caused by virtually any social encounter comes with surges in systemic glucocorticoids, which affect individual energetics, learning and memory formation via dose-dependent effects on the nervous system (McEwen and Sapolsky 1995), and will also modulate an individual’s disposition to respond to future challenges (Sapolsky et al. 2000, Kruk et al. 2004). In many social systems, the experience of previous social interactions, as well as the presence of social allies, will affect the balance between key hormones, such as oxytocin, glucocorticoids and androgens, as well as neurotransmitters. This, in turn, will affect individual motivation and the likelihood of engaging and succeeding in prospective social interactions (e.g., McGregor et al. 1997, Oliveira et al. 1998, Peake et al. 2001, 2002). Via epigenetic inheritance such socially induced changes may even extend over generations (Roemer et al. 1997, Champagne and Curley 2005, Daisley et al. 2005, Bertin et al. 2008, 2009).
5.2 Social efficiency and social competence Ultimately, individual success in any biological system is defined by the number of reproductively successful offspring produced. In addition to being adapted for coping optimally with the physical and ecological environment, success in a social system will depend upon ‘social efficiency’ and ‘social competence’, which may be considered as two sides of the same coin. Socially competent individuals will reach their immediate (social) goals with a minimal agonistic and other behavioural effort and with minimal damage, if any, to its long-term valuable relationships. Thereby, socially competent individuals will also be efficient, i.e. they will reach their immediate (social) goals with a minimum of energetic investment. Hence, individual performance and the extent of embedding in the social web should be fitness-relevant, because energy saved in interactions should be available for other domains, such as reproduction. Social competence and efficiency will probably become the more important, the more complex a social system is. Social performance may depend upon sex, behavioural phenotype, early socialisation and individual experience and life
Individual performance in complex social systems
125
history state, on partner behaviour, audience, and season, just to name a few of the most important factors.
5.3 Cognition-based complex social systems There is no consent on how to define a complex social system. Social systems may either be considered complex if they result in complex patterns and outcomes, such as in Hymenoptera, or if they feature intreractions, which rely at least partly on complex interactions and cognition, such as mutual, long-term valuable dyadic relationships (among mates, parents and offspring, unrelated social allies, friends, etc.), adaptive and varied patterns of conflict resolution (Aureli and de Waal 2000, Aureli et al. 2002), the ability to track higher-level relationships (Judge and Mullen 2005), social support (Sapolsky 1993, von Holst 1998, Abbott et al. 2003, Goymann and Wingfield 2004), distinctive differences in individual behavioural phenotypes and associated social roles (Sih et al. 2004), individual contextdependent flexibility, the forming of traditions, or ‘cultural divergence’ (van Schaik this volume) via social learning, etc. Such an understanding of social complexity includes flexibility in behavioural tactics and hence, is based on cognitive mechanisms, rather than on strategies, i.e., inherited decision rules (Whiten and Byrne 1997, Taborsky and Brockman this volume). As a result, vertebrate societies will show a different kind of complexity than insect societies, with the prevalence of strategies in the latter (see Heinze this volume) and tactics in the former. At least in the homoeothermic vertebrates, social complexity seems to select for large brains and complex cognition (Dunbar 1995, Dunbar and Bever 1998; but see Barrett and Henzi 2005, Barrett et al. 2007, Beauchamp and Fernández-Juricic 2004, Healy and Rowe 2007).
5.4 Complex social systems in birds: how large a brain does one need? For a long time, birds have been held incapable of complex cognition because of their mainly ‘striatal’ forebrain. Today, it is recognised that birds have a proportion of pallial forebrain equivalent to the mammalian cortex (Jarvis et al. 2005). Moreover, the nidopallium caudolaterale in birds is functionally equivalent to the mammalian prefrontal cortex, which is involved in higher functions such as controlling of instinctive impulses, reasoning, all kinds of decision making, generating socially appropriate be-
126
Kurt Kotrschal, Isabella B.R. Scheiber and Katharina Hirschenhauser
haviour and conscious thought (Divac et al. 1994, Güntürkün 2005). Hence, the striking parallels of social organisation in birds and mammals may be based on similar (both, homologous and convergent) cognitive mechanisms (Emery and Clayton 2004a). Some birds, such as geese, are indeed able social learners (Fritz and Kotrschal 2002), and the learning and reasoning abilities of birds closely parallel those of mammals (Huber et al. 2001, Huber 2002, 2007, Schloegl et al. 2009). In fact, advanced cognitive abilities were recently shown in the ‘brainy’ crow family (Dally et al. 2006, Bugnyar 2007) and in some parrots (Pepperberg 1999, Iwaniuk and Nelson 2003). These abilities include mental time travelling (Clayton and Dickinson 1998, Clayton et al. 2001, Raby et al. 2007), advanced cooperative abilities (Huber et al. 2008), technical and physical understanding (Auersperg et al. 2009), self-recognition in a mirror (Prior et al. 2008), and theory of mind (i.e. knowing about others’ minds; Dally et al. 2006, Bugnyar 2007, Kotrschal et al. 2007). Despite the fact that relatively smaller-brained birds express social complexities, which rival those of some mammals, there is still scepticism to what extent this may be based on cognitive abilities (Emery et al. 2007; but see Scheiber et al. 2008). In support of the involvement of social cognition, greylag geese show differentiated heart rate responses when watching third party interactions (Wascher et al. 2009) and perform remarkably well in a transitive inference task (Weiß et al. 2009; i.e. a well established operant procedure, in which the ordering of a set of arbitrary stimuli can be inferred from a series of dyadic comparisons; Bond et al. 2003). This does not imply, however, that all social interactions appearing complex require high-level cognition (Barrett et al. 2007, Healy and Rowe 2007).
5.5 The greylag goose society Concepts of social complexity have been discussed mainly in the mammalian, notably primate literature (see de Waal and Tyack 2003 for a review). However, recent evidence indicates considerable mammal-like social complexity in birds as well, for example in corvids, parrots and greylag geese (Emery and Clayton 2004b, Kotrschal et al. 2007, Scheiber et al. 2008). Greylag geese (Anser anser), in general, are long-lived and long-term monogamous birds, showing family cohesion over years and a female-centred clan organisation, elaborate post-conflict behaviour and distinct behavioural and physiological patterns related to social support; they form social traditions, assume personality-related individual social roles and may even be knowledgeable of third party relationships. The basics of the greylag
Individual performance in complex social systems
127
BOX 5.1 Greylag goose social system and biology Greylag geese (Anser anser) are long-lived (more than 14 years in the wild, Hudec and Rooth 1970) and form long-term monogamous pairs (Lorenz 1988), which are the elementary social unit of a flock. Even at a balanced flock sex ratio, males may engage in pair-bonds with other males, which is a male tactic to maintain high rank (Kotrschal et al. 2006). Excess females will attach as a ‘secondary’ female to a heterosocial pair. Trios of two males and one female are formed when a female attaches to a homosocial male pair. Social units maintain spatial proximity and perform the ‘triumph ceremony’ together (Fischer 1965, Radesäter 1974). Individual dominance rank is conditional on social relationships (Lamprecht 1986, 1987, Lorenz 1988, Black et al. 2007): highest ranking are family units, where family members acquire the gander’s rank. Pairs without offspring rank intermediate, singletons rank lowest. Family members provide active and passive social support to each other (Weiß and Kotrschal 2004, Scheiber et al. 2005a, 2009a,b). Interindividual behavioural variation exists also with regards to social roles based on personalities (Pfeffer et al. 2002, Kralj-Fiser et al. 2007). Geese flock from summer into late winter to avoid predation (Lazarus 1978, Lazarus and Inglis 1978, Kotrschal et al. 1992). As facultative migrants, flocks may temporarily or permanently cease their migratory traditions when mild winters afford sufficient food supply (Rutschke 1982, 1997, Kear 1990). After returning from their wintering grounds, flocks disintegrate into pairs. At this time, greylag females form loose breeding colonies. The non-breeders stay together or aggregate for moulting in May and June. Females lay up to 8 eggs, which they alone incubate for 28 days. Young females tend to dump eggs into the nests of experienced geese (Weigmann and Lamprecht 1991). During incubation, the gander stays close, but does not approach the nest unless it needs defending. Goslings and females leave the nest approximately 24 – 48 hours after hatching, when also the gander joins again. Usually the pair raises their young in proximity of other families. Goslings need to be brooded regularly by the female for their first 3 weeks of life. They forage for themselves immediately after leaving the nest, but pay attention to the parental beaks, thereby forming feeding traditions (Fritz and Kotrschal 2002). A gander defends female and goslings against other flock members or predators. Approximately 5 weeks after hatching, parents start moulting their wing feathers. Parents regain the ability to fly at the time their young fledge. Then families form summer foraging flocks with non-breeders, increasingly integrating into winter flocks in autumn. For example, up to 20.000 greylag geese from all over Europe aggregate at Neusiedlersee. They may stay there until cold spells or snowfall inhibits access to food at harvested fields around the lake. Only then geese leave for their wintering areas at the Mediterranean coast of Tunisia (Rutschke 1982, 1997).
128
Kurt Kotrschal, Isabella B.R. Scheiber and Katharina Hirschenhauser
BOX 5.2 The Grünau flock of greylag geese Konrad Lorenz established a free-flying, non-migratory flock of greylag geese in the Upper Austrian valley of the river Alm in 1973. The flock is unrestrained and roams the valley between the Konrad Lorenz research station (KLF) and lake Almsee 10 km to the South, which is used as a night roost. For most of the year, the flock can be found on the meadows surrounding the KLF during the day, where it is provided with supplemental (summer) or sustaining (winter) amounts of food twice a day. From breeding (March) to moult (June/July) the flock disintegrates and the geese spread to various locations in the valley, most of which are accessible to researchers. All individuals are marked with coloured leg rings and show neither behavioural nor physiological (heart rate) responses when being approached to a distance of 1.5 m by humans they are acquainted with. Individual life histories and social relationships have been monitored on a daily to weekly basis since the establishment of the flock. Flock size varied between 120 and 170 individuals over the years. Every year up to 10% of the individuals are lost to natural predators, mainly red foxes (Vulpes vulpes; Hemetsberger 2001). Except for the lack of a migratory tradition, the seasonal patterns of the KLF flock closely resemble that of wild geese (Kotrschal and Hemetsberger 1995, Rutschke 1997, Hirschenhauser et al. 1999b). After break-up of the winter flock, females nest at various locations between the KLF and Almsee. They either build nests in relatively predator-safe breeding boxes, or they nest in reeds, where predation pressure is high: approximately 10 females and clutches are lost per year. This leads to a male-biased sex ratio in the flock (up to 70%) and fosters a tradition of breeding in safe boxes (Weiß et al. 2008). Approximately 80% of the hatched goslings die within the first 2 weeks of age due to predation or parasite infections. In general, fledging success increases with maternal age (Hemetsberger 2001). Although the number of heterosexual pairs increased from 16 in 1973 to over 40 in 2000, the number of pairs with fledged young remains remarkably constant at 4.4 ± 2.9 (SD) per year, with a total of 16.5 ± 11.4 fledglings per year. This barely balances the fledged geese lost to predators and dispersal (Hemetsberger 2001). Over the years, 20-30% of the geese in the flock have been hand-raised in sibling groups, resulting in individuals accessible for experiments. Eggs for hand-raising are artificially incubated and frequently originate from outside populations. Thereby, the gene pool is increased and inbreeding is counterbalanced. Shortly after hatching, hand-raised geese are in contact with the flock to ensure proper socialisation. After fledging they fully integrate into the flock and are socially indistinguishable from goose-raised geese, except for a tendency to maintain stable homosocial pair-bonds between brothers (Kotrschal et al. 2006).
Individual performance in complex social systems
129
social system are given in BOX 5.1 and in some detail, in the following, where we will guide the reader through this social system from an individual’s perspective and, as much as possible, also from a proximate point of view (sensu Tinbergen 1963). We will focus on the pair-bond, i.e. behavioural and hormonal synchrony between pair partners, as a cornerstone for coping with the demands of a complex social life. Finally, we will discuss individual social efficiency based on our long-term heart rate data as a proxy for emotional involvement and social energetics, and will emphasise stress reduction by social support as a key factor of the greylag social system. These results are mainly based on our long-term studies of a flock at Grünau (BOX 5.2). 5.5.1 The start of a social career: mothers and eggs Individual dispositions to behave in a certain way in the social domain (‘personality’ or ‘individual behavioural phenotype’: i.e., influence of individual emotionality, stress coping and bonding style, plus experience) are genetically heritable and can be epigenetically affected by ‘maternal effects’ (Bergmüller this volume), as well as by early socialisation and parenting (Sachser and Kaiser this volume). In fact, bird mothers differ in how much they invest into single eggs (Bertin et al. 2008, Groothuis and Schwabl 2008). Egg size varies between females and generally decreases with laying order, the latter being interpreted as an evolutionary preadjustment to varying conditions during raising of young (Groothuis et al. 2005). However, there is also differential investment in regard to the qualitative components of the eggs. The amount of carotenoids, for instance, will affect the chicks’ immune system (Saino et al. 2003), whereas the amount of androgens will affect the behaviour of the offspring. The more androgens the yolk contains, the more vigorously the chick will beg (Schwabl et al. 1997), the more aggressive it may be (Groothuis and Carere 2005) and the more its behavioural phenotype will be shifted towards being proactive (sensu Koolhaas et al. 1999, e.g., Daisley et al. 2005, Bertin et al. 2009). In response to environmental conditions, females may epigenetically adjust offspring phenotype, mainly via hormones in the yolk (Daisley et al. 2005, Groothuis and Carere 2005, Bertin et al. 2008, 2009). Proactive individuals, in contrast to reactive ones, are relatively bold and aggressive in social and non-social contexts, are prone to form routines and scrounge from others and should be less socially dependent and hence, are likely to disperse. Proactives are also generally less stressed by social isolation than reactives. In agreement with the producer-scrounger
130
Kurt Kotrschal, Isabella B.R. Scheiber and Katharina Hirschenhauser
paradigm (Barnard and Sibly 1981), we found that the reactives, rather than the proactives tended to be the innovators, in a group of unmanipulated greylag goslings (Pfeffer et al. 2002): individuals, which had higher baseline levels of glucocorticoids at the age of two weeks solved an operant task faster than others at 6 weeks of age and were innovative producers of food at 10 months of age. Hence, the expression of social performance and social roles seems to involve some predisposition by individual behavioural phenotype (Kralj-Fiser et al. 2007), which is probably mediated to some degree by the maternal deposition of steroid compounds in the yolk (Daisley et al. 2005, Groothuis and Schwabl 2008). 5.5.2 The first year The precocial goslings are faced with social, physical and ecological challenges beginning with their first day after leaving the nest. As an effect of high yolk steroid levels, particularly high levels of corticosterone metabolites are excreted up to 20 days after hatching (McNabb et al. 1998, Frigerio et al. 2001a). Right after hatching, goslings need to be kept safe from predators and apart from other families to prevent fusion with gosling groups from other families (Lorenz 1988, Kalmbach et al. 2005). This is mainly achieved by the male, who also shields his female from being disturbed by other geese when brooding the goslings (Lorenz 1988). Consequently, the males’ corticosterone levels, as well as their involvement in agonistic encounters, increase after hatching of their goslings (Kotrschal et al. 1998, Swoboda et al. submitted). Males reduce their agonistic involvement at approximately 6-7 weeks after hatching. From then on, goslings gradually increase their participation in aggressive encounters towards fledging. In fact, they win agonistic encounters against larger and older individuals, with the active help of their fathers (Scheiber 2009a), but generally lose such agonistic interactions if not supported. Thus, before fledging, the main beneficiaries of social support are the goslings: they tend to win encounters and show low faecal corticosterone metabolites levels (Swoboda et al. submitted). But do parents also benefit from the presence of their young? Contrary to many avian species, goose parents remain with their young for an extended period of time, i.e. approximately one year, after the goslings fledge (‘primary family’). Such a relatively long-lasting family cohesion is uncommon among birds and seems to be not only in the interest of the offspring. Shortly before the goslings fledge, parents have re-grown their wing feathers after moult. Now, particularly females seem to benefit from passive social support in the company of their young. Females did not excrete
Individual performance in complex social systems
131
elevated glucocorticoid metabolites when experimentally exposed to a social density situation (Scheiber et al. 2005a) when they were accompanied by at least three fledged young. Thereby, the fledged young appear to be the ‘physiological helpers’ of their parents (Scheiber et al. 2009a), sensu ‘helpers at the nest’ in communally breeding species (Brown 1987), because females who successfully raised young in one year will enter the next breeding season in better condition than females which failed. Energetic costs of reproduction are usually higher for females than for males (Adkins-Regan 2005). Any activation of the stress systems is energetically costly and frequent/chronic activation may negatively affect an individual’s reproductive success (Bowman et al. 1978, Mendl et al. 1992) and health (von Holst 1998). Therefore, for the females it is particularly crucial to respond adequately and economically to stressors (Nephew et al. 2003). The young also benefit from active social support when still integrated in their family. In case of lost agonistic interactions, they may reverse a prior defeat experience, when family members retaliate by repeatedly attacking the opponent which previously had won against the primarily targeted offspring/sibling (Scheiber et al. 2009b). This may be one of the reasons why juvenile geese rank much higher in the flock hierarchy than expected from their age and size. Such benefits of being socially supported by social allies are probably also the reason for female kin to maintain loose clan bonds (Weiß et al. 2008). 5.5.3 The second year If parents fail to reproduce in their next breeding attempt a year later, the young of previous years may rejoin their family for a second or even third year (‘secondary or tertiary families’, Lorenz 1988). To determine the potential functionality of this, we investigated active and passive social support mechanisms in secondary families (Scheiber et al. 2009a). Contrary to primary families, we were unable to detect any form of active social support in secondary families during agonistic interactions with other flock members, but – similar to primary families – the beneficiaries were the adult and subadult females, with respect to a dampened glucocorticoid modulation (i.e. ‘passive’ social support). For subadult males, ‘motivational components’ (Lamprecht 1986) are most likely the main explanation why they join their parents for a second year: via enhanced agonistic motivation, subadult males benefit from winning agonistic interactions, thereby climbing higher in rank than would be possible outside their family unit (Weiß et al. 2008). When accepting last year’s young, costs for parents are probably negligible. Therefore, joining
132
Kurt Kotrschal, Isabella B.R. Scheiber and Katharina Hirschenhauser
Fig. 5.3 Goose Beleriand (right) threatened and attacked by another female, Lanzelot (middle). Her partner Boston (left back) and an unrelated goose, Nazca (left front) provide active social support by co-threatening the opponent. Such an attack may result in a ‘serial attack’ (Scheiber et al. 2009b), in which family members will repeatedly attack one particular opponent. These serial attacks are thought to serve in reversing previous losses, reinforce a losing experience on the side of the opponent or signal the agonistic potential of a family to other flock members. Photo © Brigitte Weiß.
a secondary family when no appropriate mate is available during their first year after fledging may be viewed as an alternative tactic for subadult geese (Scheiber et al. 2009a). 5.5.4 Adult years: dynamic clan structure and associated benefits for females In most mammals, male-biased dispersal and female natal philopatry (Greenwood 1980, Waser and Jones 1983) are the rule; in most cases, their social groups are matrilines, with high levels of female relatedness (Coltman et al. 2003). Most birds, on the other hand, show male philopatry, and in some species neighbourhood male groups are closely related (Höglund et al. 1999, Petrie et al. 1999, Pirtney et al. 1999, Shorey et al. 2000). These differences probably root in the different possibilities in mammals
Individual performance in complex social systems
133
and birds for investing in offspring. Waterfowl (Anatidae) pose a notable exception, where female-biased natal philopatry is the rule, while males usually follow their mate to her hatching area for breeding (Waldeck et al. 2008). Barnacle geese (Branta leucopsis) were shown to nest close to their parents and sisters when breeding on the same island. However, when parents and sisters nested on different islands, females stayed close to their same-age sisters (van der Jeugd et al. 2002). In greylag geese, adult female sisters, but not brothers, were shown to seek each other’s company during rest (Frigerio et al. 2001b). Even when already paired, females were found close to their sisters. The same seems to be true for adult daughters and their mothers, although in this case spatial proximity was less pronounced than in sister-sister pairs (Scheiber and Weiß submitted). A number of hypotheses have been generated to explain the femalecentered population structure in waterfowl (e.g., Eadie et al. 1988, Chesser 1991, Avise et al. 1992, Regehr et al. 2001, van der Jeugd et al. 2002, McKinnon et al. 2006, Waldeck et al. 2008), but stress-reduction through the permanent presence of social allies has seemingly been overlooked. We suggest that social support may be one of the driving forces behind this female-centred social organisation. Any reduction of female (social) stress should be advantageous, particularly during the incubation phase of the breeding cycle and while the goslings need to be brooded (see above). Indeed, females, but not males, enjoyed dampened glucocorticoid responses during stressful situations when part of a secondary family (Scheiber et al. 2009a). The observed female-centred clan structures are a much less determining factor in social organisation than, for example, in macaques (de Ruiter and Geffen 1998, Kappeler and van Schaik 2002) or baboons (Silk et al. 2003, 2009), probably because maternal rank is strictly heritable in macaques, whereas in geese, female rank mainly depends on the male partner. 5.5.5 Pair formation, pair-bond maintenance and hormonal synchrony between pair partners The major function of monogamy is biparental care (Black 1996), the effectiveness of which is probably supported by at least some behavioural and physiological coordination and synchronisation between pair partners. In fact, assortative mating with respect to age and size was shown to optimise lifetime reproductive success in barnacle geese (Choudhury et al. 1996), whereas reproducing with non-preferred partners, as well as divorce may have negative fitness consequences (Black et al. 1996, Bluhm and Gowaty 2004, Angelier et al. 2007). Particularly in monomorphic species
134
Kurt Kotrschal, Isabella B.R. Scheiber and Katharina Hirschenhauser
with long-term pair-bonds, mate choice is inevitably a two-way decision process as each individual is both, the chooser and a chosen (AdkinsRegan 2005). Also, the maintenance of a pair-bond is the result of the ‘bilateral’ interactions between pair partners and of the ‘multilateral’ interactions between the pair and its physical and social environment. Therefore, in search for behavioural and physiological correlates of successful reproduction it may be revealing to shift the unit of analysis from the individual to the pair. For example, goose pairs with a high degree of within-pair testosterone co-variation (TC; i.e. the degree of seasonal testosterone covariation between the male and the female pair partner) produced more offspring in the year sampled, as well as over their lifetime than pairs low in TC (Hirschenhauser et al. 1999a). But why are androgens particularly relevant in social careers? Throughout the vertebrates, male testosterone (T) regulates and responds to courtship, sexual and agonistic behaviour (Goymann and Hofer this volume). Thus, individual T responsiveness is a function of the stability of the social environment (Wingfield et al. 1990). Furthermore, T is the main physiological mediator shifting male investment towards male-male aggressiveness and constrained paternal care. The maintenance of elevated T levels bears costs (Wingfield et al. 2001), pointing at two fundamental phenomena: i) a male must be sufficiently healthy to afford both, T responses to certain behaviours and the behavioural performance itself. Thus, T-related behaviours and traits efficiently advertise fitness and immunocompetence, particularly because T may be regarded a physiological handicap (Folstad and Karter 1992, Zahavi and Zahavi 1997); ii) the male should benefit from the expression of post-conflict T responses. Perhaps T facilitates the likelihood of winning in future agonistic interactions (Oliveira et al. 2009). In female birds, androgens generally mediate sexual receptivity and prebreeding territoriality (Gill et al. 2007). This seems to be a general phenomenon, as also in female mammals androgens were linked to sexual desire and receptivity, which is supported by the fact that peaks occur around ovulation (Longcope 1986, Alexander and Sherwin 1993). Androgens in both sexes may be of gonadal, as well as adrenal origin (Lee and Bahr 1994, Rodríguez-Maldonado et al. 1996, Boonstra et al. 2008). In geese, the androgen metabolites we measure in droppings from female geese are predominantly of gonadal origin (Hirschenhauser et al. 2010). Female androgens as indicators of sexual motivation contribute to explain the parallel androgen levels in the male and female partners of a successful pair. The within-pair testosterone-co-variation (TC) studies in greylag geese (Hirschenhauser et al. 1999a, Weiß et al. 2010) provide one of the rare examples in which steroid patterns were linked with long-term reproductive success (Adkins-Regan 2005). TC predicted both, the pair’s reproductive
Individual performance in complex social systems
135
output, as well as individual fitness of both pair partners. We suggest different contributions to a pair’s TC from females and males: the female needs to assemble with a complementary and compatible male partner able to adapt behaviourally and physiologically to her needs as related to breeding. A male’s continuous and flexible androgen responsiveness to the female seems essential for the pair’s joint status and performance within the flock. This certainly includes both partners’ stress responsivity to winning or losing a pair-bond challenge during frequent ‘soap operas’ in the mating season (Hirschenhauser et al. 2000). Surprisingly, however, pair-bond duration was not related to hormonal synchrony between pair partners (Hirschenhauser et al. 1999a). Meanwhile, we know from analyses of further 53 greylag goose pairs that hormonal synchrony between pair partners may even decrease over time spent together. Simple ageing of the pair partners could not explain this pattern, as experienced older females had higher TC ranks with their pair partners than younger females (Weiß et al. 2010).
Fig. 5.4 A wing-shoulder fight of two ganders. Individuals grasp each other by the shoulder and violently strike the opponent with the knob at the frontal edge of their wings. Such severe fights may last seconds to minutes and usually occur in competition for partners. Such interactions will cause maximum activity of the stress axes. Particularly losers of such interactions would benefit from social support provided by their partners (‘consolation’). Photo © Brigitte Weiß.
136
Kurt Kotrschal, Isabella B.R. Scheiber and Katharina Hirschenhauser
Experiments with domestic geese revealed the female contribution to a pair’s TC: females with preferred partners had higher seasonal androgen peaks during egg formation and later on, were more likely to initiate incubation than females paired at random; however, mate choice per se did not explain TC variation. When the same individuals were allowed to freely attach and interact in a large flock, the TC-ranks we previously observed in pairs were generally reduced. Thus, TC is responsive and vulnerable to the social environment (Hirschenhauser et al. 2010). Also in greylag geese, TC must be viewed as a physiological correlate of the current social condition of the pair in the flock context rather than a pair-specific, lasting and stable trait (Weiß et al. 2010). In sum, it seems that partners, which do not match early on, probably never will. Yet, on top of this, compatible partners still need a favourable social environment to express high TC. 5.5.6 Social energetics Winning or a losing in a single encounter does not have to be particularly stressful, whereas repeated challenge or defeat may result in chronic stress load. Whether social stress affects dominants or subordinates to a greater degree is context-dependent (Kotrschal et al. 1998, Sapolsky 2002, Abbott et al. 2003, Goymann and Wingfield 2004). As in other species, individual geese differ in how they cope with social conflicts, reflected in individual differences of glucocorticoid responsiveness (Koolhaas et al. 1999, Goymann and Wingfield 2004, Kralj-Fiser et al. 2007). The modulation of both stress axes, SAS and HPA, correlates with oxygen consumption; hence, social conflict may be energetically expensive (McEwen and Wingfield 2003). A prime physiological parameter to study social stress is heart rate (HR), which is highly variable and influenced by virtually all factors relevant for an individual (Bastian 1984). Particularly important HR modulators are physical activity, season and time of the day (Moen 1978, Dressen et al. 1990, Boyd et al. 1999, Arnold et al. 2006, Nilsson et al. 2006), as well as ambient temperature and thermoregulation (Bartholomew et al. 1962, Müller 1982, Arnold et al. 2006). Generally, physical activity received the most attention in the context of HR, because of its clear connection to energy expenditure (Wieser 1986). Consequently, most studies in birds focused on flight, which is among the energetically most demanding behaviours. In greater white-fronted geese (Anser albifrons), for example, HR has been shown to rise from 112 beats per minute (bpm) during rest to a maximum of 446 bpm during flight (Ely et al. 1999). Our data from 25 greylags implanted with HR transmitters (for a detailed description of
Individual performance in complex social systems
137
technology and procedures see Wascher et al. 2009) revealed that in greylags the mean HR at rest is around 85 bpm, while it rises to around 400 bpm before and during take-off (Wascher et al. 2008a). Particularly striking are data from bystanding geese not moving themselves, but watching either social or non-social events: HR increases in these observers were greater when they watched social rather than non-social events (mean maximal heart rates 170 bpm versus 146 bpm, Wascher et al. 2008b) and HR varied with the intensity and duration of an agonistic interaction they watched, as well as with the identity and rank of the opponents involved in the interactions (Wascher et al. 2009). Based on these data, we conclude that geese may have some understanding of third-party relationships. We also recorded the long-term patterns of HR and body temperature. We found circannual and diurnal variation, with lows during early winter and late night (yearlong, midnight to morning) and highs in spring and summer and during the day (Kotrschal et al. unpublished data). This reflects the seasonal modulation of metabolic rate adapted to ecological conditions and social tasks (Kotrschal et al. 1998, Hirschenhauser et al. 2000). On top of this, HR was 13% higher in the females than in the males and pair-bonded individuals showed lower HR during potentially stressful situations than singletons (Wascher et al. 2008b). From these long-term data we concluded that roughly 30% of the total individual energy may be spent in the social domain and that inter-individual variation in that respect is substantial (Kotrschal et al. unpublished). For example, during the 28day incubation period we found great individual differences in mean HR of five females, ranging from 60 bpm to 180 bpm. This indicates a three-fold difference in metabolic rate and energy expense between these females, even in an evident ‘standard’ situation, such as incubation (Scheiber et al. 2006). 5.5.7 Social support among clan members Social interactions are known to be among the most potent stressors (DeVries et al. 2003) and greylag geese are no exception (Wascher et al. 2008b). But this is counterbalanced via the support social allies may provide. The greylag geese social system is characterised by the integration of social units, such as pairs, families and female-centred clans into a flock, which includes agonistic interactions between and social support within these social units. Although the advantages of group living (Krause and Ruxton 2002) certainly outweigh the costs of social stress, we have demonstrated that social life does not come cheap. Individuals in a flock differ with respect to their personalities and related to that, in their physiology
138
Kurt Kotrschal, Isabella B.R. Scheiber and Katharina Hirschenhauser
and basic metabolism (Koolhaas et al. 2007). Still, for coping effectively with the challenges of sociality they all need long-term allies. With a competent and matching partner they will be able to budget their energy efficiently and, thereby, not only reproduce successfully, but also reap benefits from social support through their offspring. Hence, we propose that social support per se is a core factor in stabilising long-term monogamous pairbonds, family cohesion and female-centred clans in greylags.
5.6 Relating to other complex social systems: more questions than answers Social organisation, social structure and mating system have been defined as distinct components of a social system (Kappeler and van Schaik 2002). In fact, basic social organisation, monogamous pairs, female-centred clans, male dominance systems, multi-male groups, etc. may differ greatly between species. Some of the causation of the basic structuring of social systems is reasonably well understood. For instance, the multi-male groups in chimpanzees (Pan troglodytes), and to some extent, pack structure in wolves (Canis lupus), seem to be related to the often deadly skirmishes with neighbouring groups at the territorial borders. The lion harem and infanticide system (as well as mammalian infanticide systems in general) results from the constraints imposed by the male reproductive interests (Packer et al. 1990). And the prevalence of monogamy in birds is certainly linked to the greater opportunities for males to invest in offspring directly. However, the causation of other social structuring remains enigmatic, for instance the female dominance system in most lemurs (Kappeler and Kraus this volume) or the rigid female hierarchies in macaques and baboons (Cheney and Seyfarth 2008). The greylag example shows that passive social support affects the energetic efficiency of social life, making it a prime candidate for structuring this and other vertebrate social systems. Because the ability to profit from social support depends on personality and attachment style (Kotrschal et al. 2009), not all individuals will be affected by social support in the same way. We still lack data from other species, but social support may affect individuals in diverse social systems and examples exist in species from all vertebrate taxa. Lionesses, for example, may mutually support each other for stress reduction and also may support their males to ensure long residency, thereby decreasing the likelihood of infanticide over their lifetime (Packer et al. 1990). As another example, grooming networks in baboons become more exclusive in times of social instability when individuals evi-
Individual performance in complex social systems
139
dently focus on partners, which are able social supporters (Cheney and Seyfarth 2008). Thus, social stress reduction may be a hidden mechanism in many complex vertebrate social systems. Moreover, stress reduction via social support and activation of the oxytocin system dampens the HPAglucocorticoid cascade in a number of ways (DeVries et al. 2003), thereby decreasing anxiety and enhancing individual sociability. By this means, social support positively affects individual sociability. In the past, mainly the direct links between social performance and fitness have been in the focus of quantitative behavioural biology. In contrast, the fitness relevance of feedbacks and dependencies between social behaviour, structure and organisation, as well as the underlying physiological dynamics is known, at best, at a qualitative level. Knowledge within the research levels, proximate, ultimate, ontogeny and evolutionary history (Tinbergen 1963) is advancing rapidly, but linking the levels is necessary for the systemic understanding of social evolution. This remains still a widely open field.
References Abbott DH, Keverne EB, Bercovitch FB, Shively CA, Mendoza SP, Saltzman W, Snowdon CT, Ziegler TE, Banjevic M, Garland T Jr, Sapolsky RM (2003) Are subordinates always stressed? A comparative analysis of rank differences in cortisol levels among primates. Horm Behav 43:67-82 Adkins-Regan E (2005) Hormones and Animal Social Behavior: Monographs in Behavior and Ecology. Princeton University Press, Princeton Alexander GM, Sherwin BB (1993) Sex steroids, sexual behavior, and selection attention for erotic stimuli in women using oral contraceptives. Psychoneuroendocrinology 18:91-102 Angelier FH, Moe B, Clement-Chastel C, Bech C, Chastel O (2007) Corticosterone levels in relation to change of mate in black-legged kittiwakes. Condor 109:668-674 Arnold W, Ruf T, Kuntz R (2006) Seasonal adjustment of energy budget in a large wild mammal, the Przewalski horse (Equus ferus przewalskii). II. Energy expenditure. J Exp Biol 209:4566-4573 Auersperg AM, Gajdon GK, Huber L (2009) Kea (Nestor notabilis) consider spatial relationships between objects in the support problem. Biol Lett 5:455-458 Aureli F, de Waal FBM (2000) Natural Conflict Resolution. University of California Press, Berkeley Aureli F, Cords M, van Schaik CP (2002) Conflict resolution following aggression in gregarious animals: a predicitive framework. Anim Behav 64:325-343 Avise JC, Alisauskas RT, Nelson WS, Ankney CD (1992) Matriarchal population genetic structure in an avian species with female natal philopatry. Evolution 46:1084-1096
140
Kurt Kotrschal, Isabella B.R. Scheiber and Katharina Hirschenhauser
Barnard CJ, Sibly RM (1981) Producers and scroungers: a general model and its application to captive flocks of house sparrows. Anim Behav 29:543-550 Barrett L, Henzi SP (2005) The social nature of primate cognition. Proc R Soc Lond B 272:1865-1875 Barrett L, Henzi SP, Rendall D (2007) Social brains, simple minds? Does social complexity really require congnitive complexity? Philos Trans R Soc Lond B 362:561-575 Bartholomew GA, Hudson JW, Howell TR (1962) Body temperature, oxygen consumption, evaporative water loss, and heart rate in poor-will. Condor 64:117-127 Bastian H-V (1984) Die Änderung der Herzfrequenz als Maß der Erregung – eine Literaturübersicht. Vogelwarte 32:226-233 Beauchamp G, Fernández-Juricic E (2004) Is there a relationship between forebrain size and group size in birds? Evol Ecol Res 6:833-842 Bertin A, Richard-Yris A-M, Houdelier C, Lumineau S, Möstl E, Kuchar A, Hirschenhauser K, Kotrschal K (2008) Habituation to humans affects yolk steroid levels and offspring phenotype in quail. Horm Behav 54:396-402 Bertin A, Hirschenhauser K, Kotrschal K (2009) Trans-generational influence of human disturbances in Japanese quail: egg quality influences male social and sexual behavior. Ethology 115:879-887 Black JM (1996) Partnerships in Birds: The Study of Monogamy. Oxford University Press, Oxford Black JM, Choudhury S, Owen M (1996) Do barnacle geese benefit from lifelong monogamy? In: Black JM (ed) Partnerships in Birds: The Study of Monogamy. Oxford University Press, Oxford, pp 91-117 Black JM, Prop J, Larsson K (2007) Wild Goose Dilemmas: Population Consequences of Individual Decisions in Barnacle Geese. Branta Press, Groningen Bluhm CK, Gowaty PA (2004) Social constraints on female mate preferences in mallards, Anas platyrhynchos, decrease offspring viability and mother productivity. Anim Behav 68:977-983 Bond AB, Kamil AC, Balda RP (2003) Social complexity and transitive inference in corvids. Anim Behav 65:479-487 Boonstra R, Lane JE, Boutin S, Bradley A, Desantis L, Newman AEM, Soma KK (2008) Plasma DHEA levels in wild, territorial red squirrels: seasonal variation and effects of ACTH. Gen Comp Endocrinol 158:61-67 Bowman LA, Dilley SR, Keverne EB (1978) Suppression of oestrogen induced LH surges by social subordination in talapoin monkeys. Nature 275:56-58 Boyd IL, Bevan RM, Woakes AJ, Butler PJ (1999) Heart rate and behaviour of fur seals: implications for measurement of field energetics. Am J Physiol 276:H844-H857 Brown JL (1987) Helping and Communal Breeding in Birds. Princeton University Press, Princeton Bugnyar T (2007) An integrative approach to the study of ‘theory-of-mind’-like abilities in ravens. Jpn J Anim Psychol 57:15-27
Individual performance in complex social systems
141
Byrne RW, Whiten A (1988) Machiavellian Intelligence: Social Expertise, and the Evolution of Intellect in Monkeys, Apes, and Humans. Clarendon Press, Oxford Champagne FA, Curley JP (2005) How social experiences influence the brain. Curr Opin Neurobiol 15:704-709 Cheney DL, Seyfarth RM (2008) Baboon Metaphysics: The Evolution of a Social Mind. University of Chicago Press, Chicago Chesser RK (1991) Gene diversity and female philopatry. Genetics 127:437-447 Choudhury S, Black JM, Owen M (1996) Body size, reproductive success and compatibility in barnacle geese. Ibis 138:700-709 Clayton NS, Dickinson A (1998) Episodic-like memory during cache recovery by scrub jays. Nature 395:272-274 Clayton NS, Griffiths DP, Emery NJ, Dickinson A (2001) Elements of episodiclike memory in animals. Philos Trans R Soc Lond B 356:1483-1491 Coltman DW, Pilkington JG, Pemberton JM (2003) Fine-scale genetic structure in a free-living ungulate population. Mol Ecol 12:733-742 Curley JP, Keverne EB (2005) Genes, brains and mammalian social bonds. Trends Ecol Evol 20:561-567 Daisley NJ, Bromundt V, Möstl E, Kotrschal K (2005) Enhanced yolk testosterone influences behavioral phenotype independent of sex in Japanese quail chicks Coturnix japonica. Horm Behav 47:185-194 Dally J, Emery NJ, Clayton NS (2006) Food-caching scrub jays keep track of who was watching when. Science 312:1662-1665 de Ruiter JR, Geffen E (1998) Relatedness of matrilines, dispersing males and social groups in long-tailed macaques (Macaca fascicularis). Proc R Soc Lond B 265:79-87 DeVries AC, Glasper ER, Detillion CE (2003) Social modulation of stress responses. Physiol Behav 79:399-407 de Waal FBM (1982) Chimpanzee Politics: Power and Sex among Apes. Harper and Row, New York de Waal FBM, Tyack PL (2003) Animal Social Complexity: Intelligence, Culture and Individualized Societies. Harvard University Press, Cambridge/MA Divac I, Thibault J, Skageberg G, Palacios JM, Dietl MM (1994) Dopaminergic innervation of the brain in pigeons. The presumed ‘prefrontal cortex’. Acta Neurobiol Exp 54:227-234 Dressen W, Grün H, Hendrichs H (1990) Radio telemetry of heart rate in male tammat wallabies (Marsupialia: Macropodidae): temporal variations and behavioural correlates. Austr J Zool 38:89-103 Dunbar RIM (1995) Neocortex size and group size in primates: a test of the hypothesis. J Hum Evol 28:287-296 Dunbar RIM, Bever J (1998) Neocortex size predicts group size in carnivores and some insectivores. Ethology 104:695-708 Eadie JM, Kehoe FP, Nudds TD (1988) Pre-hatch and post-hatch brood amalgamation in North American Anatidae. A review of hypotheses. Can J Zool 66:1709-1721
142
Kurt Kotrschal, Isabella B.R. Scheiber and Katharina Hirschenhauser
Ely CR, Ward DH, Bollinger KS (1999) Behavioral correlates of heart rates of free-living greater white-fronted geese. Condor 101:390-395 Emery NJ, Clayton NS (2004a) The mentality of crows: convergent evolution of intelligence in corvids and apes. Science 306:1903-1907 Emery NJ, Clayton NS (2004b) Comparing the complex cognition of birds and primates. In: Rogers LJ, Kaplan GT (eds) Comparative Vertebrate Cognition: Are Primates Superior to Non-Primates? Springer, Berlin, pp 3-55 Emery NJ, Seed AM, von Bayern AMP, Clayton NS (2007) Cognitive adaptations of social bonding in birds. Philos Trans R Soc Lond B 362:489-505 Fischer H (1965) Das Triumphgeschrei der Graugans (Anser anser). Z Tierpsychol 22:247-304 Folstad I, Karter AJ (1992) Parasites, bright males, and the immunocompetence handicap. Am Nat 139:603-622 Frigerio D, Möstl E, Kotrschal K (2001a) Excreted metabolites of gonadal steroid hormones and corticosterone in greylag geese (Anser anser) from hatching to fledging. Gen Comp Endocrinol 124:246-255 Frigerio D, Weiß BM, Kotrschal K (2001b) Spatial proximity among adult siblings in greylag geese (Anser anser): evidence for female bonding? Acta Ethol 3:121-125 Fritz J, Kotrschal K (2002) On avian imitation: cognitive and ethological perspectives. In: Nehaniv CL, Dauterhahn K (eds) Imitation in Animals and Artifacts. MIT Press, Boston, pp 133-155 Gill SA, Alfson ED, Hau M (2007) Context matters: female aggression and testosterone in a year-round territorial neotropical songbird (Thryothorus leucotis). Proc R Soc Lond B 274:2187-2194 Goodson JL (2005) The vertebrate social behavior network: evolutionary themes and variations. Horm Behav 48:11-22 Goodson JL, Schrock SE, Klatt JD, Kabelik D, Kingsbury MA (2009) Mesotocin and nonapeptide receptors promote estrildid flocking behavior. Science 325:862-866 Goymann W, Wingfield JC (2004) Allostatic load, social status and stress hormones: the costs of social status matter. Anim Behav 67:591-602 Greenwood PJ (1980) Mating systems, philopatry and dispersal in birds and mammals. Anim Behav 28:1140-1162 Groothuis TGG, Carere C (2005) Avian personalities: characterization and epigenesis. Neurosci Biobehav Rev 29:137-150 Groothuis TGG, Schwabl H (2008) Hormone-mediated maternal effects in birds: mechanisms matter but what do we know of them? Philos Trans R Soc Lond B 363:1647-1661 Groothuis TGG, Müller W, von Engelhardt N, Carere C, Eising C (2005) Maternal hormones as a tool to adjust offspring phenotype in avian species. Neurosci Biobehav Rev 29:329-352 Güntürkün O (2005) The avian prefrontal cortex. Curr Opin Neurobiol 15:686-693 Hamilton WD (1964) The genetical evolution of social behaviour, I and II. J Theor Biol 7:1-52
Individual performance in complex social systems
143
Healy SD, Rowe C (2007) A critique of comparative studies of brain size. Proc R Soc Lond B 274:453-464 Hemetsberger J (2001) Die Entwicklung der Grünauer Graugansschar seit 1973. [The demographic development of Konrad Lorenz’ flock of greylag geese in Grünau/Austria since 1973.] In: Kotrschal K, Müller G, Winkler H (eds) Konrad Lorenz und seine verhaltensbiologischen Konzepte aus heutiger Sicht. Filander, Fürth, pp 249-260 Hirschenhauser K, Möstl E, Kotrschal K (1999a) Within-pair testosterone covariation and reproductive output in greylag geese Anser anser. Ibis 141:577586 Hirschenhauser K, Möstl E, Kotrschal K (1999b) Seasonal patterns of sex steroids determined from feces in different social categories of greylag geese (Anser anser). Gen Comp Endocrinol 114:67-79 Hirschenhauser K, Möstl E, Wallner B, Dittami J, Kotrschal K (2000) Endocrine and behavioural responses of male greylag geese (Anser anser) to pairbond challenges during the reproductive season. Ethology 106:63-77 Hirschenhauser K, Weiß BM, Haberl W, Möstl E, Kotrschal K (2010) Female androgen patterns and within-pair testosterone compatibility in domestic geese (Anser domesticus). Gen Comp Endocrinol 165:195-203 Höglund J, Alatalo RV, Lundberg A, Rintamäki PT, Lindell J (1999) Microsatellite markers reveal the potential for kin selection on black grouse leks. Proc R Soc Lond B 266:813-816 Huber L (2002) Clever birds: keas learn through observation. Interpret Bird Bull 3:57-59 Huber L (2007) Emulation learning: the integration of technical and social cognition. In: Nehaniv CL, Dautenhahn K (eds) Imitation and Social Learning in Robots, Humans and Animals: Behavioural, Social and Communicative Dimensions. Cambridge University Press, Cambridge, pp 427-439 Huber L, Rechberger S, Taborsky M (2001) Social learning affects object exploration and manipulation in keas, Nestor notabilis. Anim Behav 62:945-954 Huber L, Gajdon GK, Federspiel I, Werdenich D (2008) Cooperation in keas: social and cognitive factors. In: Itakura S, Fujita K (eds) Origins of the Social Mind: Evolutionary and Developmental Views. Springer, Tokyo, pp 99-119 Hudec K, Rooth J (1970) Die Graugans. Westarp-Wissenschaft, Magdeburg Iwaniuk AN, Nelson JE (2003) Developmental differences are correlated with relative brain size in birds: a comparative analysis. Can J Zool 81:1913-1928 Jarvis ED, Güntürkün O, Bruce L, Csillag A, Karten H, Kuenzel W, Medina L, Paxinos G, Perkel DJ, Shimizu T, Striedter G, Wild JM, Ball GF, Dugas-Ford J, Durand SE, Hough GE, Husband S, Kubikova L, Lee DW, Mello CV, Powers A, Siang C, Smulders TV, Wada K, White SA, Yamamoto K, Yu J, Reiner A, Butler AB (2005) Avian brains and a new understanding of vertebrate brain evolution. Nat Rev Neurosci 6:151-159 Judge PG, Mullen SH (2005) Quadratic postconflict affiliation among bystanders in a hamadryas baboon group. Anim Behav 69:1345-1355
144
Kurt Kotrschal, Isabella B.R. Scheiber and Katharina Hirschenhauser
Kalmbach E, van der Aa P, Komdeur J (2005) Adoption as a gosling strategy to obtain better parental care? Experimental evidence for gosling choice and agedependency of adoption in greylag geese. Behaviour 142:1515-1533 Kappeler PM, van Schaik CP (2002) Evolution of primate social systems. Int J Primatol 23:707-740 Kear J (1990) Man and Wildfowl. Poyser, London Koolhaas JM, Korte SM, de Boer SF, van der Vegt BJ, van Reenen CG, Hopster H, de Jong IC, Ruis MA, Blokhuis HJ (1999) Coping styles in animals: current status in behavior and stress-physiology. Neurosci Biobehav Rev 23:925935 Koolhaas JM, de Boer SF, Buwalda B, van Reenen K (2007) Individual variation in coping with stress: a multidimensional approach of ultimate and proximate mechanisms. Brain Behav Evol 70:218-226 Kotrschal K, Hemetsberger J (1995) Social constraints in feeding and individual specialization for transportable food in greylag geese (Anser anser). Ökol Vögel 17:157-163 Kotrschal K, Hemetsberger J, Dittami J (1992) Vigilance in a flock of semi-tame greylag geese (Anser anser) in response to approaching eagles (Haliaeetus albicilla and Aquila chrysaetos). Wildfowl 43:215-219 Kotrschal K, Hirschenhauser K, Möstl E (1998) The relationship between social stress and dominance is seasonal in greylag geese. Anim Behav 55:171-176 Kotrschal K, Hemetsberger J, Weiß BM (2006) Making the best of a bad situation: homosociality in male greylag geese. In: Sommer V, Vasey PL (eds) Homosexual Behaviour in Animals: An Evolutionary Perspective. Cambridge University Press, Cambridge, pp 45-76 Kotrschal K, Schlögl C, Bugnyar T (2007) Lektionen von Rabenvögeln und Gänsen: Instinkt oder Verstand? Biol Unserer Zeit 37:366-374 Kotrschal K, Schöberl I, Bauer B, Thibeaut A-M, Wedl M (2009) Dyadic relationships and operational performance of male and female owners and their male dogs. Behav Proc 81:383-391 Kralj-Fiser S, Scheiber IBR, Blejec A, Möstl E, Kotrschal K (2007) Individualities in a flock of free-roaming greylag geese: behavioral and physiological consistency over time and across situations. Horm Behav 51:239-248 Krause J, Ruxton GD (2002) Living in Groups. Oxford University Press, Oxford Kruk MR, Halász J, Meelis W, Haller J (2004) Fast positive feedback between the adrenocortical stress response and a brain mechanism involved in aggressive behavior. Behav Neurosci 118:1062-1070 Lamprecht J (1986) Structure and causation of the dominance hierarchy in a flock of bar-headed Geese (Anser indicus). Behaviour 96:28-48 Lamprecht J (1987) Female reproductive strategies in barheaded geese (Anser indicus): why are geese monogamous? Behav Ecol Sociobiol 21:297-305 Lazarus J (1978) Vigilance, flock size and domain of danger size in the whitefronted goose. Wildfowl 29:135-145 Lazarus J, Inglis IR (1978) The breeding behaviour of the pink-footed goose: parental care and vigilant behaviour during the fledging period. Behaviour 65:62-88
Individual performance in complex social systems
145
Lee KA, Bahr JM (1994) Utilization of substrates for testosterone and estradiol-17 beta production by small follicles of the chicken ovary. Domest Anim Endocrinol 11:307-314 Longcope C (1986) Adrenal and gonadal androgen secretion in normal females. Clin Endocrinol Metab 15:213-228 Lorenz K (1988) Hier bin ich – wo bist Du? Ethologie der Graugans. Piper, München McEwen BS, Sapolsky RM (1995) Stress and cognitive function. Curr Opin Neurobiol 5:205-216 McEwen BS, Wingfield JC (2003) The concept of allostasis in biology and biomedicine. Horm Behav 43:2-15 McGregor PK (2005) Animal Communication Networks. Cambridge University Press, Cambridge McGregor PK, Dabelsteen T, Holland J (1997) Eavesdropping in a territorial songbird communication network: preliminary results. Bioacoustics 8:253254 McKinnon L, Gilchrist HG, Scribner KT (2006) Genetic evidence for kin-based female social structure in common eiders (Somateria mollissima). Behav Ecol 17:614-621 McNabb AFM, Scanes CG, Zeman M (1998) The endocrine system. In: Starck JM, Ricklefs RE (eds) Avian Growth and Development: Evolution within the Altricial-Precocial Spectrum. Oxford University Press, London, pp 174-202 Mendl M, Zanella AJ, Broom DM (1992) Physiological and reproductive correlates of behavioural strategies in female domestic pigs. Anim Behav 44:11071121 Moen AN (1978) Seasonal changes in heart rates, activity, metabolism and forage intake of white-tailed deer. J Wildl Manage 42:715-738 Müller EF (1982) Heart rate in slow loris (Nycticebus coucang). Daily variation, effects of ambient temperature and role of oxygen transport in blood. Folia Primatol 38:250-258 Nephew BC, Kahn SA, Romero LM (2003) Heart rate and behavior are regulated independently of corticosterone following diverse acute stressors. Gen Comp Endocrinol 133:173-180 Nilsson A, Ahman B, Norberg H, Redbo I, Eloranta E, Olsson K (2006) Activity and heart rate in semi-domesticated reindeer during adaptation to emergence feeding. Physiol Behav 88:116-123 Oliveira RF, McGregor PK, Latruffe C (1998) Know thine enemy: fighting fish gather information from observing conspecific interactions. Proc R Soc Lond B 265:1045-1049 Oliveira RF, Silva A, Canário AVM (2009) Why do winners keep winning? Androgen mediation of winner but not loser effects in cichlid fish. Proc R Soc Lond B 276:2249-2256 Packer C, Scheel D, Pusey AE (1990) Why lions form groups: food is not enough. Am Nat 136:1-19 Panksepp J (1998) Affective Neuroscience: The Foundations of Human and Animal Emotions. Oxford University Press, Oxford
146
Kurt Kotrschal, Isabella B.R. Scheiber and Katharina Hirschenhauser
Panksepp J (2005) Affective consciousness: core emotional feelings in animals and humans. Conscious Cogn 14:30-80 Peake TM, Terry AMR, McGregor PK, Dabelsteen T (2001) Male great tits eavesdrop on simulated male-to-male vocal interactions. Proc R Soc Lond B 268:1183-1187 Peake TM, Terry AMR, McGregor PK, Dabelsteen T (2002) Do great tits assess rivals by combining direct experience with information gathered by eavesdropping? Proc R Soc Lond B 269:1925-1929 Pepperberg IM (1999) The Alex Studies: Cognitive and Communicative Abilities of Grey Parrots. Harvard University Press, Cambridge/MA Petrie M, Krupa A, Burke T (1999) Peacocks lek with relatives even in the absence of social environmental cues. Nature 401:155-157 Pfeffer K, Fritz J, Kotrschal K (2002) Hormonal correlates of being an innovative greylag goose, Anser anser. Anim Behav 63:687-695 Pirtney SB, MacColl ADC, Lambin X, Moss R, Dallas JF (1999) Spatial distribution of genetic relatedness in a moorland population of red grouse (Lagopus lagopus scoticus). Biol J Linn Soc 68:317-331 Prior H, Schwarz A, Güntürkün O (2008) Mirror-induced behavior in the magpie (Pica pica): evidence of self-recognition. PLoS Biol 6:e202, doi:10.1371/ journal.pbio.0060202 Raby CR, Alexis DM, Dickinson A, Clayton NS (2007) Planning for the future by western scrub-jays. Nature 445:919-921 Radesäter T (1974) On the ontogeny of orienting movements in the triumph ceremony of two species of geese (Anser anser L. and Branta canadensis L.). Behaviour 50:1-15 Regehr HM, Smith CM, Arquilla B, Cooke F (2001) Post-fledging broods of migratory Harlequin ducks accompany females to wintering areas. Condor 103:408-412 Rodríguez-Maldonado E, Velázquez PN, Juárez-Oropeza MA, Pedernera E (1996) Steroid metabolism in theca externa cells from preovulatory follicles of domestic hen (Gallus domesticus). Gen Comp Endocrinol 101:173-179 Roemer I, Reik W, Dean W, Klose J (1997) Epigenetic inheritance in the mouse. Curr Biol 7:277-80 Rutschke E (1982) Stability and dynamics in the social structure of the greylag goose (Anser anser L.). Aquila 89:39-55 Rutschke E (1997) Wildgänse. Lebensweise, Schutz, Nutzung. Parey, Berlin Saino N, Ferrari R, Romano M, Martinelli R, Møller AP (2003) Experimental manipulation of egg carotenoids affects immunity of barn swallow nestlings. Proc R Soc Lond B 270:2485-2489 Sapolsky RM (1992) Neuroendocrinology of the stress response. In: Becker S, Breedlove SM, Crews D (eds) Behavioral Endocrinology. MIT Press, Cambridge/MA, pp 287-324 Sapolsky RM (1993) Endocrinology alfresco: psychoendocrine studies of wild baboons. Recent Prog Horm Res 48:437-468
Individual performance in complex social systems
147
Sapolsky RM (2002) Endocrinology of the stress response. In: Becker JB, Breedlove SM, Crews D, McCathy MM (eds) Behavioral Endocrinology, 2nd edn. MIT Press, Cambridge/MA, pp 409-450 Sapolsky RM, Romero LM, Munck AU (2000) How do glucocorticoids influence stress responses? Integrating permissive, suppressive, stimulatory, and preparative actions. Endocr Rev 21:55-89 Scheiber IBR, Weiß BM (submitted) ‘Girls united’: spatial proximity among adult female lineal kin in greylag geese (Anser anser). Scheiber IBR, Weiß BM, Frigerio D, Kotrschal K (2005a) Active and passive social support in families of greylag geese (Anser anser). Behaviour 142:15351557 Scheiber IBR, Kralj S, Kotrschal K (2005b) Sampling effort/frequency necessary to infer individual acute stress responses from fecal analysis in greylag geese (Anser anser). Ann NY Acad Sci 1046:154-167 Scheiber IBR, Wascher CAF, Kotrschal K (2006) Biparental care in greylag geese: heart rate as a measure of parental contribution. J Ornithol 147:245-246 Scheiber IBR, Weiß BM, Hirschenhauser K, Wascher CAF, Nedelcu IT, Kotrschal K (2008) Does ‘relationship intelligence’ make big brains in birds? Open Biol J 1:6-8 Scheiber IBR, Kotrschal K, Weiß BM (2009a) Benefits of family reunions: social support in secondary greylag goose families. Horm Behav 55:133-138 Scheiber IBR, Kotrschal K, Weiß BM (2009b) Serial agonistic attacks by greylag goose families (Anser anser) against the same opponent. Anim Behav 77:1211-1216 Schloegl C, Dierks A, Gajdon GK, Huber L, Kotrschal K, Bugnyar T (2009) What you see is what you get? Exclusion performances in ravens and keas. PLoS ONE 4:e6368, doi:10.1371/journal.pone.0006368 Schwabl H, Mock DW, Gieg JA (1997) A hormonal mechanism for parental favouritism. Nature 386:231 Shorey L, Pirtney SB, Stone J, Höglund J (2000) Fine-scale genetic structuring on Manacus manacus leks. Nature 408:352-353 Sih A, Bell AM, Johnson JC, Ziemba RE (2004) Behavioral syndromes: an integrative overview. Q Rev Biol 79:241-277 Silk JB, Alberts SC, Altmann J (2003) Social bonds of female baboons enhance infant survival. Science 302:1231-1234 Silk JB, Beehner JC, Bergman, Crockford C, Engh AL, Moscovice LR, Wittig RM, Seyfarth RM, Cheney DL (2009) The benefits of social capital: close social bonds among female baboons enhance offspring survival. Proc R Soc Lond B 276:3099-3104 Summers CH (2002) Social interactions over time, implications for stress responsiveness. Integr Comp Biol 42:591-599 Swoboda R, Kotrschal K, Scheiber IBR (submitted) Ontogenetic changes of agonistic behaviour and physiology in greylag goose families. Tinbergen N (1963) On aims and methods of ethology. Z Tierpsychol 20:410-433 van der Jeugd HP, van der Veen IT, Larsson K (2002) Kin clustering in barnacle geese: familiarity or phenotype matching? Behav Ecol 13:786-790
148
Kurt Kotrschal, Isabella B.R. Scheiber and Katharina Hirschenhauser
von Holst D (1998) The concept of stress and its relevance for animal behavior. Adv Stud Behav 27:1-131 Waldeck P, Andersson M, Kilpi M, Öst M (2008) Spatial relatedness and brood parasitism in a female-philopatric bird population. Behav Ecol 19:67-73 Wascher CAF, Arnold W, Kotrschal K (2008a) Heart rate modulation by social contexts in greylag geese (Anser anser). J Comp Psychol 122:100-107 Wascher CAF, Scheiber IBR, Kotrschal K (2008b) Heart rate modulation in bystanding geese watching social and non-social events. Proc R Soc Lond B 275:1653-1659 Wascher CAF, Scheiber IBR, Weiß BM, Kotrschal K (2009) Heart rate responses to agonistic interactions in greylag geese, Anser anser. Anim Behav 77:955961 Waser PM, Jones WT (1983) Natal philopatry among solitary mammals. Q Rev Biol 58:355-390 Weigmann C, Lamprecht J (1991) Intraspecific nest parasitism in bar-headed geese, Anser indicus. Anim Behav 41:677-688 Weiß BM, Kotrschal K (2004) Effects of passive social support inn juvenile greylag geese (Anser anser): a study from fledging to adulthood. Ethology 110:429-444 Weiß BM, Kotrschal K, Frigerio D, Hemetsberger J, Scheiber IBR (2008) Birds of a feather stay together: extended family bonds and social support in greylag geese (Anser anser). In: Columbus F (ed) Family Relations: Behavioral, Psychological and Sociological Aspects. Nove Science Publishers, New York, pp 69-88 Weiß BM, Kehmeier S, Mikolasch S, Schlögl C (2009) Transitive inference in greylag geese. Primate Rep (special issue, february):38 Weiß BM, Kotrschal K, Möstl E, Hirschenhauser K (2010) Social and life history correlates of hormonal partner compatibility in greylag geese (Anser anser). Behav Ecol 21:138-143 Whiten A, Byrne RW (1997) Machiavellian Intelligence. II. Extensions and Evaluations. Cambridge University Press, Cambridge Wieser W (1986) Bioenergetik. Energietransformation bei Organismen. Thieme Verlag, Stuttgart Wilson EO (1975) Sociobiology: The New Synthesis. Harvard University Press, Cambridge/MA Wingfield JC, Hegner RF, Dufty AM Jr, Ball GF (1990) The ‘challenge hypothesis’: theoretical implications for patterns of testosterone secretion, mating systems, and breeding strategies. Am Nat 136:829-846 Wingfield JC, Lynn SE, Soma KK (2001) Avoiding the ‘costs’ of testosterone: ecological bases of hormone-behavior interactions. Brain Behav Evol 57:239251 Zahavi A, Zahavi A (1997) The Handicap Principle: A Missing Piece of Darwin’s Puzzle. Oxford University Press, New York
Part II Conflict and cooperation
Chapter 6
Conflict and conflict resolution in social insects JÜRGEN HEINZE
ABSTRACT The major transitions in evolution are characterised by cooperation and division of labour among biological entities. Such transitions have led to the evolution of complex genomes from independent oligonucleotides, of eukaryotic cells from independent prokaryotes and proto-eukaryotes, of multicellular organisms from multiple cells, and of complex animal societies from individuals. For higher-level entities to function as a unit and to compete with other such higher-level entities it is fundamental that withingroup conflict among its constituents is resolved. Indeed, selfishness by lower-level entities, e.g., genes, organelles, and cells, appears to be prevented or at least minimized by higher-level mechanisms. Insect societies have often been regarded as harmonious superorganisms, in which all individuals cooperate to increase the reproductive output of the society as a whole. Recent research on social insects has revealed the occurrence of similar conflict of interest among group members, however. For example, individual workers may have selfish interests concerning the origin of male offspring, which go against the interests of other workers and the whole society. Theoretical and empirical studies suggest that many insect societies are structured by a fine-tuned balance between the interests of individuals and the group, and that this balance is maintained by a complex system of behavioural mechanisms, including mutual surveillance, policing, and punishment. The aims of this chapter are to review the various conflicts of interest that may occur in social insects, in particular ants, as well as the behavioural and chemical mechanisms by which conflict is resolved. Furthermore, I will summarise our recent understanding of insect societies as governed by kin selected, ‘enforced altruism’.
152
Jürgen Heinze
Table 6.1 Major types of conflict in the societies of ants, bees, and wasps.
1
Antagonists
Subject of conflict
Predicted outcome
Observed outcome
Queens ↔ workers
Sex allocation ratio
Under worker control: higher female-bias at low queen numbers and queen mating frequencies; under queen control: equal investment in both sexes
Variable: evidence for pure queen, pure worker and mixed control in different species
Queens ↔ workers
Origin of males
From relatedness alone: worker reproduction in monogynous, monandrous societies; queen reproduction in polygynous, polyandrous societies
Usually queen monopoly
Worker ↔ worker
Origin of males in queenless colonies
Workers strive for producing own sons
In small colonies: formation of hierarchies, top-ranking workers lay eggs
Queen ↔ queen
Partitioning of reproduction
Reproductive skew varies with relatedness, probability of successful dispersal and other factors
High skew in a minority of specialists inhabiting patchy habitats; variation in relatedness relatively unimportant
Queen ↔ queen
Production of sexuals under lethal local mate competition
Queens aim at increasing their own fitness by producing males earlier and in larger numbers
Queens in polygynous colonies of Cardiocondyla sp. produce males earlier than queens in monogynous colonies1; sex ratio less female-biased in polygynous colonies
Larvae ↔ adults
Caste differentiation
More female larvae strive to develop into sexuals than is optimal for colony as a whole
Workers control caste fate and kill surplus queens in stingless bees
Different genetic lineages
Production of sexuals
Workers prefer sexuals of their own genetic lineage
Evidence for nepotistic queen rearing only in Formica ants2
Male ↔ male
Access to female sexuals
Yamauchi et al. (2006), 2Hannonen and Sundström (2003)
Male fighting in a few ant genera with local mating
Conflict and conflict resolution in social insects
153
6.1 Conflict and cooperation in insect societies Ants, bees, and wasps have long fascinated mankind, and their societies have been idealized since Biblical times as models of virtue and perfect social organisation, where all leadership belongs to females, where everyone abides by the law, and where all cooperate harmoniously for the common good of the society (e.g., Drouin 2005). However, the conception of life in insect societies has shifted over time, following general trends and fashions of science, and our contemporary understanding of what is going on inside a bee hive or an ant mound is quite different from the image of noble communitarianism commonly praised in the 19th and early 20th century (Sleigh 2007). The acceptance of insect societies as supra-individual biological units (‘superorganisms’) has waxed and waned over the last century, and, although colony-level phenomena have never lost their attraction for researchers, the last few decades have been characterised by an increasing interest in conflict among selfish individuals and how these disruptive forces are counterbalanced by mutual manipulation and policing: the superorganism as a police state (Whitfield 2002; Table 6.1). The amount of theoretical and empirical data on potential and actual conflict within insect societies makes it difficult to summarise all that is known on a few pages. In this chapter I can therefore not provide a complete summary of conflict and conflict resolution in social insects; instead, focusing on ants, I will summarise our current understanding of a few important types of conflict involving queens and workers. Other types of conflict, e.g., potential nepotism in the rearing of female sexuals in societies with multiple queens, conflict concerning caste determination between female larvae and adult workers, and conflict involving males, have been reviewed elsewhere (e.g., Heinze 2004, Ratnieks et al. 2006).
6.2 Levels of selection and conflict resolution Cooperation is a powerful driving force in evolution and has repeatedly facilitated the formation of new levels of complexity in the hierarchy of biological organisation. Many biological units have evolved through the grouping together of simpler units, be it in the formation of chromosomes through the assembly of independently replicating oligonucleotides, the evolution of the eukaryotic cell through endosymbiotic associations, and the origin of multicellularity through cooperation among individual cells that failed to separate after division. In these ‘major transitions in evolution’ (Maynard Smith and Szathmáry 1995), lower-level units often be-
154
Jürgen Heinze
come specialised for complementary tasks and forego their autonomous reproduction. This may result in the emergence of new properties and the creation of new levels of selection. Rather than competing for resources to reproduce autonomously, the constituents of higher-order units may form a community of interest, which interacts as a single individual with the environment and competes with other such higher-order units (Michod 1996). The benefits from cooperation do not preclude the existence of selfishness in lower-level units, which may strive to achieve short-term benefits from overexploiting the common pool of resources. This results in the well known ‘tragedy of the commons’, as in the long run selfishness may damage the integrity of the higher-level unit and, hence, also the selfish lowerlevel units themselves (Hardin 1968, Rankin et al. 2007). For example, mobile, repetitive nucleotide sequences, such as transposons and retrotransposons, may replicate independently and increase the number of sequence copies at the cost of the efficiency of the entire genome; defective, but fast replicating mitochondria, such as the ‘petite’ mutant of yeast, may accumulate and reduce the fitness of the whole cell; and selfish genetic cell lineages, such as tumours and cancers, have well-known detrimental effects for the whole organism (e.g., Burt and Trivers 2006). The evolution of individuality of higher level units requires that between-unit selection overrides within-unit selection and that within-unit conflict must be suppressed. Cellular and genetic mechanisms, such as DNA methylation, RNA interference, unicellular inheritance of organelles, single cell stages in early development, and tumor suppression genes, have been interpreted as defense mechanisms, through which higher-level entities punish or prevent harmful selfishness by genes, organelles, and cells (Maynard Smith and Szathmàry 1995, Michod 1996, Leigh 1999). For example, the mechanisms of a fair meiosis usually guarantee that homologue alleles have an equal chance of being transmitted into a gamete, which to some extent prevents selfishness. Similarly, uniparental inheritance helps to avoid costly conflict among genetically distinct lineages of organelles within the host (Burt and Trivers 2006). Social insects (bees, wasps, ants, and termites) are the classic examples for yet another major transition – from solitary animals to ‘eusociality’ (defined as a life history with cooperative brood care, overlapping generations, and reproductive division of labour: Wilson 1971). In insect societies, queens (and, in termites, kings) specialise in reproduction, whereas workers engage in brood care, foraging, nest defense, and nest maintenance. Reproductive division of labour allows the evolution of striking group-level adaptations, such as fungus cultivation, aphid farming, optimised trails free of traffic congestion, and perfectly tempered bee hives. This specialisation is certainly one of the causes of the unrivaled ecologi-
Conflict and conflict resolution in social insects
155
cal and evolutionary success of social insects (Wilson 1971, Seeley 1985, Moritz and Southwick 1992, Hölldobler and Wilson 1990, 2009). Reproductive division of labour requires close collaboration among nestmates, and any disharmony may threaten the success of the group as a whole. Nevertheless, the societies of social Hymenoptera are not less conflictridden than other higher-level units. Instead, their organisation reflects a fine-tuned balance between the interests of individual group members and the society as a whole. Due to efficient mechanisms of conflict prevention and resolution, potential conflict rarely breaks open and actual conflict with violent antennation, biting, or stinging can be observed only under special conditions (Ratnieks 1988, Heinze et al. 1994, Bourke 1999, Heinze 2004, Ratnieks et al. 2006). Some of these conflicts resemble those well known from other group-living animals and concern the partitioning of reproductive rights. They arise, for example, when multiple potential egg layers co-occur in a society and fight for reproductive dominance. In addition, the unusual genetic family structure of social Hymenoptera resulting from haplodiploid sex determination (males develop from unfertilised eggs and are haploid, females develop from fertilised eggs and are diploid) introduces additional types of conflict, which are absent from diploid animals: queen-worker conflict about sex allocation and queen-worker conflict about the origin of males.
6.3 Kin selection explains both conflict and cooperation in social animals Most researchers agree that inclusive fitness theory (Hamilton 1964a) provides the best explanation for the evolution of eusociality. Through foregoing reproduction and helping relatives to produce and raise extra offspring, workers indirectly increase their inclusive fitness, because the offspring of relatives carry the helper’s genes in copies that are identical by descent. If the total offspring produced exclusively through the helper’s efforts carry more copies of the helper’s genes than would have been present in all of the helper’s own young, helping can be favoured. Hamilton (1964a) formalised this model in his famous inequality rB > C, where B represents the benefits of helping (the extra offspring the beneficiary of the help produces only because of the assistance provided by the helper) and C the costs of helping (i.e., the helper’s offspring not produced because of helping). r is the coefficient of relatedness, i.e., the probability of the alleles at a randomly chosen locus in helper and recipient being identical by descent from a common ancestor. The inclusive fitness of a helper then consists of its di-
156
Jürgen Heinze
rect fitness, i.e., its personal reproductive success excluding all effects of its social environment, plus the indirect fitness it gains through the surplus offspring produced by the beneficiary of the help, weighted by the coefficient of relatedness between helper and beneficiary. This looks like a simple summation, but measuring inclusive fitness in practice can be rather tricky (e.g., Queller 1996, West et al. 2007a). Kinship (r) is of critical importance in inclusive fitness theory, which is therefore often referred to as ‘kin selection theory’. It must not be forgotten, however, that inclusive fitness theory ascribes equally prominent roles to ecological and behavioural costs and benefits. Kinship among two individuals can be quantified relatively easily from pedigrees or with population genetic methods by determining the genetic similarity between two individuals relative to that between two randomly drawn individuals from a carefully chosen reference population (e.g., Queller 1994). In contrast, B and C are notoriously difficult to determine. Several authors have therefore negated the usefulness of inclusive fitness theory and advanced alternative approaches (Wilson 2005, 2008, Wilson and Hölldobler 2005, Wilson and Wilson 2007). One of these alternatives is multilevel selection theory, in which selection is partitioned in within-group and between-group components. Kin and multilevel selection are mathematically congruent and essentially two sides of the same coin (e.g., Queller 1992a,b, Korb and Heinze 2004, Foster et al. 2006, Lehmann et al. 2007, West et al. 2007b, Hölldobler and Wilson 2009), as evident from Price’s covariance method for the hierarchical analysis of natural selection (Price 1970). The ongoing discussion about how the evolution of altruism and eusociality is explained best therefore boils down to the semantic issue about which term is more appropriate. The recurrent outbreak of debate about the adequacy of inclusive fitness theory is probably kindled in part by longstanding misinterpretations of the role of haplodiploidy in the evolution of eusociality (Dawkins 1979, Foster et al. 2006). Several independent evolutionary origins of eusociality exist within the Hymenoptera, an insect order characterised by haplodiploid sex determination. Haplodiploidy creates special degrees of relatedness (Table 6.2), which were thought to facilitate the evolution of eusociality: females are more closely related to their sisters than to their own offspring and therefore appear to achieve higher fitness gains from helping their mothers to produce additional sisters than by producing own daughters (Hamilton 1964b). This simple conclusion quickly turned out to be wrong, because the disproportionally low relatedness of females to their brothers counterbalances the disproportionately high fitness gains arising from the close relatedness among sisters (e.g., Bourke and Franks 1995, Crozier and Pamilo 1996). In any case, the recent rejection of inclusive fitness theory because
Conflict and conflict resolution in social insects
157
Table 6.2 Life-for-life relatedness (regression relatedness multiplied by the sexspecific reproductive values of individuals, i.e., 1 for females, 0.5 for males) of a Hymenopteran female to its relatives.
Life-for-life relatedness of a Hymenopteran female to its Mother
0.5
Daughter
0.5
Sister
0.75
Half-sister
0.25
Son
0.5
Brother
0.25
Nephew
0.375
Half-nephew
0.125
not all haplodiploids are eusocial and not all eusocial species are haplodiploid is wrong for two reasons. First, it does not necessarily follow from the observation that a certain trait promotes the evolution of eusociality that all organisms exhibiting this trait are inevitably eusocial. Second, and more importantly, kin selection does not rely on haplodiploidy but works whenever the genotypes of helper and beneficiary are statistically associated, so that Hamilton’s rule is satisfied. Male haploidy might promote the evolution of eusociality in other ways, e.g., through facilitating the spread of mutations causing maternal care and reproductive altruism (Linksvayer and Wade 2005, Teyssèdre et al. 2006). Nevertheless, the multiple evolutions of sterile workers in the Hymenoptera presumably relies also on those ecological and behavioural traits that are believed to underlie the evolution of eusociality in termites and molerats: the commonness of brood care and stable nest sites in solitary ancestors (e.g., Bourke and Franks 1995, Korb and Heinze 2008). Furthermore, the sting of aculeate Hymenoptera is a potent weapon for brood defense and may additionally favour group living in that helping becomes easier (e.g., Starr 1985). Finally, the unusual life-long monogamy, characteristic of all social insects, might have been a fundamental pre-adaptation in the evolution of altruistic worker castes, because it stabilises the relatedness of helpers to the brood and cost-benefit ratios (Boomsma 2007).
158
Jürgen Heinze
6.4 Haplodiploidy and queen-worker conflict about sex allocation Inclusive fitness theory predicts that haplodiploidy creates a conflict between queens and workers about how much resources are invested in female vs. male sexuals (sex allocation ratio; e.g., Trivers and Hare 1976, Mehdiabadi et al. 2003). Because of the relatedness asymmetries resulting from haplodiploidy, workers in a colony with a single, singly-mated queen (monogyny, monandry) can maximize their inclusive fitness by allocating three times more resources to female sexuals than to males. The ‘fitness return’ workers receive from both sexes, given by a worker’s life-for-life relatedness (see glossary) to a sexual, multiplied by the relative mating success of its sex, will then be equal end evolutionarily stable (e.g., Bourke and Franks 1995, Crozier and Pamilo 1996). In contrast, queens are equally related to their male and female offspring (Table 6.2) and gain most from a balanced sex ratio. The resulting conflict about sex allocation may be less pronounced when colonies contain multiple, related queens (polygyny) or a multiply mated queen (polyandry). For example, when a queen mates multiply, some of the female sexuals will be sisters of a given worker and others will be its halfsisters. While the relatedness of the worker to its brothers remains unchanged, its average relatedness to female sexuals will decrease with increasing queen mating frequency and approach the relatedness to brothers. Queen-worker conflict about sex allocation ratios therefore may vanish at high mating frequencies (Table 6.2). When queen number and mating frequency vary among colonies of a population, workers may be selected to rear either only male or female sexuals, depending on the genetic structure of their own colony relative to the average colony structure in the population, which leads to ‘split sex ratios’ (Boomsma and Grafen 1990, Ratnieks and Boomsma 1997). For example, workers will benefit from the exclusive production of males, if their colony has an aboveaverage number of queens. Note that this does not require that workers have information on the average colony structure in the population. Instead, selection will optimise the response of workers to the structure of their own colony over time. Data summarised in the seminal paper by Trivers and Hare (1976) and many subsequent studies in the heydays of sex ratio research suggested worker control of sex ratios, particularly in ants, and thus provided powerful evidence for the importance of inclusive fitness and kin selection in social evolution. Workers have been shown to manipulate the primary sex ratio produced by the queen by selective culling of male brood (Sundström
Conflict and conflict resolution in social insects
159
et al. 1996) or overfeeding of female larvae so that a larger proportion grows into female sexuals (Hammond et al. 2002). During the last years, however, the accumulation of new data has considerably blurred this previously clear picture. Overall, variation in relatedness asymmetry and queen number has been found to explain only 21% of the variance in sex allocation ratios (Meunier et al. 2008). Worker control therefore appears to be far from complete and a variety of factors other than relatedness may introduce considerable noise in sex allocation (Kümmerli and Keller 2009). These include ecological parameters and physiological or behavioural tactics of the queens. For example, female sexuals are more costly and colonies endowed with fewer resources might therefore concentrate on the production of the cheaper males (Nonacs 1986, Deslippe and Savolainen 1995); queens may force workers to rear male-biased broods simply by limiting the number of fertilised eggs they lay (Passera et al. 2001); ongoing tugs-of-war between queens and workers may result in sex ratios intermediate between the optima of both castes (Reuter and Keller 2001); and sex ratios may be affected by queen age (Schwander et al. 2008). In addition, dispersal and colony founding tactics (e.g., solitary founding vs. colony fragmentation, local resource competition, Bourke and Franks 1995) and local mate competition (Hamilton 1967) strongly influence the production of sexuals. Local resource competition is common, wherever female sexuals show limited dispersal and compete for care by workers, food, or nest sites at or around the maternal nest (e.g., Pearcy and Aron 2006). When brothers compete locally for mating opportunities, mother queens in monogynous societies are predicted to produce just the number of males that guarantees that all their daughters are inseminated, resulting in a highly female-biased sex ratio. If multiple queens contribute to the brood, sex ratios are expected to be more balanced, as each queen will be selected to increase its chances of propagating copies of its genes also via its sons. Local mating in the nest and local mate competition, culminating in lethal combat among wingless males for access to female sexuals, have recently been documented in a few taxa of social Hymenoptera (BOX 6.1). Despite all this theoretical and empirical work, one fundamental aspect of sex ratio optimisation has attracted surprisingly little attention. The adaptive evolution of sex allocation ratios requires genetic variation in this trait. Because of the long lifespan of many social insects it is often difficult to obtain data on lifetime reproductive success. The heritability of sex ratios has therefore rarely been studied. Nevertheless, cross-breeding studies in the ant Cardiocondyla kagutsuchi indicate that heritable variation occurs (Frohschammer and Heinze 2009), which, though needed for adaptive evo-
160
Jürgen Heinze
BOX 6.1 Lethal male fighting in Cardiocondyla The genus Cardiocondyla is characterised by wingless males, which engage in lethal fighting for the monopolisation of matings with the female sexuals produced within a colony. According to local mate competition theory, mother queens in monogynous nests are predicted to produce only the number of males needed to inseminate all daughters. In contrast, in polygynous nests, queens are selected to raise the percentage of sons among their offspring to increase the chance that one of their own sons survives competition for mating. The number of fighter males among the first 20 sexuals produced was indeed significantly lower in single-queen than two-queen colonies of Cardiocondyla obscurior (mean 5.3 vs. 9.8). Colonies also produced a higher proportion of fighter males when eggs from alien polygynous colonies were added to focal monogynous colonies, but not when eggs from alien monogynous colonies were added. This outcome suggests that workers do not manipulate sex ratios, but that queens react to the presence of other queens by increasing the proportion of unfertilised eggs (Cremer and Heinze 2002). This interpretation could be confirmed through direct analysis of the ploidy of freshly laid eggs by fluorescence in situ hybridization (de Menten et al. 2005).
Fig. 6.1 Two wingless males of the ant Cardiocondyla obscurior locked in lethal combat about access to female sexuals (photo © Sylvia Cremer)
Conflict and conflict resolution in social insects
161
lution, might momentarily constrain the power of queens and workers to bias sex allocation.
6.5 Conflict about the origin of males The second fundamental conflict arising from haplodiploidy concerns the origin of males. Workers of most species of social Hymenoptera cannot mate and lack a spermatheca for the storage of sperm (e.g., Bourke and Franks 1995). Nevertheless, they usually have ovaries and can in principle produce haploid males from unfertilised eggs. Due to haplodiploidy, workers are more closely related to their own sons than to their brothers. In addition, in a monogynous, monandrous society they are even more closely related to the sons of other workers, i.e., their nephews, than to their brothers (Table 6.2). On the one hand, selection acting on the workers therefore favours the production of males by workers. On the other hand, the queen, being more closely related to her own sons than to her grandsons, is selected to prevent worker reproduction. As with the conflict about sex allocation, multiple mating and the presence of multiple queens change the average relatedness of workers to the male offspring of other workers and the queens in such a way that workers may oppose worker egg laying. For example, if a queen uses equal amounts of sperm from two males to fertilise her eggs (effective queen mating frequency me = 2), the work force will consist of sisters and halfsisters. The relatedness of workers to average worker-produced males will then be 1/2 (0.125 + 0.375) = 0.25 (Table 6.2). With increasing effective mating frequencies relatedness decreases towards 0.125 and workers will finally be more closely related to their brothers than to other worker-produced males. Queens might be capable of suppressing worker reproduction by aggression and eating their eggs if colonies are very small (e.g., Franks and Scovell 1983, Nakata and Tsuji 1996, Wenseleers et al. 2005), but physical queen control will break down in societies with hundreds or thousands of workers. In such colonies, the predictions from relatedness alone seem clear: males are expected to be the workers’ offspring in monogynous, monandrous societies and, if worker policing occurs, queen offspring in polygynous or polyandrous societies. Indeed, the proportion of males produced by workers in the Saxon wasp, Dolichovespula saxonica, was associated with queen mating frequency (Foster and Ratnieks 2000), but whether the prediction holds more generally for social insects is a contentious matter (Hammond and Keller 2004, Heinze 2004, 2008, Wenseleers and Ratnieks 2006a).
162
Jürgen Heinze
Maternity analyses using genetic markers, such as microsatellites, revealed that in most cases males are (almost) exclusively offspring of the queen, regardless of queen number and mating frequency. Significant worker reproduction appears to occur only in a minority of taxa and here again independent of genetic colony structure (e.g., Helanterä and Sundström 2007). As in the case of sex allocation, the exact values of relatedness are therefore probably less important in the regulation of who produces males than expected from theory. Instead, the rarity of worker reproduction might indicate that selfish egg laying is associated with high costs (Ratnieks 1988, Cole 1986). Indeed, egg laying workers do not forage or defend the nest, engage less in brood care, and, because each is most closely related to its own offspring, might waste energy in prolonged dominance interactions for egg laying rights with their nestmates (Gobin et al. 2003, Hartmann et al. 2003; see Sect. 6.6). Furthermore, workers, in particular in species with a pronounced caste polymorphism, have less ovarioles and a smaller abdomen than queens and can therefore only lay a few eggs. On the whole, worker egg laying thus reduces the total output of the colony in several ways, thereby also reducing the average inclusive fitness of workers. This reduction will be even more pronounced when workers are less closely related to an average worker-produced male than that to an average queen-produced male, i.e., in polygynous and / or polyandrous societies, but it appears to be large enough to prevent worker reproduction even in most monogynous and monandrous species (Hammond and Keller 2004, Heinze 2004). But still: each individual worker gains most from laying its own eggs, even though this might decrease the inclusive fitness of everybody else. The interest of the summed individuals therefore conflicts with the sum of the interests of the individuals – a clear entomological exemplification of Rousseau’s contrast between volonté générale and volonté de tous. What keeps individual workers from being selfish? This tragedy of the commons is resolved through ‘worker policing’, a phenomenon first observed in honey bees, but since then reported from a large number of wasps and ants. When a honey bee worker lays a haploid egg into an empty cell on the comb of a queenright colony, other workers quickly destroy and eat the egg (Ratnieks and Visscher 1989) and also attack the egg layer (Visscher and Dukas 1995). As worker egg laying is usually a rare event, and policing is therefore difficult to study in natural colonies, researchers have split insect colonies into two halves, one with a queen and the other without, and re-united the fragments after a worker had become reproductive in the queenless part. After reunification, workers that have become reproductive are fiercely attacked, expelled from the nest and even killed by their nestmates, both from the queenless and the queenright colony parts (e.g.,
Conflict and conflict resolution in social insects
163
Monnin and Peeters 1997, Kikuta and Tsuji 1999, Gobin et al. 1999, Liebig et al. 1999, Monnin and Ratnieks 2001, Hartmann et al. 2003). Similarly, the introduction of worker-laid, but not of queen-laid eggs results in egg eating (Foster et al. 2002, D’Ettorre et al. 2004). It appears that the threat of being policed in the presence of a queen is often enough to prevent workers from laying eggs. This ‘self-restraint’ probably explains why worker egg laying is rare despite of the lack of constant aggression among workers (Ratnieks 1988) The recognition of reproductives relies on particular odour cues, presumably hydrocarbons on the workers’ cuticle, which are believed to signal fertility. Non-reproductive workers and reproductive queens differ significantly in their hydrocarbon bouquets. Whereas such ‘queen pheromones’ were long regarded as inhibitive substances, through which queens suppress worker reproduction, they are now commonly understood as honest signals, through which queens reliably signal their fertility to the workers (Keller and Nonacs 1993). The odour of workers, which have recently begun to lay eggs in a policing experiment, first resembles the scent of non-reproductives but approaches that of the queen with increasing fecundity (Monnin 2006, Heinze and D’Ettorre 2009). Workers appear to police new reproductives as long as they are not yet fully fertile and differ in scent from the old reproductive, but the odour of new reproductives, which have laid eggs for several weeks, may be indistinguishable from that of an old reproductive. After reunification, such established new reproductives are often not policed by the workers, but instead old and new reproductives may fight and besmear each other with substances, which elicit aggression from other workers (e.g., Heinze et al. 1998, Monnin et al. 2002, Hartmann et al. 2005). Chemical marking of rivals has been referred to as ‘punishment’ and is considered to be different from policing, because it permanently prevents selfish behaviour – the selfish individual may be attacked and killed. Policing, e.g., through egg eating, usually prevents selfishness only temporarily (Monnin and Ratnieks 2001). The concepts of policing and punishment widely overlap with a third type of aggression among group members: dominance (Monnin and Ratnieks 2001, Frank 2003; see Sect. 6.6). Through policing, individuals repress competition among group members, increase group cohesion, and achieve indirect fitness gains. In contrast, the winners of dominance interactions increase their own potential direct fitness at the cost of other group members (Monnin and Ratnieks 2001). Recent observations show that aggression may occasionally serve both purposes. Workers are not equally likely to engage in policing (Frank 1996, van Zweden et al. 2007). Rather, the policing elite consist of those workers that are most likely to inherit the top rank in the hierarchy when the reproductive is removed. Policing there-
164
Jürgen Heinze
BOX 6.2 Dominance and policing in the ant Temnothorax unifasciatus Societies of the ant Temnothorax unifasciatus usually contain only a few dozen workers and a single, singly-mated queen. When colonies are split into two fragments, workers in the queenless part form dominance hierarchies by aggressive antennation and biting, and one or a few workers begin to lay eggs. When the two fragments are later reunited, reproductive workers are attacked both by individuals from the former queenless and the former queenright parts (worker policing). Aggression leads to the expulsion of reproductive workers or at least causes them to stop laying eggs. This consequence can directly be shown by providing workers in the queenless fragment with food stained with fat soluble dyes, which are incorporated into their eggs. By removing the queen from the reunited colony, it was shown that those workers, which were most active in policing reproductive workers after reunification, tended to become dominant and started laying eggs themselves. Policing therefore has a selfish component (Stroeymeyt et al. 2007). Becoming dominant is associated with a change in the bouquet of cuticular hydrocarbons. Queens and fertile workers are characterised by significantly higher abundances of heptacosane and nonacosane than nonlaying workers, but whether these linear alkanes serve as fertility signals needs to be shown (Brunner et al. 2009).
Fig. 6.2 Dominance interaction between two Temnothorax unifasciatus workers. Both workers are individually marked with loops of thin copper wire (photo © Bartosz Walter).
Conflict and conflict resolution in social insects
165
fore has a selfish component: by eliminating egg laying rivals, police workers at the same time fight for dominance and increase their present indirect fitness and their future direct fitness (Saigo and Tsuchida 2004, Wenseleers et al. 2005, Stroeymeyt et al. 2007; BOX 6.2). Worker policing is thus an adaptation on the level of the individual, rather than a group adaptation (Gardner and Grafen 2009).
6.6 Fighting for dominance: workers vs. workers, queens vs. queens In colonies without mated reproductives, workers may produce male or, in a few species with thelytokous parthenogenesis, female offspring from unfertilised eggs. Usually only a minority of the workers becomes reproductive while the other workers continue to engage in non-reproductive tasks. Division of reproductive labour appears to be associated with age, e.g., in the thelytokous Cape honey bee and the thelytokous ant Pristomyrmex punctatus (Crewe 1988), and is maintained by pheromones that presumably signal fecundity (Monnin 2006, Heinze and D’Ettorre 2009). Workers of many species with smaller colonies engage in dominance interactions after their colonies have lost their reproductives or when the worker hierarchy is disturbed, as in the policing experiments described above. Aggression reveals the existence of linear or near-linear hierarchies, in which the highest ranking workers later begin to lay eggs, whereas the low-ranking ones continue with the daily duties in the nest (e.g., Trunzer et al. 1999). In species with a limited caste dimorphism, such as queenless ants (see below) and wasps, dominance relations among workers may be clearly visible even in the presence of an egg layer (e.g., Ito and Higashi 1991, Deshpande et al. 2006). In contrast, the aggressive establishment and maintenance of rank orders in queenright colonies of highly eusocial insects might be selected against, because they are costly (Gobin et al. 2003) and disrupt the division of labour within the colony (Cole 1986). Nevertheless, careful observations allow predicting which worker will become dominant after orphaning. This suggests that rank relationships based on more subtle interactions already exist in the presence of the queen. For example, future dominants are often characterised by a higher rate of interaction with the queen (E. Brunner and J. Heinze, unpubl. data). Similar dominance interactions commonly occur also among young queens, which jointly initiate a new colony. In paper wasps and several species of ants, in which founding queens search for food, rank orders may be associated with a division of labour between the dominants, which lay
166
Jürgen Heinze
eggs and stay close to the brood pile, and the subordinates, which forage for food (Pardi 1946, Gadagkar 1980, Kolmer and Heinze 2000). In ant species, in which founding queens do not forage but rely on stored fat reserves and histolyzed body tissue to produce their first young, the initially peaceful coexistence and mutual help among queens are quickly replaced by severe fighting once the first workers have eclosed. The latter often take part in expelling or killing all but one of the queens (e.g., Strassmann 1989). In established multi-queen colonies, queens usually behave amicably or ignore each others’ presence, and rank orders among queens have been observed only in a small minority of species. Theory predicts that hierarchies and high reproductive skew, e.g., an unbalanced partitioning of reproduction among potential egg layers, may be evolutionarily stable when the success of dispersal and becoming reproductive away from the established nest is low and when relatedness among nestmates is high (e.g., Keller and Reeve 1994). The boreal ants of the genus Leptothorax, in which one dominant queen monopolises egg laying, are indeed specialists of patchy habitats, such as dry areas in spruce bogs. Low skew species, in which queens do not form hierarchies and contribute equally to the colony’s offspring, live in more homogeneous, extended habitats, such as the coniferous forests, which cover large parts of the Northern Hemisphere (Bourke and Heinze 1994). Dominance hierarchies are probably best known from social Hymenoptera with a secondarily reduced or lost caste polymorphism. For example, in several genera of the ant subfamily Ponerinae workers have retained a spermatheca and are in principle capable of mating and laying fertilised eggs. In Diacamma, Dinoponera, Streblognathus and other genera, mated workers (‘gamergates’) have completely replaced morphological queens (Peeters 1991). In these taxa, reproductive conflict is particularly pronounced, because high ranking workers can supersede the top-ranking gamergate, mate and then produce both daughters and sons (e.g., Ito and Higashi 1991, Peeters et al. 1992, Monnin and Peeters 1999, Monnin and Ratnieks 2001). Similar to these conflicts about reproductive rights among totipotent individuals is the potential conflict among developing females and the rest of the colony about which and how many larvae will develop into sexuals (Bourke and Ratnieks 1999). Hymenopteran larvae often lack the power to control their own development, because food is provided by the workers. Nevertheless, conflict about caste fate appears to be realised in stingless bees. Here, female larvae are in charge of their own food intake, because they develop in identical, mass-provisioned, sealed cells, and caste size dimorphism is low. A large percentage of female larvae develop into female sexuals, but many of them are later executed by the workers
Conflict and conflict resolution in social insects
167
(Wenseleers et al. 2004a). Interestingly, the proportion of larvae developing into excess female sexuals is smaller in those species in which males are produced by workers, presumably because of the higher relatedness of workers to worker-produced males (Wenseleers and Ratnieks 2004).
6.7 Proximate aspects of dominance and policing Dominance, punishment, and policing may involve overtly aggressive behaviour, such as biting, pulling of legs and antennae, immobilisation, and stinging, but in many cases ritualised aggression appears to be sufficient to clarify rank relationships. Antennation bouts, often referred to as antennal boxing, have been described from ants, wasps, and bees, and are probably the most common type of agonistic interaction. In contrast to the rather slow, inspective antennation commonly seen in insect societies, antennal boxing involves rapid strikes directed mostly towards the head of the opponent. When rank relations are clear, subordinates may respond to antennation by crouching with retracted antennae and legs and the dominant may step onto the subordinate with extended legs and antennae, assuming a ‘big game hunter’s position’ on top of it for several seconds. Antennal boxing closely resembles food begging and subordination is occasionally associated with the offering of food. Appeasing regurgitation of food might thus have provided the behavioural basis for the evolution of food exchange in social Hymenoptera (Liebig et al. 1997). When rank relations are not yet settled, antennation may elicit counterantennation and result in mutual antennal boxing, which may intensify into overt aggression, from elegant fencing with elongated, beak-like mandibles (Peeters and Hölldobler 1995) to ‘sumo wrestling’ with shaking contests (Gobin and Ito 2003). In Leptothorax ants, dominance interactions among workers usually remain ritualised and rarely lead to injuries, whereas dominance interactions among queens more frequently escalate and may result in the expulsion or death of an individual (e.g., Heinze and Smith 1990). Similarly, in Temnothorax ants, policing but not worker dominance may involve biting and stinging and result in the death of the attacked individual (E. Brunner and J. Heinze, unpubl. data). Antennation and biting serve to establish rank orders, but what determines, which individual becomes dominant and which becomes subordinate? Obviously, a positive feedback exists between social and reproductive dominance, in that physical aggression often ceases when one or several individuals have begun to lay eggs and signal their fertility by pheromones. This is nicely documented by an experiment in which only
168
Jürgen Heinze
the lowest ranking queens in colonies of a high-skew ant were allowed to become reproductive after overwintering, while the more dominant queens were kept under prolonged artificial hibernation. Dominants did not attack the now egg laying former subordinate when they were later transferred into the nest and instead were policed themselves by the workers (Ortius and Heinze 1999). An association between ovarian development and dominance is also indicated by the observation that workers in orphaned colonies of the ants Temnothorax nylanderi and T. affinis with ovaries consisting of three or four ovarioles achieved higher social and reproductive ranks than ‘normal’ workers with two ovarioles (Heinze et al. 1997). A promising avenue for untangling the interrelations between fertility and dominance is the surgical removal of ovaries, which allows separating social and reproductive dominance in paper wasps. Ovariectomized queens of paper wasps were still capable of socially dominating their nestmates but no longer prevented them from egg laying (Röseler and Röseler 1989). In addition to reproductive status, the age of contestants may also influence their rank. In perennial social insects, such as ants or many tropical wasps, the youngest individuals become dominant when an older reproductive is removed (Ito and Higashi 1991), whereas in annual, temperate wasp species old individuals dominate the young. This difference was explained by the relationship between individual and society life span. Because of the decline of annual societies in fall, younger individuals gain more from helping and saving the costs of fighting for dominance. In contrast, becoming dominant is particularly beneficial for young individuals in perennial societies because of the long future tenure (Tsuji and Tsuji 2005). Closely connected with this phenomenon is the peculiar inverse relationship between fecundity and longevity in perennial social insects. Whereas most animals show a trade-off between reproduction and life span, laying eggs apparently prolongs the life of perennial social insects (Heinze and Schrempf 2008), i.e., once an individual has become socially and reproductively dominant it will remain so for a long period. The evidence for an association between social status and other physical attributes, such as size or fluctuating asymmetry, is as yet ambiguous (Heinze and Oberstadt 1999, Gobin and Ito 2003, Clémencet et al. 2008), but the linearity of many insect hierarchies suggests that social experience might play a role in the establishment of rank orders. As in other animals, winners keep winning and losers keep losing, i.e., experience from the previous interaction feeds back on the performance in future fights (Dugatkin 1997). In accordance with models on hierarchy formation (Chase 1982), domination in Leptothorax colonies was most frequently followed by the attacker attacking a third individual (double dominance; J.
Conflict and conflict resolution in social insects
169
Heinze, unpubl. data). Winner and loser effects presumably depend on hormone titers, but the association between aggression, reproduction, and hormones are not yet fully elucidated: elevated brain levels of octopamine were associated with social dominance in bumble bees (Bloch et al. 2000) but with egg laying in the queenless ant Streblognathus peetersi (CuvillierHot and Lenoir 2006).
6.8 Conclusion: the insect society – superorganism or police state? This review clearly demonstrated that insect societies are often ridden with potential conflict. Three aspects might merit a few additional thoughts. First, most previous research in social insects has focused on individual types of conflict, but because inclusive fitness is affected by numerous factors, a more comprehensive approach might be needed. For example, how strongly female larvae of stingless bees strive to develop into female sexuals appears to be associated with the extent of male production by workers (Wenseleers and Ratnieks 2004), and conflict about sex allocation is tightly interwoven with conflict about reproductive allocation, i.e., the partitioning of resources into colony maintenance and the production of sexuals (Herbers et al. 2001), and workers that focus on egg laying instead of working have less opportunities to control and manipulate queen sex ratios. As always in evolution, it is impossible to simultaneously optimise all individual fitness components. Instead, trade-offs might lead to results that seem suboptimal when studied in isolation. In addition, phylogenetic inertia might lead to unexpected phenomena. The parthenogenetic ant Platythyrea punctata has retained ‘selfish policing’ from their sexual ancestors despite of the evolutionary futility of selfishness in clonal societies (Hartmann et al. 2003, K. Kellner, E. Brunner and J. Heinze, unpubl. data). The case of clonal Platythyrea also emphasizes a second point: the role of relatedness in the occurrence of conflict in insect societies appears to be considerably less pronounced than previously thought. This is evidenced by the comparatively low percentage of variance in sex allocation explained by variation in kinship (Meunier et al. 2008) and the common absence of worker reproduction from monogynous and monandrous insect societies (Hammond and Keller 2004). Note that this does not reduce the fundamental importance of inclusive fitness and kinship in the evolution and maintenance of eusociality. Instead, research on conflict and conflict resolution in insect societies again and again gives evidence of the robustness of predictions from inclusive fitness theory. Insect societies generally
170
Jürgen Heinze
consist of more or less extended families and are closed against unrelated individuals by efficient nestmate discrimination (e.g., Wilson 1971, Hölldobler and Wilson 1990). Like the single-cell stage in the early development of multicellular animals counteracts the accumulation of selfish,parasitic cell lineages (Maynard Smith and Szathmàry 1995), the single-queen stage in the early life of many social insects prevents intraspecific parasitism and the erosion of relatedness. Nevertheless, in particular in complex insect societies, the costs arising from individual selfishness for the inclusive fitness of average group members societies appear to outweigh the inclusive fitness effects of variation in relatedness. Third, individuals in insect societies are not inherently altruistic but their cooperation is achieved by policing, punishment, and dominance. Selfish behaviour, which threatens the efficiency of the colony and decreases the average inclusive fitness of others, is suppressed, and individuals are forced to cooperate. The more efficient mutual surveillance, the less is to be gained from cheating. The percentage of individuals that selfishly pursue their interests decreases with the likelihood of failure, e.g., due to policing (Wenseleers and Ratnieks 2006b). Likewise, workers in many ant species with large, polygynous colonies, in which old queens are readily replaced by new queens reared from the brood, have completely lost their ovaries, presumably because their chance of laying unfertilised eggs is extremely small (Bourke 1999, Wenseleers et al. 2004b). Once internal conflict has been repressed, group-level adaptations may evolve (Gardner and Grafen 2009). Seen from outside, such societies come closest to the traditional image of the harmonious superorganism, in which ‘individuality’ is achieved through the suppression of competition within the colony and which compete as single units with other such units in territorial disputes.
Acknowledgements Supported by Deutsche Forschungsgemeinschaft (He 1623/17). Peter Kappeler, Rolf Kümmerli and an anonymous referee made helpful comments on the manuscript.
Conflict and conflict resolution in social insects
171
GLOSSARY Gamergate: mated, fertile worker, in particular in ponerine ants Monogyny: one single mated egg layer (queen or gamergate) per colony Monandry: single-mating by female sexuals Polygyny: multiple mated egg layers (queens or gamergates) per colony; if reproduction is highly skewed due to dominance hierarchies among egg layers, apparent polygyny may in fact be ‘functional monogyny’. Polyandry: multiple mating by females; as paternity is often skewed, the pedigree-effective mate number (the reciprocal of the sum of the squared average proportional contributions of each male) reflects the influence of multiple mating on the genetic structure of the colony better than the actual number of mates. Relatedness: the coefficient of relatedness is defined as the proportion of alleles that two individuals share by common descent from a recent common ancestor. As pedigrees are usually not known for social insects, most studies estimate kinship from ‘regression relatedness’, the slope of the regression line obtained by regressing the average genotype (e.g., at a microsatellite locus) in individuals of type X (e.g., female sexuals), across all colonies, on the genotype in individuals of type Y (e.g., workers). Due to haplodiploidy, the genes of males contribute only 1/3 to the gene pool of future generations, whereas females contribute 2/3 (assuming that workers do not reproduce). Regression relatedness therefore needs to be multiplied by the sex-specific reproductive values of individuals (1 for females, 0.5 for males) to obtain the commonly used ‘lifefor-life’ relatedness as given in Table 6.1. In diploids, regression relatedness equals ‘life-for-life’ relatedness. Relatedness asymmetry: relatedness of workers to female sexuals / relatedness of workers to males; usually 3 in monogynous societies, but approaching 1 with increasing queen mating frequency or increasing number of related queens Sex allocation ratio: in social insects usually given as the amount of resources invested in female sexuals relative to that invested in all sexuals. Sex allocation ratio equals the numerical sex ratio when males and female sexuals are similar in size and equally costly to produce, but as female sexuals may be much larger and richer in fat than males (particular in ants), sex allocation ratios are often very different from numerical sex ratios.
172
Jürgen Heinze
References Bloch G, Simon T, Robinson GE, Hefetz A (2000) Brain biogenic amines and reproductive dominance in bumble bees (Bombus terrestris). J Comp Physiol A 186:261-268 Boomsma JJ (2007) Kin selection versus sexual selection: why the ends do not meet. Curr Biol 17:R673-R683 Boomsma JJ, Grafen A (1990) Intraspecific variation in ant sex ratios and the Trivers-Hare hypothesis. Evolution 44:1026-1034 Bourke AFG (1999) Colony size, social complexity and reproductive conflict in social insects. J Evol Biol 12:245-257 Bourke AFG, Franks NR (1995) Social Evolution in Ants. Princeton University Press, Princeton Bourke AFG, Heinze J (1994) The ecology of communal breeding: the case of multiple-queen leptothoracine ants. Philos Trans R Soc Lond B 345:359-372 Bourke AFG, Ratnieks FLW (1999) Kin conflict over caste determination in social Hymenoptera. Behav Ecol Sociobiol 46:287-297 Brunner E, Kroiss J, Heinze J (2009) Chemical correlates of reproduction and worker policing in a myrmicine ant. J Insect Physiol 55:19-26 Burt A, Trivers RL (2006) Genes in Conflict. The Biology of Selfish Genetic Elements. Harvard University Press, Cambridge/MA Chase ID (1982) Behavioral sequences during dominance hierarchy formation in chickens. Science 216:439-440 Clémencet J, Rome Q, Fédérici P, Doums C (2008) Aggressions and size-related fecundity of queenless workers in the ant Cataglyphis cursor. Naturwissenschaften 95:133-139 Cole BJ (1986) The social behavior of Leptothorax allardycei (Hymenoptera, Formicidae): time budgets and the evolution of worker reproduction. Behav Ecol Sociobiol 18:165-173 Cremer S, Heinze J (2002) Adaptive production of fighter males: queens of the ant Cardiocondyla adjust the sex ratio under local mate competition. Proc R Soc Lond B 269:417-422 Crewe RM (1988) Natural history of honey-bee mandibular gland secretions: development of analytical techniques and the emergence of complexity. In: Needham GR, Page RE Jr, Delfinado-Baker M, Bowman CE (eds) Africanized Honey Bees and Bee Mites. Wiley, New York, pp 149-158 Crozier RH, Pamilo P (1996) Evolution of Social Insect Colonies. Sex Allocation and Kin Selection. Oxford University Press, Oxford Cuvillier-Hot V, Lenoir A (2006) Biogenic amine levels, reproduction and social dominance in the queenless ant Streblognathus peetersi. Naturwissenschaften 93:149-153 Dawkins R (1979) Twelve misunderstandings of kin selection. Z Tierpsychol 51:184-200 de Menten L, Cremer S, Heinze J, Aron S (2005) Primary sex ratio adjustment by ant queens in response to local mate competition. Anim Behav 69:1031-1035
Conflict and conflict resolution in social insects
173
Deshpande SA, Sumana A, Surbeck M, Gadagkar R (2006) Wasp who would be queen: a comparative study of two primitively eusocial species. Curr Sci 91:332-336 Deslippe RJ, Savolainen R (1995) Sex investment in a social insect: the proximate role of food. Ecology 76:375-382 D’Ettorre P, Heinze J, Ratnieks FLW (2004) Worker policing by egg eating in the ponerine ant Pachycondyla inversa. Proc R Soc Lond B 271:1427-1434 Drouin J-M (2005) Ants and bees. Between the French and the Darwinian revolution. Ludus Vitalis XIII:3-14 Dugatkin LA (1997) Winner and loser effects and the structure of dominance hierarchies. Behav Ecol 8:583-587 Foster KR, Ratnieks FLW (2000) Facultative worker policing in a social wasp. Nature 407:692-693 Foster KR, Gulliver J, Ratnieks FLW (2002) Worker policing in the European hornet Vespa crabro. Insectes Soc 49:41-44 Foster KR, Wenseleers T, Ratnieks FLW (2006) Kin selection is the key to altruism. Trends Ecol Evol 21:57-60 Frank SA (1996) Policing and group cohesion when resources vary. Anim Behav 52:1163-1169 Frank SA (2003) Perspective: repression of competition and the evolution of cooperation. Evolution 57:693-705 Franks NR, Scovell E (1983) Dominance and reproductive success among slavemaking worker ants. Nature 304:724-725 Frohschammer S, Heinze J (2009) A heritable component in sex ratio and caste determination in a Cardiocondyla ant. Front Zool 6:27 Gadagkar R (1980) Dominance hierarchy and division of labour in the social wasp, Ropalidia marginata (Lep.) (Hymenoptera: Vespidae). Curr Sci 49:772775 Gardner A, Grafen A (2009) Capturing the superorganism: a formal theory of group adaptation. J Evol Biol 22:659-671 Gobin B, Ito F (2003) Sumo wrestling in ants: major workers fight over male production in Acanthomyrmex ferox. Naturwissenschaften 90:318-321 Gobin B, Billen J, Peeters C (1999) Policing behaviour towards virgin egg layers in a polygynous ponerine ant. Anim Behav 58:1117-1122 Gobin B, Heinze J, Strätz M, Roces F (2003) The energetic cost of reproductive conflicts in the ant Pachycondyla obscuricornis. J Insect Physiol 49:747-752 Hamilton WD (1964a) The genetical evolution of social behaviour. I. J Theor Biol 7:1-16 Hamilton WD (1964b) The genetical evolution of social behaviour. II. J Theor Biol 7:17-52 Hamilton WD (1967) Extraordinary sex ratios. Science 156:477-488 Hammond RL, Keller L (2004) Conflict over male parentage in social insects. PLoS Biol 2:e248, doi:10.1371/journal.pbio.0020248 Hammond RL, Bruford MW, Bourke AFG (2002) Ant workers selfishly bias sex ratios by manipulating female development. Proc R Soc Lond B 269:173-178
174
Jürgen Heinze
Hannonen M, Sundström L (2003) Worker nepotism among polygynous ants. Nature 421:910 Hardin G (1968) The tragedy of the commons. Science 162:1243-1248 Hartmann A, Wantia J, Torres JA, Heinze J (2003) Worker policing without genetic conflicts in a clonal ant. Proc Natl Acad Sci USA 100:12836-12840 Hartmann A, D’Ettorre P, Jones GR, Heinze J (2005) Fertility signaling – the proximate mechanism of worker policing in a clonal ant. Naturwissenschaften 92:282-286 Heinze J (2004) Reproductive conflict in insect societies. Adv Stud Behav 34:1-57 Heinze J (2008) The demise of the standard ant (Hymenoptera: Formicidae). Myrmecol News 11:9-20 Heinze J, D’Ettorre P (2009) Honest and dishonest communication in social Hymenoptera. J Exp Biol 212:1775-1779 Heinze J, Oberstadt B (1999) Worker age, size and social status in queenless colonies of the ant Leptothorax gredleri. Anim Behav 58:751-759 Heinze J, Schrempf A (2008) Aging and reproduction in social insects. Gerontology 54:160-167 Heinze J, Smith TA (1990) Dominance and fertility in a functionally monogynous ant. Behav Ecol Sociobiol 27:1-10 Heinze J, Hölldobler B, Peeters C (1994) Conflict and cooperation in ant societies. Naturwissenschaften 81:489-497 Heinze J, Puchinger W, Hölldobler B (1997) Worker reproduction and social hierarchies in Leptothorax ants. Anim Behav 54:849-864 Heinze J, Oberstadt B, Tentschert J, Hölldobler B, Bestmann HJ (1998) Colony specificity of Dufour gland secretions in a functionally monogynous ant. Chemoecology 8:169-174 Helanterä H, Sundström L (2007) Worker reproduction in Formica ants. Am Nat 170:E14-E25 Herbers JM, DeHeer CJ, Foitzik S (2001) Conflict over sex allocation drives conflict over reproductive allocation in perennial social insect colonies. Am Nat 158:178-192 Hölldobler B, Wilson EO (1990) The Ants. Harvard University Press, Cambridge/MA Hölldobler B, Wilson EO (2009) The Superorganism: The Beauty, Elegance, and Strangeness of Insect Societies. Norton, New York Ito F, Higashi S (1991) A linear dominance hierarchy regulating reproduction and polyethism of the queenless ant Pachycondyla sublaevis. Naturwissenschaften 78:80-82 Keller L, Nonacs P (1993) The role of queen pheromones in social insects: queen control or queen signal? Anim Behav 45:787-794 Keller L, Reeve HK (1994) Partitioning of reproduction in animal societies. Trends Ecol Evol 9:98-102 Kikuta N, Tsuji K (1999) Queen and worker policing in the monogynous and monandrous ant, Diacamma sp. Behav Ecol Sociobiol 46:180-189 Kolmer K, Heinze J (2000) Rank orders and division of labour among unrelated cofounding ant queens. Proc R Soc Lond B 267:1729-1734
Conflict and conflict resolution in social insects
175
Korb J, Heinze J (2004) Multilevel selection and social evolution of insect societies. Naturwissenschaften 91:291-304 Korb J, Heinze J (2008) Ecology of Social Evolution. Springer, Heidelberg Kümmerli R, Keller L (2009) Patterns of split sex ratio in ants have multiple evolutionary causes based on different within-colony conflicts. Biol Lett 5:713716 Lehmann L, Keller L, West S, Roze D (2007) Group selection and kin selection: two concepts but one process. Proc Natl Acad Sci USA 104:6736-6739 Leigh EG Jr (1999) Levels of selection, potential conflicts, and their resolution: the role of the ‘common good’. In: Keller L (ed) Levels of Selection in Evolution. Princeton University Press, Princeton, pp 15-30 Liebig J, Heinze J, Hölldobler B (1997) Trophallaxis and aggression in the ponerine ant, Ponera coarctata: implications for the evolution of liquid food exchange in the Hymenoptera. Ethology 103:707-722 Liebig J, Peeters C, Hölldobler B (1999) Worker policing limits the number of reproductives in a ponerine ant. Proc R Soc Lond B 266:1865-1870 Linksvayer TA, Wade MJ (2005) The evolutionary origin and elaboration of sociality in the aculeate Hymenoptera: maternal effects, sib-social effects, and heterochrony. Q Rev Biol 80:317-336 Maynard Smith J, Szathmáry E (1995) The Major Transitions in Evolution. WH Freeman, Oxford Mehdiabadi NJ, Reeve HK, Mueller UG (2003) Queens versus workers: sex-ratio conflict in eusocial Hymenoptera. Trends Ecol Evol 18:88-93 Meunier J, West SA, Chapuisat M (2008) Split sex ratios in the social Hymenoptera: a meta-analysis. Behav Ecol 19:382-390 Michod RE (1996) Cooperation and conflict in the evolution of individuality. II. Conflict mediation. Proc R Soc Lond B 263:813-822 Monnin T (2006) Chemical recognition of reproductive status in social insects. Ann Zool Fennici 43:515-530 Monnin T, Peeters C (1997) Oophagy of subordinate’s eggs in the monogynous queenless ant Dinoponera quadriceps. Naturwissenschaften 84:499-502 Monnin T, Peeters C (1999) Dominance hierarchy and reproductive conflicts among subordinates in a monogynous queenless ant. Behav Ecol 10:323-332 Monnin T, Ratnieks FLW (2001) Policing in queenless ponerine ants. Behav Ecol Sociobiol 50:97-108 Monnin T, Ratnieks FLW, Jones GR, Beard R (2002) Pretender punishment induced by chemical signalling in a queenless ant. Nature 419:61-65 Moritz RFA, Southwick EE (1992) Bees as Superorganisms: An Evolutionary Reality. Springer, Heidelberg Nakata K, Tsuji K (1996) The effect of colony size on conflict over maleproduction between gamergate and dominant workers in the ponerine ant Diacamma sp. Ethol Ecol Evol 8:147-156 Nonacs P (1986) Sex-ratio determination within colonies of ants. Evolution 40:199-204 Ortius D, Heinze J (1999) Fertility signaling in queens of a North American ant. Behav Ecol Sociobiol 45:151-159
176
Jürgen Heinze
Pardi L (1946) Ricerche sui Polistini. VII. La ‘dominazione’ e il ciclo ovarico annuale in Polistes gallicus L. Boll Ist Entomol Univ Bologna 15:25-84 Passera L, Aron S, Vargo EL, Keller L (2001) Queen control of sex ratio in fire ants. Science 293:1308-1310 Pearcy M, Aron S (2006) Local resource competition and sex ratio in the ant Cataglyphis cursor. Behav Ecol 17:569-574 Peeters C (1991) The occurrence of sexual reproduction among ant workers. Biol J Linn Soc 44:141-152 Peeters C, Hölldobler B (1995) Reproductive cooperation between queens and their mated workers: the complex life history of an ant with a valuable nest. Proc Natl Acad Sci USA 92:10977-10979 Peeters C, Billen J, Hölldobler B (1992) Alternative dominance mechanisms regulating monogyny in the queenless ant genus Diacamma. Naturwissenschaften 79:572-573 Price GR (1970) Selection and covariance. Nature 227:520-521 Queller DC (1992a) Quantitative genetics, inclusive fitness, and group selection. Am Nat 139:540-558 Queller DC (1992b) A general model for kin selection. Evolution 46:376-380 Queller DC (1994) Genetic relatedness in viscous populations. Evol Ecol 8:70-73 Queller DC (1996) The measurement and meaning of inclusive fitness. Anim Behav 51:229-232 Rankin DJ, Bargum K, Kokko H (2007) The tragedy of the commons in evolutionary biology. Trends Ecol Evol 22:643-651 Ratnieks FLW (1988) Reproductive harmony via mutual policing by workers in eusocial Hymenoptera. Am Nat 132:217-236 Ratnieks FLW, Boomsma JJ (1997) On the robustness of split sex ratio predictions in social Hymenoptera. J Theor Biol 185:423-439 Ratnieks FLW, Visscher PK (1989) Worker policing in the honeybee. Nature 342:796-797 Ratnieks FLW, Foster KR, Wenseleers T (2006) Conflict resolution in insect societies. Annu Rev Entomol 51:581-608 Reuter M, Keller L (2001) Sex ratio conflict and worker production in eusocial Hymenotera. Am Nat 158:166-177 Röseler P-F, Röseler I (1989) Dominance of ovariectomized foundresses of the paper wasp, Polistes gallicus. Insectes Soc 36:219-234 Saigo T, Tsuchida K (2004) Queen and worker policing in monogynous and monandrous colonies of a primitively eusocial wasp. Proc R Soc Lond B 271:S509-S512 Schwander T, Humbert J-Y, Brent CS, Helms Cahan S, Chapuis L, Renai E, Keller L (2008) Maternal effect on female caste determination in a social insect. Curr Biol 18:265-269 Seeley TD (1985) Honeybee Ecology. Princeton University Press, Princeton Sleigh C (2007) Six Legs Better: A Cultural History of Myrmecology. Johns Hopkins University Press, Baltimore Starr CK (1985) Enabling mechanisms in the origin of sociality in the Hymenoptera – the sting’s the thing. Ann Entomol Soc Am 78:836-840
Conflict and conflict resolution in social insects
177
Strassmann JE (1989) Altruism and relatedness at colony foundation in social insects. Trends Ecol Evol 4:371-374 Stroeymeyt N, Brunner E, Heinze J (2007) ‘Selfish worker policing’ controls reproduction in a Temnothorax ant. Behav Evol Sociobiol 61:1449-1457 Sundström L, Chapuisat M, Keller L (1996) Conditional manipulation of sex ratios by ant workers: a test of kin selection theory. Science 274:993-995 Teyssèdre A, Couvet D, Nunney L (2006) Lower group productivity under kinselected reproductive altruism. Evolution 60:2023-2031 Trivers RL, Hare H (1976) Haplodiploidy and the evolution of the social insects. Science 191:249-263 Trunzer B, Heinze J, Hölldobler B (1999) Social status and reproductive success in queenless ant colonies. Behaviour 136:1093-1105 Tsuji K, Tsuji N (2005) Why is dominance hierarchy age-related in social insects? The relative longevity hypothesis. Behav Ecol Sociobiol 58:517-526 van Zweden JS, Fürst MA, Heinze J, D’Ettorre P (2007) Specialization in policing behaviour among workers in the ant Pachycondyla inversa. Proc R Soc Lond B 274:1421-1428 Visscher KP, Dukas R (1995) Honey bees recognize development of nestmates’ ovaries. Anim Behav 49:542-544 Wenseleers T, Ratnieks FLW (2004) Tragedy of the commons in Melipona bees. Proc R Soc Lond B 271:S310-S312 Wenseleers T, Ratnieks FLW (2006a) Comparative analysis of worker reproduction and policing in eusocial Hymenoptera supports relatedness theory. Am Nat 168:E163-E179 Wenseleers T, Ratnieks FLW (2006b) Enforced altruism in insect societies. Nature 444:50 Wenseleers T, Hart AG, Ratnieks FLW, Quezada-Euán JJG (2004a) Queen execution and caste conflict in the stingless bee Melipona beecheii. Ethology 110:725-736 Wenseleers T, Hart AG, Ratnieks FLW (2004b) When resistance is useless: policing and the evolution of reproductive acquiescence in insect societies. Am Nat 164:E154-E167 Wenseleers T, Tofilski A, Ratnieks FLW (2005) Queen and worker policing in the tree wasp Dolichovespula sylvestris. Behav Ecol Sociobiol 58:80-86 West SA, Griffin AS, Gardner A (2007a) Evolutionary explanations for cooperation. Curr Biol 17:R661-R672 West SA, Griffin AS, Gardner A (2007b) Social semantics: altruism, cooperation, mutualism, strong reciprocity and group selection. J Evol Biol 20:415-432 Whitfield J (2002) The police state. Nature 416:782-784 Wilson EO (1971) The Insect Societies. Harvard University Press, Cambridge/MA Wilson EO (2005) Kin selection as the key to altruism: its rise and fall. Soc Res 72:159-168 Wilson EO (2008) One giant leap: how insects achieved altruism and colonial life. BioScience 58:17-25 Wilson EO, Hölldobler B (2005) Eusociality: origin and consequences. Proc Natl Acad Sci USA 102:13367-13371
178
Jürgen Heinze
Wilson DS, Wilson EO (2007) Rethinking the theoretical foundation of sociobiology. Q Rev Biol 82:327-348
Chapter 7
Social insects, major evolutionary transitions and multilevel selection JUDITH KORB
ABSTRACT The history of life is characterised by an increase in biological complexity from simple replicators to multicellular organisms. These major evolutionary transitions have in common that independent entities came together and cooperated and that finally a new entity was formed with a new fitness and a single evolutionary fate. Yet, the stable evolution of cooperation poses a classical Darwinian puzzle: Organisms compete over reproduction and selfish individuals that reap the benefits of the cooperation without paying the costs (cheaters) can invade a population of cooperators and drive the disappearance of cooperation. Social insects have become model organisms to study stable cooperation and how conflict between individuals is resolved. Here, I will first summarise what we have learned from social insect research about the evolution of stable cooperation. Besides little-studied ecological factors that determine the benefits and costs of cooperation, two common mechanisms to prevent the spread of cheaters have been identified: (i) common ancestry and aligned evolutionary interests mainly achieved through relatedness and (ii) enforcement mechanisms that make cheating costly. Then, I will show that similar mechanisms have evolved at other levels of the biological hierarchy that favour cooperation. Thirdly, I will present the multilevel selection approach, which promises to be a useful tool to study evolution at multiple selection levels. I will end by showing how a multilevel selection approach in future research might help to quantify benefits and costs of cooperation, so that insect societies and all major evolutionary transitions alike are being recognised as more than the sum of their components.
180
Judith Korb
7.1 Life on earth – a hierarchy of selection levels The history of life is characterised by an increase of biological complexity. While evolution need not intrinsically drive towards increasing complexity on a short time scale, one can nevertheless track a progression in sophistication over geological time. The rise in complexity from simple replicating molecules to multicellular organisms can be characterised as a series of ‘major transitions’ in evolution where replicating units came together to form a new, more complex unit. At least three such major transitions can be identified (Fig. 7.1; Maynard Smith and Szathmáry 1995). At the origin of life, independent replicators evolved into cooperatively replicating chromosomes that formed the first protocells (Szathmáry 2006). Around 1.4 billion years ago, eukaryotes orginated via endosymbioses from two independent prokaryotic ancestors (e.g. Margulis 1981). To date, the last clear major transition was the multiple and independent origins of multi-
CTTGGTACCGACTCGGACCCACTA GTAACGGCCGCCAGTGTGCTGGAA TTCGGCTTTTCTGCTTCGGTAACTA ACGTCATCACAGGGGCATTCCCTC CCCCGCTTATTCTTCAGCAAC
Fig. 7.1 Levels of complexity. This termite colony comprises a hierarchy of levels of cooperation. Genes cooperate in genomes, nuclear genes and cytoplasmic elements cooperate and build cells, cells cooperate and build multicellular organisms, and individuals cooperate and form colonies. At the top-most level, even colonies have their own ‘phenotype’: complex mounds arise through self-organised processes.
Social insects, major evolutionary transitions and multilevel selection
181
cellular life (e.g. Herron et al. 2009). Maynard Smith and Szathmáry (1995) also identified a fourth major transition, the evolution of eusocial groups in which individuals live in complex societies (see below). Each of these events constitutes an increase in structural complexity, as groups of individuals become individuals in their own right. Put another way, there is a transfer of fitness from the individuals making up the group to the group itself, a new entity is formed with a new fitness and a single evolutionary fate (Herron et al. 2009). The evolution of high-level complexity in this way makes considerable sense as it allows organisms to become larger, occupy new niches and perhaps dominate old ones. However, at the same time, the major transitions pose a major problem for evolutionary biology (Maynard Smith and Szathmáry 1995, Herron et al. 2009). 7.1.1 The problem of cooperation A key feature of each of the major transitions is the requirement for cooperation (see Glossary) between independent entities and this represents a classic problem for Darwinian thinking. Why should low-level units that compete among each other over reproduction invest in other individuals, especially when it compromises their own reproduction? At first glance, it appears that such behaviours will result in reduced passage of genes to the next generation and so reduced fitness. A necessary condition then for cooperation to evolve is that the benefits for a cooperative group must be larger than the costs paid by the constituent members (Fig. 7.2). Cooperation must increase the fitness of cooperators over selfish solitary organisms.
Evolutionary Dilemma A
B
Aco + Bco
Aco + Bch
Bch
Fig. 7.2 The evolutionary dilemma of cooperation. For cooperation to evolve each cooperator (indicated by the subscript co) must have a higher fitness (indicated by the size of the circle) than a solitary entity. Yet, this is not sufficient. If a cheater mutant arises, that invests less in the cooperation but still reaps the benefit of cooperation (indicated by the subscript ch), this mutant will be evolutionary favoured as it has a higher fitness than the cooperator. In the long-term, this will lead to the breakdown of cooperation.
182
Judith Korb
Yet, this condition is not sufficient. If a mutant arises among cooperators which invests less in cooperation but can still reap the benefit of cooperation, it can outreproduce cooperators because it gains the benefits of cooperation without paying the cost. Such ‘cheaters’ might then invade the population and drive the disappearance of cooperators and the breakdown of cooperation. Thus, for evolutionarily stable cooperation to evolve, mechanisms must exist which prevent the origin and spread of cheaters (see also Bshary this volume).
7.2 Social insects as model organisms for cooperation One group of organisms is especially suited to study social life, both its conflicts and conflict resolution mechanisms: eusocial insects, which appear themselves to be close to making a new evolutionary transition that transcends the level of the multicellular organism (Maynard Smith and Szathmáry 1995). Eusociality is defined by colony life in which only one or a few individuals reproduce while the large majority of individuals − the workers and soldiers − forego direct reproduction, at least temporarily, and help the others reproduce (Wilson 1971). Worker and soldier behaviour take many and extreme forms, ranging from helping with brood care, through foraging to the famously suicidal defense of the honeybee worker or of termite soldiers that explode upon contact with a predator. Such examples of cooperation − in particular suicidal behaviours − are linked to reduced reproductive fitness on the part of the workers/soldiers, an example of what is called biological altruism (see Glossary; West et al. 2007, Foster 2008). A range of insect species display eusociality, including the Hymenoptera (ants and some bees and wasps) and termites − and the less familiar social aphids and thrips (Chapman et al. 2008, Pike and Foster 2008). Why then do workers/soldiers so strikingly forgo their personal reproduction to help others raise offspring in these different lineages? With this question, we return to the central question in the study of major transitions in evolution, and it is for this reason − the altruism of workers and soldiers − that the social insects have become a model system for studying cooperation (e.g. Bourke and Franks 1995, Crozier and Pamilo 1996, Bourke 1997, Queller and Strassmann 1998, Korb and Heinze 2008a, Gadau and Fewell 2009). Several key factors favouring cooperation and altruism became evident from these studies, which I will briefly summarise in the following (for more details see also Heinze this volume, Kraus and Moritz this volume).
Social insects, major evolutionary transitions and multilevel selection
183
7.2.1 Explaining cooperation and altruism The key for explaining the evolution of cooperation and altruism is kin selection theory (Hamilton 1963, 1964, Maynard Smith 1964), the idea that genes are not only transmitted to the next generation via own offspring (direct fitness) but also through offspring of close relatives (indirect fitness). Note, kin selection is not a separate force to natural selection and its application is not only restricted to interactions between kin (see Hamilton 1963, 1964, Gardner and Foster 2008). Thus, the term inclusive fitness (direct and indirect fitness effects) theory might be more appropriate. Inclusive fitness theory is encapsulated in Hamilton’s rule (1963, 1964). It states that a behaviour is evolutionarily favoured if it results in a net increase of the inclusive fitness of the individual: br – c > 0 where: br comprises the indirect fitness component, composed of the fitness benefit (b) for the recipient multiplied by the coefficient of relatedness (r) between actor and recipient, and c being the direct fitness component measured as the actor’s direct fitness cost of the behaviour. From Hamilton’s rule it is easily derived that an altruistic behaviour that decreases the direct fitness of an individual can only be evolutionarily favoured if it increases its indirect fitness component sufficiently. Accordingly, insect societies where individuals behave altruistically are generally comprised of family groups with offspring helping their mother (social Hymenoptera, thrips, aphids) or parents (termites) to reproduce (e.g. Wilson 1971, Korb and Heinze 2008a, Gadau and Fewell 2009). Thus, the altruists gain indirect fitness benefits through raising siblings. At the same time, however, the degree of relatedness (r) alone is often not sufficient to explain the occurrence of altruism or details in the organisation of social life (Korb and Heinze 2008b, see below). For instance, variation in relatedness cannot explain the pattern of helping behaviour in the stenogastrine wasp, Liostenogaster flavolineata (Field 2008), or the occurrence of workers in the lower termite Cryptotermes secundus (Korb 2008; for more examples see Korb and Heinze 2008a). This is not surprising, given that Hamilton’s rule is composed of benefits (b) and costs (c) as well. Yet, ecological costs and benefits of cooperation have often been disregarded, also in standard textbooks, for example when attributing the evolution of eusociality in Hymenoptera erroneously to haplodiploidy alone (i.e. the fact that males derive from haploid eggs while females develop from fertilized diploid eggs; this haplodiploidy leads to relatedness asymmetries within colonies; Heinze this volume, Kraus and Moritz this vol-
184
Judith Korb
ume). One reason for this negligence is the paucity of empirical studies explicitly testing these costs and benefits (for exceptions see e.g., Nonacs and Reeve 1995, Reeve et al. 1998, Field et al. 1998, 2000, Korb 2006, Foster and Xavier 2007). Additionally, with the advent of molecular tools, r can easily be quantified but ecological factors hidden in the c and b term of Hamilton’s rule are much more difficult to measure. 7.2.2 Ecological factors favouring cooperation: sociality syndromes The limited data available, supplemented by data on cooperatively breeding vertebrates, have revealed a number of ecological factors that repeatedly show up as vital for the evolution of cooperation and altruism (resultig in social life; see Glossary) and three sociality syndromes have been identified, each with a unique combination of ecological factors (Korb and Heinze 2008b; Fig. 7.3). The importance of relatedness for the evolution of cooperation and altruism should depend on the syndrome to which a species belongs. From syndrome I to III, the importance of indirect fitness benefits through rais-
• Progressive food provisioning
Indirect fitness
allofeeding • Inbreeding impossible no inheritance opportunities Workers
Syndrome III:
Most ants,most social bees, foraging termite species
• No bonanza type food resource
part. progressive food provisioning allofeeding • Limited inbreeding limited inheritance opportunities • Less fortress defense Helpers
Syndrome II: Most wasps, most cooperatively breeding birds and mammals
• Bonanza type food resource
no allofeeding
• Inbreeding possible
inheritance opportunities • Fortress defense Soldiers
Syndrome I:
Aphids, thrips, wood-dwelling termites, naked mole-rat
Direct fitness
Fig. 7.3 Sociality syndromes. Shown are the three sociality syndromes positioned along the direct and indirect fitness axis. For more information see text.
Social insects, major evolutionary transitions and multilevel selection
185
ing offspring increases, while those of direct benefits mainly through nest inheritance decrease (Fig. 7.3). The importance of relatedness for the evolution of altruism is predicted to increase from syndrome I to III. It is important to recognise that each sociality syndrome is characterised by a set of ecological traits and that these traits determine the importance of direct versus indirect benefits for the evolution of sociality. For instance, the possibility to reduce the reproductive load of breeders through alloparental care determines the benefit of helping (Heinsohn 2004), or inbreeding avoidance limits inheritance of a territory or it leads to group instability (Emlen 1997). Sociality syndrome I: These species live in groups that are composed of totipotent individuals protected by altruistic defenders. They monopolise a long-lasting bonanza-type food source (Wilson 1971), which supports the co-existence of many individuals without selection for dispersal (Hamilton and May 1977). The totipotent individuals do not provide intensive alloparental care, probably because food is easily accessible to all individuals and alloparental care can hardly alleviate the reproductive burden of breeders substantially. Helpers seem to stay because the nest is a safe haven with plenty of food, and there is a substantial possibility of inheriting the natal breeding position. Moreover, the chances of founding an own nest independently are low due to high mortality risks during dispersal. The only truly altruistic individuals in these groups are soldiers (fortress defenders after Queller and Strassmann 1998), which mainly protect the resource against competitors and their nestmates against predators. Inbreeding occurs regularly in such societies and it seems to play an important role, not necessarily through increasing relatedness, but through reducing relatedness asymmetries in the haplodiploid thrips (Chapman et al. 2008) and stabilising groups over longer periods as heirs do not have to mate with unrelated partners (in contrast to vertebrates, Emlen 1997). Aphids, thrips, wood-dwelling termites and the naked mole rat belong to this group of social organisms. Sociality syndrome II: These species take an intermediate position between societies consisting of totipotent individuals of class (I) and those with altruistic, subfertile workers of class (III), and include social Hymenoptera with totipotent workers (e.g. wasps and queenless ants) and cooperatively breeding vertebrates. Helpers can gain indirect fitness benefits through alloparental care as well as direct benefits through inheriting the breeding position or by founding a nest of their own. The ecological factors favouring alloparental care in totipotent workers are identical to those for subfertile workers of class (III), namely the potential to provide costly
186
Judith Korb
help that frees the reproductives from provisioning their offspring. As they still have the opportunity to reproduce, it is expected that they adjust their degree of costly helping according to their opportunity to breed (Kokko and Johnstone 1999). Limited evidence suggests that this is indeed the case. Depending, for instance, on their rank in the society’s hierarchy, wasps and birds invest differentially in alloparental care (Field et al. 1999, Koenig and Dickinson 2004, Cant and Field 2005, Cant et al. 2006). Accordingly, the comparatively small group sizes in syndrome II species might be explained by several factors: (i) The opportunity of founding a nest independently, (ii) presumed decreasing benefits of helping with increasing group size (Michener 1964, Reyer 1984, Karsai and Wenzel 1998) and (iii) the limitation of food sources, which causes local resource competition. Sociality syndrome III: Species in this category comprise the classical social insects, i.e. most social Hymenoptera (such as the honeybee and most ants) and foraging termites with sterile or subfertile workers. They are characterised by intensive, altruistic alloparental care. They engage in costly helping with low chances of personal direct reproduction. Brood care usually involves progressive food provisioning (Strohm and Liebig 2008), which is costly to the reproductives and can be ‘handed over’ to workers. Consequently, reproductives can concentrate on egg-laying. These sociality syndromes cover (i) the classification of species along a eusociality gradient, where sociality was classified along the degree of altruistic helping (Sherman et al. 1995), (ii) the classification according to reproductive skew (in high-skew societies, actual reproduction is concentrated in one or a small set of individuals within a group, in low-skew societies reproduction is distributed more evenly among group members; Reeve 1998, Johnstone 2000), or (iii) the social trajectory approach in which a species social structure is viewed as the result of a trajectory of decisions individuals make about whether or not to disperse, whether to co-breed and so on (Helms Cahan et al. 2002). It might help to solve the longstanding debate in cooperatively breeding vertebrates whether their systems are driven by direct or indirect fitness benefits by showing that it can be both, and it aids to identify to what extent direct and indirect benefits are important. By identifying the ecological factors that are associated with each syndrome the different causes for social life are explicitly revealed. Note, these syndromes should not be considered as a new classification system, rather this approach aims at identifying various common combina-
Social insects, major evolutionary transitions and multilevel selection
187
tions of ecological factors that in concert seem to favour social life. Thus, apparently similar social organisations can be driven by different syndromes (e.g. ant and wood-dwelling termites), while similar ecological syndromes occur in phylogenetically distant groups (e.g. naked mole rat and wood-dwelling termites). 7.2.3 Conflict, enforcement and coercion The above examples explain cooperation and altruism as a ‘voluntary’ tactic (sensu Wenseleers and Ratnieks 2006). Yet, there have been recurrent discussions of whether they might not be the result of manipulation, either by parents or siblings (Alexander 1974, Michener and Brothers 1974, West-Eberhard 1975, Charnov 1978, Zimmerman 1983, Stubblefield and Charnov 1986, Roisin 1994). Recently these discussions received renewed interest under the question whether altruism in insect societies is voluntary or enforced (Wenseleers and Ratnieks 2006, Ratnieks and Wenseleers 2008). Most likely it is a bit of both. Coercion clearly can play a role in social evolution but it always does in a social context where relatedness is important. Thus, it probably is a mechanism which evolved secondarily within a social context (Boomsma 2007). In terms of inclusive fitness, coercion reduces the benefit of attempting to reproduce directly, relative to the benefit of rearing non-descendent kin (Lehmann and Keller 2006). Having addressed the benefits of cooperation above, I will now summarise evidence for enforcement in the following section. Behavioural observations show that insect societies are not the harmonious entities once supposed and that policing and punishment seem to be important mechanisms in solving within-colony conflicts in modern-day insect societies (Ratnieks and Visscher 1989, Ratnieks 1993, Liebig et al. 1999, Monnin and Ratnieks 2001, Foster et al. 2002, Hartmann et al. 2003, Hammond and Keller 2004, Wenseleers et al. 2004a,c, Bourke 2007). Additionally, new theoretical models suggested that the relatedness in present-day social Hymenoptera often is too low to account for their high degree of worker altruism, which might therefore only be explained by coercion (Wenseleers et al. 2004a,c, Ratnieks and Wenseleers 2008). Evidence for enforced altruism comes in several forms (according to Ratnieks and Wenseleers 2008). (i) Worker reproduction and policing. In many social Hymenoptera, workers can still produce unfertilized, male-destined eggs and, all else being equal, they are selected to do so because they are more related to their own sons than to either the sons of their mother queen or sister
188
Judith Korb
workers (Ratnieks 1988). The proportion of worker reproduction in a colony should depend on the costs of worker reproduction measured in colony efficiency (Ratnieks 1988, Wenseleers et al. 2004c). It decreases if workers reproduce instead of caring for the brood and/or if queens can produce more offspring than workers for the same investment. Based on these factors, models predicted that more workers should lay male eggs than is observed in present-day colonies and this restraint from egg-laying is interpreted as enforced altruism (Wenseleers and Ratnieks 2006, Ratnieks and Wenseleers 2008). Yet, there are few studies that actually measured the efficiency costs of worker reproduction in field colonies (Cole and Wiernasz 1999, Dampney et al. 2004). In societies with multiple-mated queens, such as the honeybee, relatedness considerations predict worker policing (i.e. the removal of worker laid eggs by other workers) because workers are more closely related to the queen’s sons than to their sister’s sons (Ratnieks 1988, Kraus and Moritz this volume). Indeed, worker policing occurs often under such situations (Ratnieks and Visscher 1989, Ratnieks 1993, Foster et al. 2002, Helenterä and Sundström 2007), but it also occurs in some species with a single-mated queen, suggesting that it can also have other benefits (Hartmann et al. 2003, Hammond and Keller 2004, Saigo and Tsuchida 2004). Evidence for coercion of egg-laying, and as a consequence reduced worker reproduction, comes from a comparative study of ten species. Species in which worker-laid eggs had a greater chance of being killed had smaller proportions of egg-laying workers (Wenseleers and Ratnieks 2006). Similarly, the presence of egg-laying workers in orphaned colonies (Monnin and Ratnieks 2001, Wenseleers and Ratnieks 2006) where policing is absent has been interpreted as evidence that workers are enforced to behave altruistically. (ii) Control over caste fate. In most social Hymenoptera, caste fate is under the control of the queen or workers. The food provided during larval development is critical for caste determination (Ratnieks et al. 2006). Yet, there are exceptions that support the idea that food control is evidence for coercion. In Melipona stingless bees, queens and workers are reared in identical, closed cells so that there are few possibilities for nestmate workers to influence caste fate during larval development (Bourke and Ratnieks 1999, Ratnieks 2001, Wenseleers and Ratnieks 2004). In some of these species, up to 20% of the larvae develop into queens. This is greatly in excess of the few needed to head a swarm, to replace a mother queen or to invade foreign colonies (Wenseleers et al. 2004b, Wenseleers and Ratnieks 2004). These extra
Social insects, major evolutionary transitions and multilevel selection
189
queens are later executed by the workers (Wenseleers et al. 2004b). A model showed that the number of these extra queens seems to reflect the optimal value from the developing workers’ point of view (Wenseleers et al. 2003, Ratnieks and Wenseleers 2008). Conversely, it was concluded that the lower numbers of new queens in species with worker control over caste fate is a result of coercion (Ratnieks and Wenseleers 2008). A similar phenomenon, where caste fate seems to be under the control of the developing individual, exists in drywood termites, the Kalotermitidae (Lenz 1985, Lenz et al. 1985). In contrast to social Hymenoptera, the workers of termites are not adults, but more or less differentiated (larval) immature stages (Roisin 2000, Korb and Hartfelder 2008). As hemimetabolous insects, these immatures are miniature-adults, which can perform all colony duties and are less dependent on alloparental care than the altricial grub-like larvae of social Hymenoptera (Korb 2007, 2008a). In wood-dwelling termites, to which the drywood termites belong, all individuals are totipotent to remain workers or to develop into soldiers or two kinds of reproductives (Roisin 2000, Korb and Katrantzis 2004, Korb and Hartfelder 2008): winged dispersing alates that found a new nest elsewhere or neotenic, replacement reproductives that inherit the natal breeding position when the same-sex reproductive of the colony dies (in contrast to social Hymenoptera, termite colonies are headed by a male and female reproductive).Thus, conflict over inheritance is predicted to occur when one of the natal reproductives dies (Korb 2005). As in Melipona species, the death of a natal reproductive can lead to an excess development of workers into replacement reproductives (Lenz 1985, Lenz et al. 1982, 1985). Yet, in the end only one pair survives and all other reproductives are being killed. This pattern seems to fit the Melipona example (Ratnieks et al. 2006, Ratnieks and Wenseleers 2008), but this might be a premature conclusion. Although caste fate is similarly ‘self-controlled’ in all Cryptotermes species, in many species only the lost reproductive is replaced without excess development of replacement reproductives. No general pattern in the mode of replacement exists (Lenz et al. 1982, Lenz 1985). Even closely-related sympatric species have different modes of replacement (J. Korb, unpubl. data). Thus, further studies are needed to address whether excess development of reproductives is really evidence for relief from coercion. Currently, it is assumed that there is little evidence for a significant role of parental manipulation in the origin of eusociality (Ratnieks and Wensel-
190
Judith Korb
eers 2008). Yet, coercion is considered to be a major cause of altruism in present-day insect societies. ‘Without coercion, altruism would still occur and societies would still function because family levels of relatedness are sufficient to cause most individuals to act altruistically. However, such societies would be more similar to queenless honey bee colonies or colonies of Melipona bees, in which a large proportion of the individuals tries to reproduce by developing into queens or by laying eggs’ (Ratnieks and Wenseleers 2008). In general, coercion should be more important in species with a higher degree of conflict between colony members. The potential for conflict depends on relatedness but even more important is whether individuals still can reproduce. Accordingly, the potential for the outbreak of conflict – and thus the evolution of coercion – should be most pronounced in sociality syndrome I and II species, where individuals can still gain direct fitness. In many syndrome III species conflicts might have been resolved through the evolution of sterility.
7.3 Social insects and the major transitions in evolution: Common mechanisms What do these insights from social insects tell us about the major evolutionary transitions? Why was cooperation evolutionarily stable and why did it lead to increasing evolutionary complexity? Studies on lower level systems (e.g. the transition to multicellularity studied in Volvocales: Kirk 1998, Michod 1999, Herron and Michod 2008; genomic conflicts: Hurst et al. 1996, Pomiankowski 1999) revealed striking similarities to the results on social insects. At least two common mechanisms prevent the spread of cheaters and favour stable cooperation among social insects: interactions among relatives align the evolutionary interests of individuals and enforcement mechanisms make cheating costly. In the following, I will show similar mechanisms at other levels of the biological hierarchy to illuminate their potential generality. 7.3.1 Common ancestry and aligned interests A major explanatory principle that promotes cooperation over cheating is genetic relatedness, whereby like genotypes preferentially interact. More formally, genetic relatedness is defined as the probability above chance that individuals have identical alleles at one or more loci (see Glossary). Preferential interaction by relatedness ensures that cooperator genotypes
Social insects, major evolutionary transitions and multilevel selection
191
will occur together and that cheater genotypes do the same preventing the exploitation of the former by the latter (Bourke and Franks 1995, Gilbert et al. 2007). In social insects, individuals live in families. Hence, individuals share any ‘cooperator/altruist’ alleles with a high probability through common ancestry and one individual can increase the frequency of its alleles that are carried to the next generation by helping the other individual to reproduce. Note that the important measure of relatedness that determines the evolutionary trajectory of an allele for a social action is relatedness at its locus (Bourke and Franks 1995). Similarly, the cells in multicellular organisms derive from a single cell and are thus identical clones. A notable exception are slime molds: In the slime mold, Dictyostelium, aggregates of independent single cells build a ‘slug’ and ‘fruiting body’ for dispersal when resources in the environment become rare (Queller et al. 2003). The cells of fruiting bodies seem to be closely related (Gilbert et al. 2007). Besides kin recognition, which leads to preferred aggregation of relatives (Mehdiabadi et al. 2006), cheating seems to be rare because of pleiotropic gene effects (Foster et al. 2004). Common descent is probably the most common mechanism to form groups of cooperators at the exclusion of cheaters. Yet, other mechanisms, such as green-beard alleles (see Glossary), habitat heterogeneity or population viscosity in general, may in principle lead to a positive assortment of cooperators (Dawkins 1976, Wilson and Dugatkin 1997, Pepper and Smuts 2002, Axelrod et al. 2004, Penn and Frommen this volume). But the latter mechanisms seem to be uncommon in nature (Grafen 2006). Yet the Gp-9 locus in the red fire ant, Solenopsis invicta, proves a rare example for a green-beard mechanism (Keller and Ross 1998). In multiple-queen colonies, all egg-laying queens are Bb heterozygotes at this locus. Workers that carry the b allele of this gene kill BB queens (which lack the b allele). This implies that allele Gp-9b is a green-beard allele that preferentially induces workers bearing the allele to kill all queens not bearing it. Not all major evolutionary transitions evolved from cooperation within a species: some have arisen as between-species cooperations. This includes the evolution of chromosomes, where ‘species’ are genes, and eukaryotes, which evolved from different prokaryotic ancestors (Maynard Smith and Szathmáry 1995, Cavalier-Smith and Chao 2003, Emelyanov 2003). The equivalent of common descent for cooperation between species is the linkage of the two cooperating partners during multiplication or reproduction (Fig. 7.4). If the reproductive success of both partners is coupled so that an increase in reproductive success of one partner is correlated with an increase in reproductive success of the other, stable cooperation can evolve (Fig. 7.4; Frank 2003).
192
Judith Korb
(a) Common ancestry and aligned future: Related entities with vertical inheritance
(b) No common ancestry and aligned future: Non related entities with vertical inheritance
(c) Common ancestry and not-aligned future: Related entities with horizontal inheritance
(d) No common ancestry and not-aligned future: Non related entities with horizontal inheritance
Fig. 7.4 The impact of common ancestry and aligned future interests for the evolutionary stability of cooperation. Fitness is indicated by the size of the circles; large open circles indicate that entities can invade or leave the group; large closed circles indicate that the group is closed; blue: cooperator; red: cheater that invades from outside; yellow: cheater mutant that arises within the cooperative group. (a) Common ancestry and aligned future (indicated by only closed circles) prevent the spread of cheaters. If a cheater mutant arises within a cooperative group (yellow circle in group with blue circles), it might have a higher within-group fitness (larger circle) than cooperators, but it decreases the fitness of the group (reduced size of enclosing circle). As the cheater cannot spread because of vertical transmission, this reduction in group fitness reduces its own direct fitness which selects against cheating. (b) No common ancestry (indicated by the 1. open circle) and aligned future (indicated by the 2. + 3. closed circle). Cheaters can easily invade the group from outside (red circle coming into the group circle), which reduces the group fitness. Similar to (a) cheaters will not easily spread because their fitness is linked to group fitness. (c) Common ancestry (1.+ 2. closed circle) and not-aligned future (3.+ 4. open circle). A cheater mutant can arise within a cooperative group (yellow circle in group with blue circles). It will spread and annihilate cooperation as it can leave the exploited group through horizontal transmission. (d) No common ancestry and not-aligned future (open circles only). Cheaters can easily invade the group from outside (red circle coming into the group circle), which reduces the group fitness. Cheating will spread and annihilate cooperation as the cheater can leave the exploited group through horizontal transmission.
Social insects, major evolutionary transitions and multilevel selection
193
This process can be studied in symbiotic associations such as fungus growing ants or termites (Korb and Aanen 2003, Mikheyev et al. 2006). Here, the transition from mutualism to parasitism is gradual, as each partner is selected to exploit the other. Yet, if reproduction of both partners is linked, there is an alignment of reproductive interests and interactions are more mutualistic. One mechanism to link reproduction is vertical inheritance, i.e. the transmission of the symbiont via hosts’ offspring (Fig. 7.4; Frank 2003). Alternatively, symbionts can be re-acquired each generation anew (horizontal inheritance), with symbionts reproducing independently from their hosts (e.g. as is the case for viruses, or disease in general; Fig. 7.4). Cytoplasmic elements of eukaryotes are transmitted via vertical inheritance (Cosmides and Tooby 1981, Hoekstra 1990). Both mitochondria and plastids are propagated to the next generation together with the nucleus in the germline. Interestingly, this inheritance is exclusively maternal, i.e. cytoplasmic elements are propagated only via eggs but not via sperm. Uniparental inheritance reduces the amount of genetic mixing of cytoplasmic elements from one generation to the next, and thus reduces competition. Hence, it is discussed to be an adaptation to reduce genetic conflict (Cosmides and Tooby 1981). (Note, at the same time uniparental inheritance creates new conflict, see below). Vertical inheritance aligns the reproductive interests of both partners because, if the symbiont harms its host, and thus decreases the host’s reproductive success, it indirectly harms itself (Fig. 7.4). Similar to relatedness, the linkage between both partners favours self-restraint. Furthermore, it provides a mechanism for cooperating partners to stay together and prevents infiltration by cheaters. In summary, for both stable cooperation within and between species, mechanisms are essential that (i) stably assort groups/pairs of cooperators in space and time and separate them from potential cheaters, and (ii) align the reproductive interests of cooperators over time. Common ancestry, through classical relatedness or vertical inheritance, seems to be a major mechanism that led to stable cooperation. Through common ancestry and linked/aligned future interests, new evolutionary levels can emerge (Fig. 7.4). 7.3.2 Conflict and conflict resolution Through common ancestry and aligned future, organisms appear as homogeneous entities whereupon selection acts. Yet, similar to social insects, they are not the harmonious entities that they were once considered to be. Evidence has accumulated indicating that conflict occurs at all levels below the individual (Burt and Trivers 2006).
194
Judith Korb
Nuclear genes in a diploid genome generally cooperate because each allele has an equal probability of being represented in a gamete. This fairness is guaranteed by meiosis, which aligns the interests of nuclear genes (Frank 2003). However, there are genes, segregation distorters, which cheat during meiosis or gametogenesis and are therefore present in more than half of the functional gametes. The most studied examples of segregation distorters are sd in Drosophila melanogaster (Temin et al. 1991), the t-haplotype in Mus musculus (Lyon 1991, Ardlie and Silver 1996, 1998) and sk in Neurospora fungi (Turner and Perkins 1991, van der Gaag et al. 2000). Segregation distorters that are present in sexual chromosomes (as the X chromosome in several Drosophila species) are denominated sexratio distorters, as they induce a sex-ratio bias in the offspring of the carrier. These genes cheat during transmission to the next generation. Homing endonuclease genes (HEG) convert their rival allele into a copy of themselves, and are thus inherited by nearly all meiotic daughter cells of a heterozygote cell (Gutz and Leslie 1976). They achieve this imbalance by encoding an endonuclease that breaks the rival allele. This break is repaired by using the sequence of the HEG as template. A second class of selfish genes cheats by multiplying themselves within the genome. For example, transposons are autonomously replicating genes that encode the ability to move to new positions in the genome and therefore accumulate in the genomes (reviewed in Craig et al. 2002). They can replicate themselves in spite of being detrimental to the rest of the genome. At the next level within eukaryotes, conflict also occurs between the cytoplasmatic elements and the nuclear genes. As detailed above, cytoplasmatic elements are transmitted to the next generation via maternal inheritance. Thus, they have no evolutionary interest in the production of male offspring, which do not transmit mitochondria and plastids. By contrast, the nuclear genome is transmitted through female and male offspring equally, and an evolutionary stable 1:1 sex ratio is favoured. Thus, conflict over sex ratios arises. One outcome of this conflict seems to be cytoplasmic male sterility (CMS) in many flowering plants: Most plants are hermaphrodites – they produce both pollen and ovules – but their mitochondria are only transmitted through ovules. So, mitochondrial mutants that abolish male production, causing CMS, are positively selected (Lewis 1941). Because nuclear genes are transmitted equally through pollen and ovules, a nuclear gene causing male sterility will spread only if it more than doubles female fertility. As a result of this conflict, the spread of CMS genes usually selects for nuclear suppressor genes that counteract the CMS gene and restore male fertility (e.g. Budar et al. 2003). Due to this co-evolutionary arms race, when nuclear genes have the upper hand, CMS genes are often hidden within a population. They only re-appear when
Social insects, major evolutionary transitions and multilevel selection
195
CMS genes are ‘uncoupled’ from their nuclear repressor genes during cross-population- or interspecific hybridisation (Budar et al. 2003). Mechanisms which align the reproductive interests of the selfish gene and the rest of the genome, or which make drive directly more costly for the selfish gene (e.g. through punishment) could result in conflict resolution. Yet, while the former seems to be widespread – for instance, the physical linkage of genes in chromosomes or the process of meiosis – direct punishment as is found in social insects seems to be rare, the closest equivalent being nuclear repressor alleles. At the inter-cell level of multicellular organisms, conflicts seem to be less common. Although cancer is a well-known example of cells replicating selfishly at the cost of the organism, lethal cancer is strongly selected against if expressed before cessation of reproduction. Reasons for the rarity of selfish cells in multicellular organisms include their common descent from a single cell and the early separation of germ and soma in animals. This leads to limited opportunities for cheater mutants to invade and to aligned interests of the cells of an organism. Notable exceptions are the canine transmissible venereal disease, and its analogue in the Tasmanian devils, the devil facial tumor disease, which are contagious tumors that are transmitted directly from individual to individual (e.g. Murgia et al. 2006, Pearse and Swift 2006). This horizontal transmission leads to non-aligned future interests (Fig. 7.4).
7.4 The level of selection debate: multilevel selection So far, we have seen that animals consist of a hierarchy of selection levels and that the entities at each level do not always agree in their evolutionary interests, so that conflicts can arise. The question then becomes: At which level does selection act? What is the unit of selection? There has been a longstanding debate about the level of selection (Reeve and Keller 1999). Before the 1960s it was not uncommon to regard species as the unit of selection (as reviewed by Williams 1966). Wynne-Edwards (1962) used adaptations at the group level to reason about the evolution of population size. He and many others suggested that self-restraint in reproduction (voluntary birth control) should evolve to prevent overexploitation of resources within populations because it is good for the survival of the species. Such ‘good for the species’ arguments are examples of the ‘old’ group selection, where behaviours were carelessly explained as group- or species-level benefits (Grafen 1984). As Williams (1966) pointed out, self-restraint will generally not be stable. As seen in the ‘tragedy of the commons’ (Hardin
196
Judith Korb
BOX 7.1 The Price equation and multilevel selection (after Wenseleers et al. in press) The Price equation (Price 1970, 1972) is the foundation for a universally applicable theory of selection (for details see Frank 1995, Wenseleers et al. in press). Consider a population of n entities indexed by j. These entities are usually individuals, but they can also be genes within genomes, cells, or social groups. Let wj be the absolute fitness of the j th entity (i.e. how many successful offspring entities it leaves in the next generation), and vj the fitness relative to the population average (wj/w ¯ ). The standard form of Price’s theorem states that the average change in the value of some trait z (Δz) from one generation to the next is given by wj wj z cov , z j E z j cov v j , z j E v j z j w w
(1)
where the terms cov and E denote covariance (a measure of how two variables change together; here vj and zj) and expectation (arthimetric average), respectively, both taken over all entities in the population. The term Δzj is the change in the entity’s trait value zj between parent (zj) and offspring (zj’), where Δzjz = zj’ – zj. The first term in equation (1) generally reflects the effects of selection (Price 1970, Frank 1995, Okasha 2006). This can be illustrated by decomposing it into two separate components: cov(vj, zj) = βvz.Vz, with a leastsquares regression coefficient, βvz., and a statistical variance Vz. The regression term β describes the intensity of selection (whether the trait of interest z will increase or decrease the relative fitness v of the focal entity) and the trait-variance term V gives us the rate at which selection acts. The more variable the focal trait, the more possibilities for selection. The second term in equation (1), E(vj Δzj), captures all effects other than selection. Social evolution in terms of opposing selection can be analysed as follows: The standard Price equation (1) must be slightly changed in notation. We will use subscripts i and ij to refer to the i th group and the j th individual within group i, respectively. The evolutionary change in the average gene frequency g is a function of the mean fitness W and mean gene frequency G in the i th group w g covwi , g i Ei wi g i
(2)
Equation (2) describes selection on the groups in our population. To account for selection on individuals within each group, the expectation term Ei(wiΔgi) can easily be expended to capture the effects of within-group selection
Social insects, major evolutionary transitions and multilevel selection
Ei wi g i Ei cov i wij , g ij E j.i wij g ij
197
(3)
where the right-hand side is a second version of the standard Price equation, but on the next lower level in the selective hierarchy, i.e. it describes withingroup selection. Substituting equation (3) into equation (2) yields:
w g covwi , g i Ei cov i wij , g ij E j.i wij g ij
(4)
where the expectations and covariances are taken over their subscripts, with i standing for groups, ij standing for individual j of group i, and j.i for individuals j for a specified group i. The first covariance term captures the effects of the gene on group success, the second covariance term captures the effect of the gene on the relative success of individuals within a group, and the final term accounts for any effects caused by processes other than selection. One of the beauties of Price’s equation is that it can be expanded to include multiple levels of selection until all relevant levels are included. Doing so, and disregarding effects other then selection, the last term (Ej.i(wijΔgij)) can be set to zero. As the mean fitness W is always greater than zero, a gene for a social trait is selected for when
covwi , g i Ei cov i wij , g ij wi gi V gi wij gij.i V gij .i 0
(5)
where the covariances are broken up into their constituent regression and variance terms. In this inequality, the two components reflect between-group and within-group (among individual) selection, respectively. Each level of selection comprises a selective response which equals the intensity of selection of that level weighed by the genetic variance present at that level. The between- and within-group genetic variances can be calculated using population genetics, namely Wright’s hierarchical F-statistics (Yang 1998). Importantly, however, they can also be expressed as a function of genetic relatedness, which links back to kin selection (Hamilton 1975).
1968), cheaters that reproduce at the expense of others will be evolutionarily favoured. This insight, together with inclusive fitness theory (Hamilton 1963, 1964), led to the general consensus that groups of individuals cannot be units of selection. Instead, as popularised by Dawkins (1976), genes are the ultimate units of selection and organisms can be viewed as higher-level ‘vehicles’ upon which selection acts. As a consequence, during the 1960s and 1970s, group selection became such a heretical concept that many evolutionary biologists stopped reading the actual literature (Wilson 1997, 2007). Parallel to this development, mainly Price (1970, 1972), Hamilton (1975) and Wade (1978) developed quantitative models, which are now often referred to as the ‘new’ group selection theory (common other terms:
198
Judith Korb
intrademic group selection, trait-group selection, levels of selection or multilevel selection; I will use the latter in the following). These models date back to some simple models by Wright and Haldane in the 1930s (Gardner and Foster 2008). In Hamilton’s (1996) autobiographical account, he recalls excitedly telling Price that ‘through a ‘group-level’ extension of his formula I now had a far better understanding of group selection and was possessed of a far better tool for all forms of selection acting at one level or at many than I had ever had before’ (Wilson 2007:173). These models showed that group selection can occur, yet ‘arguments must be applied carefully without neglecting competition between individuals within each of these units’ (Gardner and Foster 2008) as was done before in the case of the old group selection arguments. Using Price’s covariance theorem, this approach phrases social evolution in terms of selection within and between groups (BOX 7.1), rather than separating individual fitness into direct and indirect components. This partition can be very useful for conceptualising the potential tension between the interests of individuals and the group (Hamilton 1975). For example, it can be analysed whether social traits, which may be favoured at one level but counter-selected at another level, would still evolve. Interests of entities at the same levels are aligned if within-group variance is small compared to between-group variance. Mechanisms to reduce within-group variance include relatedness or any other mechanism that leads to the formation of groups composed of kind (see above). One of the beauties of the multilevel selection approach is that the same conceptual framework can be applied to all levels of the biological hierarchy, from genes to groups of organisms (Wilson 1997), because it can be mathematically formalised with Price’s covariance equations whenever there is a hierarchical cluster of groups (BOX 7.1). Addressing cooperation within species, this equation is mathematically equivalent to the inclusive fitness approach. It is important to note that the multilevel selection approach is not in contradiction to inclusive fitness or similar fitness approaches (e.g. neighbour modulated fitness). Rather, they are complementary perspectives to look at the same problem. It is sad that there is a continuing tendency to mistakenly assume that switching between the methods also means that different biological processes are at play (e.g. Wilson 1975, Sober and Wilson 1997, Fehr and Fischbacher 2003, Wilson and Hölldobler 2005; for a thorough treatise of the problem see: e.g. Foster et al. 2006). Each approach has its advantages and disadvantages (Wenseleers et al. in press). Some important caveats of the multilevel selection approach are that it still suffers from semantic difficulties (Okasha 2006, West et al. 2007) or that, when wrongly applied, nonsocial traits that are independent of group effects will be attributed to the
Social insects, major evolutionary transitions and multilevel selection
199
operation of between-group selection (Heisler and Damuth 1987, Gardner and Foster 2008). Probably the most important problem at present is that multilevel selection theory comprises a large amount of verbal discussion and a collection of mathematical models that appear to provide helpful insights but a conceptual unity is still missing (reviewed in Okasha 2006). There are two main advantages of adopting a multilevel selection perspective (Wenseleers et al. in press). First, it offers a possibility to analyse selection at more than two levels. Thus, it can cover tensions at all levels of the biological hierarchy and can make quantitative predictions about the outcome. Second, in social insects, it might offer a possibility to switch from the relatedness-centered research to studies that address those factors that are hidden in the c and b term of Hamilton’s rule. This might be especially promising as insect societies with their colony level phenomena (e.g. self-organisation) are clearly more than the sum of their components.
7.5 Conclusions, open questions and future research Insect societies are more than the sum of their components. Through the interaction with many individuals, more than additive benefits derive, which probably explains the impressive evolutionary and ecological success of social insects. These non-linear effects are also the basis for the efficiency costs that often seem to prevent the occurrence of conflicts (see above). Such colony-level phenomena (emergent properties) ‘equip’ a colony with new properties, including: (i) Division of labour. Division of labour allows specialisation with increased efficiency in the performance of tasks (e.g. Beshers and Fewell 2001). In social insects this specialisation is commonly reflected in the evolution of morphological castes, each caste being adapted for particular tasks. Due to division of labour, queens are released from brood care and can concentrate on egg-laying. An impressive example are queens of the fungus-growing termite Macrotermes bellicosus: they increase in body size more than 10fold as they age (Fig. 7.1). This physogastry is caused by an increase in the number of active ovarioles, so that queens become true ‘egg-laying’ machines that can produce more than 20 millions eggs daily! These queens can hardly move around, let alone care for their brood. This extreme specialisation is only possible because workers care for the brood and build a protective nest, and specialised soldiers defend them in case of danger. Such a specialisation might also release individuals from de-
200
Judith Korb
velopmental constraints (Roux et al. 2009). For instance, a trade-off between fecundity and defense (i.e. investment in weapons is associated with reduced fecundity) seems to be common in many male insects (Simmons and Emlen 2006). By devoting different individuals to different castes, this trade-off can be solved (Roux et al. 2009). Yet, the trade-off between defense and fecundity might be reflected in the caste composition of the colony; the caste for defense, the soldiers, are always sterile and the reproductives generally lack defensive adaptations. Thus, the trade-off might have shifted from the individual to the colony level (Roux et al. 2009). (ii) Information transfer. Living in social groups requires information transfer (communication) between group members. Indeed, social insects have evolved very elaborate types of communication. Communication during foraging is often achieved through trail pheromones (Kaib et al. 1982): chemical substances are deposited by foragers on the ground when a rewarding food item is found. Through positive feedback processes (i.e. each successful forager deposits the chemical blend), this can lead to the recruitment of nestmates to rewarding food sites (Bonabeau et al. 1997). Yet, communication via trail pheromones only works if there is a minimum number of foragers (Beekman et al. 2001), otherwise the pheromones evaporate too quickly to provide information. The equivalent to trail pheromones in honeybees is their ‘dance language’ (von Frisch 1946, 1967, Lindauer 1954, Dyer 2002, Grüter and Farina 2009, Pahl et al. this volume). Such ‘sophisticated’ communication mechanisms provide insect colonies with very efficient means to exploit food resources. Mass recruitment becomes possible that allows the exploitation of new food sources, inaccessible to solitary insects, as well as their monopolisation from neighbours. (iii) Building. The existence of a protective nest is a central characteristic of all social insects (Seger 1991). It is a necessary requirement to have a common place where individuals interact and the brood is reared. Yet, the nests of social insects are more than that. Through selforganisational processes elaborate ‘buildings’ can be constructed, especially in species with large colony sizes (Hansell 1984, Wenzel 1991, Heinrich 1993, Turner 2000; Fig. 7.1). Such mounds/nests protect the colony against predators and harsh environmental conditions, providing homeostatic conditions that are largely independent of environmental fluctuations, so that a year-round production of offspring is possible. An especially striking example is the fungus-cultivating termite M. bellicosus (Fig. 7.1). It has air-conditioned mounds with efficient mechanisms for the exchange of respiratory gases that provide constant temperatures, fluctuating less than 2°C daily and annually
Social insects, major evolutionary transitions and multilevel selection
201
(Lüscher 1961, Korb and Linsenmair 2000, Korb 2003). The construction and maintenance of such structures is only possible because the individuals live in large colonies. Although we are only beginning to understand how macroscopic features of insect buildings emerge, the key lies in self-organisation – the emergence of higher-level patterns and collective action from simple low-level behaviours (e.g. Bonabeau et al. 1997, Camazine et al. 2001). Similar to the social insects, the lower level selection units are also characterised by properties that are more than the sum of their components. Multicellular organisms and genomes share division of labour with social insects. In multicellular organisms, different organs are specialised in performing different tasks (e.g. the gonads for reproduction, the liver for disposal of metabolic waste or the skin for protection), as are the genes of chromosomes that encode these different functions (although in a less simple 1:1 correspondence). Interestingly, recent data at the genome level indicate that gene effects at the phenotype are also less additive than formerly thought. There are many non-linear epigenetic effects between the interactions of genes that determine the phenotype. This again reminds us of the interactions of nestmates in an insect colony, which result in new, emergent phenotypes at the colony level. Whether the genetic architecture of organisms and their phenotypes is governed by the same principles as insect colonies will be an exciting question for future researchers to address. The rapidly increasing technology for fast and cheap sequencing will accumulate enough genomic data to reveal patterns of organisation. Unraveling the mechanisms and algorithms between nestmate interactions and their resulting colony phenotypes might help to interpret the patterns observed at the genotype-phenotype transition. It might be these emergent properties that arise through the interaction of many ‘simple’ units that explain the evolutionary stability of the ‘major transitions in evolution’. These group-level benefits that provide the new, more complex level with beneficial attributes beyond those possible at the lower level, provide a high direct fitness benefit for cooperation as new niches can be occupied or old ones exploited more efficiently. These benefits have scarcely been measured. Taking a multilevel selection perspective and comparing the reproductive success of insect colonies with various traits might become an important aim for future studies. By manipulating the degree of cooperation and conflict within insect societies it is possible to measure the benefits and costs of cooperation at the colony level and to transfer them back to the individual. Thus, for instance, efficiency costs of conflicts can be quantified. Measuring these costs at the colony level − within a multilevel selection framework, which does not forget the indi-
202
Judith Korb
vidual level and the covariance (= relatedness, see BOX 7.1) between group members − it might be possible to determine the importance of ecological factors. During the last two decades, most social insect research was devoted to measuring the influence of relatedness on social evolution, and we have learned a lot. Yet, as Hamilton’s rule states that relatedness cannot explain everything, now might be the right time to consider and measure the costs and benefits of social interactions. Tsuji’s (1995) work on the ant Pristomyrmex pungens might serve as an illustrative example. In this species, workers reproduce pathenogenetically and a worker dimorphism exists with large reproducing workers having a higher within-colony fitness than small reproducing worker. However, large workers reduce a colony’s fitness at the between-colony level. Using a multilevel selection approach (contextual analysis) and partitioning of covariance Tsuji (1995) showed that selection on the proportion of foragers appeared to be responsible for the evolutionary maintenance of cooperative breeding in this species. A further promising approach in this context is provided by social network analyses. This analytical tool examines social groups as networks of nodes connected by social ties (e.g. Wey et al. 2008, Krause et al. 2009). Thus, network analyses are especially suited to characterise, analyse and compare interactions among colony members at the colony level, and they are probably an appropriate means to quantify emergent colony properties. Social insects have become model organisms for the study of social evolution. We have learned that relatedness through common ancestry is an important means to favour cooperation and altruism. It is an efficient mechanism that prevents cheating because like genotypes interact preferentially. Similar mechanisms that exclude cheaters and align the reproductive interests of group members can also be found at other levels of the evolutionary hierarchy. Future research might take a multilevel selection perspective to quantify the benefits and costs of cooperation, which often seem to have non-additive fitness consequences, so that insect societies and all major evolutionary transitions alike are being recognised as more than the sum of their components.
Acknowledgements I thank Peter Kappeler for the invitation to contribute to this volume. He, Kevin Foster and two anonymous referees also provided very helpful comments on the manuscript.
Social insects, major evolutionary transitions and multilevel selection
203
GLOSSARY Altruism: Carrying out an action that benefits a recipient (i.e. increases the evolutionary fitness of the recipient) at a cost to an individual’s own lifetime fitness (i.e. direct fitness) Cooperation: Carrying out an action that benefits a recipient without incurring a net cost to the actor Division of labour: Specialisation of cooperative labour in specific, circumscribed tasks Emergent properties: Emergence is the way complex systems can arise out of relatively simple interactions. Emergent properties can appear when a number of simple entities operate and form more complex behaviours as a collective. Green-beard gene: A gene that causes a phenotypic effect (such as the presence of a green-beard or any other conspicuous feature), allows the bearer of this feature to recognise it in other individuals, and causes the bearer to behave differently towards other individuals depending on whether or not they possess the feature. Relatedness: A genetic correlation between individual loci or organisms Social life: Living in a group with cooperative or altruistic interactions among individuals Social organisation: The characteristics of a social group, e.g. its sex ratio or its reproductive skew
References Alexander RD (1974) The evolution of social behavior. Annu Rev Ecol Syst 5:325-383 Ardlie KG, Silver LM (1996) Low frequency of mouse t haplotypes in wild populations is not explained by modifiers of meiotic drive. Genetics 144:17871797 Ardlie KG, Silver LM (1998) Low frequency of t haplotypes in natural populations of house mice (Mus musculus domesticus). Evolution 52:1185-1196 Axelrod R, Hammond RA, Grafen A (2004) Altruism via kin-selection strategies that reply on arbitrary tags with which they coevolve. Evolution 58:1833-1838 Beekman M, Sumpter DJT, Ratnieks FLW (2001) Phase transition between disordered and ordered foraging in Pharaoh’s ants. Proc Natl Acad Sci USA 98:9703-9706 Beshers SN, Fewell JH (2001) Models of division of labor in social insects. Annu Rev Entomol 46:413-440 Bonabeau E, Theraulaz G, Deneuborug JL, Aron S, Camazine S (1997) Selforganization in social insects. Trends Ecol Evol 12:188-193
204
Judith Korb
Boomsma JJ (2007) Kin selection versus sexual selection: why the ends do not meet. Curr Biol 17:R673-R683 Bourke AFG (1997) Sociality and kin selection in insects. In: Krebs JR, Davies NB (eds) Behavioural Ecology: An Evolutionary Approach, 4th edn. Blackwell, Oxford, pp 203-227 Bourke AFG (2007) Social evolution: community policing in insects. Curr Biol 17:R519-R520 Bourke AFG, Franks NR (1995) Social Evolution in Ants. Princeton University Press, Princeton Bourke AFG, Ratnieks FLW (1999) Kin conflict over caste determination in social Hymenoptera. Behav Ecol Sociobiol 46:287-297 Budar F, Touzet P, De Paepe R (2003) The nucleo-mitochondrial conflict in cytoplasmic male sterilities revisited. Genetica 117:3-16 Burt A, Trivers R (2006) Genes in Conflict. The Biology of Selfish Genetic Elements. Harvard University Press, Cambridge/MA Camazine S, Deneubourg JL, Franks NR, Sneyd J, Theraulaz G, Bonabeau E (2001) Self-Organization in Biological Systems. Princeton University Press, Princeton/NJ Cant MA, Field J (2005) Helping effort in a dominance hierarchy. Behav Ecol 16:708-715 Cant MA, Llop JB, Field J (2006) Individual variation in social aggression and the probability of inheritance: theory and a field test. Am Nat 167:837-852 Cavalier-Smith T, Chao EE-Y (2003) Phylogeny of choanozoa, apusozoa, and other protozoa and early eukaryote megaevolution. J Mol Evol 56:540-563 Chapman TW, Crespi BJ, Perry SP (2008) The evolutionary ecology of eusociality in Australian gall thrips: a ‘model clades’ approach. In: Korb J, Heinze J (eds) Ecology of Social Evolution. Springer, Heidelberg, pp 57-83 Charnov EL (1978) Evolution of eusocial behavior − offspring choice or parental parasitism. J Theor Biol 75:451-465 Cole BJ, Wiernasz DC (1999) The selective advantage of low relatedness. Science 285:891-893 Cosmides ML, Tooby J (1981) Cytoplasmic inheritance and intragenomic conflict. J Theor Biol 89:83-129 Craig NL, Craigie R, Gellert M, Lambowitz AM (2002) Mobile DNA II. ASM Press, Washington/DC Crozier RH, Pamilo P (1996) Evolution of Social Insect Colonies: Sex Allocation and Kin Selection. Oxford University Press, Oxford Dampney JR, Barron AB, Oldroyd BP (2004) Measuring the cost of worker reproduction in honeybees: work tempo in an ‘anarchic’ line. Apidologie 35:8388 Dawkins R (1976) The Selfish Gene. Oxford University Press, Oxford Dyer FC (2002) The biology of the dance language. Annu Rev Entomol 47:917949 Emelyanov VV (2003) Mitochondrial connection to the origin of the eukaryotic cell. Europ J Biochem 270:1599-1618
Social insects, major evolutionary transitions and multilevel selection
205
Emlen ST (1997) Predicting family dynamics in social vertebrates. In: Krebs JR, Davies NB (eds) Behavioural Ecology: An Evolutionary Approach, 4th edn. Blackwell, Oxford, pp 228-253 Fehr E, Fischbacher U (2003) The nature of human altruism. Nature 425:785-791 Field J (2008) The ecology and evolution of helping in hover wasps (Hymenoptera: Stenogastrinae). In: Korb J, Heinze J (eds) Ecology of Social Evolution. Springer, Heidelberg, pp 85-107 Field J, Foster W, Shreeves G, Sumner S (1998) Ecological constraints on independent nesting in facultatively eusocial hover wasps. Proc R Soc Lond B 265:973-977 Field J, Shreeves G, Sumner S (1999) Group size, queuing and helping decisions in facultatively eusocial hover wasps. Behav Ecol Sociobiol 45:378-385 Field J, Shreeves G, Sumner S, Casiraghi M (2000) Demographic advantages in the evolution of eusociality. Nature 404:869-871 Foster KR (2008) Behavioral ecology: altruism. In: Encyclopedia of Ecology. Elsevier, Amsterdam, pp 154-159 Foster KR, Xavier JB (2007) Cooperation: bridging ecology and sociobiology. Curr Biol 17:R319-R321 Foster KR, Gulliver J, Ratnieks FLW (2002) Worker policing in the European hornet Vespa crabro. Insectes Soc 49:41-44 Foster KR, Shaulsky G, Strassmann JE, Queller DC, Thompson CRL (2004) Pleiotropy as a mechanism to stabilize cooperation. Nature 431:693-696 Foster KR, Wenseleers T, Ratnieks FLW (2006) Kin selection is the key to altruism. Trends Ecol Evol 21:57-60 Frank SA (1995) George Price’s contributions to evolutionary genetics. J Theor Biol 175:373-388 Frank SA (2003) Perspective: repression of competition and the evolution of cooperation. Evolution 57:693-705 Gadau J, Fewell JH (2009) Organization of Insect Societies: From Genes to Sociocomplexity. Harvard University Press, Cambridge/MA Gardner A, Foster KR (2008) The evolution and ecology of cooperation − history and concepts. In: Korb J, Heinze J (eds) Ecology of Social Evolution. Springer, Heidelberg, pp 1-36 Gilbert OM, Foster KR, Mehdiabadi NJ, Strassmann JE, Queller DC (2007) High relatedness maintains multicellular cooperation in a social amoeba by controlling cheater mutants. Proc Natl Acad Sci USA 104:8913-8917 Grafen A (1984) Natural selection, kin selection and group selection. In: Krebs JR, Davies NB (eds) Behavioural Ecology: An Evolutionary Approach, 2nd edn. Blackwell, Oxford, pp 62-84 Grafen A (2006) Various remarks on Lehmann and Keller’s article. J Evol Biol 19:1397-1399 Grüter C, Farina WM (2009) The honeybee waggle dance: can we follow the steps? Trends Ecol Evol 24:242-247 Gutz H, Leslie JF (1976) Gene conversion: a hitherto overlooked parameter in population-genetics. Genetics 83:861-866 Hamilton WD (1963) The evolution of altruistic behavior. Am Nat 97:354-356
206
Judith Korb
Hamilton WD (1964) The genetical evolution of social behaviour, I and II. J Theor Biol 7:1-52 Hamilton WD (1975) Innate social aptitudes of man: an approach from evolutionary genetics. In: Fox R (ed) Biosocial Anthropology. Malaby, London, pp 133-155 Hamilton WD (1996) Narrow Roads of Gene Land. WH Freeman, Oxford Hamilton WD, May RM (1977) Dispersal in stable habitats. Nature 269:578-581 Hammond RL, Keller L (2004) Conflict over male parentage in social insects. PLoS Biol 2:e248, doi:10.1371/journal.pbio.0020248 Hansell MH (1984) Animal Architecture and Building Behaviour. Longman, London Hardin G (1968) The tragedy of the commons. Science 162:1243-1248 Hartmann A, Wantia J, Torres JA, Heinze J (2003) Worker policing without genetic conflicts in a clonal ant. Proc Natl Acad Sci USA 100:12836-12840 Heinrich B (1993) The Hot-Blooded Insects. Strategies and Mechanisms of Thermoregulation. Harvard University Press, Cambridge/MA Heinsohn RG (2004) Parental care, load-lightening, and costs. In: Koenig WD, Dickinson JL (eds) Ecology and Evolution of Cooperative Breeding in Birds. Cambridge University Press, Cambridge, pp 67-80 Heisler IL, Damuth J (1987) A method for analyzing selection in hierarchically structured populations. Am Nat 130:582-602 Helenterä H, Sundström L (2007) Worker reproduction in Formica ants. Am Nat 170:E14-E25 Helms Cahan S, Blumstein DT, Sundström L, Liebig J, Griffin A (2002) Social trajectories and the evolution of social behaviour. Oikos 96:206-216 Herron MD, Michod RE (2008) Evolution of complexity in the volvocine algae: transitions in individuality through Darwin’s eye. Evolution 62:436-451 Herron MD, Hackett JD, Aylward FO, Michod RE (2009) Triassic origin and early radiation of multicellular volvocine algae. Proc Natl Acad Sci USA 106:3254-3258 Hoekstra RF (1990) Evolution of uniparental inheritance of cytoplasmic DNA. In: Maynard Smith J, Vida G (eds) Organizational Constraints on the Dynamics of Evolution. Manchester University Press, Manchester, pp 269-278 Hurst LD, Atlan A, Bengtsson BO (1996) Genetic conflicts. Q Rev Biol 71:317364 Johnstone RA (2000) Models of reproductive skew: a review an synthesis. Ethology 106:5-26 Kaib M, Bruinsma O, Leuthold RH (1982) Trail-following in termites: evidence for a multicomponent system. J Chem Ecol 8:1193-1205 Karsai I, Wenzel JW (1998) Productivity, individual-level and colony-level flexibility, and organization of work as consequences of colony size. Proc Natl Acad Sci USA 96:8665-8669 Keller L, Ross KG (1998) Selfish genes: a green beard in the red fire ant. Nature 394:573-575 Kirk DL (1998) Volvox: Molecular-Genetic Origins of Multicellularity and Cellular Differentiation. Cambridge University Press, Cambridge
Social insects, major evolutionary transitions and multilevel selection
207
Koenig WD, Dickinson J (2004) Ecology and Evolution of Cooperative Breeding in Birds. Cambridge University Press, Cambridge Kokko H, Johnstone RA (1999) Social queuing in animal societies: a dynamic model of reproductive skew. Proc R Soc Lond B 266:571-578 Korb J (2003) Thermoregulation and ventilation of termite mounds. Naturwissenschaften 90:212-219 Korb J (2005) Regulation of sexual development in termites: mutilation, pheromonal manipulation or honest signal? Naturwissenschaften 92:45-49 Korb J (2006) Limited food induces nepotism in drywood termites. Biol Lett 2:364-366 Korb J (2007) Workers of a drywood termite do not work. Front Zool 4:e7, doi:10.1186/1742-9994-4-7 Korb J (2008) The ecology of social evolution in termites. In: Korb J, Heinze J (eds) Ecology of Social Evolution. Springer, Heidelberg, pp 151-174 Korb J, Aanen DK (2003) The evolution of uniparental transmission of fungal symbionts in fungus-growing termites (Macrotermitinae). Behav Ecol Sociobiol 53:65-71 Korb J, Hartfelder K (2008) Life history and development − a framework for understanding developmental plasticity in lower termites. Biol Rev 83:295-313 Korb J, Heinze J (2008a) Ecology of Social Evolution. Springer, Heidelberg Korb J, Heinze J (2008b) The ecology of social life: a synthesis. In: Korb J, Heinze J (eds) Ecology of Social Evolution. Springer, Heidelberg, pp 245-259 Korb J, Katrantzis S (2004) Influence of environmental conditions on the expression of the sexual dispersal phenotype in a lower termite: implications for the evolution of workers in termites. Evol Dev 6:342-352 Korb J, Linsenmair KE (2000) Ventilation of termite mounds: new results require a new model. Behav Ecol 11:486-494 Krause J, Lusseau D, James R (2009) Animal social networks: an introduction. Behav Ecol Sociobiol 63:967-973 Lehmann L, Keller L (2006) The evolution of cooperation and altruism − a general framework and a classification of models. J Evol Biol 19:1365-1376 Lenz M (1985) Is inter- and intraspecific variability of lower termite neotenic number due to adaptive thresholds for neotenic elimination? − considerations from studies on Porotermes adamsoni (Froggatt) (Isoptera: Termopsidae). In: Watson JAL, Okot-Kotber BM, Noirot C (eds) Caste Differentaition in Scoial Insects. Pergamon Press, Oxford, pp 125-146 Lenz M, McMahan EA, Williams ER (1982) Neotenic production in Cryptotermes brevis (Walker): influence of geographical origin, group composition, and maintenance conditions (Isoptera: Kalotermitidae). Insectes Soc 29:148-163 Lenz M, Barrett A, Williams ER (1985) Reproductive strategies in Cryptotermes: neotenic production in indigenous and ‘tramp’ species in Australia (Isoptera: Kalotermitidae). In: Watson JAL, Okot-Kotber BM, Noirot C (eds) Caste Differentiation in Social Insects. Pergamon Press, Oxford, pp 147-164 Lewis D (1941) Male sterility in natural populations of hermaphrodite plants: the equilibrium between females and hermaphrodites to be expected with different types of inheritance. New Phytol 40:56-63
208
Judith Korb
Liebig J, Peeters C, Hölldobler B (1999) Worker policing limits the number of reproductives in a ponerine ant. Proc R Soc Lond B 266:1865-1870 Lindauer M (1954) Temperaturregulierung und Wasserhaushalt im Bienenstaat. Z Vgl Physiol 36:391-432 Lüscher M (1961) Air-conditioned termite nests. Sci Am 205:138-145 Lyon MF (1991) The genetic basis of transmission-ratio distortion and malesterility due to the tert-complex. Am Nat 137:349-358 Margulis L (1981) Symbiosis in Cell Evolution. Freeman and Co, San Fransisco Maynard Smith J (1964) Group selection and kin selection. Nature 201:1145-1147 Maynard Smith J, Szathmáry E (1995) The Major Transitions in Evolution. WH Freeman, Oxford Mehdiabadi N, Jack CN, Farnham TT, Platt TG, Kalla SE, Shaulsky G, Queller DC, Strassmann J (2006) Kin preference in a social microbe. Nature 442:881882 Michener CD (1964) Reproductive efficiency in relation to colony size in hymenopterous societies. Insectes Soc 11:317-342 Michener CD, Brothers DJ (1974) Were workers of eusocial hymenoptera initially altruistic or oppressed. Proc Natl Acad Sci USA 71:671-674 Michod RE (1999) Individuality, immortality, and sex. In: Keller L (ed) Levels of Selection in Evolution. Princeton University Press, Princeton, pp 53-74 Mikheyev AS, Mueller UG, Abbott P (2006) Cryptic sex and many-to-one coevolution in the fungus-growing ant symbiosis. Proc Natl Acad Sci USA 103:10702-10706 Monnin T, Ratnieks FLW (2001) Policing in queenless ponerine ants. Behav Ecol Sociobiol 50:97-108 Murgia C, Pritchard J, Kim S, Fassati A, Weiss R (2006) Clonal origin and evolution of a transmissible cancer. Cell 126:477-487 Nonacs P, Reeve HK (1995) The ecology of cooperation in wasps: causes and consequences of alternative reproductive decisions. Ecology 76:953-967 Okasha S (2006) Evolution and the Levels of Selection. Oxford University Press, Oxford Pearse AM, Swift K (2006) Allograft theory: transmission of devil facial-tumour disease. Nature 439:549 Pepper JW, Smuts BB (2002) A mechanism for the evolution of altruism among nonkin: positive assortment through environmental feedback. Am Nat 160:205-213 Pike N, Foster WA (2008) The ecology of altruism in a clonal insect. In: Korb J, Heinze J (eds) Ecology of Social Evolution. Springer, Heidelberg, pp 37-56 Pomiankowski A (1999) Intragenomic conflict. In: Keller L (ed) Levels of Selection in Evolution. Princeton University Press, Princeton, pp 121-152 Price GR (1970) Selection and covariance. Nature 277:520-521 Price GR (1972) Extension of covariance selection mathematics. Annal Hum Genet 35:485-490 Queller DC, Strassmann JE (1998) Kin selection and social insects. BioScience 48:165-175
Social insects, major evolutionary transitions and multilevel selection
209
Queller DC, Foster KR, Fortunato A, Strassmann JE (2003) Cooperation and conflict in the social amoeba, Dictyostelium discoideum. In: Kikuchi T, Azuma N, Higashi M (eds) Genes, Behaviors and Evolution of Social Insects. Hokkaido University Press, Sapporo, Japan, pp 173-200 Ratnieks FLW (1988) Reproductive harmony via mutual policing by workers in eusocial Hymenoptera. Am Nat 132:217-236 Ratnieks FLW (1993) Egg-laying, egg-removal, and ovary development by workers in queenright honey-bee colonies. Behav Ecol Sociobiol 32:191-198 Ratnieks FLW (2001) Heirs and spares: caste conflict and excess queen production in Melipona bees. Behav Ecol Sociobiol 50:467-473 Ratnieks FLW, Visscher PK (1989) Worker policing in the honeybee. Nature 342:796-797 Ratnieks FLW, Wenseleers T (2008) Altruism in insect societies and beyond: voluntary or enforced? Trends Ecol Evol 23:45-52 Ratnieks FLW, Foster KR, Wenseleers T (2006) Conflict resolution in insect societies. Annu Rev Entomol 51:581-608 Reeve HK (1998) Game theory, reproductive skew, and nepotism. In: Dugatkin LA, Reeve HK (eds) Game Theory and Animal Behaviour. Oxford University Press, Oxford, pp 118-145 Reeve HK, Keller L (1999) Levels of selection: burying the units-of-selection debate and unearthing the crucial new issues. In: Keller L (ed) Levels of Selection in Evolution. Princeton University Press, Princeton, pp 3-14 Reeve HK, Peters JM, Nonacs P, Starks PT (1998) Dispersal of first ‘workers’ in social wasps: causes and implications of an alternative reproductive strategy. Proc Natl Acad Sci USA 95:13737-13742 Reyer H-U (1984) Investment and relatedness: a cost/benefit analysis of breeding and helping in the pied kingfisher (Ceryle rudis). Anim Behav 32:1163-1178 Roisin Y (1994) Intragroup conflicts and the evolution of sterile castes in termites. Am Nat 143:751-765 Roisin Y (2000) Diversity and evolution of caste patterns. In: Abe T, Bignell DE, Higashi M (eds) Termites: Evolution, Sociality, Symbiose, Ecology. Kluwer Academic Publishers, Dordrecht/NL, pp 95-119 Roux EA, Roux M, Korb J (2009) Selection on defensive traits in a sterile caste − caste evolution: a mechanism to overcome life-history trade-offs? Evol Dev 11:80-87 Saigo T, Tsuchida K (2004) Queen and worker policing in monogynous and monandrous colonies of a primitively eusocial wasp. Proc R Soc Lond B 271:S509-S512 Seger J (1991) Cooperation and conflict in social insects. In: Krebs JR, Davies NB (eds) Behavioural Ecology. An Evolutionary Approach. Blackwell, Cambridge/MA, pp 338-373 Sherman PW, Lacey EA, Reeve HK, Keller L (1995) The eusociality continuum. Behav Ecol 6:102-108 Simmons LW, Emlen DJ (2006) Evolutionary trade-off between weapons and testes. Proc Natl Acad Sci USA 103:16346-16351
210
Judith Korb
Sober E, Wilson DS (1997) Unto Others: The Evolution of Altruism. Harvard University Press, Cambridge/MA Strohm E, Liebig J (2008) Why are so many bees but so few digger wasps social? The effect of provisionning mode and helper efficiency on the distribution of sociality among the Apoidea. In: Korb J, Heinze J (eds) Ecology of Social Evolution. Springer, Heidelberg, pp 109-128 Stubblefield JW, Charnov EL (1986) Some conceptual issues in the origin of eusociality. Heredity 57:181-187 Szathmáry E (2006) The origin of replicators and reproducers. Philos Trans R Soc Lond USA 361:1761-1776 Temin RG, Ganetzky B, Powers PA, Lyttle TW, Pimpinelli S, Dimitri P, Wu C-I, Hiraizumi Y (1991) Segregation distortion in Drosophila melanogaster: genetic and molecular analyses. Am Nat 137:287-331 Tsuji K (1995) Reproductive conflicts and levels of selection in the ant Pristomyrmex pungens: contextual analysis and partitioning of covariance. Am Nat 146:586-607 Turner JS (2000) The Extended Organism: The Physiology of Animal-Built Structures. Harvard University Press, Cambridge/MA Turner BC, Perkins DD (1991) Meiotic drive in Neurospora and other fungi. Am Nat 137:416-429 van der Gaag M, Debets AJM, Oosterhof J, Slakhorst M, Thijssen JAGM, Hoekstra RF (2000) Spore-killing meiotic drive factors in a natural population of the fungus Podospora anserina. Genetics 156:593-605 von Frisch K (1946) Die Tänze der Bienen. Österr Zool Z 1:1-48 von Frisch K (1967) The Dance Language and Orientation of Bees. Harvard University Press, Cambridge/MA Wade MJ (1978) Kin selection: a classical approach and a general solution. Proc Natl Acad Sci USA 75:6154-6158 Wenseleers T, Ratnieks FLW (2004) Tragedy of the commons in Melipona bees. Proc R Soc Lond B 271:S310-S312 Wenseleers T, Ratnieks FLW (2006) Enforced altruism in insect societies. Nature 444:50 Wenseleers T, Ratnieks FLW, Billen J (2003) Caste fate conflict in swarmfounding social Hymenoptera: an inclusive fitness analysis. J Evol Biol 16:647-658 Wenseleers T, Hart AG, Ratnieks FLW (2004a) When resistance is useless: policing and the evolution of reproductive acquiescence in insect societies. Am Nat 164:E154-E167 Wenseleers T, Hart AG, Ratnieks FLW, Quezada-Euan JJG (2004b) Queen execution and caste conflict in the stingless bee Melipona beecheii. Ethology 110:725-736 Wenseleers T, Helanterä H, Hart A, Ratnieks FLW (2004c) Worker reproduction and policing in insect societies: an ESS analysis. J Evol Biol 17:1035-1047 Wenseleers T, Gardner A, Foster KR (in press) Social evolution theory: a review of methods and approaches. In: Székely T, Komdeur J, Moore AJ (eds) Social
Social insects, major evolutionary transitions and multilevel selection
211
Behaviour: Genes, Ecology and Evolution. Cambridge University Press, Cambridge Wenzel J (1991) Evolution of nest architecture. In: Ross KG, Matthews RW (eds) The Social Biology of Wasps. Cornell University Press, Cornell, Ithaka, pp 480-519 West SA, Griffin AS, Gardner A (2007) Social semantics: altruism, cooperation, mutualism, strong reciprocity and group selection. J Evol Biol 20:415-432 West-Eberhard MJ (1975) The evolution of social behavior by kin selection. Q Rev Biol 50:1-33 Wey T, Blumstein DT, Shen W, Jordán F (2008) Social network analysis of animal behaviour: a promising tool for the study of sociality. Anim Behav 75:333-344 Williams GC (1966) Adaptation and Natural Selection: A Critique of Some Current Evolutionary Thoughts. Princeton University Press, Princeton Wilson EO (1971) The Insect Societies. Harvard University Press, Cambridge/MA Wilson DS (1975) A theory of group selection. Proc Natl Acad Sci USA 72:143146 Wilson DS (1997) Altruism and organism: disentangling the themes of multilevel selection theory. Am Nat 150:S122-134 Wilson DS (2008) Social semantics: toward a genuine pluralism in the study of social behaviour. J Evol Biol 21:368-373 Wilson DS, Dugatkin LA (1997) Group selection and assortative interactions. Am Nat 149:336-351 Wilson EO, Hölldobler B (2005) Eusociality: origin and consequences. Proc Natl Acad Sci USA 102:13367-13371 Wynne-Edwards VC (1962) Animal Dispersion in Relation to Social Behavior. Oliver and Boyd, Edinburgh Yang R-C (1998) Estimating hierarchical F-statistics. Evolution 52:950-956 Zimmerman RB (1983) Sibling manipulation and indirect fitness in termites. Behav Ecol Sociobiol 12:143-145
Chapter 8
Cooperation between unrelated individuals – a game theoretic approach REDOUAN BSHARY
ABSTRACT Cooperation between unrelated individuals has attracted a lot of research interest because the acts of mutual helping have to be reconciled with evolutionary theory and its focus on individual benefits. Various theoretical frameworks exist, and this chapter will focus specifically on the game theoretic approach. Game theory captures key ecological and life history features like longevity, mutual dependency or mobility in simple games in order to explore conditions that allow cooperative solutions. As behaviour is embedded into underlying strategies, game theory is particularly suited to investigate the conditionality of cooperative behaviour. A great variety of game theoretic concepts offer explanations why cooperation between two individuals may exist in nature. By providing selected examples and describing in detail a case study on marine cleaning mutualism I will argue that the variety of concepts is indeed necessary to capture the diversity of documented examples. In the next part of the chapter, concepts and evidence for cooperation in groups is presented. The focus is on the ‘tragedy of the commons’ and the conditions under which humans may solve the tragedy. At the end and in two boxes I highlight key topics of debate that warrant future research.
8.1 Introduction Natural selection favours behaviours that yield individuals on average a higher fitness than the population mean for alternative behaviours. Therefore, an intuitive reflection would suggest that any form of helping behaviour – a behaviour that increases the fitness of another individual – should be under negative selection. However, helping behaviours are frequently observed in nature, both unilateral helping where the helper reduces its
214
Redouan Bshary
own direct fitness (termed ‘altruism‘) and mutual helping where partners increase their direct fitness (termed ‘cooperation‘ within species and ‘mutualism’ between species, see BOX 8.1 for definitions of key terms). The widespread existence of helping offers scientists the wonderful challenge to explain helping within the framework of evolutionary theory. Hamilton’s theory of kin selection (Hamilton 1964) provides the basic explanation for altruistic behaviours, i.e. behaviours that reduce the lifetime direct fitness of the actor: altruism may evolve if the costs of helping (c) are outweighed by the benefits for the receiver (b) times the degree of genetic relatedness (r) between helper and receiver (r x b > c). Otherwise, altruistic behaviour is under negative selection. Altruism towards unrelated individuals is thus typically under negative selection (there is the possible exception that the recipient compensates a helper’s direct fitness loss by helping the helper’s relatives in return). In contrast to the straightforward conditions for altruism to evolve, explanations for the evolution of cooperative behaviour are diverse. The aim of this chapter is both to introduce and defend the diversity of cooperation concepts. The key challenge for the understanding of cooperative behaviour is to explain how a cooperative individual may assure that the partner(s) cooperates as well. The basic problem is best illustrated with the well-known prisoner’s dilemma game. In this game two players can either cooperate or defect. There are thus four possible behavioural combinations, leading to different payoff distributions between the two players. In the standard payoff matrix, both players receive three units for mutual cooperative behaviour and one unit for mutual defective behaviour. If one cooperates and one defects, the cooperator receives zero units and the cheater five units. Mutual cooperation is therefore better than mutual defection but a player receives more units if he defects than if he cooperates, independently of the partner’s behaviour: five units instead of three if the partner cooperates and one unit instead of zero if the partner defects. In other words, cooperative behaviour in the prisoner’s dilemma game is an investment: it reduces the actor’s immediate payoffs and increases the recipient’s immediate payoff. Any investment must yield more than compensating future benefits or there is selection against it. Therefore, it does not pay to cooperate in a single-round prisoner’s dilemma game, whereas defection is the only evolutionarily stable strategy (ESS, Maynard Smith 1982). The question of how conditional investments, and hence stable cooperation, may evolve in an iterated version of the prisoner’s dilemma game (Axelrod and Hamilton 1981, further references in Dugatkin 1997) has long distracted empiricists and theoreticians from the fact that the prisoner’s dilemma framework is just one out of many possible scenarios that describe the setting for cooperation in nature. In fact, already in the 1990s
Cooperation between unrelated individuals – a game theoretic approach
215
BOX 8.1 Terminology Helping: a behaviour that on average increases the direct fitness of a recipient and that has been under positive selection at least in part because of this positive effect on the recipient. Helping comprises both altruistic and cooperative behaviour. Altruistic behaviour: a behaviour that on average increases the direct fitness of a recipient and which reduces the direct fitness of the actor. Therefore, altruism is under positive selection only if it increases the actor’s inclusive fitness because of indirect fitness benefits. Note that the definition is about lifetime reproductive success. In contrast, social scientists define altruism in a proximate way, namely as other-regarding behaviour. Similarly, Trivers (1971) defines altruism as a short-term cost while he assumes that ultimately the act will increase the actor’s lifetime direct fitness. I use the term ‘investment‘ for such behaviours to avoid the confusion between short-term and lifetime effects. Cooperative behaviour: a behaviour that on average increases the direct fitness of a recipient and which on average also yields direct fitness benefits to the actor. The ‘on average’ is important because in many cases, for example in cooperative hunting, cooperating does not always yield success. Furthermore, West et al. (2007a) pointed out that cooperative behaviour should at least in part be selected because of the benefits to the recipient. This addition allows us to exclude cases like an elephant self-servingly producing dung and thereby benefiting dung beetles. Cooperation: the outcome of an interaction (or repeated interactions) where all participants on average increase their direct fitness. The distinction between individual behaviours and the outcome of interactions is essential for a game theoretic approach, which focuses on the conditionality of cooperative behaviour. Investment: a behaviour that increases the immediate payoff of a recipient and decreases the immediate payoff of the actor. Self-serving behaviour: a behaviour that increases the actor’s direct fitness independently of what the partner does. The effect on the partner’s fitness can be positive or negative. Public good: a public good is created if a helping behaviour benefits two or more recipients in addition to potential benefits to the actor. Tragedy of the commons (n-player prisoner’s dilemma): this phenomenon occurs if a contribution to a public good is an investment, which normally implies that the contribution is altruistic.
several authors (Dugatkin and Wilson 1991, Noë et al. 1991, Connor 1995) made the point that most examples of cooperation do not present solutions to an iterated prisoner’s dilemma game, and Bergstrom et al. (2003) con-
216
Redouan Bshary
cluded that the game does not capture the essential features of any case of interspecific mutualism. The iterated prisoner’s dilemma is only one of many frameworks that address cooperative behaviour in pairs, and further concepts are needed if cooperation takes place in groups of more than two individuals. In this chapter, I will first introduce the game theoretic approach to studying cooperation. I will then introduce the variety of game theoretic concepts that have been put forward in order to explain stable cooperation in pairs. The chapter will end with a presentation of concepts that may explain cooperation in n-player interactions. The concepts will be illustrated with selected empirical examples. In two separate boxes, I briefly introduce two highly contentious topics as additional food for thought for those who are interested in studying cooperation.
8.2 The game theoretic approach 8.2.1 Conditionality of behaviour: the key feature of the game theoretic approach Three approaches to studying cooperation are prominent in the biological literature: social evolution theory, ecological modelling, and game theory. The key difference between evolutionary game theory and the other two fields is that social evolution theory and ecological theory study the conditions under which cooperative behaviour is under positive selection, while evolutionary game theory embeds cooperative behaviour into underlying strategies and decision rules (Maynard Smith and Price 1973, Maynard Smith 1982). As long as behaviour is unconditional, behaviour and strategy mean the same thing, and the three approaches converge. The general question then is which ecological or life history variables promote unconditional cooperative behaviour. In contrast, if cooperative behaviour is just one option out of the behavioural repertoire of an individual for a given situation, only the game theoretic approach with its emphasis on strategies and decision rules can grasp the conditionality of cooperative behaviour. The question then is not any more whether cooperative behaviour is under positive selection but which decision rule specifying the conditions under which the individual behaves cooperatively is under positive selection. As a consequence of the conditionality of cooperative behaviour, the very same individual may sometimes cooperate and sometimes defect. Because of such flexible behaviour it is essential for the game theoretic approach to distinguish between the behaviour of an individual and the outcome of an interaction. Only if both players cooperate can one speak of cooperation (Dugatkin 1997, see BOX 8.1). Scientists embedded in social evolution
Cooperation between unrelated individuals – a game theoretic approach
217
theory do not distinguish between cooperation and cooperative behaviour (West et al. 2007a). 8.2.2 The methods of the game theoretic approach The behaviour of individuals in real-life interactions may be influenced by many variables, both proximately and due to evolutionary processes. These variables include aspects of the life history of a species, such as longevity, migration patterns, or the degree of overlap between generations. Other aspects concern the stakes and the degree of dependency on cooperation to achieve the goals. Furthermore, behaviour may be conditional on the identity of the partner, past experience, body condition, or aspects of the situation: number of previous encounters, likelihood of future interactions, presence or absence of bystanders, etc. The game theoretic approach attempts to capture these aspects in a synthetic way. Life history variables are translated into the probability of repeated interactions, and the stakes and dependencies are translated into a payoff matrix. The aspects of conditionality may influence behaviour through the likely number of interactions, the payoff matrix, and the partners’ past behaviour. The challenge is to identify the few key variables where the combination of parameter states of these key variables can be said to adequately describe the game structure. Bshary and Bronstein (2004) compiled an extensive list of key variables that may influence cooperation and mutualism. Among this list, the following four variables are probably the most essential ones: 1) Investment: is the act of helping an investment or does it provide immediate benefits to the actor independently of how partners behave? If the behaviour is an investment, further questions arise: 2) Payoff relations between ‘C’ (cooperating) and ‘D’ (defecting): if the investment yields foreseeable benefits because the recipient(s) will use the investment in a self-serving way which helps the investor as a by-product, unconditional investment will be selected (‘C > D’). If the benefits of an investment depend on return investments, then the highest payoff would be achieved by defecting a cooperative partner (‘D > C’). Under these circumstances, only conditional strategies (like ‘cooperate as long as the partner(s) cooperate(s), defect if the partner(s) defect’) may yield stable cooperation. 3) Number of interactions: cooperative behaviour may more readily evolve if partners interact often with each other rather than just a few times or even only once. 4) Partner choice: the possibility to exert choice may be a very powerful mechanism to prevent cheating because cheaters risk to be left alone or they will/may end up matched with each other.
218
Redouan Bshary
The alternative parameter states of the four variables can be combined freely to create different game structures. Theoreticians and empiricists can then explore which game structures yield cooperative outcomes and to assess how (with what partner control mechanisms) individuals can reduce the payoffs of defectors to a level that cooperative behaviour is selected for. Most models actually specify the conditions under which a cooperative strategy can be an evolutionarily stable strategy (ESS, Maynard Smith 1982). An ESS yields the highest payoff of all strategies considered in a population where everybody uses the strategy, which makes the ESS resistant to invasion by a rare mutant strategy. Identifying the game structure and cooperative ESS for the iterated prisoner’s dilemma game, one can note that cooperative behaviour is an investment because it reduces the actor’s immediate payoff independently of how the partner behaves. Also, it is clear that ‘D > C’ because a player’s ideal solution (yielding the highest payoff) is to always cheat an always cooperating partner. Furthermore, partners interact repeatedly (200 times in Axelrod and Hamilton 1981) and partner choice does not exist. For this specific parameter combination strategies that are based on ‘positive reciprocity‘ (Clutton-Brock and Parker 1995) – strategies that make individuals generally reward cooperative behaviours and as controlling mechanism defect in response to cheating – provide cooperative ESS (Nowak and Sigmund 1992, 1993; discussed in detail in Dugatkin 1997). If we change one of the four parameter states, we obtain a different game structure and therefore also different strategies with different control mechanisms that may emerge as cooperative solutions, as developed below (Sect. 8.3). 8.2.3 On the importance of the game theoretic approach The strength of game theory is that behaviour (loosely defined, so including physiological responses in plants or bacteria) is embedded in a strategy with decision rules that specify the conditions under which an individual cooperates, cheats, or responds to a partner’s behaviour in an appropriate way. If one assumes that the behaviour rather than the decision rules is under selection, game theory is of minor importance. This is because game theoreticians would capture the conditions with a payoff matrix that offers higher payoffs for cooperating than for defecting, making the answer trivial. In contrast, asking which ecological or life history parameters cause such a payoff matrix is very interesting. A long list of theoretical work has identified potential key variables like low migration, longevity, overlapping generations, or interdependency between group members (Nowak and May 1992, van Baalen and Rand 1998, Killingback et al. 1999, Kokko and
Cooperation between unrelated individuals – a game theoretic approach
219
Johnstone 1999, Taylor and Irwin 2000, Aviles 2002, further references in Lehmann and Keller 2006). The issue of unconditional helping will be a major focus of the part on n-player cooperation. Forms of helping that are not conditional on a partner’s behaviour are clearly widespread in nature: kin selection in the case of altruism, byproduct mutualism and positive pseudoreciprocity in the case of cooperation. They all have in common that as long as basic conditions are fulfilled (like Hamilton’s inequality in the case of altruism) cheating is never a profitable option. In by-product mutualism the act of helping provides benefits to the actor independently of how partners behave. Thus, the act of helping is a self-serving behaviour and the benefits to others a mere byproduct. Many examples of cooperation fit this scenario: a classic case is hunting in golden jackals, where individuals had a six-fold increase in hunting success in pairs, compared by singletons hunts (Lamprecht 1978). With such an increase in success probability, the best response to a partner hunting is to join the hunt (to cooperate) rather than to defect and gain access to a prey hunted by the partner with a comparatively low probability. Positive pseudoreciprocity is similar to by-product mutualism but differs with respect to the timing of benefits. In by-product mutualism, the act of helping provides immediate net benefits to the actor, whereas the benefits are delayed in positive pseudoreciprocity. Therefore, the act of helping becomes an investment and there is a certain risk that the benefits will never be accrued. However, that would be due to the recipient(s) dying rather than cheating: because the investment in principle enables a recipient to perform self-serving behaviour that benefits the donor as a by-product. From the outline above, it appears that cases of cooperation where helping is conditional on the behaviour of the partner might be relatively rare. However, relative payoffs for cooperating and cheating may change repeatedly during the life of individuals, either because ecological conditions fluctuate or because payoffs may depend on an individual’s state. For example, helping might be beneficial if an individual is in good condition but costly if an individual is in poor condition (Sherratt and Roberts 2001, Lotem et al. 2003). Such variability in payoffs should select for conditional behaviour. In any case, conditional cooperation has attracted great interest in the literature, probably because such cases provide a greater intellectual challenge. A further advantage of the game theoretic approach is that it can incorporate the coexistence of cooperative behaviour and cheating. Real life observations document such variation. Therefore, rather than asking under what conditions cooperative behaviour will become fixed in a population the more realistic question is to ask why variation in cooperative behaviour is maintained. There are several solutions proposed in the literature. One
220
Redouan Bshary
possibility is to assume that individuals make errors and hence do not always cooperate (Nowak and Sigmund 1992, 1993). Alternative scenarios explain variation in cooperative behaviour by including assumptions about condition dependency and frequency dependence (Sherratt and Roberts 2001, Lotem et al. 2003). Finally, McNamara et al. (2004) developed a scenario based on an iterated prisoner’s dilemma game with the assumption that the initial state of a population is variation in levels of cooperation. The result was a distribution of strategies that vary in the degree of cooperativeness.
8.3 Theoretical concepts for cooperation between two individuals The conditions that yield stable cooperation when interactions take place in pairs have been studied in much detail compared to interactions between n individuals. A large variety of theoretical concepts exists. It is often difficult to assess in what respect each concept is unique, or whether different terms actually mean the same thing. To give a non-exhaustive list: byproduct mutualism, pseudoreciprocity, partner choice, sanctions, power, punishment, threat of reciprocity, generalised reciprocity, tit-for-tat like reciprocity, pay-to-stay, indirect reciprocity, building up relationships, group augmentation, strong reciprocity, social prestige, and policing are all concepts that have been proposed to yield stable cooperation. My aim is not to present all these concepts in detail but rather to develop a scheme that logically links the most basic concepts in my view. The concepts differ with respect to the responses to a cheating partner that may reduce the cheater’s fitness, thereby causing selective pressure against cheating. I refer to such responses as ‘partner control mechanisms’. There are several key strategic answers to the basic question ‘why should an individual help another individual?’: because the behaviour increases the direct fitness of the actor irrespective of the recipient’s actions because the behaviour is an investment that causes self-serving responses that benefit the investor as a by-product because the behaviour causes a return investment because the behaviour causes the absence of negative responses Furthermore, one has to ask who provides the benefits to the actor/refrains from reducing the actor’s payoff. If it is the recipient, the link is said to be
Cooperation between unrelated individuals – a game theoretic approach
221
Terms from the literature
no
yes
By-product mutualism
+
Pseudoreciprocity
–
Sanction, power, partner choice
+
Social prestige
–
Pay-to-stay
+
‘Tit-for-tat’ like reciprocity
–
Punishment
+
Image scoring, GR
–
Policing, ‘strong reciprocity’
direct Pseudoreciprocity no
indirect
Costly response direct
yes Reciprocity
indirect
Fig. 8.1 A decision tree to determine nine basic cooperation concepts by identifying the state of four key parameters: investment (‘yes’ or ‘no’), costly response (‘yes’ or ‘no’), response by the recipient (‘direct’) or by someone else (‘indirect’), controlling behaviour a reward for cooperative behaviour (+) or a reduction of a cheater’s payoff (-). In the column to the right, terms from the literature are given. GR: generalized reciprocity. Adapted from Bshary and Bergmüller 2008.
‘direct’. If the benefits of helping are due to the behaviour of third parties, the link is said to be ‘indirect’. Note that the use of the terms ‘direct’ and ‘indirect’ has nothing to do with inclusive fitness theory: we only consider direct fitness benefits. All the strategic aspects mentioned above can be combined into a simple scheme with four parameters that can be in two different states (see Bshary and Bergmüller 2008). The combination of the states of the parameters explains what concept/partner control mechanism may explain why an individual helps another one. 1) Investment: yes or no. 2) short term costly response: yes or no. 3) Benefits: direct from receiver or indirect from third parties. 4) Benefits: reward (positive) or absence of negative responses. Nine basic concepts can be identified (Fig. 8.1). Several corresponding well known terms from the literature are also presented in Fig. 8.1. The advantage of this classification is that it specifies the similarities and the differences between the basic concepts, and that it allows precise definitions of concepts. To give two examples, punishment is a concept/control mechanism that causes an individual to invest into a recipient in order to avoid a costly response from the recipient that would reduce the individual’s payoff. Punishment is thus negative direct reciprocity (Clutton-Brock
222
Redouan Bshary
and Parker 1995). In contrast, sanctions as defined by Herre et al. (1999) are a form of negative direct pseudoreciprocity: subjects invest because failure to do so would cause self-serving response from the recipient that would reduce the actor’s payoff. The terms listed in Fig. 8.1 may often be used with different meanings in the literature. Therefore, the aim of Fig. 8.1 is not necessarily to define the terms in my favourite way, but to make clear how many terms we need to specify the most basic concepts. Further information about other parameters is needed to distinguish between more specific concepts. For example, partner choice differs from other forms of negative direct pseudoreciprocity by the assumption that an individual’s outside option is to find another partner if the current one does not behave cooperatively. In contrast, sanctions and power assume that the outside option is to simply terminate the interaction and not interact at all.
8.4 Empirical evidence that we need all the basic cooperation concepts for two-player interactions 8.4.1 General assessment Relatively few studies on cooperation between unrelated individuals use a game theoretic approach. Studies on mutualism typically focus on ecological questions rather than on the strategic behaviour of individuals. Therefore, it is currently impossible to rate the relative importance of the basic concepts by counting the number of examples that fit each concept. However, as long as there is at least one convincing example for a concept, its existence is already justified. Table 8.1 summarises convincing examples for all nine basic cooperation concepts for the situation where interactions take place between two individuals. As a general rule, there is considerably less convincing evidence for reciprocity concepts than for pseudoreciprocity concepts, in particular outside humans. It seems likely that the difference in abundance is real. Cooperation based on investments by one partner in order to gain by-product benefits or to avoid negative effects of self-serving behaviour seems to be inherently more stable than cooperation based on mutual investments (Bergstrom et al. 2003, Hammerstein 2003, Bshary and Bronstein 2004). The one important reservation against this conclusion is that it is notoriously difficult to demonstrate for a cooperative behaviour that it is contingent on cooperative behaviour of the partner. Furthermore, even if a contingency has been demonstrated the discussion may continue. A prime example is the preda-
Cooperation between unrelated individuals – a game theoretic approach
223
Table 8.1 Examples and references for the nine basic cooperation concepts where interactions always take place between two players. Concept/ control mechanism
Example
Reference
By-product mutualism
Golden jackals increase hunting success six fold if hunting in pairs rather than alone
Lamprecht 1978
Positive direct pseudoreciprocity
Leafcutter ants invest in farming fungi because the fungi’s self-serving response to grow healthy colonies yields by-product benefits to the ants as the latter harvest fungi for food
Mueller et al. 2005
Negative direct pseudoreciprocity
Leguminose plants stop growing roots in areas where rhizobia fail to fix nitrogen but rather invest in areas where nitrogen is fixed
Kiers et al. 2003
Positive indirect pseudoreciprocity
Cleaners give a better service to clients in the presence of bystanders because the latter self-servingly prefer cooperative cleaners
Bshary and Grutter 2006
Negative indirect pseudoreciprocity
Cichlid helpers contribute to help offspring to avoid self-serving eviction from the territory by the dominant
Bergmüller and Taborsky 2005
Positive direct reciprocity
Sticklebacks inspect predators in pairs where the level of cooperation (approach distance) of one fish depends on the cooperativeness of the partner
Milinski 1987, Milinski et al. 1990, 1997
Negative direct reciprocity
Resident clients chase cleaners in response to cheating, which causes cleaners to be more cooperative in future interactions
Bshary and Grutter 2005
Positive indirect reciprocity
Humans are willing to pay to help individuals they have observed helping others
Wedekind and Milinski 2000
Negative indirect reciprocity
Humans are willing to pay to reduce the payoff of individuals they have observed cheating others
Fehr and Fischbacher 2004
224
Redouan Bshary
tor inspection behaviour shown by various fish species. A close inspection yields information about the predator’s hunger level, which can then be used for one’s own foraging decisions (Häberli et al. 2005). Milinski (1987) demonstrated that single sticklebacks paired with a mirror that suggested the presence of a conspecific approached a predator more closely if the mirror image approached in parallel than if the mirror image lagged behind (due to a different positioning of the mirror). Milinski interpreted the behaviour as consistent with a tit-for-tat strategy during pair inspections. A further experiment clearly demonstrated that a stickleback’s current minimal approach distance is contingent on a partner’s approach behaviour during past joint inspections (Milinski et al. 1990). Most importantly, Milinski et al. (1997) could show that lagging behind in an inspecting pair significantly reduced the laggard’s predation risk at the expense of the leading partner. In the experiment, dead sticklebacks ‘performed’ predator inspections by remote control according to an algorithm that mimicked natural inspection. Despite this unique combination of evidence, colleagues still remained doubtful about the exact payoff matrix and the tit-for-tat interpretation (Hammerstein 2003). Thus, the reciprocity debate in behavioural ecology became similar to the ‘theory of mind’ debate in animal cognition (Heyes 1998): a final decisive proof is very difficult, while the absence of reciprocity or theory of mind is the default hypothesis. Below I will use marine cleaning interactions as a model mutualism complex to illustrate the main point of the first part of the chapter: there are many different game structures in nature and as a consequence many different control mechanisms that ensure that partners typically behave cooperatively. 8.4.2 On the diversity of game theoretic concepts found in marine cleaning mutualism Over 100 fish and shrimp species have been observed to inspect the surface and sometimes even the gills and the mouth of fishes (Côté 2000). These interactions apparently have evolved because the ‘cleaners’ remove ectoparasites from their ‘clients’ (Grutter 1997, Becker and Grutter 2004). There is variation among cleaner species with respect to their dependency on interactions for their diet, and most cleaner fish species only clean as juveniles (Côté 2000). The most likely evolutionary starting point for cleaning mutualism is that small fish that feed on invertebrates living on substrate included other fish species as substrate and thus removed their ectoparasites. This scenario suggests that the starting point was a by-
Cooperation between unrelated individuals – a game theoretic approach
225
product mutualism. By-product mutualism is inherently stable because the behaviours of partners are self-serving. The lack of investments makes cheating either impossible or unprofitable. Caribbean gobies of the genus Elacatinus, where member species are highly dependent on cleaning for their diet, still seem to be engaged in a by-product mutualism with their clients. There is no evidence that these cleaners manipulate client decisions or that clients use particular partner control mechanisms to prevent gobies from cheating (eating mucus instead of ectoparasites; Soares et al. 2008a,b). These observations suggest that cleaning gobies prefer ectoparasites over mucus and therefore invariably prefer to cooperate, which appears to be the case (Soares et al. unpubl. data). Clients then just have to leave in time to avoid excessive mucus feeding by the goby once parasites become rare/absent on their body. The situation is very different in the cleaner wrasse Labroides dimidiatus, the most important cleaner in the Indopacific. Individuals occupy small territories (‘cleaning stations’) and have about 2000 interactions per day with 100-500 clients belonging to about 30-50 species (Grutter 1997, Bshary 2001). Two findings make L. dimidiatus a particular interesting study object. First, they prefer client mucus over ectoparasites (Grutter and Bshary 2003). Therefore, there is a major conflict between cleaner and client over what a cleaner should eat, and clients have to make cleaners eat against their preference in order to receive a good service. Second, these cleaners often give tactile stimulation to clients with their pectoral and in particular pelvic fins, a behaviour that is used to manipulate client decisions and behaviour in various circumstances (Bshary and Würth 2001, Grutter 2004). The cleaners interact with a large diversity of client species, and clients differ with respect to key variables that affect the game structure of cleaner-client interactions. Therefore, the cleaners switch between several game structures during a chain of interactions with various client species. The most fundamental distinction with respect to game structure is to be made between reef fish clients and pelagic clients. Reef fishes have defined territories or home ranges and hence interactions with cleaners are potentially repeated. In contrast, truly pelagic fishes may effectively visit a cleaning station only once and then move on to new areas. Most cooperation concepts rely on repeated interactions, hence the one-off interactions between cleaners and pelagic clients are particularly intriguing. A similar problem appears to exist in the closely related cleaner wrasse L. bicolor, where the cleaners rove over large areas. Roving by potential cheaters hinders stable cooperation (Dugatkin and Wilson 1991), so the challenge is to explain why cooperation nevertheless persists. A possible explanation is that cleaners may largely cooperate in such one-off interactions because a
226
Redouan Bshary
prolonged search for ectoparasites may yield a higher payoff than a short interaction terminated prematurely by clients as a response to cheating by the cleaner (Johnstone and Bshary 2002). Currently, no published test of this concept exists. For the L. dimidiatus system, the client reef fish can be categorised mainly along two criteria: predatory/non-predatory and residents/visitors. Residents have small home ranges and hence access to one cleaning station only, while visitors have larger home ranges and hence access to > 1 cleaning stations. Interactions between cleaners and residents, visitors and predators have been studied in quite some detail. Trivers (1971) used interactions between cleaners and predators as one potential example to explain his concept of reciprocity: he proposed that predatory clients refrain from eating a cleaner that enters their mouth because the short-term benefits of such cheating would be outweighed by the cumulative long-term benefits of cooperating due to the cleaner repeatedly removing parasites. This hypothesis appears to be surprisingly difficult to test; it has not been done so far. Trivers (1971) was not concerned about cheating by cleaners because at that time it was not yet known that they would prefer to eat mucus. So both cleaners and predators have symmetrical behavioural options, i.e. they can cooperate or cheat, and cheating a cooperative partner appears to offer the highest short-term benefit. Despite these conditions that fit a prisoner’s dilemma payoff matrix, titfor-tat like reciprocity (cooperate during the first interaction and then typically cooperate as long as your partner cooperated, Axelrod and Hamilton 1981, Dugatkin 1997) cannot explain the mutualism between cleaners and predators. This is because a cheating predator effectively terminates the game, and hence annihilates the very reason why a tit-for-tat like strategy is effective: if the partner cheats, it risks that one cheats in return in the next interaction (Hammerstein and Hoekstra 1995). A cleaner that has been cheated by a predator cannot cheat by eating mucus during the next interaction because it is dead. The solution seems to be that cleaners have to provide such a good service that the payoff for cooperating for a predator is higher than the payoff for cheating. If a cleaner cheats, it is not a cleaner anymore but a food item. The predator’s ‘threat of reciprocity’ (Bshary and Bronstein 2004), which would be terminal, seems to keep the system stable: cleaners hardly ever cheat predators and provide them tactile stimulation much more frequently than they give tactile stimulation to non-predatory clients (Bshary and Würth 2001), in particular when predators are hungry (Grutter 2004). The vast majority of clients do not predate on fishes the size of a cleaner wrasse but instead feed on plankton, polyps or algae. These clients hence do not have the option to cheat a cleaner and the strategic options become
Cooperation between unrelated individuals – a game theoretic approach
227
asymmetric. One therefore has to ask how these clients make cleaners feed against their preference. Visitors apparently use their choice options as a means to control cleaner fish behaviour: if the service was good they are likely to return for their next inspection, but if the cleaner cheated, they are likely to visit another station (Bshary and Schäffer 2002). Models show that the risk of spending time without a partner, because cheating stops an interaction, may select for cooperative behaviour, in particular if the cheated partner may find a new partner with ease while the cheater does not (Ferrière et al. 2002, Johnstone and Bshary 2008). Such partner choice in a biological market (Noë et al. 1991) is a form of direct negative pseudoreciprocity: potential cheaters opt to cooperate in order to avoid that the partner makes a self-serving decision (it would abandon the cheater because the next partner would on average be more cooperative) that would reduce the cheater’s fitness as a by-product. Resident clients cannot simply switch to another cleaner because there is no alternative for them. Instead of switching, they rely on punishment sensu Clutton-Brock and Parker (1995) to make cleaners behave cooperatively: a cleaner that cheats risks that the client chases it. Chasing is a short-term investment by the client that inflicts energetic and opportunity costs on the cleaner, and which causes them to behave more cooperatively during their next interaction with the punisher (Bshary and Grutter 2002, 2005). In conclusion, cleaners usually cooperate with residents in order to avoid direct negative reciprocity. Residents do not only chase cleaners for cheating but they actually also chase immigrant cleaners (Bshary 2002a). Immigrant cleaners provide residents with a lot of tactile stimulation and largely refrain from inspecting and cheating. Thus, cleaners and residents build up relationships based on mutual investments, and only established relationships appear to yield mutual benefits through parasite removal for the client and food for the cleaner. Cleaners and visitors do not build up relationships in any visible way (Bshary 2002a). Partner switching and punishment typically cause a good service quality but sometimes these mechanisms fail: a minority of cleaners switches to a temporarily biting strategy, excepting predatory clients (Bshary 2002b). The best strategy for clients is to avoid any interactions with these biting cleaners, and indeed both visitors and residents appear to use image scoring as an additional partner control mechanism. They observe any ongoing interaction when they arrive at a station and typically invite for inspection if the observed interaction ends without apparent conflict, and avoid the cleaner if the observed interaction ends with a conflict (the current client flees or chases the cleaner).
228
Redouan Bshary
As a consequence of image scoring by clients, cleaners behave more cooperatively in the presence of such eavesdropping bystanders (McGregor 1993) than when alone with a client (Bshary and Grutter 2006). The scenario fits the social prestige idea (Zahavi 1995, Roberts 1998), which is the equivalent of positive indirect pseudoreciprocity: cleaners cooperate with a current client in order to make bystanding clients take a self-serving decision (invite inspection) that benefits the cleaner as a by-product. Until now we only know of humans showing the more complex form of positive indirect reciprocity based on image scoring (Wedekind and Milinski 2000), where every single act is an investment that is more than compensated for by the investment of bystanders (Nowak and Sigmund 1998). In conclusion, a large diversity of game structures occurs in the cleaning mutualism involving L. dimidiatus, where differences in the clients’ strategic options lead to the use of different mechanisms that contribute to the control of the foraging behaviour of cleaners. A final complication concerning cleaner-client interactions is that cleaners may often inspect the same client in an established pair of a male and typically the largest female of his harem. Such pairs do not stay together for life, but the female will eventually switch sex once she is big enough and become a competitor for the male (Robertson 1973). During pair inspections a client may still respond to cheating by one cleaner with evasive action, which reduces the payoff for the cooperating cleaner as well. A game theoretic model shows that the game between the two cleaners resembles an iterated prisoner’s dilemma for a wide parameter space, and ‘always cheat’ (biting immediately) is always an ESS for the game. In reality, however, clients seem to prefer cleaning stations with a cleaner pair (Bshary and Schäffer 2002), which becomes understandable once one realises that both model and data suggest that pairs provide a better service quality (a lower cheating rate per time unit inspection) than singletons (Bshary et al. 2008). Cleaner pairs thus appear to readily solve a problem cooperatively where ‘always cheat’ would be an ESS. The solution is asymmetric in the sense that females are more cooperative during pair inspections than males are, while the two sexes offer similar service qualities when inspecting alone. Such asymmetries are due to the larger males coerce females into showing particularly cooperative behaviour. Males often chase females if the latter cheated. This causes females to behave more cooperatively during future joint inspections, which in turn benefits not only future clients but also the males because they obtain more food (Raihani et al. 2009). Thus, males use their size advantage to increase their own payoff at the expense of their female partners.
Cooperation between unrelated individuals – a game theoretic approach
Pair inspections: reciprocity based on coercion?
Cleaner prefers ectoparasites
229
Predator: Threat of reciprocity
Cleaner prefers mucus Resident: Punishment Building up relationships Social prestige
All clients: By-product mutualism Visitor: partner switching Social prestige Pelagic client: Power? Social prestige?
Fig. 8.2 A summary of games/partner control mechanisms that have been described in marine cleaning mutualisms.
In summary, marine cleaning mutualism harbours an amazing variety of game structures and corresponding partner control mechanisms. Fig. 8.2 summarises this diversity.
8.5 n-player cooperation; theory and evidence It is generally assumed that n-player games are fundamentally different from two-player games. The essential feature of n-player games is that an individual’s contribution cannot be directed to specific group members or been withheld from some other group members. In other words, cooperative behaviour produces a public good. This critical assumption leads to the following problem for players: suppose you have three players, where two players cooperate and one cheats and the gains are shared equally between them. The cheater will have the highest payoff between the three of them. Unfortunately, a cooperative player that decides to cheat in response in the next round will not only produce a negative effect for the cheater, but also for the cooperative partner: not contributing to the public good affects/harms all group members. I prefer to make a distinction between a public good and the tragedy of the commons (BOX 8.1). I use the former
230
Redouan Bshary
term for the general condition where a cooperative behaviour benefits more than one recipient, where a tragedy of the commons is one possible payoff matrix (see next section). 8.5.1 Two basic forms of public goods It is important to distinguish two basic forms of public goods based on the payoffs that a cooperating individual receives from its contribution, independently of what other partners are doing. First, as assumed in most models, cooperating can be an investment where the individual contribution is larger than the individual returns due to the contribution. Under these conditions, investing is altruistic in evolutionary terminology, which means that only kin selection may explain helping under such circumstances, as long as r x b > c. Between unrelated individuals, the tragedy of the commons arises: the overall payoff would be highest if all contribute, but individual contribution is altruistic and hence selected against, with the result that cooperation breaks down. The question which extensions to the basic game may yield cooperative solutions to the tragedy of the commons has been the key focus in the cooperation literature on human behaviour. In a second payoff matrix for public goods games cooperating is a self-serving act because for each unit of contribution, the cooperating individual receives more than one unit in return. If the returns are immediate, the concept of by-product mutualism applies. If the contribution allows recipients to act in a self-serving way in the future that benefits the investor as a byproduct, then the concept of pseudoreciprocity applies. Thus, by-product mutualism and pseudoreciprocity are concepts that are not limited to 2player interactions but can easily be extended to n-player games. The challenge for empiricists is to adequately describe the payoffs in natural systems. This will be particularly difficult in systems where immediate payoffs of cooperating may fluctuate between self-serving and investment. 8.5.2 Unconditional benefits for contributing to a public good Few empirical examples have explicitly tested the idea that public goods may be based on immediate unconditional benefits (by-product mutualism) or delayed unconditional benefits (pseudoreciprocity). The idea that the benefits of group-living are due to the selfish herd (Hamilton 1971) fits well. Each individual joins the group for self-serving reasons, while all other group members benefit from the increase in dilution effects. Another important concept is group augmentation (Kokko and Johnstone 1999), which is well studied in meerkats (Suricata suricatta). Individual meerkats
Cooperation between unrelated individuals – a game theoretic approach
231
often act as sentinels in exposed places while the rest of the group forages. Detailed analyses demonstrated that individuals take the sentinel position only if they have fed well before and are therefore satiated. Only under these conditions is their best option to watch out for predators, hence increasing the probability of survival for all other group members (CluttonBrock et al. 1999). The sentinels benefit from the behaviour because their inclusive fitness depends crucially on group size. Also, cooperative breeding in meerkats seems to be based on self-serving behaviour. Many individuals contribute without any evidence for mutual control concerning relative contribution, which is again explained with the benefits of group augmentation (Clutton-Brock et al. 2000, Clutton-Brock 2002). A recent model by Sherratt et al. (2009) demonstrated that contributions to a public good can be further stabilised if a contributing individual receives an extra proportion of the benefits created by its contribution. For example, bacteria or spiders may communally digest host cells/prey (West et al. 2007b, Schneider and Bilde 2008), where the production of digestive enzymes constitutes a public good. The model assumes that each individual has priority of access to the food digested by its own enzymes just because of spatial proximity. Under these conditions, contributions to the public good exist under a wider parameter space even though individual contributions correlate negatively with the number of recipients (Sherratt et al. 2009). Both model and reality work without invoking kin selection, though kin selection reduces the conflict: Schneider and Bilde (2008) demonstrated that in social spiders, related individuals digest prey more efficiently than unrelated individuals do. By-product mutualism and pseudoreciprocity in n-player games can be found under a different name in the literature: ‘weak altruism‘ (Wilson 1990). However, as should be clear from above, this term is misleading. An important point to make is that while by-product mutualism and pseudoreciprocity are not exciting concepts for game-theory because cheating is never a profitable option, these concepts deserve plenty of attention. We need to know what ecological factors cause a situation where cooperative behaviour in groups is under positive selection without being contingent on the behaviour of others. The very same models that were mentioned in the section on unconditional helping in pairs may also apply to n-player games (Nowak and May 1992, van Baalen and Rand 1998, Killingback et al. 1999, Kokko and Johnstone 1999, Taylor and Irwin 2000, Aviles 2002, further references in Lehmann and Keller 2006).
232
Redouan Bshary
BOX 8.2 Hot debates in the cooperation literature I Inclusive fitness theory versus group selection/multi-level selection The most basic insight of Hamilton’s inclusive fitness theory is that a behaviour is under positive selection if it increases the actor’s inclusive fitness – the sum of the behaviour’s effect on the direct fitness and the indirect fitness – relative to the population average. Group selection theory measures the relative importance of within-group competition to between-group competition. Supporters of group selection theory argue that group selection is fundamentally different from inclusive fitness theory, while proponents of the latter concept argue that group selection theory and inclusive fitness theory can be transformed mathematically into each other. Therefore, the question is not which concept is right or wrong, but how useful one finds each alternative. My personal view is that inclusive fitness theory is simpler, easier to understand and asks precisely the question I am interested in: how a behaviour benefits an individual, which is the essential unit that makes reproductive decisions. I prefer to think about between-group competition as an ecological parameter that may select for helping among group members. Group selection theory does not answer the fundamental question whether an individual helps because of direct or indirect fitness benefits. Also, if an individual dies, then it is clear that its future fitness is zero, whereas group extinction does not automatically mean that all members died. Some might have migrated or were assimilated in the invading group; in humans, victorious warriors often reproduce with the local women. Group selection offers an interesting way of thinking, if the trait of interest is not simply the sum of individual behaviours, but if individuals adopt group standards. This is the case in cultural group selection. In humans, language, religious beliefs, or norms are better seen as group traits than as individual traits. And such traits can go extinct if a group goes extinct and eventual survivors adopt the trait of the winning group. Note, however, that also a cultural trait is still only under positive selection if it increases on average the inclusive fitness of individuals who express the trait. Some relevant recent literature: Boyd et al. 2003, Gintis et al. 2003, Grafen 2006, Lehmann and Keller 2006, Traulsen and Nowak 2006, Lehmann et al. 2007a, West et al. 2007a, Wilson and Wilson 2007.
8.5.3 Solving the tragedy of the commons Public goods, where individual contributions are investments and the benefits contingent upon the investment of others, have captured most attention in recent research on human cooperative behaviour. This body of research
Cooperation between unrelated individuals – a game theoretic approach
233
was sparked by the obvious discrepancy between the theoretical prediction that social dilemmas cannot be solved and the general perception that humans often manage to cooperate in large groups of unrelated individuals in their daily life. Experiments demonstrated that human bystanders readily accept costs to punish individuals who they observed cheating others, or to reward individuals who helped others (Fehr and Gächter 2002, Rockenbach and Milinski 2006, Egas and Riedl 2008, Gächter et al. 2008). Humans show punishment in response to cheating even in anonymous one-off interactions and such behaviour effectively causes punished individuals to behave more cooperatively in the future with other partners (Fehr and Gächter 2002). These results prompted the development of the cultural group selection concept (Boyd et al. 2003, Gintis et al. 2003), which states that strong competition between groups selected for cultural traits in humans that benefitted group survival. Recent efforts by biologists focussed on the translation of cultural group selection into inclusive fitness theory. Such a translation is important for evolutionary biologists because the original economic experiments (Fehr and Gächter 2002) demonstrated a mechanism (‘altruistic punishment‘) out of place: one can measure the amount of money people received in the experiment as a correlate of fitness and finds that punishment is under negative selection in one-off interactions in groups consisting of unrelated individuals. The analyses demonstrated that punishment in one-off interactions may only be under positive selection if the beneficiaries of the punishment are related to the punisher (Gardner and West 2004, Lehmann et al. 2007b). Alternatively, the mechanism underlying punishment, the stimulation of the punisher’s reward system in the brain (de Quervain et al. 2004), evolved in a different context and cannot be switched off even when humans know that the rational decision would be not to punish in one-off interactions. At the moment, however, the importance of punishment for the stabilisation of cooperation in n-player games is contentious, independently of the number of rounds played (Rockenbach and Milinski 2006, Egas and Riedl 2008, Nikiforakis 2008). One possibility that has not been tested yet is that punishers are feared and that this may yield benefits in other contexts. Along this line of argument, even seemingly needless aggression towards a partner may be theoretically explained with the gain of a reputation of being nasty, which may deter competitors (Johnstone and Bshary 2004). Currently, we only have one clear empirical demonstration of a functional explanation of why humans may solve the tragedy of the commons. The general idea is that a group of humans do engage both in two-player interactions and in public goods games and how they behave in any interaction may have implications for how their partners behave in future inter-
234
Redouan Bshary
actions, across the different types of interactions. In this scenario, contributors to public goods may gain an increase in their image score, and this image score could then yield benefits during two-player interactions. The idea of an image score was introduced by Alexander (1987). Nowak and Sigmund (1998) presented the first model that helping in two player interactions may evolve due to a resulting increase in the helper’s image score and the consequently increased probability that the helper will receive support from image scoring bystanders. The basic idea works well in humans (Wedekind and Milinski 2000). In an extension, the indirect reciprocity game was combined with a social dilemma game (Milinski et al. 2002). The results were that individuals who contributed to the public good received more help in the indirect reciprocity game and left the experiment with more money (= a higher fitness) than individuals who did contribute little to the public good. In an additional experiment, Semmann et al. (2005) demonstrated that investments do not need to be restricted to group members. Instead, participants who donated parts of their gain to charity also gained an increased image score as visible by the increased amount of help they received compared to participants who did not donate to charity. Finally, Sommerfeld et al. (2008) tackled the problem of how individuals acquire the necessary information if one accepts that one cannot observe all interactions where help is needed. They found that gossip is both a reliable indicator of other players’ cooperativeness and that humans readily use gossip information for their decisions on whether or not to help.
8.6 Conclusions and outlook As cooperation between unrelated individuals occurs in a variety of game structures we need a great diversity of concepts to explain the evolution and persistence of cooperation in nature. We face major unresolved questions that offer plenty of future research opportunities. Cooperation theory is currently much more advanced than our empirical knowledge. This might partly be due to the theoreticians’ focus on reciprocity, which is most likely rare compared to pseudoreciprocity and by-product mutualism outside humans. The diversity of existing concepts should nevertheless encourage empiricists to study cooperation problems in their study systems. Studying cooperation between n players provides a particular challenge for both theoreticians and empiricists, where a profound knowledge of
Cooperation between unrelated individuals – a game theoretic approach
235
the ecology may help to understand the conditions for the evolution and stability of cooperation in groups in nature. Theoreticians typically focus on quite simple conditions and find quite sophisticated strategies as solutions. During the Hamilton lecture at the ISBE conference 2008, John McNamara proposed that the future might be to model complex worlds and likely find more rule-of-thumb type solutions. Such an approach may indeed offer a major step forward towards a deeper understanding of cooperation in nature. BOX 8.3 Hot debates in the cooperation literature II What is so special about human cooperation? Very few people would contest the notion that human cooperation is far more developed and complex than cooperation in other species: we reciprocate, we give other people an image score depending on how cooperatively they behave towards others, we may punish transgressors without being the victim of cheating and reward cooperators without having been the beneficiary, and we manage to cooperate in very large groups, including conditions that constitute a tragedy of the commons. Disagreement concerns the level at which differences to other animals exist. Some authors proposed that we need to extend evolutionary theory in order to explain human cooperation. The issue returns to the debate on whether cultural group selection can properly be represented with inclusive fitness theory (see BOX 8.2). In my view, the fundamental differences between cooperation in humans and other species are due to differences in underlying mechanisms. Thanks to their large brain, humans can negotiate efficiently using language. In addition, culture, norms, policing, and features of human life seem to have selected for subjective reward mechanisms that enable us to often avoid the pitfalls of immediate benefit maximisation and allow us to show otherregarding behaviours. The subjective reward systems are built on emotions and ultimately physiological reactions in the brain, which could at least in principle, evolve in any species but apparently rarely have. Nevertheless, I always wonder whether a policing ant ‘feels good’ about eating the egg laid by a worker (and how one could test that). Some relevant recent literature: Fehr and Gächter 2002, Milinski et al. 2002, Hammerstein 2003, de Quervain et al. 2004, Lehmann et al. 2007a, Bshary and Bergmüller 2008, Kappeler and Silk 2010.
236
Redouan Bshary
Acknowledgements I thank Manfred Milinski, Dirk Semmann, Peter Kappeler and an anonymous referee for comments. Ana Pinto extracted all the fish silhouettes for Fig. 8.2, where the picture of the goby and its client was taken by Karen Cheney. Funding was provided by the Swiss Science Foundation.
References Alexander RD (1987) The Biology of Moral Systems. Aldine de Gruyter, New York Avilés L (2002) Solving the freeloaders paradox: genetic associations and frequency-dependent selection in the evolution of cooperation among nonrelatives. Proc Natl Acad Sci USA 99:14268-14273 Axelrod R, Hamilton WD (1981) The evolution of cooperation. Science 211:13901396 Becker JHA, Grutter AS (2004) Cleaner shrimp do clean. Coral Reefs 23:515-520 Bergmüller R, Taborsky M (2005) Experimental manipulation of helping in a cooperative breeder: helpers ‘pay-to-stay’ by pre-emptive appeasement. Anim Behav 69:19-28 Bergstrom CT, Bronstein JL, Bshary R, Connor RC, Daly M, Frank SA, Gintis H, Keller L, Leimar O, Noë R, Queller DC (2003) Group report: interspecific mutualism – puzzles and predictions. In: Hammerstein P (ed) Genetic and Cultural Evolution of Cooperation. MIT Press, Cambridge, pp 241-256 Boyd R, Gintis H, Bowles S, Richerson PJ (2003) The evolution of altruistic punishment. Proc Natl Acad Sci USA 100:3531-3535 Brown JL (1983) Cooperation: a biologist’s dilemma. In: Rosenblatt JS (ed) Advances in the Study of Behaviour. Academic Press, New York, pp 1-37 Bshary R (2001) The cleaner fish market. In: Noë R, van Hooff JARAM, Hammerstein P (eds) Economics in Nature: Social Dilemmas, Mate Choice and Biological Markets. Cambridge University Press, Cambridge, pp 146-172 Bshary R (2002a) Building up relationships in asymmetric co-operation games between the cleaner wrasse Labroides dimidiatus and client reef fish. Behav Ecol Sociobiol 52:365-371 Bshary R (2002b) Biting cleaner fish use altruism to deceive image-scoring client fish. Proc R Soc Lond B 269:2087-2093 Bshary R, Bergmüller R (2008) Distinguishing four fundamental approaches to the evolution of helping. J Evol Biol 21:405-420 Bshary R, Bronstein JL (2004) Game structures in mutualistic interactions: what can the evidence tell us about the kind of models we need? Adv Stud Behav 34:59-101 Bshary R, Grutter AS (2002) Asymmetric cheating opportunities and partner control in a cleaner fish mutualism. Anim Behav 63:547-555
Cooperation between unrelated individuals – a game theoretic approach
237
Bshary R, Grutter AS (2005) Punishment and partner switching cause cooperative behaviour in a cleaning mutualism. Biol Lett 1:396-399 Bshary R, Grutter AS (2006) Image scoring and cooperation in a cleaner fish mutualism. Nature 441:975-978 Bshary R, Schäffer D (2002) Choosy reef fish select cleaner fish that provide high-quality service. Anim Behav 63:557-564 Bshary R, Würth M (2001) Cleaner fish Labroides dimidiatus manipulate client reef fish by providing tactile stimulation. Proc R Soc Lond B 268:1495-1501 Bshary R, Grutter AS, Willener AST, Leimar O (2008) Pairs of cooperating cleaner fish provide better service quality than singletons. Nature 455:964-967 Clutton-Brock TH (2002) Breeding together: kin selection and mutualism in cooperative vertebrates. Science 296:69-72 Clutton-Brock TH, Parker GA (1995) Punishment in animal societies. Nature 373:209-216 Clutton-Brock TH, O’Riain MJ, Brotherton PNM, Gaynor D, Kansky R, Griffin AS, Manser MB (1999) Selfish sentinels in cooperative mammals. Science 284:1640-1644 Clutton-Brock TH, Brotherton PNM, O’Riain MJ, Griffin AS, Gaynor D, Sharpe L, Kansky R, Manser MB, McIlrath GM (2000) Individual contributions to babysitting in a cooperative mongoose, Suricata suricatta. Proc R Soc Lond B 267:301-305 Connor RC (1995) Altruism among non-relatives: alternatives to the ‘Prisoner’s Dilemma’. Trends Ecol Evol 10:84-86 Côté IM (2000) Evolution and ecology of cleaning symbioses in the sea. Oceanogr Mar Biol 38:311-355 de Quervain DJ-F, Fischbacher U, Treyer V, Schellhammer M, Schnyder U, Buck A, Fehr E (2004) The neural basis of altruistic punishment. Science 305:12541258 Dugatkin LA (1997) Cooperation Among Animals: An Evolutionary Perspective. Oxford University Press, Oxford Dugatkin LA, Wilson DS (1991) Rover: a strategy for exploiting cooperators in a patchy environment. Am Nat 138:687-701 Dugatkin LA, Mesterton-Gibbons M, Houston AI (1992) Beyond the prisoner’s dilemma: towards models to discriminate among mechanisms of cooperation in nature. Trends Ecol Evol 7:202-205 Egas M, Riedl A (2008) The economics of altruistic punishment and the maintenance of cooperation. Proc R Soc Lond B 275:871-878 Fehr E, Fischbacher U (2004) Third-party punishment and social norms. Evol Hum Behav 25:63-87 Fehr E, Gächter S (2002) Altruistic punishment in humans. Nature 415:137-140 Ferrière R, Bronstein JL, Rinaldi S, Law R, Gauduchon M (2002) Cheating and the evolutionary stability of mutualisms. Proc R Soc Lond B 269:773-780 Gächter S, Renner E, Sefton M (2008) The long-run benefits of punishment. Science 322:1510 Gardner A, West SA (2004) Cooperation and punishment, especially in humans. Am Nat 164:753-764
238
Redouan Bshary
Gintis H, Bowles S, Boyd R, Fehr E (2003) Explaining altruistic behavior in humans. Evol Hum Behav 24:153-172 Grafen A (2006) Optimization of inclusive fitness. J Theor Biol 238:541-563 Grutter AS (1997) Spatiotemporal variation and feeding selectivity in the diet of the cleaner fish Labroides dimidiatus. Copeia 1997:346-355 Grutter AS (2004) Cleaner fish use tactile dancing behavior as a preconflict management strategy. Curr Biol 14:1080-1083 Grutter AS, Bshary R (2003) Cleaner wrasse prefer client mucus: support for partner control mechanisms in cleaning interactions. Proc R Soc Lond B 270:S242-S244 Häberli MA, Aeschlimann PB, Milinski M (2005) Sticklebacks benefit from closer predator inspection: an experimental test of risk assessment. Ethol Ecol Evol 17:249-259 Hamilton WD (1964) The genetical evolution of social behaviour, I and II. J Theor Biol 7:1-52 Hamilton WD (1971) Geometry for the selfish herd. J Theor Biol 31:295-311 Hammerstein P (2003) Why is reciprocity so rare in social animals? A protestant appeal. In: Hammerstein P (ed) Genetic and Cultural Evolution of Cooperation. MIT Press, Cambridge, pp 83-93 Hammerstein P, Hoekstra RF (1995) Mutualism on the move. Nature 376:121-122 Herre EA, Knowlton N, Mueller UG, Rehner SA (1999) The evolution of mutualisms: exploring the paths between conflict and cooperation. Trends Ecol Evol 14:49-53 Heyes CM (1998) Theory of mind in nonhuman primates. Behav Brain Sci 21:101-134 Johnstone RA, Bshary R (2002) From parasitism to mutualism: partner control in asymmetric interactions. Ecol Lett 5:634-639 Johnstone RA, Bshary R (2004) The evolution of spite through indirect reciprocity. Proc R Soc Lond B 271:1917-1922 Johnstone RA, Bshary R (2008) Mutualism, market effects and partner control. J Evol Biol 21:879-888 Kappeler PM, Silk JB (2010) Mind the Gap: Tracing the Origins of Human Universals. Springer, Heidelberg Kiers ET, Rousseau RA, West SA, Denison RF (2003) Host sanctions and the legume-rhizobium mutualism. Nature 425:78-81 Killingback T, Doebeli M, Knowlton N (1999) Variable investment, the continuous prisoner’s dilemma, and the origin of cooperation. Proc R Soc Lond B 266:1723-1728 Kokko H, Johnstone RA (1999) Social queuing in animal societies: a dynamic model of reproductive skew. Proc R Soc Lond B 266:571-578 Lamprecht J (1978) The relationship between food competition and foraging group size in some larger carnivores. A hypothesis. Z Tierpsychol 46:337-343 Lehmann L, Keller L (2006) The evolution of cooperation and altruism – a general framework and a classification of models. J Evol Biol 19:1365-1376 Lehmann L, Keller L, West S, Roze D (2007a) Group selection and kin selection: two concepts but one process. Proc Natl Acad Sci USA 104:6736-6739
Cooperation between unrelated individuals – a game theoretic approach
239
Lehmann L, Rousset F, Roze D, Keller L (2007b) Strong reciprocity or strong ferocity? A population genetic view of the evolution of altruistic punishment. Am Nat 170:21-36 Lotem A, Fishman MA, Stone L (2003) From reciprocity to unconditional altruism through signalling benefits. Proc R Soc Lond B 270:199-205 Luce RD, Raiffa H (1957) Games and Decisions: Introduction and Critical Survey. Wiley, New York Maynard Smith J (1982) Evolution and the Theory of Games. Cambridge University Press, Cambridge Maynard Smith J, Price G (1973) The logic of animal conflict. Nature 246:15-18 McGregor PK (1993) Signalling in territorial systems: a context for individual identification, ranging and eavesdropping. Philos Trans R Soc Lond B 340:237-244 McNamara JM, Barta Z, Houston AI (2004) Variation in behaviour promotes cooperation in the Prisoner’s Dilemma game. Nature 428:745-748 Milinski M (1987) Tit for tat in sticklebacks and the evolution of cooperation. Nature 325:433-435 Milinski M, Külling D, Kettler R (1990) Tit for tat: sticklebacks (Gasterosteus aculeatus) ‘trusting’ a cooperating partner. Behav Ecol 1:7-11 Milinski M, Lüthi JH, Eggler R, Parker GA (1997) Cooperation under predation risk: experiments on costs and benefits. Proc R Soc Lond B 264:831-837 Milinski M, Semmann D, Krambeck H-J (2002) Reputation helps solve the ‘tragedy of the commons’. Nature 415:424-426 Mueller UG, Gerardo NM, Aanen DK, Six DL, Schultz TR (2005) The evolution of agriculture in insects. Annu Rev Ecol Evol Syst 36:563-595 Nikiforakis N (2008) Punishment and counter-punishment in public good games: can we really govern ourselves? J Publ Econ 92:91-112 Noë R, van Schaik CP, van Hooff JARAM (1991) The market effect: an explanation for pay-off asymmetries among collaborating animals. Ethology 87:97118 Nowak MA, May RM (1992) Evolutionary games and spatial chaos. Nature 359:826-829 Nowak MA, Sigmund K (1992) Tit for tat in heterogeneous populations. Nature 355:250-253 Nowak MA, Sigmund K (1993) A strategy of win-stay, lose-shift that outperforms tit-for-tat in Prisoner’s Dilemma game. Nature 364:56-58 Nowak MA, Sigmund K (1998) Evolution of indirect reciprocity by image scoring. Nature 393:573-577 Raihani NJ, Grutter AS, Bshary R (2009) Punishers benefit from third-party punishment in fish. Science 327:171 Roberts G (1998) Competitive altruism: from reciprocity to the handicap principle. Proc R Soc Lond B 265:427-431 Robertson DR (1973) Sex change under the waves. New Sci 58:538-540 Rockenbach B, Milinski M (2006) The efficient interaction of indirect reciprocity and costly punishment. Nature 444:718-723
240
Redouan Bshary
Schneider JM, Bilde T (2008) Benefits of cooperation with genetic kin in a subsocial spider. Proc Natl Acad Sci USA 105:10843-10846 Semmann D, Krambeck H-J, Milinski M (2005) Reputation is valuable within and outside one’s own social group. Behav Ecol Sociobiol 57:611-616 Sherratt TN, Roberts G (2001) The importance of phenotypic defectors in stabilizing reciprocal altruism. Behav Ecol 12:313-317 Sherratt TN, Roberts G, Kassen R (2009) Evolutionary stable investment in products that confer both an individual benefit and a public good. Front Biosci 14:4557-4564 Soares MC, Bshary R, Cardoso SC, Côté IM (2008a) The meaning of jolts by fish clients of cleaning gobies. Ethology 114:209-214 Soares MC, Côté IM, Cardoso SC, Bshary R (2008b) On the absence of punishment, partner switching and tactile stimulation in the cleaning goby – client mutualism. J Zool Lond 276:306-312 Sommerfeld RD, Krambeck K-J, Milinski M (2008) Multiple gossip statements and their effect on reputation and trustworthiness. Proc R Soc Lond B 275:2529-2536 Taylor PD, Irwin AJ (2000) Overlapping generations can promote altruistic behavior. Evolution 54:1135-1141 Traulsen A, Nowak MA (2006) Evolution of cooperation by multilevel selection. Proc Natl Acad Sci USA 103:10952-10955 Trivers RL (1971) The evolution of reciprocal altruism. Q Rev Biol 46:35-57 van Baalen M, Rand DA (1998) The unit of selection in viscous populations and the evolution of altruism. J Theor Biol 193:631-648 Wedekind C, Milinski M (2000) Cooperation through image scoring in humans. Science 288:850-852 West SA, Griffin AS, Gardner A (2007a) Social semantics: altruism, cooperation, mutualism, strong reciprocity and group selection. J Evol Biol 20:415-432 West SA, Diggle SP, Buckling A, Gardner A, Griffin AS (2007b) The social lives of microbes. Annu Rev Ecol Evol Syst 38:53-77 Wilson DS (1990) Weak altruism, strong group selection. Oikos 59:135-140 Wilson DS, Wilson EO (2007) Rethinking the theoretical foundation of sociobiology. Q Rev Biol 82:327-348 Zahavi A (1995) Altruism as a handicap – the limitations of kin selection and reciprocity. J Avian Biol 26:1-3
Chapter 9
Group decision-making in animal societies GERALD KERTH
ABSTRACT Individuals need to coordinate their activities to benefit from group living. Thus group decisions are essential for societies, especially if group members cooperate with each other. Models show that shared (democratic) decisions outperform unshared (despotic) decisions, even if individuals disagree about actions. This is surprising as in most other contexts, differences in individual preferences lead to sex-, age-, or kin-specific behaviour. Empirical studies testing the predictions of the theoretical models have only recently begun to emerge. This applies particularly to group decisions in fission-fusion societies, where individuals can avoid decisions that are not in their interest. After outlining the basic ideas and theoretical models on group decision-making I focus on the available empirical studies. Originally most of the relevant studies have been on social insects and fish but recently an increasing number of studies on mammals and birds have been published, including some that deal with wild long-lived animals living in complex societies. This includes societies where group members have different interests, as in most mammals, and which have been less studied compared to eusocial insects that normally have no conflict among their colony members about what to do. I investigate whether the same decision rules apply in societies with conflict and without conflict, and outline open questions that remain to be studied. The chapter concludes with a synthesis on what is known about group decision-making in animals and an outlook on what I think should be done to answer the open questions.
242
Gerald Kerth
9.1 Why are group decisions important in animal societies? Group decisions are important in all human and non-human societies (stable individualised groups) because group-living requires individuals to coordinate their activities (Bonabeau et al. 1997, Seeley and Buhrman 1999, Franks et al. 2002, Conradt and Roper 2003, 2005, List 2004, Conradt and List 2009). Group decisions are needed whenever group coordination is beneficial but individuals can choose between alternatives. Group deciTable 9.1 Different forms of animal sociality
Forms of animal sociality Aggregation
Anonymous assemblage of individuals. Aggregations are generally less stable than societies. Animals in aggregations show no social bonds and do not engage in cooperative or other affiliate social interactions. Examples include many fish swarms, large flocks of migrating birds that meet at night roosts, and other transient animal groups.
Society
Group of individuals that show social bonds, that may engage in cooperative behaviours, and that recognise each other individually or as members of the same society. Despite the occurrence of social bonds and cooperation, in societies with a heterogeneous demographic and genetic structure individuals are likely to differ in their interests because of individual differences in age, dominance, relatedness, reproductive status, or sex. Examples for heterogeneous societies from mammals include troops of primates, bands of many social carnivores, and colonies of some bat species.
Fission-fusion society
Group that shows all characteristics of a society – social bonds, cooperation, group or individual recognition – but which regularly splits into smaller subgroups (fission), which later merge again (fusion). Fission-fusion societies are found in elephants, dolphins and some other cetaceans, in some primates, in a few social carnivores, in some ungulates, and in several bat species.
Group decision-making in animal societies
243
sion-making occurs when an action by one, several, or all group members affects the behaviour of the entire group. Group-living animals have to communally decide when and where to move, where and on what to feed, and where to rest, roost, or nest (Byrne 2000, Franks et al. 2002, Conradt and Roper 2005, Seeley et al. 2006). Group decisions also occur in more or less transient aggregations of animals, such as fish swarms or large flocks of migrating birds (Conradt and List 2009). However, they are particularly important in stable societies where the fitness of individuals strongly depends on the behaviour of their group members, for instance because they show cooperative behaviour. Eusocial insects for example, depend on group decisions for the functioning of their colonies during foraging and nest-site choice (Seeley et al. 1991, 2006, Franks et al. 2002). Group decision-making may also be necessary to coordinate reproduction of group members where individuals benefit from synchronised breeding via reduced predation or infanticide risk, and from energetic benefits through communal warming (Conradt and Roper 2005). Consequently, information on how animals make group decisions has significant implications for our understanding of how their societies function, particularly with respect to cooperation and group stability. To understand decision-making in animal groups, we need to determine who makes the decisions, what factors affect the way in which they are made, and what decision-making processes are optimal under different circumstances (Conradt and Roper 2005). Before I introduce several of the models and empirical studies on group coordination in animals, it is necessary to define some of the terms used in this chapter. Table 9.1 defines three forms of animal sociality, while Table 9.2 defines the most important terms used to describe group decision-making in animals. Table 9.2 Definitions of terms used to describe group decision-making within groups of animals (based on Conradt and Roper 2005 and Conradt and List 2009)
Definitions Consensus
Binding agreement among group members on a decision.
Consensus cost
Cost to an individual group member that arises from not taking an action that would be optimal for the individual and instead complying with the consensus decision of the group.
244
Gerald Kerth
Table 9.2 Continued Coordination
Outcome of a group decision; can involve behaviour (e.g. joint travelling or communal nesting/roosting) or physiological states (e.g. synchronisation of reproduction or torpor) of a group.
Grouping benefits
Benefits that arise from staying in a group compared to a situation where an individual is on its own. Examples include energetic benefits from social thermoregulation or safety from predators from increased group vigilance.
Shared decisions
Decisions made by most or all group members; corresponds to democratic decision-making in humans. Shared decisions are ‘equally weighted’ if each group member has the same influence on the decision or ‘weighted’ if certain individuals have more influence, for example depending on their age, sex, information status, dominance, or individual needs.
Expression of preference
Signalling of individual preferences during the decisionmaking process; corresponds to voting in humans.
Informationpooling
Transfer of individual information to other group members during the decision-making process.
Leadership
If a single group member influences a group decision; may be restricted to a single decision and taken in turn by all or many of the group members (distributed leadership) or stable over several decisions (personalised leadership).
Quorum
Number of group members needed to make a group decision. Responses to a quorum threshold have been observed in many species making group decision, such as ants, honeybees, fish, and even humans.
Self-organisation
Group behaviour, which emerges in the absence of global control when individuals behave according to (simple) behavioural rules that are based on local information and that are influenced by the behaviour of neighbouring group members. Widespread in nature, occurs for example in moving fish swarms or bird flocks and even in humans, for example in pedestrians moving in a crowd.
Unshared decisions
Decisions made by one or a few (minority) of the group members; corresponds to despotic decision-making in humans.
Group decision-making in animal societies
245
9.2 Group decision-making: Basic ideas and theoretical models The particular group decision-making processes should optimise the benefits of living in groups for the involved individuals given the limits that conflicts between individuals impose. When group members share a common goal, such as finding a suitable place for communal nesting or a profitable food resource, optimal group decisions depend on the ability to compare the information available to different group members and to select the option that is best for all. Several verbal and mathematical models (Conradt and Roper 2003, List 2004, Simons 2004, Couzin et al. 2005) proposed that shared decisions, in which many individuals pool their individual information, are advantageous as they are more likely to be correct (optimal outcome for all group members) than decisions made by one or a few ‘leaders’. Mechanisms for making group decisions of this kind range from relatively simple self-organisation rules to highly evolved information-pooling behaviours. Self-organising processes during which complex group behaviours emerge through simple behavioural rules at the individual level are widespread among animals, and also exist in humans (Deneubourg and Goss 1989, Bonabeau et al. 1997, Camazine et al. 2001, Couzin and Krause 2003). Self-organisation occurs for example in cockroaches (Blatta germanica) seeking a shelter (Amé et al. 2006), army ants (Eciton burchelli) forming foraging lanes (Couzin and Franks 2003), bird flocks avoiding predators (Ballerini et al. 2008), and foraging fish swarms (Sumpter et al. 2008). Complex information-pooling behaviours, such as the honeybee’s (Apis mellifera) waggle dance, or ‘teaching’ in ants (Temnothorax albipenis), are found in eusocial insects selecting new communal nest-sites (Franks and Richardson 2006, Seeley et al. 2006). Although these different self-organisation processes and information-pooling behaviours differ in their complexity, all are regulated at the local level through positive and negative feedback processes that amplify or dampen the emergent group behaviours (Couzin 2008). Group decision-making is most complex if individual preferences vary depending on the age, sex, and social or reproductive status of the group members, and, thus, the best decision for the average group member is not optimal for all. A first model by Conradt and Roper (2003) suggested that in situations with conflicting interests, decisions made by a majority of group members should be beneficial as they avoid extreme outcomes by averaging over individual preferences, thereby keeping the consensus costs equally low for each individual. The model concludes that shared decisions, to which many or all group members contribute, outperform un-
246
Gerald Kerth
shared decisions by one or a few leaders, even in situations where individuals disagree about actions. This prediction was unexpected as in many other contexts different individual preferences lead to sex-, age-, status- or kin-specific behaviour (Krause and Ruxton 2002). For example, many ungulates as well as some bats and carnivores show social sexual segregation. Here, males and females live in separate groups because they have different activity budgets or feed on different food (Gompper et al. 1996, Conradt 1998, Ruckstuhl and Neuhaus 2002, Safi et al. 2007). While the initial model of Conradt and Roper’s (2003) could not explain how shared decisions evolved, more recent models by Conradt and Roper (2007, 2009) and Conradt et al. (2009) with an evolutionary approach overcame this problem by exploring different circumstances under which shared or unshared decisions are likely to evolve. They predicted that the evolution of shared decisions might depend on a variety of factors, including group size, the level of inter-individual conflict, and the modality of the group decision. Two factors were found to be most important: 1) the level of inter-individual conflict weighted against the grouping benefits that the individuals gain if they stay together; 2) whether the group decision-making process allows for a feasible compromise, which seems more likely for activity synchronisation (i.e., when to go) than for situations where a group has to decide about a spatial target (i.e., where to go to; Conradt and Roper 2009). Evolutionary models of this kind are very helpful if we want to understand ‘real world’ group decision-making in animal societies because they consider the diversity of situations under which animals have to make group decisions. One important assumption of most of the models dealing with group decision-making is that group members only gain grouping benefits if all of them maintain group cohesion (Conradt and Roper 2003, 2007, Rands et al. 2003, Couzin et al. 2005, Conradt et al. 2009). This assumption, however, is probably unrealistic for a substantial number of social species. In many animal societies, group members regularly form subgroups for certain time periods without leaving the society permanently (Aureli et al. 2008). Such fission-fusion behaviour (see BOX 9.1) could reflect situations where a beneficial consensus cannot be reached because interindividual conflicts or time constraints lead to a temporary group fission instead of a compromise (Franks et al. 2003, Kerth et al. 2006, King et al. 2008, Conradt et al. 2009). Alternatively, splitting into subgroups could also be an optimal group decision, if it is best for all individuals to temporarily forage or roost in smaller subgroups (Kerth et al. 2006). It will depend on the shape of the function describing the relationship between the grouping benefits and the size of a group whether individuals in subgroups can still gain the full range of grouping benefits.
Group decision-making in animal societies
247
BOX 9.1 Fission-fusion behaviour Fission-fusion behaviour is the temporary splitting and reformation of animal groups. Kummer (1968) originally introduced the term in his description of the social organisation of hamadryas baboons. Fission-fusion behaviour is widespread among animals, occurring in social insects, fish, birds, and mammals, including humans. Understanding the fission-fusion dynamics of animal groups is important as the extent to which groups can temporarily split into smaller social units has far reaching consequences for a species’ social organisation, mating system, and social interactions. Whether fissionfusion behaviour requires special communication and cognitive skills is still an open question (Aureli et al. 2008). Moreover, fission-fusion societies provide us with novel prospects to study group decisions (Kerth et al. 2006). The temporary formation of subgroups that better represent their preferences than the group as a whole could help individuals that disagree about an action to avoid a consensus without foregoing grouping benefits. The option of splitting into subgroups has largely been neglected in studies on group decision-making or has been treated as a non-adaptive outcome (e.g. Couzin et al. 2005). However, fission-fusion behaviour is important for our understanding of group coordination because whether or not group members are able to temporarily avoid group decisions that are not in their favour may strongly affect the way group decisions are made (Conradt and Roper 2005, Kerth et al. 2006). For the analyses of fission-fusion societies, association indices and social network analyses are available (Croft et al. 2008, Whitehead 2008). Both methods allow one to assess to what degree relatedness and shared interests – resulting from the same reproductive status, sex, age, or rank – explain the fission-fusion dynamics, and hence the social organisation of species (Kerth and König 1999, Archie et al. 2006, Sundareasan et al. 2007, Aureli et al. 2008, Kerth 2008, Sueur and Petit 2008). Such data are prerequisites for understanding cooperation and coordination in fissionfusion societies.
Conradt and Roper (2005) distinguish between consensus decisions in situations when all group members need to stay together and combined decisions when groups can temporarily split into subgroups. They argued that consensus and combined group decisions are conceptually different. However, several recent empirical studies suggest that consensus and combined decisions may result from the same decision-making process and the outcome of a group decision may depend more on the situation (i.e. the amount of conflict, and ultimately the ratio of grouping benefits versus consensus costs) than on the way decisions are made (e.g. Biro et al. 2006, Kerth et al. 2006, King et al. 2008).
248
Gerald Kerth
9.3 Group decision-making: empirical studies The first empirical studies on group decision-making in animals observed the coordination of travelling individuals in relatively conspicuous species, such as primates, ungulates, and birds (Kummer 1968, Wallraff 1978, Reinhardt 1983, Black 1988, Boinski and Campell 1995, Prins 1996). For some of these species, such as mountain gorillas (Gorilla gorilla beringei) or cattle (Bos indicus), the studies reported that a single individual more or less consistently led the group during travel (‘personalised leadership’; Schaller 1963, Reinhardt 1983). For other species, such as capuchin monkeys (Cebus capucinus) and African buffalos (Syncerus caffer), a ‘distributed leadership’, where many or all individuals contributed to the leading of a group, was described (Boinski and Campell 1995, Prins 1996). Although largely descriptive, these studies showed that the way group decisions are made could differ between species and sometimes even between different groups of the same species (Boinski and Campell 1995). In gorillas even a within-species contrast between unshared decisions about travelling destination and partially shared decisions about activity synchronisation was found (Stewart and Harcourt 1994). The observational field studies on mammals and birds were followed by a large number of experimental studies on social insects and fish, which were mostly carried out under controlled laboratory conditions (e.g. Seeley et al. 1991, Krause et al. 1992, Lachlan et al. 1998, Seeley and Buhrman 1999, 2001, Reebs 2000, Mallon et al. 2001, Franks et al. 2002, 2003, Pratt et al. 2002, Amé et al. 2006). Again, the majority of these studies explored group decisions over movements, either to a profitable food resource or a suitable shelter. Only recently, studies on wild mammals have started to combine field experiments and behavioural observations of recognisable individuals with the aim to investigate group decisions in heterogeneous animal societies (McComb et al. 2001, Kerth et al. 2006, King et al. 2008). These recent studies on group decision-making in mammals, birds, fish, and social insects (Fig. 9.1) illustrate the flexibility of animal group decision-making in situations with and without conflict.
Group decision-making in animal societies a
b
c
d
249
Fig. 9.1 Examples of animal societies that differ in how many individuals influence group decisions. (a) Groups of African elephants are led by a single female (Loxodonta africana; photo © C. Schradin). (b) Swarms of honeybees are led to a new nest-site by scouts that comprise about 5% of the colony members (Apis mellifera; photo © T.D. Seeley). (c) Colonies of house-hunting ants are led to a new nest-site by scouts that comprise about a third of the colony members (Temnothorax albipennis formerly Leptothorax albipennis; photo © N.R. Franks). (d) In groups of chacma baboons the dominant male decides where to feed, but leadership is shared during other travel decisions (Papio ursinus; photo © H. Peck/ZSL Tsaobis Baboon Project).
250
Gerald Kerth
9.3.1 Shared versus unshared decisions, and the importance of a quorum Whether group decisions are shared or unshared depends at least on four factors, which may affect the asymmetry of the influence of group members on the rest of the group: 1) the time available to make the decision (Franks et al. 2003), 2) the distribution of information on which the decision is based (List 2004, Simons 2004, Couzin et al. 2005), 3) the cognitive abilities of the organism (Mallon et al. 2001, McComb et al. 2001), and 4) the amount of conflict among the group members (Conradt and Roper 2005, Conradt and List 2009). Time constraints may override other factors influencing group decisions. When fast decisions are needed, all group members may benefit by following the decision of the best-informed individual (Laland 2004). Thus, situations requiring fast responses should favour unshared decisions. Indeed, in species that emit alarm calls to approaching predators, the first individual to spot the danger gives the call and causes the others to respond aptly (Sherman 1977). Moreover, when a decision has to be made almost immediately, individuals commonly copy the behaviour of their neighbour (Laland 2004). However, copying can also generate information-cascades that may lead to wrong decisions. Blindly copying the behaviour of others can therefore be maladaptive (Laland and Williams 1998, Danchin et al. 2004). The trade-off between decision accuracy and the time it takes to make a decision has been shown in ants searching for a new nest site. The more ants are involved in the decision, the more accurate a decision might become but it also takes longer to arrive at a consensus (Franks et al. 2009). Ward et al. (2008) recently showed experimentally that sticklebacks (Gasterosteus aculatus) were able to avoid maladaptive informationcascades by copying the travelling behaviour of others only if a minimum number (quorum) of conspecifics moved in the same direction. Finally, a study by List et al. (2009) looking at the group decisions of honeybees demonstrated that it depends on the interplay between inter-dependence and independence during the gathering and transfer of information in order to avoid information-cascades and to reach a consensus for the best nestsite instead. All these studies underline the importance of quorum responses during group decision-making in the common situation when a more or less graded trade-off exists between speed and accuracy (Sumpter and Pratt 2009).
Group decision-making in animal societies
251
9.3.2 Group decisions without conflict In situations in which group members share a common goal but vary in the kind of information they hold, theoretical models predict shared decisions (List 2004, Simons 2004, Couzin et al. 2005). The degree of sharing observed in empirical studies, however, differs between species. An example of a partially shared decision is the choice for a new nest-site in swarming honeybees (A. mellifera). Here, only about 5% of the colony members, the so-called scouts, decide where to lead the swarm (Seeley and Buhrman 1999). At the end of each summer, after a new queen has hatched, the old queen leaves the hive with a part of the original colony to move to a new nesting site, for example in a hollow tree. The scouts searching for new nesting-sites decide among each other which one is most suitable. By varying the intensity and duration of their waggle dance for a certain nesting site, the scouts signal their individual preferences. During this process it is not required that each scout has visited all potential nesting-sites. After the scouts have agreed on a site, they lead the swarm to the chosen place. The remaining 95% of the 3,000 – 10,000 swarm bees and the queen are not actively involved in the selection of a new home. Similarly, in the ant T. albipennis, which lives in relatively small colonies of about 200 – 500 individuals, colonies have to search for a new nest-site whenever their old nest, which is typically located in a fragile rock crevice or a nutshell, has been destroyed. In these ‘house-hunting’ ants about a third of the colony members are responsible for selection of and recruitment to a new nest-site (Pratt et al. 2002). Group decisions that involve only part of a group are also found in primates. In hamadryas baboons, only adult males are involved in the decisions about travel timing and direction (Kummer 1968), whereas in two lemur species specific females lead most of the time during travel (Erhart and Overdorff 1999). In contrast, in chacma baboons (Papio ursinus), Verreaux’s sifakas (Propithecus verreauxi), brown lemurs (Eulemur fulvus fulvus), and capuchin monkeys (C. capucinus), all adults more or less equally influence most travel decisions (Leca et al. 2003, Trillmich et al. 2004, Jacobs et al. 2008, Stueckle and Zinner 2008). Such inter-specific differences raise the question whether there are optimal proportions of individuals contributing to a group decision, depending on the situation. In ants, honeybees, African elephants (Loxodonta africana), and some primates the oldest or experienced individuals lead a social group (Seeley and Buhrman 1999, Mallon et al. 2001, Byrne 2000, McComb et al. 2001, Pratt et al. 2002). The long-term study of McComb and co-workers (2001) on elephants in Kenya provides a fine example of unshared group decision-making in animal societies, in which individuals differ in their experi-
252
Gerald Kerth
ence. Groups of elephants comprise several adult females and their offspring. Groups are led by the eldest female, the matriarch. The researchers used playback experiments to present different groups of elephants with calls of individuals that did not belong to their own group but lived in the same area. The experiment showed that the older a matriarch was, the better she was in discriminating between the calls of foreign individuals. This was the case because old matriarchs knew a large number of foreign elephants from previous encounters. McComb et al. (2001) also found that old matriarchs were most efficient in leading their groups away from those foreign individuals that were most aggressive and dangerous. This remarkable field study shows that it can be very advantageous to follow an experienced leader, and that leading a group may require special cognitive abilities if a lot of information has to be stored. More influence on decisions by experienced individuals has also been found in fish where information about food was experimentally restricted to a few members of a shoal (Krause et al. 1992, Reebs 2000, Couzin and Krause 2003, Laland 2004). This coincides with the model of Couzin et al. (2005), which predicts that in large groups of animals, such as shoal-living fish or swarming honeybees, a small proportion of informed individuals is sufficient to make an accurate decision about where to move. Finally, if conflict among group members is low and information is generally high, it may become less crucial to pool information, as each individual already makes sufficiently accurate decisions, and this might also favour unshared, fast decisions. In this case, any group member could initiate the group decision as suggested for some kinds of decisions in dolphins (Lusseau and Conradt 2009). 9.3.3 Group decisions with conflict In many circumstances, the interests of the members of a group vary, generating conflict over group decisions (Conradt and Roper 2005, 2009). Inter-individual conflict may be caused by differences in phenotype, such as age, sex, dominance status or reproductive and nutritional status. The level of inter-individual conflict also depends on the distribution of individual genotypes among group members. Colonies of eusocial insects that are founded by a single queen will often have lower conflict levels than groups of vertebrates where the members generally have a more variable degree of relatedness. Differences among individuals may also vary over time. Consequently, the level of conflict can differ depending on the situation. For example, female mammals are likely to experience less conflict outside the reproductive period than during lactation, when the physiological needs of mothers differ more from that of non-reproductive females (Kerth et al.
Group decision-making in animal societies
253
2001, Dall and Boyd 2004, Fischhoff et al. 2007). Several models (Rands et al. 2003, Conradt et al. 2009) predicted the identity of leading individuals according to the individual needs and this has been confirmed in several empirical studies (Krause et al. 1992, Fischhoff et al. 2007, Furrer et al. submitted). In their initial model, Conradt and Roper (2003) suggested that in most situations with conflict, shared decisions are favoured as subordinates are likely to resist an unfavourable ‘despotic’ decision of a dominant individual. However, a recent field study on chacma baboons (P. ursinus) suggests that the way group decisions are made does not only depend on the distribution of immediate individual payoffs of a decision, but also on the asymmetry of influence in a group and the opportunity of subordinates to avoid dominants that manipulate the outcome of a group decision in their favour (King et al. 2008). King and co-workers (2008) provided two chacma baboon groups with experimental food patches, where food was spatially more concentrated than in natural food patches. As a result, the dominant males could only monopolise food in the experimental patches. If a dominant male could obtain foraging benefits by leading his group to an experimental food patch he consistently did so, even though under other travel conditions leadership in chacma baboons is more widely distributed among group members (Stueckle and Zinner 2008). King et al. (2008) also investigated the influence of kinship, rank, and social bonds on the likelihood of following a despotic decision of the dominant individual. They observed two types of close-followers: The first type consisted of relatively high-ranking males that arrived soon after the dominant leader at an experimental patch. This assured them a disproportionately high share of the food, compared to the other, lower-ranking group members. The second type of close followers comprised lowranking animals that were highly socially affiliated with the leader. They were also very likely to closely follow the dominant male to an experimental patch, even though there they received a consensus cost from lower food intake compared to a natural food patch. Kinship had no influence on the likelihood to follow the leader closely. King et al. (2008) concluded that following behaviour in the presence of a conflict is more likely to occur when followers have strong social relationships with the leader. Longterm benefits of associating with a dominant male, such as protection from predators and lower infanticide risk (Stueckle and Zinner 2008), could explain why individuals followed in situations where this behaviour resulted in a considerable consensus cost (King et al. 2008). In the larger of the two groups, however, low-ranking individuals did not always follow the dominant male. On a few occasions, group fission occurred, resulting in the formation of two subgroups. One subgroup con-
254
Gerald Kerth
BOX 9.2 Group decisions over communal roosts in Bechstein’s bat fission-fusion societies Bechstein’s bats (M. bechsteinii) are forest-dwelling bats that can reach an age of 20 years. Females breed communally in colonies consisting of 10 – 45 adult females (Fig. 9.2). Females are philopatric and stay in their natal colony whereas males disperse in their first year of life and afterwards live solitarily during summer (Kerth and Morf 2004). As the philopatric females mate with different males each year, colonies comprise both, closely related (e.g. mother-daughter pairs) and genetically largely unrelated females (Kerth et al. 2002). Females do not give birth every year so that colonies comprise reproductive and non-reproductive females. Within their home range, colonies switch almost daily among communal day roosts (tree cavities and bat boxes) to avoid parasites and to select optimal roost temperatures (Kerth and König 1999, Kerth et al. 2001, Reckardt and Kerth 2007). Over the last 17 years, my co-workers and I collected data on the demography, reproductive success, survival, behaviour, and relatedness of more than 300 PIT-tagged individuals from four colonies living in forests near Würzburg, Germany. We found evidence for complex communication, group and individual recognition, flexible context-related social interaction, and benefits of sociality that include social thermoregulation and opportunities for information transfer about suitable roosts (Kerth and König 1999, Kerth et al. 2001, 2002, Kerth and Reckardt 2003, Safi and Kerth 2003, Kerth 2008, Pretzlaff et al. 2010). Despite their stable individual composition, Bechstein’s bat colonies are fission-fusion societies that regularly split into 2 – 6 temporary subgroups that use separate roosts for a few days before they remerge (Kerth and König 1999). As a consequence of their frequent roost switching, colony members must make daily group decisions over where to roost. We study group decision-making in wild Bechstein’s bat colonies using experiments in which we provided individuals with conflicting information about the suitability of potential roosts (Kerth et al. 2006). We also manipulated roost quality to increase asymmetries in individual preferences among colony members, for example between lactating females that prefer warmer roosts compared to non-reproductive females (Kerth et al. 2001). Permanent roost monitoring with automatic PIT-tag readers allowed us to record the bats’ nightly information transfer as well as the day-roosting behaviour (Kerth and Reckardt 2003). In one field experiment, we provided individuals with conflicting information about the suitability of new bat boxes placed inside the home ranges of two colonies. In another experiment, we provided members of one colony with conflicting information (disturbance versus no disturbance) about the suitability of their current day roost. The bats’ individual behaviour suggested that they considered both their own information and the behaviour of
Group decision-making in animal societies
255
other colony members when deciding when to switch a roost and where to roost next (Kerth et al. 2006). Conflicting interests in the heterogeneous colonies may have prevented the bats from relying entirely on social information, as this only makes sense if the needs of individuals are similar (Danchin et al. 2004). We also observed that most of the colony members inspected a novel roost and transferred information about its suitability days before it is used as a day roost for the first time. By relying on many inspecting individuals, a colony may ensure that the best communal roost is chosen. Bechstein’s bat colonies are small compared to those of eusocial insects and a large fraction of a bat colony may be required to make an optimal decision. Finally, the group decisions about communal day roosts reflected the information available to a majority of the bats roosting together but conflicting information led to increased fission in one of the two colonies. Our study suggests that fission-fusion societies allow individuals to avoid majority decisions that are not in their favour without foregoing grouping benefits that arise from communal roosting, such as social thermoregulation (Kerth et al. 2006).
Fig. 9.2 Part of a colony of Bechstein’s bats that daily make group decisions about communal day roosts. The bats are individually marked with coloured rings and subcutaneously implanted PIT-tags (Myotis bechsteinii; photo © by K. Weissman, naturefilm).
256
Gerald Kerth
tained the relatively high-ranking individuals, which received a foraging benefit at the experimental patches. The other subgroup comprised the lower-ranking individuals that would have experienced a consensus cost at the experimental food patches. During group fission, only the high-ranking animals that suffered no consensus costs visited the experimental patch. Finally, whenever the dominant male had been mate-guarding a receptive female, the group did not visit the experimental food patches. On those days this receptive female determined where the group moved and she did not visit the experimental food patch since she was relatively low in rank and would have suffered foraging costs there. The study by King et al. (2008) convincingly shows that unshared group decisions can emerge if a potential leader has both a strong incentive to lead and sufficient social influence to make the other group members follow even though this means they suffer consensus costs. That strong inter-individual conflicts can lead to temporary group fission instead of a consensus decision has also been shown in domestic pigeons (Columba livia f. domestica) that make group decisions about travel routes (Biro et al. 2006) and in Bechstein’s bats (Myotis bechsteinii) that make group decisions about communal roosts (Kerth et al. 2006; BOX 9.2). Biro and co-workers (2006) released single pigeons that carried small GPS receivers, which allowed the researchers to reconstruct the route of the individuals flying home. Each of the singly released pigeons followed an individual travel route that differed from that of other individuals but which was stable over time. In a second step, the researchers released the same individuals in pairs. They observed that the two birds chose an intermediate route, which represented a compromise between their original individual travel routes, whenever the original routes had been similar to each other. However, if the initial travel routes differed strongly between the two individuals, two different outcomes were possible. Either one bird gave up its own route and followed that of its partner or the two pigeons split up and each of them used its original travel route. This elegant study provides further evidence that the outcome of group decisions depends on the level of inter-individual conflict and may vary depending on the situation. Currently we do not know how larger pigeon flocks react to interindividual conflict. In Bechstein’s bats colonies, which comprise up to 40 females, colony members can also avoid group decisions that are against their individual interest by temporarily splitting into smaller subgroups that later merge again. Nevertheless, field experiments showed that even in situations with conflicting information about the suitability of a communal roost, Bechstein’s bats often do achieve a consensus, which reflects the information available to the majority of the colony members (Kerth et al. 2006; see
Group decision-making in animal societies
257
BOX 9.2 for more details). This study, as well as the studies on chacma baboons and domestic pigeons (Biro et al. 2006, King et al. 2008), suggests that group decision-making processes in fission-fusion societies may not be fundamentally different from those in animal societies that depend more strongly on reaching a consensus.
9.4 Open questions about group decision-making Despite the recent increase in studies on group decision-making in animals, we still lack the empirical data from a sufficient number of wild vertebrates to fully evaluate the assumptions and predictions of the models dealing with group decisions. Future empirical research must identify in what context different forms of group decisions (shared versus unshared; self-organised versus decision-making in a situation where one or several individuals have global overview) occur in different species in the wild, and then to make comparisons to other species. In particular, new empirical studies must consider the constraints (time, cognitive abilities) of group decision-making and measure the influence individuals have on group decisions in different contexts, and over longer time periods. To understand reasons for a potential asymmetry of individual influence, one also has to investigate the genetic and social relationships among group members, as well as their individual ‘personalities’ (Wolf et al. 2007, Harcourt et al. 2009, Bergmüller this volume). In nature, this will often require long-term studies, particularly in long-lived mammals (Kruuk and Hill 2008). Studies on wild animals are needed that vary the time available for a decision and then measure to what degree the resulting group decision are shared among group members in situations where individuals have different interests, analogous to what has been done for ants and honeybees in situations with no conflict of interest (Franks et al. 2003, Seeley et al. 2006). By manipulating the level of conflict in a group, its influence on the group decision processes can be tested (Biro et al. 2006, Kerth et al. 2006, King et al. 2008). An obvious experiment would be to vary group structure, for example by increasing the variation in age, relatedness, reproductive state, or body condition and then presenting the group with a situation that makes compromises between individuals difficult. In many animal societies it may be difficult to perform such manipulations, particularly in the field. Here, it will still be rewarding to study group decision-making by detailed observations of individual behaviour and describing the relationship among group members in their natural habitat (Fischhoff et al. 2007). At the level of the individual, one has to identify alternative decisions avail-
258
Gerald Kerth
able, as well as their costs and benefit in each situation. This remains a challenge for field studies on long-lived vertebrates, but King et al. (2008) showed that it is feasible. Another open question is the influence of kinship and cooperation on group decision-making processes. Kinship among group members may lower the consensus costs if an individual that refrains from taking its optimal action receives indirect benefits from helping a close relative to implement his or her optimal decision. Kin selection is not the only factor that may influence the formation of coalitions during group decisionmaking. Other forms of relevant cooperative behaviours include direct and indirect reciprocity (Couzin 2008, Conradt and List 2009). As long as subordinates are not able to form coalitions, a dominant individual does not have to fight against all subordinates together. In several cooperatively breeding species where only the dominant female breeds, she concentrates her aggression on specific individuals, and the other subordinates do not support the attacked group member (Clutton-Brock et al. 1998). Hence, the dominant individual could enforce despotic group decision-making. In addition, different interests of individual subordinates may prevent the formation of coalitions. Only in primates do subordinates form coalitions against dominant group members. Even in humans where coalition forming is common, alliances by opposing people are typically successfully suppressed in despotic societies (Harcourt 1992, Summers 2005). As a result, in the absence of kin selection or other forms of cooperation that may lower inter-individual conflict-levels, despotic decisions may be more common in heterogeneous animal societies than suggested by the initial model by Conradt and Roper (2003). Finally, it is unclear to what degree group decision-making processes are constrained by the cognitive abilities of the interacting individuals. Most of the theoretical models assume that group decisions in animals are based on simple behavioural rules, which do not involve high cognitive abilities (Couzin et al. 2005, Couzin 2008). This probably reflects many of the group decisions well where no conflict over the outcome exists, and group members only try to find the optimal way to reach and implement a decision. Travelling fish and social insects often make this kind of group decision. However, in situations with conflict among group members, the few empirical studies available on mammals suggest that complicated cognitive processes are involved in decision-making, for example in elephants that avoid potentially dangerous conspecifics (McComb et al. 2001). Since complexity of information processing also results from the social environment, the structure and size of a group should influence group decisionmaking processes. Mallon and co-workers (2001) proposed that in situations when group decisions are based on information gathering and trans-
Group decision-making in animal societies
259
fer among group members that share a common goal, small groups might place a greater cognitive burden on individuals than larger groups. This idea is in agreement with the model by Couzin and co-workers (2005), which predicts that in larger groups a smaller proportion of informed individuals is necessary for achieving an accurate decision. Mechanisms used to make group decisions that involve self-organisation do not require high cognitive abilities (Couzin 2008). Nevertheless, it should be highly rewarding to identify differences in group decision-making processes depending on the cognitive abilities and the social and ecological environment of a species, while correcting for phylogeny.
9.5 Synthesis and outlook Even though most models predict shared group decisions, several field studies show that in heterogeneous animal societies, specific individuals may have more influence than others. Reasons for this are: 1) their dominance status may give them more power in conflicts, 2) their personality makes them bolder leaders, 3) they may be favourite associates of other group members because they provide protection, 4) they may have the best knowledge because they are more experienced, 5) hold more information, or 6) have higher cognitive abilities. In all these cases, it may be beneficial for other individuals to follow their decision, even if this means accepting some (short-term) consensus costs (King et al. 2008). Depending on the social structure of a group and the situation in which a decision has to be made, individual influence on a group decision may be stable over several decisions or it may differ from decision to decision. Long-term leadership is the result of a strong asymmetry of individual influence over many decisions in different contexts. Several studies suggest that interactions between the different factors (conflict, distribution of information, constraints) influencing group decisions cause trade-offs, which can lead to flexible and sometimes suboptimal group decisions. For example, the number of individuals involved in the group decision-making process of house-hunting ants appears to be a compromise between accuracy and speed (Franks et al. 2003). Experiments with varying time-constraints confirmed that ant colonies were able to speed up the group decision-making by concentrating the process to a quorum involving fewer individuals, albeit at the cost of lower accuracy (Pratt et al. 2002, Franks et al. 2003). Trade-off between accuracy and speed is also observed in human group decisions where time constraints create a uniformity of preferences, lead to decisions with fewer individuals
260
Gerald Kerth
involved, and may prevent groups to achieve the best solution (Kerr and Tindale 2004). Furthermore, human groups are often not able to use the available information in the optimal way when a conflict among group members exists (Kerr and Tindale 2004). Research on group decision-making made tremendous progress in the last decade. However, many open questions remain (see Sect. 1.4) and empirical studies continue to be difficult and new approaches are required to successfully investigate the complexity of group decision-making in nature. More studies on group decision-making in wild animal societies that combine detailed observation of individual behaviour with carefully designed experiments are required to answer the remaining open questions. The available studies of this kind demonstrate that this can yield fascinating and unexpected results (McComb et al. 2001, Biro et al. 2006, Kerth et al. 2006, King et al. 2008). More sophisticated studies on group decisionmaking in animals will further also our understanding of the social structure and the stability of animal societies over time.
Acknowledgements This review was inspired by a workshop on communal decision-making, which Marta Manser and I organised in Zürich in September 2004 and which was funded by the Cogito Foundation. This book chapter benefited greatly from the comments of many people sharing their ideas on group decision-making with me over the last years, in particular Marta Manser and Tim Clutton-Brock. For comments on the manuscript I thank Roman Furrer, Stefan Greif, Marta Manser, Rachel Page and two anonymous referees. The German Research Foundation (DFG) funded me while I was writing this book chapter (KE476/3-1).
References Amé JM, Halloy J, Rivault C, Detrain C, Deneubourg JL (2006) Collegial decision making based on social amplification leads to optimal group formation. Proc Natl Acad Sci USA 103:5835-5840 Archie EA, Moss CJ, Alberts SC (2006) The ties that bind: genetic relatedness predicts the fission and fusion of social groups in wild African elephants. Proc R Soc Lond B 273:513-522
Group decision-making in animal societies
261
Aureli F, Schaffner CM, Boesch C, Breader SK, Call J, Chapman CA, Connor R, Di Fiore A, Dunbar RIM, Henzi SP, Holekamp K, Korstjens AH, Layton R, Lee P, Lehmann J, Manson JH, Ramos-Fernandez G, Strier KB, van Schaik CP, Boehm C, Izar P, Kreth G, Kummer H, Talebi M, Yamagiwa J (2008) Fission-fusion dynamics: new research frameworks. Curr Anthropol 49:627654 Ballerini M, Cabbibo N, Candelier R, Cavagna A, Cisbani E, Giardina I, Orlandi A, Parisi G, Procaccini A, Viale M, Zdravkovic V (2008) Empirical investigation of starling flocks: a benchmark study in collective animal behaviour. Anim Behav 76:201-215 Biro D, Sumpter DJT, Meade J, Guilford T (2006) From compromise to leadership in pigeon homing. Curr Biol 16:2123-2128 Black JM (1988) Preflight signaling in swans – a mechanism for group cohesion and flock formation. Ethology 79:143-157 Boinski S, Campbell AF (1995) Use of trill vocalizations to coordinate troop movement among white-faced capuchins – a second field-test. Behaviour 132:875-901 Bonabeau E, Theraulaz G, Deneubourg JL, Aron S, Camazine S (1997) Selforganization in social insects. Trends Ecol Evol 12:188-193 Byrne RW (2000) How monkeys find their way: leadership, coordination, and cognitive maps of African baboons. In: Boinski S, Garber PA (eds) On the Move: How and Why Animals Travel in Groups. University of Chicago Press, Chicago Camazine S, Deneubourg JL, Franks NR, Sneyd J, Theraulaz G, Bonabeau E (2001) Self-Organization in Biological Systems. Princeton University Press, Princeton Clutton-Brock TH, Brotherton PNM, Smith R, McIlrath GM, Kansky R, Gaynor D, O’Riain MJ, Skinner JD (1998) Infanticide and expulsion of females in a cooperative mammal. Proc R Soc Lond B 265:2291-2295 Conradt L (1998) Could asynchrony in activity between the sexes cause intersexual social segregation in ruminants? Proc R Soc Lond B 265:1359-1363 Conradt L, List C (2009) Group decisions in humans and animals: a survey. Philos Trans R Soc Lond B 364:719-742 Conradt L, Roper TJ (2003) Group decision-making in animals. Nature 421:155158 Conradt L, Roper TJ (2005) Consensus decision making in animals. Trends Ecol Evol 20:449-456 Conradt L, Roper TJ (2007) Democracy in animals: the evolution of shared group decisions. Proc R Soc Lond B 274:2317-2326 Conradt L, Roper TJ (2009) Conflicts of interest and the evolution of decision sharing. Philos Trans R Soc Lond B 364:807-819 Conradt L, Krause J, Couzin ID, Roper TJ (2009) ‘Leading according to need’ in self-organizing groups. Am Nat 173:304-312 Couzin ID (2008) Collective cognition in animal groups. Trends Cog Sci 13:36-43 Couzin ID, Franks NR (2003) Self-organized lane formation and optimized traffic flow in army ants. Proc R Soc Lond B 270:139-146
262
Gerald Kerth
Couzin ID, Krause J (2003) Self-organization and collective behavior in vertebrates. Adv Stud Behav 32:1-75 Couzin ID, Krause J, Franks NR, Levin SA (2005) Effective leadership and decision-making in animal groups on the move. Nature 433:513-516 Croft DP, James R, Krause J (2008) Exploring Animal Social Networks. Princeton University Press, Princeton Dall SRX, Boyd IL (2004) Evolution of mammals: lactation helps mothers to cope with unreliable food supplies. Proc R Soc Lond B 271:2049-2057 Danchin E, Giraldeau L-A, Valone TJ, Wagner RH (2004) Public information: from nosy neighbors to cultural evolution. Science 305:487-491 Deneubourg JL, Goss S (1989) Collective patterns and decision-making. Ethol Ecol Evol 1:295-311 Erhart EM, Overdorff DJ (1999) Female coordination of group travel in wild Propithecus and Eulemur. Int J Primatol 20:927-940 Fischhoff IR, Sundaresan SR, Cordingley J, Larkin HM, Sellier M-J, Rubenstein DI (2007) Social relationships and reproductive state influence leadership roles in movements of plains zebra, Equus burchellii. Anim Behav 73:825831 Franks NR, Richardson T (2006) Teaching in tandem-running ants. Nature 439:153 Franks NR, Pratt SC, Mallon EB, Britton NF, Sumpter DJT (2002) Information flow, opinion polling and collective intelligence in house-hunting social insects. Philos Trans R Soc Lond B 357:1567-1583 Franks NR, Dornhaus A, Fitzsimmons JP, Stevens M (2003) Speed versus accuracy in collective decision making. Proc R Soc Lond B 270:2457-2463 Franks NR, Dechaume-Moncharmont F-X, Hanmore E, Reynolds JK (2009) Speed versus accuracy in decision-making ants: expediting politics and policy implementation. Philos Trans R Soc Lond B 364:845-852 Furrer RD, Kunc HP, Manser MB (submitted) Variable leadership in the lowskew, cooperatively breeding banded mongoose is influenced by reproductive state Gompper ME (1996) Sociality and asociality in white-nosed coatis (Nasua narica): foraging costs and benefits. Behav Ecol 7:254-263 Harcourt AH (1992) Coalitions and alliances: are primates more complex than non-primates? In: Harcourt AH, de Waal FBM (eds) Coalitions and Alliances in Human and Non-Human Animals. Oxford University Press, New York Harcourt JL, Ang TZ, Sweetman G, Johnstone RA, Manica A (2009) Social feedback and the emergence of leaders and followers. Curr Biol 19:248-252 Jacobs A, Maumy M, Petit O (2008) The influence of social organisation on leadership in brown lemurs (Eulemur fulvus fulvus) in a controlled environment. Behav Process 79:111-113 Kerr NL, Tindale RS (2004) Group performance and decision making. Annu Rev Psychol 55:623-655 Kerth G (2008) Causes and consequences of sociality in bats. BioScience 58:737746
Group decision-making in animal societies
263
Kerth G, König B (1999) Fission, fusion and nonrandom associations in female Bechstein’s bats (Myotis bechsteinii). Behaviour 136:1187-1202 Kerth G, Morf L (2004) Behavioural and genetic data suggest that Bechstein’s bats predominantely mate outside the breeding habitat. Ethology 110:987-999 Kerth G, Reckardt K (2003) Information transfer about roosts in female Bechstein’s bats: an experimental field study. Proc R Soc Lond B 270:511515 Kerth G, Weissmann K, König B (2001) Day roost selection in female Bechstein’s bats (Myotis bechsteinii): a field experiment to determine the influence of roost temperature. Oecologia 126:1-9 Kerth G, Safi K, König B (2002) Mean colony relatedness is a poor predictor of colony structure and female philopatry in the communally breeding Bechstein’s bat (Myotis bechsteinii). Behav Ecol Sociobiol 52:203-210 Kerth G, Ebert C, Schmidtke C (2006) Group decision making in fission-fusion societies: evidence from two-field experiments in Bechstein’s bats. Proc R Soc Lond B 273:2785-2790 King AJ, Douglas CMS, Huchard E, Isaac NJB, Cowlishaw G (2008) Dominance and affiliation mediate despotism in a social primate. Curr Biol 18:1833-1838 Krause J, Ruxton GD (2002) Living in Groups. Oxford University Press, New York Krause J, Bumann D, Todt T (1992) Relationship between the position preference and nutritional state of individuals in schools of juvenile roach (Rutilus rutilus). Behav Ecol Sociobiol 30:177-180 Kruuk LEB, Hill WG (2008) Introduction. Evolutionary dynamics of wild populations: the use of long-term pedigree data. Proc R Soc Lond B 275:593-596 Kummer H (1968) Social Organisations of Hamadryas Baboons. A Field Study. Chicago University Press, Chicago Lachlan RF, Crooks L, Laland KN (1998) Who follows whom? Shoaling preferences and social learning of foraging information in guppies. Anim Behav 56:181-190 Laland KN (2004) Social learning strategies. Learn Behav 32:4-14 Laland KN, Williams K (1998) Social transmission of maladaptive information in the guppy. Behav Ecol 9:493- 499 Leca J-B, Gunst N, Thierry B; Petit O (2003) Distributed leadership in semifreeranging white-faced capuchin monkeys. Anim Behav 66:1045-1052 List C (2004) Democracy in animal groups: a political science perspective. Trends Ecol Evol 19:168-169 List C, Elsholtz C, Seeley TD (2009) Independence and interdependence in collective decision making: an agent-based model of nest-site choice by honeybee swarms. Philos Trans R Soc Lond B 364:755-762 Lusseau D, Conradt L (2009) The emergence of unshared consensus decisions in bottlenose dolphins. Behav Ecol Sociobiol 63:1067-1077 Mallon EB, Pratt SC, Franks NR (2001) Individual and collective decision-making during nest site selection by the ant Leptothorax albipennis. Behav Ecol Sociobiol 50:352-359
264
Gerald Kerth
McComb K, Moss C, Durant SM, Baker L, Sayialel S (2001). Matriarchs as repositories of social knowledge in African elephants. Science 292:491-494 Pratt SC, Mallon EB, Sumpter DJT, Franks NR (2002) Quorum sensing, recruitment, and collective decision-making during colony emigration by the ant Leptothorax albipennis. Behav Ecol Sociobiol 52:117-127 Pretzlaff I, Kerth G, Dausmann KH (2010) Communally breeding bats use physiological and behavioral adjustments to optimize daily energy expenditure. Naturwissenschaften, in press Prins HHT (1996) Ecology and Behaviour of the African Buffalo: Social Inequality and Decision Making. Chapman and Hall, London Rands SA, Cowlishaw G, Pettifor RA, Rowcliffe JM, Johnstone RA (2003) Spontaneous emergence of leaders and followers in foraging pairs. Nature 423:432434 Reckardt K, Kerth G (2007) Roost selection and roost switching of female Bechstein’s bats (Myotis bechsteinii) as a strategy of parasite avoidance. Oecologia 154:581-588 Reebs SG (2000) Can a minority of informed leaders determine the foraging movements of a fish shoal? Anim Behav 59:403-409 Reinhardt V (1983) Movement orders and leadership in a semi-wild cattle herd. Behaviour 83:251-264 Ruckstuhl KE, Neuhaus P (2002) Sexual segregation in ungulates: a comparative test of three hypotheses. Biol Rev 77:77-96 Safi K, Kerth G (2003) Secretions of the interaural gland contain information about individuality and colony membership in the Bechstein’s bat. Anim Behav 65:363-369 Safi K, König B, Kerth G (2007) Sex differences in population genetics, home range size and habitat use of the parti-colored bat (Vespertilio murinus, Linnaeus 1758) in Switzerland and their consequences for conservation. Biol Conserv 137:28-36 Schaller GB (1963) The Mountain Gorilla: Ecology and Behavior. Chicago: University of Chicago Press Seeley TD, Buhrman SC (1999) Group decision making in swarms of honey bees. Behav Ecol Sociobiol 45:19-31 Seeley TD, Buhrman SC (2001) Nest-site selection in honey bees: how well do swarms implement the ‘best-of-N’ decision rule? Behav Ecol Sociobiol 49:416-427 Seeley TD, Camazine S, Sneyd J (1991) Collective decision-making in honey bees: how colonies choose among nectar sources. Behav Ecol Sociobiol 28:277-290 Seeley TD, Visscher PK, Passino KM (2006) Group decision making in honey bee swarms. Am Sci 94:220-229 Sherman PW (1977) Nepotism and the evolution of alarm calls. Science 197:1246-1253 Simons AM (2004) Many wrongs: the advantage of group navigation. Trends Ecol Evol 19:453-455
Group decision-making in animal societies
265
Stewart KJ, Harcourt AH (1994) Gorillas’ vocalizations during rest periods: signals of impending departure? Behaviour 130:29-40 Stueckle S, Zinner D (2008) To follow or not to follow: decision making and leadership during the morning departure in chacma baboons. Anim Behav 75:1995-2004 Sueur C, Petit O (2008) Organization of group members at departure is driven by social structure in Macaca. Int J Primatol 29:1085-1098 Summers K (2005) The evolutionary ecology of despotism. Evol Hum Behav 26:106-135 Sumpter DJT, Pratt SC (2009) Quorum responses and consensus decision making. Philos Trans R Soc Lond B 364:743-753 Sumpter DJT, Krause J, Richard James R, Couzin ID, Ward AJW (2008) Consensus decision making by fish. Curr Biol 18:1773-1777 Sundaresan SR, Fischhoff IR, Dushoff J, Rubenstein DI (2007) Network metrics reveal differences in social organization between two fission-fusion species, Grevy’s zebra and onager. Oecologia 151:140-149 Trillmich J, Fichtel C, Kappeler PM (2004) Coordination of group movements in wild Verreaux’s sifakas (Propithecus verreauxi). Behaviour 141:1103-1120 Wallraff HG (1978) Social interrelations involved in migratory orientation of birds – possible contribution of field studies. Oikos 30:401-404 Ward AJW, Sumpter DJT, Couzin ID, Hart PJB, Krause J (2008) Quorum decision making facilitates information transfer in fish shoals. Proc Natl Acad Sci USA 105:6948-6953 Whitehead H (2008) Analysing Animal Societies: Quantitative Methods for Vertebrate Social Analysis. University of Chicago Press, Chicago Wolf M, van Doorn GS, Leimar O, Weissing FJ (2007) Life-history trade-offs favour the evolution of animal personalities. Nature 447:581-584
Chapter 10
Parental care: adjustments to conflict and cooperation FRITZ TRILLMICH
ABSTRACT In many species parental care is needed to rear offspring that survive to reproduce, a good measure of benefits in fitness terms. Such care may involve major costs to the individual. Balancing benefits and costs of care almost inevitably leads to tensions among individuals that provide and use the resource ‘parental care’. Thus parental care and with it parental investment (i.e. the ultimate costs of care) is enacted in a game of conflict and cooperation. Using mostly examples from mammals, I discuss Tinbergen’s four questions as they apply to parental care. Phylogenetic analyses of parental care are complicated by substantial intraspecific variability of this trait. Understanding the physiological and ontogenetic processes underlying parental care behaviour helps to understand how differences in the cost of care depend on the state of parents and their environment. A deeper insight into the strategies of conflict and cooperation in care can be derived from consideration of the behavioural mechanisms available to participants.
10.1 Introduction In this chapter, I will concentrate on mammalian examples of parental care without restricting the content to just mammals when other groups of organisms provide better examples. As we need a combined treatment of Tinbergen’s four questions (Tinbergen 1963) to understand any aspect of animal and human behaviour comprehensively, I highlight the close connection between phylogenetic, functional, mechanistic and ontogenetic aspects of parental care. Given that parental care requires a major effort from parents in time, energy, and risk taking, selection will act on individuals participating in the rearing of offspring in such a way as to minimize the
268
Fritz Trillmich
costs incurred. Thereby, conflict between parents about the extent of care performed by self versus a partner becomes likely. Nevertheless, cooperation in brood rearing can be observed quite frequently, as often two cooperating parents are more than twice as effective in rearing offspring than one might be (Maynard Smith 1977, Houston et al. 2005) and even unrelated individuals may help caring for infants (Hrdy 2009). Similarly, selection on parents differs from that on offspring concerning the amount of brood care expended on self versus siblings (whether in the same or a subsequent litter) and this is expected to lead to parent offspring conflict (Fig. 10.1; Trivers 1974, Mock and Parker 1997). In mammals, where females gestate and provide nourishment to offspring through lactation, there are many opportunities for males to forgo parental care. Therefore, active paternal care is the exception and needs a special explanation. It is found, for example, in marmoset males, who carry young (Tardif 1994), or in carnivores, who feed young by regurgitation (Asa and Valdespino 1998), in polygynous striped mice (Rhabdomys pumilio: Schubert et al. 2009a), and monogamous prairie voles (Microtus ochrogaster: Wang and Insel 1996). Even more surprising, unrelated individuals sometimes care for young as in cooperatively breeding banded mongoose (Mungos mungo: Bell 2008). Despite these examples, paternal care is rare and male-only care is almost impossible (except in humans through specialised technology like bottle feeding) and the probability of the evolution of male care is low due to physiological constraints, even though the question remains unresolved why males did not evolve lactation (with perhaps one exception in the Dayak fruit bat, Dyacopterus spadiceus: Francis et al. 1994). Therefore, in mammals, in contrast to birds, females alone care for the offspring in 90% of the species and only in 10% do males contribute substantially to rearing of offspring (CluttonBrock 1991).
10.2 Evolutionary preconditions How did this asymmetry in parental care duties arise? In the animal kingdom and beyond, females are defined as the sex with larger gametes, and in brood care, if it exists in a species, females usually expend more effort than males. These typical sex roles have often been explained as a consequence of anisogamy (Trivers 1972). The fact that females are characterised by higher initial investment in gametes supposedly causes them to continue to invest more since every single gamete of a female is more valuable than that of a male. This kind of argument is prone to the ‘Con-
Parental care: adjustments to conflict and cooperation
269
corde fallacy‘ (Dawkins and Carlisle 1976), i.e., it assumes that large past investment makes it advantageous to continue to invest. This logic represents a fallacy because it is the probability of future pay-offs that justifies investment, not the cost of past investment. The likelihood of getting offspring to the point of independence and eventual recruitment (their expected reproductive value (RV), defined as the sum of the number of offspring produced by an individual over its lifetime devalued by population growth rate; Fisher 1930) makes them valuable to a parent and justifies taking risk or otherwise expending effort on them. Another argument is that the initial greater investment by females induces male competition for females due to a skew in the operational sex ratio (OSR), i.e., the proportion of males in the pool of individuals ready for mating (Kvarnemo and Ahnesjö 1996). This fundamental sex difference, the argument goes, leads to male investment in competitive ability rather than in brood care and therefore leaves females ‘holding the baby’, i.e., expending a higher effort on brood care. This argument is often uncritically accepted. However, it overlooks the fact that a high OSR automatically leads to frequency dependent selection since every offspring of necessity has only one father and one mother (Queller 1997, Kokko and Jennions 2008). Such frequency dependent selection should favour increased parental care by whichever sex faces more serious competition for mates. This argument is based on the same logic as in the better-known case of sex ratio evolution, where the more frequent sex faces reduced chances of reproduction and should therefore be produced less, leading to a balanced sex ratio (Fisher 1930). Analogously, a male who cannot expect to compete successfully for access to females would do better by investing his resources into increased parental care rather than in fruitless attempts to compete for females. We have to assume quite strong sexual selection due to high variance in male mating success to override such a Fishercondition (Kokko and Jennions 2008). An important factor that helps to explain the conventional sex roles is female multiple mating. This female strategy reduces male paternity certainty, thereby making male investment in offspring that may not be their own less valuable. Kokko and Jennions (2008) point out that the adult sex ratio (ASR) in the population also plays a major role in determining the ESS parental care involvement of the sexes (ESS: Evolutionary Stable Strategy; a strategy which, if adopted by everyone in the population, cannot be invaded by an alternative strategy; for details see Maynard Smith 1982). As these factors (sexual selection, multiple paternity, ASR and OSR) interact with each other, the explanation of why females are more often the caring sex than males is not as easy as suggested by the simple anisogamy argument (Kokko and Jennions 2008).
270
Fritz Trillmich
BOX 10.1 Problems with defining parental care Brood care hardly needs a definition for mammals, as this taxon is characterised by its major brood care feature, the milk glands (‘mammae’). However, it is often harder to determine for other species what constitutes brood care as the decisive characteristics, a cost to the parent and benefits of parental behaviour to offspring, are not always obvious. For example, in many fish species male brood care may be incidental to the defense of a territory or some specific resource like a burrow in which females can lay their eggs. If such a shelter is essential for the attraction of mates, as for example in some blenniid fishes (Almada and Santos 1995), it is not at all clear whether the observed defense behaviour is primarily brood care or rather mating investment. Only a male with a territory will be able to attract females that may then lay eggs into his retreat. In such a case, brood care by the male will happen coincidentally to the attraction of mates. There is a benefit to the offspring through a reduced predation risk, but the ‘care’ provided may come without an additional, brood care-specific, cost to the male. The cost of defense here should rather be classified as a cost of mating effort. Similarly, female care may also be rather coincidental. In the snail cichlid (Lamprologus ocellatus), females permit the brood to use the snail shell she inhabits until she lays the next clutch. Only careful observation can determine whether shell defense is selfprotection or brood care. Snail cichlid females were found to signal to young when danger approaches and defended a larger area around the snail shell when fry began to leave the shell (Brandmann and Trillmich, unpubl. data). This demonstrates that females adjust behaviour to the presence of the brood and do not simply defend a shell for their own protection from nocturnal predators. Thus before calling a behaviour brood care, for many species it is necessary to prove the benefits of a given behaviour for the offspring and show that the actions of the parent that cause the benefit would not occur in the absence of eggs, larvae, or young.
10.3 Asking Tinbergen’s questions about parental care 10.3.1 Phylogenetic aspects Female mammals have taken on the main load of brood care through gestation and lactation. This has led to mainly maternal care in mammals with a few, taxonomically widely spaced exceptions. We find paternal care rarely in our closest relatives, the primates, but there mostly among twinning callitrichids and in humans. This rather wide separation suggests independent origins of paternal care within the primates (Snowdon 1995,
Parental care: adjustments to conflict and cooperation
271
Reynolds et al. 2002, Hrdy 2009), and separate origins are equally likely within the other orders and families. Caring fathers are found in canids, viverrids (for example meerkats, Suricata suricatta, and banded mongoose: Solomon and French 1997), hyaenids (aardwolf, Proteles cristatus: Koehler and Richardson 1990) and rodents (Clutton-Brock 1991). Within rodents, paternal care again has evolved several times independently, and even within the Muridae paternal care appears in several subfamilies: in the Murinae (striped mouse: Schradin et al. 2009), the Gerbillinae (Mongolian gerbil, Meriones unguiculatus: Elwood 1975, Weinandy and Gattermann 1999), the Arvicolinae (pine vole, Microtus pinetorum and prairie vole: Gruder-Adams and Getz 1985, Oliveras and Novak 1986), and in the Cricetidae (California mouse, Peromyscus californicus: Gubernick and Teferi 2000; Djungarian hamster, Phodopus campbelli: Wynne-Edwards and Lisk 1989). Finally, in the Caviidae, paternal care has recently been described for the yellow toothed cavy (Galea monasteriensis: Adrian et al. 2005). At the moment, this is the only mammalian species with precocial young, where paternal behaviour has been documented. Intraspecific variability in the occurrence of parental behaviour and its complex relationship to social and endocrinological state (Schradin 2008, Schradin et al. 2009) raises the question to which extent we can consider paternal behaviour to have evolved as a fixed, species typical pattern, rather than as a phenotypically plastic trait that is flexibly adjusted to the circumstances which a male finds himself in. The surprising flexibility in the expression of paternal care will be treated below, but here it highlights a more general problem of comparative analyses by demonstrating that it is hard to justify the assignment of a given species to only one parental care category. This is not only a problem in studying the phylogeny of parental care: For many behavioural traits adaptive phenotypic plasticity might have evolved rather than one fixed trait, and underlying hormonal mechanisms have proven remarkably flexible (West-Eberhard 2003). This makes it challenging to characterise species by ascribing just one trait in order to facilitate phylogenetic analyses. However, it is evident from the scattered phylogenetic distribution of male parental care in mammals that this trait and the behavioural plasticity enabling this option under specific ecological and social circumstances has evolved many times independently in different branches of the mammalian phylogeny, and thus appears to be a trait that can evolve rather easily. This malleability is not unexpected, given that all females express the trait and male mammals therefore also should carry the genetic endowment for parental care. However, its complete development has been suppressed in males of most species.
272
Fritz Trillmich
Another trait explaining the evolution of mammalian brood care concerns the developmental state of young at birth. Species can be classified as either altricial or precocial, a difference that has been described as a major grade of adaptation (Martin and MacLarnon 1985). However, these terms each comprise a wide variety of developmental stages at birth (Derrickson 1992). For example, precocial young, such as cetaceans and pinnipeds, may be sensorily, thermoregulatorily and locomotorily highly developed; yet they are completely dependent on maternal feeding. Other precocial species, such as some bovids and cervids (Knott et al. 2005) and many caviomorphs, can feed on solid food almost from birth and become independent very early (Künkele and Trillmich 1997). It has been argued that the difference between species producing precocial and altricial young might lie in differences in the resolution of parentoffspring conflict (Stockley and Parker 2002). Essentially, the argument proposed by these authors posits that with more competition for milk after birth, offspring gain advantages by growing faster so that they surpass their siblings in size and thereby gain in sibling competition. In retaliation, mothers may shorten the period of gestation to curtail the options of offspring for additional in utero growth, thereby producing altricial young which are less able to compete aggressively amongst each other. Under these circumstances, altriciality and precociality would represent the ESS solution to this parent-offspring conflict. However, variation in traits affected, in the degree of precociality, as well as its distribution across mammals (and similarly across birds: Starck and Ricklefs 1998) appears to suggest specific phylogenetic and ecological, rather than general parentoffspring conflict scenarios to underly this variation. In addition, some parameters necessary for the model to work (especially the number of offspring per teat) are out of the range of biologically likely values. With some notable exceptions (many caviomorphs), most mammals (particularly rodents) have more teats than offspring in a litter (Gilbert 1986), yet the model assumes up to 10 young per teat and needs strong sibling competition for access to the teats to produce the predicted effects. This assumption poorly fits the basic facts of mammalian biology. For example, guinea pigs and cavies produce many (1-10; mean 3.5) precocial young, despite the fact that these species have only two teats and therefore should be competing most strongly for maternal milk. Yet, they produce perhaps the most highly precocial young among mammals and competition among offspring is weak (Fey and Trillmich 2008).
Parental care: adjustments to conflict and cooperation
273
10.3.2 Functional aspects Parental care will only evolve when the benefits of such care surpass its costs. As parental care is the period of highest energy requirements for adult mammals (Drent and Daan 1980), it is tempting to measure benefits and costs in terms of energy expenditure. This aspect is certainly very important, yet it covers only part of the cost incurred by parents. Further costs include risks and the time taken to raise offspring to independence. Given limited life time, time may sometimes be even more limited than energy. Similarly, benefits can be measured as infant growth rate and size at independence (Hofer and East 2008), as well as additional aspects that influence eventual recruitment of young. However, all of these are proximate currencies and to determine parental investment (BOX 10.2) we need to measure costs and benefits in fitness currency, best perhaps as RV. As every member of a family is under different selection because of different relatedness to the other family members, this leads to conflicting benefits and costs of a given distribution of resources to family members. In this way, conflicts arise within the family (Trivers 1974, Mock and Parker 1997). There is conflict between the parents about the effort each one of them should expend, between parents and offspring about the amount of care provided overall, and among siblings about the share of care received by self versus its siblings, whether in the same or later broods (Fig. 10.1).
Mother
Sexual conflict: how much to invest in brood care
Father
Parent-offspring conflict: how much brood care to expend on each offspring
Offspring 1 Offspring 2 Offspring 3
Fig. 10.1 The structure of conflicts within families.
Sibling conflict: which proportion of care for self versus others
274
Fritz Trillmich
BOX 10.2 Definitions and measurement of parental input, parental effort and parental investment These terms are often used with different meanings. To avoid confusion, I provide some workable definitions. Take the example of a hyena mother. She may sometimes have to run 60 km to forage in order to bring milk home to her cubs. In effect, she stays away longer from her offspring, the lower the local food abundance (Hofer and East 1993, 2008). Thus, she works harder for her offspring, expends a higher maternal effort when resources are less abundant because migrating prey have moved away from her home territory. But the increased foraging expenditure of the hyena female (in terms of time and energy spent) does not translate into increased food intake for her cubs. Instead, due to the long absence of the mother, input per unit time is reduced when mothers have to work harder for food. As a consequence, offspring growth decreases. Thus parental input to the offspring is reduced, despite increased maternal effort. Whether or not this maternal effort turns out to be parental investment in the sense of Trivers (1972) is a different question that needs to be addressed by measuring future maternal reproductive success. Therefore, we need different measures to separate these three concepts. Parental input is measured as benefit to the offspring in terms of energy intake, resulting growth or safety provided through parental behaviour. Parental effort requires measurement of energetic or time expenditure of a parent for the benefit of the offspring. Parental investment is most difficult to measure because we ideally need a lifetime measure of ultimate costs to the parent, like reduced future reproductive success, while simultaneously demonstrating that this parental investment is of benefit to the fitness of offspring. Reductions of parental fitness can come about by reduced survival or fertility due to parental care. The causes behind these effects can be highly variable. Taking more risks during parental care activities might reduce survival through increased exposure to predation. Increased energy expenditure might lead to reduced immune defenses (Harshman and Zera 2007) or production of reactive oxygen compounds thereby damaging the metabolic machinery during brood care activities (Dowling and Simmons 2009). A long time spent in brood care (for example by late weaning), high expenditure of energy, specific nutrients, or body stores on a given brood may reduce fertility in the next reproductive cycle, thereby diminishing lifetime fertility.
10.3.2.1 Conflict between parents In mammals, conflict between the parents has largely been resolved in favour of males as > 90% of the species show female care only. An excellent review dealing with the many aspects of sexual conflict about brood care across a broad taxonomic spectrum has recently been provided by Wedell
Parental care: adjustments to conflict and cooperation
275
et al. (2006; see also Arnqvist and Rowe 2005). Suffice it to say that physiological constraints like internal fertilization (with the accompanying high paternity uncertainty) and a long gestation time make males more likely to search for further mates (ecological conditions permitting) and thereby potentially increase their reproductive success (Clutton-Brock and Vincent 1991). In contrast, females gain reproductive success mainly by optimizing the use of energetic resources for gestation and lactation. Even though this sounds highly plausible, it suffers from the explanatory problems pointed out above in Sect. 10.2. Parent-offspring conflict (POC) has been studied intensively in mammals. It is expected to be particularly acute in this group as lactation directly drains maternal reserves, while buffering the provisioning of young against environmental fluctuations in food supply (Dall and Boyd 2004). Thereby, female condition not only influences her ability to provide for young, but provisioning young also directly feeds back on her own physiology and potentially her survival. For a female, the decision about allocation to self-maintenance versus brood care is expected to be biased towards self-maintenance since an adult’s RV is generally higher than that of its offspring. That the behaviour of real animals closely follows this theoretical prediction was elegantly demonstrated in a study by Schubert et al. (2009b). Female house mice confronted with a decrease in the efficiency of foraging decreased overall food intake, thereby reducing energy available to themselves as well as to the offspring. Of these diminished resources they allocated proportionally more and more to self-maintenance and thereby increasingly reduced energy export to the offspring (Fig. 10.2).
Energy
Self-maintenance Milk energy output
Increasing foraging cost
Fig. 10.2 The change of allocation to self-maintenance and maternal care (here estimated as milk energy output) with increasing foraging costs. The sum of selfmaintenance and milk energy output represents net intake, which decreases with a decrease in food abundance (after Schubert et al. 2009b).
276
Fritz Trillmich
A similar effect was found by Trillmich and Kooyman (2001) for Galápagos fur seals (Arctocephalus galapagoensis), where females during a period of lower food availability even increased their own body condition, while reducing input to their offspring as evidenced by reduced growth rate of the latter. Some details about the metabolic machinery behind such changes in allocation are currently only known for insects and the model nematode, Caenorhabditis (Harshman and Zera 2007). Even when parents save expenditure on care, the rearing of offspring can still lead to considerable costs to the mother (Festa Bianchet et al. 1998). Rearing an offspring often reduces the mother’s fertility in the next reproductive cycle. This has been shown for monotocous species, for example, red deer (Clutton-Brock et al. 1983, 1989) and Galápagos fur seals and sea lions (Trillmich 1986, Trillmich and Wolf 2008). However, even in these cases it is unclear whether the reduction in fertility is a cost of rearing an offspring or represents a reproductive strategy flexibly adapted by a female in relation to resource abundance. Only experimental manipulation of parental effort can answer this question, but this is difficult to do with large free-living mammals. Interestingly, such costs of reproduction are less evident in small mammals, like ground squirrels (Neuhaus et al. 2004) and other rodents. In striking contrast to large mammals, these smaller species often prove more fertile when mating in a post-partum oestrus and thereby exposed to the double cost of simultaneous pregnancy and lactation, rather than after a period of rest in between litters (Fuchs 1982, Martinez-Gomez et al. 2004, Rehling and Trillmich 2008a). Moreover, a cost of reproduction often becomes evident only in young and old individuals, as for example in North American red squirrels, where prime-aged females showed no detectable cost of reproduction even under unfavourable ecological conditions (Descamps et al. 2009). When analysed across a population, a positive correlation is often found between reproductive expenditure and survival or fertility: The more fertile animals are found to survive better in contrast to the naïve expectation that costly reproduction should reduce future output. This comes about because animals in good condition or with better access to resources can allocate more resources to both functions, self-maintenance and reproductive effort, than those in poor condition – for example due to poor conditions during early ontogeny (Wells 2003, Naguib et al. 2006) – or with lower resources (see BOX 10.3). In striking contrast to the expectation that the cost of reproduction determines many life history trade-offs, reproductive males and females in the eusocial mole-rat, Cryptomys anselli, enjoy higher survival prospects than non-reproductives (Dammann and Burda 2006). This exceptional case parallels the unexpectedly long survival of queens of eusocial insects, which is thought to be an adaptation to low ex-
Parental care: adjustments to conflict and cooperation
277
trinsic mortality rates and the consequent high RV of queens (Keller and Genoud 1997). BOX 10.3 Individual Optimisation Hypothesis
Survival rate
When comparing parental care behaviour between individuals, we have to scale their effort against their abilities. It may seem obvious that a female providing more milk to her offspring is expending greater effort than another female with lower milk production. However, depending on female status (age, condition), higher effort of one female may ultimately be less costly to her, i.e., reduce her survival and future reproduction less, than a lower effort of another female of lower status (van Noordwijk and deJong 1986; see figure). This explains the often found positive correlation between parental effort and survival and/or fecundity of individuals. For example, individual red deer hinds of prime age were found to have the highest birth rates, greatest success in weaning offspring and lowest mortality rates, whereas younger and older individuals suffered increased mortality or reduced fertility after rearing an offspring (Clutton Brock et al. 1989). Similarly, common terns (Sterna hirundo) that prospected their future breeding colony at a young age were found to begin breeding early and had higher breeding success throughout their lives than late arrivals (Becker et al. 2008). Such observations are best explained by the hypothesis of ‘optimal investment’ (Högstedt 1980, Pettifor et al. 2001): individuals apparently can adjust parental effort in such a way that they optimise reproductive success relative to their own individual abilities and resources. These abilities may differ due to, for example, conditions experienced in early ontogeny (Naguib et al. 2006, Reid et al. 2006), current resource availability, or age.
Variance in allocation
Variance in resources
Parental effort
Variance in resource availability within a population combined with limited variance in resource allocation to reproduction versus own survival can easily suggest a positive correlation between reproductive effort and survival.
278
Fritz Trillmich
Given the potential for high costs of reproduction, parental care should be expended on own offspring. Of course, it is sometimes also used as a kind of mating effort allowing a male to approach or remain with an adult female which might mate later on with the caring male (Price 1990, Wagner et al. 1996, but see Nguyen et al. 2009). In some species care is performed by non-breeders that are tolerated by the parents (Allainé et al. 2000): Here juveniles are ‘paying for staying’ (Kokko et al. 2002) by providing a certain amount of care for younger offspring of their parents (or the breeding pair in residence). Finally, we will later see that even alloparental care (i.e. care by unrelated individuals) occurs in cooperatively breeding species. The mechanisms involved in insuring that primarily own young are provisioned often differ between altricial and precocial species. As long as altricial young are still too small to leave the nest, parents will readily accept and nurse foster young, even though they may be able to tell own from alien young (Beach and Jaynes 1956). Only when young become mobile and leave the nest, so that a nest site can no longer provide a safe cue to recognition, discrimination against foreign offspring sets in. In contrast to altricial species, where offspring discrimination happens relatively late during brood care, recognition becomes established rapidly in an imprinting-like process in some animals producing precocial offspring (Klopfer et al. 1964). Female sheep and goats need to learn the specific features of their offspring quickly, as they live in a social group, and indiscriminate nursing would likely result in the neglect of their own offspring. Therefore, females separate from the group before birth and within a few hours after parturition establish a highly specific bond with the newborn lamb that enables them to recognise their own and rebuff alien lambs (for the mechanisms involved see below). After establishing this specific bond, they immediately return to the safety of the herd (Lévy and Keller 2008). This or a similar mechanism seems to be involved in selectivity of parental care primarily in group-living precocial mammals because in other precocial species, like cavies (Cavia aperea), mothers readily accept foreign pups even if these differ in age (Rehling and Trillmich 2008b). It is unclear whether here, as in many fish, protection of own young from predation through a dilution effect (Fraser and Keenleyside 1995) was selectively more important than the limited cost of lactation (Künkele and Trillmich 1997). In contrast, altricial mouse lemurs (Microcebus murinus) nesting with one or two other females in the same tree hole recognise their own young and yet allo-nurse and adopt offspring of their partners should one of the communally nesting females die. Eberle and Kappeler (2006) were able to show that these females always were maternally related to each
Parental care: adjustments to conflict and cooperation
279
other, thereby explaining this unusual degree of cooperation by kin selection. 10.3.2.2 Competition and cooperation in parent-offspring conflict (POC) Once recognition is established, be it through a fixed site or individual recognition, parent and offspring communicate apparently in order to enable efficient allocation of brood care. Various calls and behaviours indicate hunger, the need for warmth or the offspring’s separation from parents. They evolved under strong selection to guarantee normal development of offspring (also by maintaining parental brood care motivation; see below 10.3.3). However, these same displays are used to compete for privileged access to parental (e.g. food) and nest resources (e.g. warmth). In this context, differing selection on parent(s) and offspring (Trivers 1974) raises the question of POC and of the honesty of such communication. The cases of deadly POC clearly make the point that POC can have serious fitness consequences. In brown bears (Ursus arctos), females are far more likely to abandon singleton offspring than twins. In this case the mother can gain fitness for herself by beginning another reproductive cycle earlier at a high cost to her offspring that is likely to grow slower or even die of starvation (Tait 1980, Dahle and Swenson 2003). Similarly, domestic pigs are known to abort small numbers of fetuses and cycle again, rather than rearing a suboptimally small litter (Taborsky 1985). In these cases offspring clearly lose fitness and mothers decide the POC in their own favour. These cases demonstrate that for some species the cost of time spent rearing offspring may be more important than the energetic costs involved. Cases of brood and litter size reduction are much more difficult to interpret as the fitness consequences of brood reduction may be beneficial to both, parents and offspring (except the poor victim; Mock and Parker 1997). Offspring begging may also involve shuffling for the best place to obtain food – be this the most productive teat (Drake et al. 2008) or the best position in the nest (Bautista et al. 2008). This is achieved by more or less aggressive interactions (Fraser and Thompson 1991, Hofer and East 2008, Trillmich and Wolf 2008) among young as well as by signalling, which make the offspring particularly obvious to the parent. In birds, parents may feed young according to their signalling intensity (Kilner 1997) and may also show favouritism for weaker offspring (Stamps et al. 1985). Differential feeding of young is less easy to achieve for a lactating female mammal as there are few options for differential provisioning during suckling. When feeding on solid food by regurgitation (in canids) or by passing food items on to begging young (meerkats), such favouritism can be achieved,
280
Fritz Trillmich
however, as easily as in bird parents feeding offspring in a nest. In cooperatively breeding species, like banded mongoose, pups may actually specialise on a particular individual (their ‘escort’) that is most likely to feed them, and escorts in good body condition are more likely to feed begging pups than less well-fed ones (Bell 2008). During begging episodes, signals, including vocal and olfactory signals as well as mechanical stimulation of the teats, may be of different quality. For example in pigs, stimulation by massage of the teats by many young is needed to achieve the let-down providing every offspring simultaneously with milk. Here, a clear cooperative aspect of begging becomes obvious (Drake et al. 2008). Offspring signals serve to communicate the presence of needy young, and only several young together may provide sufficient stimulation to maintain the brood care motivation of the sow in the long term, and to induce milk ejection in the shorter term. Indeed, very small litters may be given up by mothers due to suboptimal stimulation. It has previously been suggested that siblings may compete directly through begging by honestly advertising their need for a fixed level of provisioning (Godfray 1995), or that siblings may cooperate in their begging in order to jointly elevate the level of provisioning by adults (Johnstone 2004). The honesty of such begging signals has been discussed intensively. If increases in the intensity or frequency of begging signals augment parental provisioning one may assume that deception is likely to invade existing behavioural strategies, as observed in the communication between the cuckoo chick and its host (Kilner et al. 1999). Alternatively, offspring may compete for the best position and such scramble competition will lead to phenomena which are hard to separate form those predicted for honest signalling (Royle et al. 2004). While many studies have found results that appear to be consistent with honest signalling, others have found phenomena which appear to support the existence of scramble competition or a cooperative system. Furthermore, offspring may not only signal need but also quality (Mas et al. 2009). If so, parents should base their provisioning strategy as much on offspring quality (that is their RV) as on their need. The analysis is complicated even further, because offspring are quick to learn which solicitation behaviours are rewarded and thereby change begging behaviour in such a way that rewards are maximised (Kedar et al. 2000, Langmore et al. 2008). For example, in great tits needier chicks learn to approach the position from which the female feeds because she more likely feeds hungrier chicks (Kölliker and Richner 2004). Similarly, pups of cooperatively breeding meerkats and banded mongoose signal their need in a way that is strategically adjusted to the individual they are begging from (Bell 2008, Madden et al. 2009) and not directly related to
Parental care: adjustments to conflict and cooperation
281
their hunger level. The situation is complicated even further by the finding that, depending on the situation, these pups use more than one type of begging call (Kunc et al. 2007). In addition, siblings may negotiate about the next item brought by the parent while the parents are absent, as observed in barn owls (Roulin et al. 2009). These empirical findings complicate understanding parent-offspring interactions. The present models of begging capture only part of the communication process which simultaneously appears influenced by (1) competition and cooperation among offspring, (2) the variability in offspring quality, (3) their learning about the response of caregivers to the signals, (4) the ecological situation in which these signals are given, and (5) the need for a sufficient signalling level to maintain parental care motivation to weaning or fledging. The complexity of the situation seems best suited for analyses by negotiation models tailored to the species and the ecological situation (McNamara et al. 1999), rather than by general models that elucidate principles but do not fit any specific situation (Trillmich and Weissing 2006). Even in this type of modelling we should, however, not forget that a substantial part of offspring signalling may well function to maintain parental care motivation (see below), a factor that has been stressed for in utero cooperation of embryos in maintaining pregnancy (Gosling 1986) probably through sufficiently high secretion of chorionic gonadotropins (Haig 1993, Forbes 2002). Parents take a very active role in sibling competition as most clearly shown when mothers interfere in sibling conflict by defending a weaker sibling, separating fighting sibs (in hyenas: Hofer and East 2008, White 2008; in fur seals and sea lions: Trillmich and Wolf 2008), and by evolving counter-strategies that force offspring to quit fighting during feeding. In pigs, for example, the latter mechanism involves a maternal signal for a short let-down period during which fighting must cease, lest the individual will miss the chance to feed (Drake et al. 2008). Parental offering (supply) strategies have evolved which again reflect cooperation and conflict. On the one hand, mothers stimulate feeding and entice offspring to approach the milk offering teat. Such parental signals can be mechanical, olfactory, acoustic, or visual. For example, sows signal the likelihood of milk let-down through a change in grunting rate, thereby communicating to the piglets when sucking will be efficient (Weary and Fraser 1995, Drake et al. 2008). Female rabbits visit their young only once within 24 hours for a few minutes, apparently to avoid predation on the nest. To achieve rapid milk transfer, they signal the source of the milk (in a dark burrow) in a different modality, a strongly attracting pheromone secreted around the teats (Hudson and Distel 1983, Schaal et al. 2003). The amount of milk provided is then regulated through the demand of the off-
282
Fritz Trillmich
spring via a physiological feedback mechanism: The more young suck, the more milk is produced and ejected in the medium term. The discovery of such a mechanism has led to the formulation of the ‘restaurant hypothesis’ for pigs, where young massage the teat for prolonged periods after let down, i.e., when no more milk is flowing, presumably to signal their milk demand and maintain maternal milk production at a sufficient level (Jensen et al. 1998, Drake et al. 2008). In this way, demand will positively influence supply, contrary to a honest signalling scenario, which assumes that supply is independent of signalling intensity (Royle et al. 2004). In contrast, guinea pigs and cavies have evolved a maternal strategy that responds hardly at all to offspring demand (Laurien-Kehnen and Trillmich 2003, Rehling and Trillmich 2007, 2008a,b). In this species, mothers appear to set the agenda based on their own state. This is most clearly seen in a lack of response to increased pup needs. Pups given no independent option of food intake vigorously demanded more milk, but did not induce additional milk production (Laurien-Kehnen and Trillmich 2003). Weaning conflict. Much research has been done on the initiation of brood care and the internal (hormonal) and external (communication) signals that induce parents to provide care to newly hatched or newborn young. However, there is also the problem of when to end care. Trivers (1974) has pointed out that there should be conflict about the end of parental care, but we have little insight into the processes that underlie the end of parental care. Internal processes in parents may end parental care irrespective of further signalling by offspring, thus ensuring that offspring cannot manipulate parents into providing substantially more care than is optimal for their own fitness. In guinea pigs, mothers were found to wean offspring largely according to their own preset schedule (Rehling and Trillmich 2007, 2008a) and they did not react by extending the time to weaning when their own offspring were exchanged against younger pups (Rehling and Trillmich 2008b). However, older offspring transferred to mothers of younger pups used the opportunity provided and sucked for much longer than normal (Rehling and Trillmich 2008b), suggesting the existence of a mother-offspring conflict about the timing of weaning. However, as Mock and Parker (1997) have pointed out, not every behavioural squabble observed is indicative of a real evolutionary conflict between parent and offspring. Even though there is an evolutionary conflict between parent(s) and offspring, one of the major problems in proving such conflict is the lack of sufficiently accurate measurements of parental and offspring fitness to decide whether such a conflict actually exists in a given interaction, and if so, who wins. Determining the fitness consequences for all parties involved in the conflict requires measures of the fit-
Parental care: adjustments to conflict and cooperation
283
ness consequences of decisions by parents and offspring on the RV of all participants in the conflict, a tall order indeed. In addition, for example, in the case of hyena siblicide (Hofer and East 2008), at least for the victim no such decision exists, as it does not have a say in the matter. Even if the winning sibling outcompetes the sibling before its mother would have given up (Trillmich and Wolf 2008, White 2008), this does not mean that the demise of the victim does not turn out to be the best solution for the mother as well if she cannot provide enough milk for both of her offspring. So, while conflict on the behavioural level signals problems, it need not signal evolutionary conflict that may not exist in each and every case (Mock and Forbes 1992). Lack of conflict about the timing of weaning has also been documented in a few cases when offspring end parental care. For example, in northern fur seals (Callorhinus ursinus) females alternate between foraging at sea and visits to shore where they nurse the pup. In this species, pups leave the colony before mothers stop to return (Macy 1982). Apparently, it becomes important for offspring to get started in time with the southward migration. Moreover, energy provisioned by the mother to the pup towards the end of maternal care may not be sufficient to insure continued growth of the offspring which then perhaps has a better option in foraging for itself (Trillmich 1996). The mother will return one or two times after her pup has left, but then also begins its migration. Clearly, the offspring weans itself and no parent-offspring conflict exists at this point in time. The complex measurements needed make it difficult to judge whether offspring or parents win POC about provisioning. Presently, in most cases we do not have enough information on the fitness outcomes to judge whether an ESS is reached in this (signalling) game, and, if so, whether it serves best the fitness of the offspring, the parents, or both parties (see also Kilner and Hinde 2008). 10.3.3 Mechanisms and ontogenetic influences underlying parental care To understand constraints on, and potentials of, parental behaviour it is important to know the mechanisms underlying parental care. Clearly, unlimited phenotypic plasticity cannot be assumed (DeWitt et al. 1998) and knowledge of mechanisms can help to understand limitations to parental flexibility. Here, I first describe a few aspects of mechanisms working in male parental care and then go on to the much better known female side of mechanisms. Due to the enormous extent of that literature, I can only present a few aspects that suggest how the same function may depend on
284
Fritz Trillmich
different mechanisms and how understanding mechanisms feeds back on functional interpretations. 10.3.3.1 Male brood care Male mammals often, but not exclusively, get involved in paternal care when they invest in monogamous or stable polygynous relationships because they lack better alternative ways to increase reproductive success (see Wittenberger and Tilson 1980). Thus, the function of paternal care is evident where it occurs, but it is less clear how a male mammal is changed from a mate searching, deserting beast into a caring father. Thus, the proximate question arises how such a switch in behaviour is physiologically enabled. While in birds male care usually involves a reduction in testosterone levels and an increase in progesterone and prolactin (see Buntin 1996) this may not be the same in rodents, where females enter postpartum oestrus so that males should maintain regular testosterone levels to be able to copulate during the period of brood care. Indeed, in striking contrast to birds, in the California mouse (Peromyscus californicus) testosterone was found, perhaps in a threshold manner, to even increase paternal behaviour (Trainor and Marler 2001). While prolactin is of obvious importance in brood care behaviour of females, recent studies of paternal behaviour in mammals revealed quite variable involvement of prolactin in the proximate control of paternal care. Whereas fathers were found to have higher prolactin levels than nonfathers in a captive study of Djungarian hamsters (Wynne-Edwards 2001), field studies of striped mice and meerkats revealed a more variable relationship. In striped mice, where males may follow different reproductive strategies as philopatric (young) males, territorial (dominant) breeding males or roaming males, caring territorial males had higher prolactin levels than the equally caring allopaternal (i.e. the young males that were not the fathers of these pups) philopatric males. This finding suggests that male brood care behaviour is not directly proportional to prolactin levels and that parental care may be regulated differently in breeding males and alloparenting males (Schradin 2008). In meerkats, male helpers were found to display higher prolactin levels on days when they baby-sitted at the den than when they went out foraging, and prolactin levels declined over the course of the day as these baby sitters were fasting while guarding (Carlson et al. 2006a). However, during normal foraging, when male meerkats feed pups that beg for food, cortisol levels were more closely correlated with feeding rates than prolactin levels (Carlson et al. 2006b). These data demonstrate that similar brood care behaviours may be regulated differently in male and female mammals as well as between males following
Parental care: adjustments to conflict and cooperation
285
different strategies. Therefore, it is not warranted to conclude from similar behaviours to similar underlying regulatory networks, be they endocrinological or neuronal. 10.3.3.2 Maternal care The onset of maternal care is a complex process, in which indifference or aggressive defensiveness against the unknown stimuli presented by newborns needs to be replaced by attachment to offspring and maternal care for a brood. This crucial transition in behaviour has been analysed only in a few selected species: in altricial species I here concentrate on the paradigmatic rats and mice, and in precocial species on sheep and goats. These studies have demonstrated that different mechanisms can lead to similar functional outcomes, but also that mechanisms are finely tuned to social and ecological needs. Initially, most female mammals of altricial species avoid very young, still dependent conspecifics, and if they get too close they may attack or even wound or kill them. In males the equivalent response towards young (as found in lions or male house mice before mating) can be explained by sexual selection, but in virgin female rats it is a fear response that leads to avoidance or killing of young. The avoidance can be overcome by habituation to the stimulus by repeatedly exposing females to newborns. This process is called sensitisation and consists initially of a desensitisation to certain fear-evoking pup stimuli, many of them olfactory. Thereby, a female rat gets used to the proximity of pups and is increasingly exposed to pup stimuli, which then lead to the establishment of maternal behaviour. Virgin rats repeatedly exposed to newborns over a period of about a week indeed change their response towards infants from infanticide or avoidance to maternal care behaviour. They begin nest building and gather the pups in the nest where the female hovers or huddles over them in a position similar to nursing. This change in motivation is induced by the repeated exposure to the stimulus of newborns and sets into motion changes in neuronal circuits that permit maternal care behaviour (Numan and Insel 2003). Interestingly, young females near weaning (around day 24) do not yet show such a fear response that leads to avoidance of newborn pups, but will readily accept them and show maternal behaviour after much shorter sensitisation than adult nulliparous females. In some primates such as hanuman langurs (Semnopithecus entellus) virgin females will actually fight for access to newborns and are much more attentive to them than older females (Hrdy 1977). On the ultimate level, the difficulty non-reproducing females experience in accepting young are adaptive in that they protect such females from
286
Fritz Trillmich
wasting care on non-related young, but, at the proximate level, it also serves to highlight the fine-tuning needed to overcome the avoidance of and aggression against young that all of a sudden appear at parturition. This would apply in particular for cooperatively breeding species, where helpers must habituate and later care for suddenly appearing young. It also could explain why females in some of these species commit infanticide if another female gives birth before them. Under normal circumstances and in single breeders, the endocrine changes during pregnancy, in particular the rapid change in the ratio of progesterone to estrogen before birth, and the increase of prolactin during pregnancy lead to the immediate acceptance of offspring by repressing all fear responses to the novel stimuli presented by the newborns (Numan and Insel 2003). However, hormonal stimuli in the peripheral system are less required for the maintenance of maternal behaviour in rats. The exposure of the female to the sight of pups, and in particular the mechanical stimulation of the ventrum and the teats by the rooting young, serves to maintain maternal care (even though central oxytocin may play a role; Neumann 2008). This is the basis for the phenomenon that rat mothers will maintain lactation for much longer than a normal rearing period if her own pups are experimentally exchanged against younger pups (Wiesner and Sheard 1933, Pfister et al. 1986). Thus, maternal care here is maintained by the stimuli emitted by young pups and switched off as these stimuli are replaced by increasingly adult-liked stimuli (for example, the growing fur) during the normal course of offspring development. This mechanism ensures appropriate weaning under natural circumstances. Pfister et al. (1986) maintained maternal care beyond normal weaning by exchanging only some young in a litter against very young foreign pups. In such a situation older young, which were left in the nest, continued suckling for much longer than normal (about 20 – 24 days), up to more than 60 days. This shows that there is a conflict between mother and offspring about the timing of weaning which under natural circumstances mothers appear to win. Such a process does not operate in the precocial guinea pig, where exchange of young against younger offspring does not lead to a lengthening of the lactation period. In this species, the mother decides on weaning based on her own internal timer (Rehling and Trillmich 2007). Here again, young offered a chance to suckle for longer will use this option (Rehling and Trillmich 2008b). Originally, Gubernick and Alberts (1989) described that maintenance of paternal care motivation in the California mouse depended on the presence (at least olfactorily) of the mother, not on that of the pups. Thus, the male behaves as if it would make its decision to care depending on the presence of the female he mated with and less on the presence of known offspring. More recent studies showed, however, that even ‘virgin’ males showed in-
Parental care: adjustments to conflict and cooperation
287
terest in pup stimuli (de Jong et al. 2009), and some of them even behaved paternally whereas other males were initially infanticidal and would only behave paternally after birth of their own young (Gubernick et al. 1994). Here, as in rats, the onset and maintenance of maternal care does not go along with individual recognition of young, demonstrating that these processes are regulated independently. Only late in the rearing period when young become increasingly mobile does individual recognition between mother and offspring get established. Studies of sheep and goats revealed that the birth process itself plays a major role in the acceptance of young. In sheep, in contrast to rats, steroids are not sufficient to prime maternal responses. The vagino-cervical stimulation (VCS) happening during the birth process leads to a massive release of oxytocin, not only via the pituitary into the peripheral system, but also in certain brain regions, most importantly the PVN (paraventricular nucleus). Experiments showed that both, VCS and oxytocin release within the brain, are necessary to establish maternal responsiveness. This effect is furthered by the attraction to the smell of amniotic fluid briefly after birth, whereas amniotic fluid otherwise is strongly aversive. Attraction to amniotic fluid also seems to be induced by oxytocin that is released into the main olfactory bulb, where it modulates its activity and selectivity. Selectivity of the maternal response to the lamb thereby becomes established within a few hours after birth through an imprinting-like process that leads to some rearrangement of connectivity within the main olfactory bulb (Lévy and Keller 2008). Interestingly, maternal responsiveness to the young was shown to be independent of selectivity of the response to the own lamb (Lévy et al. 2004). Females respond strongly and indiscriminately to any lamb immediately after parturition. At this stage, maternal responsiveness is fully functioning, yet selectivity has still not become established. If the mother is separated from the lamb when it is one week old, maternal responsiveness fades within 36 – 72 hours. However, at this age the selective recognition of the lamb does not fade as fast as maternal responsiveness, demonstrating that the olfactory signature of the lamb has been consolidated elsewhere (mostly in cortical areas concerned with olfactory memory). Thus, VCS synchronises the onset of learning of specific olfactory cues with the onset of maternal responsiveness, thereby generating a smooth transition form a female that rejects lambs to one that accepts them, albeit only her own. The correct specificity of mother-offspring bonding is insured by the separation of the parturient ewe from the herd before birth of her pup. Acoustic and visual recognition cues are learned much slower by the mother than the olfactory signature of her lamb(s). Recognition by hearing
288
Fritz Trillmich
works within about 24 hours, but visual recognition appears to become established only after 3 weeks. These recognition memories reside in other brain regions than the one for the olfactory signature of the lamb. This is most strikingly demonstrated when observing that an anosmic female individually recognises her lamb acoustically from a distance, but nurses indiscriminately as the decision to allow access to the udder depends entirely on olfactory cues. Thus, there is no cross-check between these modalities. Functionally, this makes sense, as a nursing lamb usually cannot call, but offers the mother every opportunity for frequent olfactory checks, thereby establishing the lamb’s identity and insuring against allo-suckling (Lévy and Keller 2008). In rats, and similarly in many other mammalian mothers, pregnancy and lactation affect behaviour profoundly even beyond direct maternal care behaviour. Whereas pregnant females tend to behave rather cautiously, anxiously avoiding unknown stimuli and situations, lactating mothers are not as easily stressed as non-reproducing females and tend to be more riskprone (Slattery and Neumann 2008). Maternal aggression also becomes established around birth and appears to be maintained (in the rat) by pup stimulation to the teats and the ventrum. Importantly, these changes in behaviour seem adaptive during the brood care period as they allow the lactating female to accept more risk during foraging, if necessary to obtain sufficient energy for lactation. Furthermore, maternal aggression against conspecifics may act in protecting offspring against infanticidal males and competing females (Ebensperger 1998). Thus, pups, at least in rats, by stimulating her ventrum and her teats, prepare the mother for defense of her offspring and this example neatly exposes the sometimes unexpected links between mechanistic (proximate) and functional (ultimate) aspects of behaviour. We know less about the mechanisms determining the end of care (weaning and post-weaning care) than about those facilitating its onset, despite the fact that Trivers (1974), 35 years ago, using the example of weaning conflict, suggested that POC is to be expected given the genetic interests of the participants in the conflict. In a way then, this lack of understanding the processes and mechanisms producing the separation of mother and offspring may be considered a case of ‘arrested development’ (Mock and Forbes 1992) of research into this aspect of POC.
Parental care: adjustments to conflict and cooperation
289
10.4 Cooperative brood care Just because of all the emphasis on conflicts over brood care, it is worth stressing the cooperation necessary among family members: siblings benefit from joint stimulation of the brood care activity of the parents (Hussell 1988), grow better through maintenance of high temperature within a nest of altricial young (Bautista et al. 2008) and may benefit in an as yet little documented way from early experience in interactions with siblings (Hudson and Trillmich 2008), as amply demonstrated for humans (Sulloway 1996). However, in a few mammalian species, members of the extended family and non-related individuals actually cooperate in brood care. Even though kinship may play an important role in the evolution of such cooperative brood care (e.g., black-backed jackals Canis mesomelas: Moehlman 1979; elephants, Loxodonta africana: Lee 1987) ecological factors also prove highly influential (for primate examples see Hrdy 2009). This is particularly evident in the process of ‘group augmentation’ (Kokko et al. 2001), where the well-being of the group is vital to the individual for ecological reasons, largely independent of kinship. For example, in meerkats, banded mongoose (Bell 2008), and wild dogs (Lycaon pictus: Malcolm and Marten 1982, Creel et al. 1997), helpers, often not directly related, are needed to enable the rearing of offspring, to maintain the group in the face of serious predation pressure, and to enable the group to compete with its neighbours. For example, in wild dogs, only a group can successfully hunt larger prey, protect young from predators, and will succeed in rearing offspring to independence. Therefore, male helpers benefit by rearing offspring even if they are not the father of these young (Malcolm and Marten 1982). In perhaps the best investigated case, individual meerkat in larger groups profit from the activity of others that act as sentinels against predators, feed (related and unrelated) young, and may even forego foraging for 24 hours to protect young that are left behind at a den. Predation pressure here plays a major role in causing the advantages of larger groups. Large groups are much better able to rear young than small groups, despite the fact that competition for food within the group increases with group size (Brotherton et al. 2001). In addition, larger group size can confer advantages in competition with neighbouring groups. But, beware that all this cooperation within the group does not prevent individuals to compete fiercely for breeding opportunities: Generally, only the dominant female breeds successfully. She drives out subdominant females during the last three weeks of her pregnancy, thereby reducing their chances to conceive
290
Fritz Trillmich
and increasing the rate of abortion. If a subordinate nevertheless manages to breed, the dominant is likely to kill its offspring even though these may be her daughter’s young. But pregnant subordinates fight back and will kill the dominant’s offspring thereby becoming the main source of pup mortality for the dominant (Young and Clutton-Brock 2006). This intense and costly conflict is strong evidence for the absolute need for grouping to survive and breed as well as for the limits of kinship arguments to explain cooperation in allo-parental care. The pinnacle of such (somewhat forced) cooperation is reached in naked mole-rats (Heterocephalus glaber), which rear young in a eusocial group (for review of the bathyergid group see Faulkes and Bennett 2007). Here the dominant female breeder even changes her brain morphology upon becoming dominant (Holmes et al. 2007) and suppresses the breeding of other females in the group by bullying subordinates (Faulkes and Abbott 1997). Even brain evolution in humans has been suggested to be based on the evolution of cooperative breeding (Hrdy 2009). In our species, Hrdy postulates that the high reproductive rate (in comparison to other great apes) can only be achieved through cooperative care of the baby which releases the mother from the extensive need to carry her rather helpless offspring for years. This saves energetic expenditure and frees the mother to invest in further offspring. The sharing of costs by helpers includes the extended family, not least post-menopausal grandmothers. This need for cooperative care, according to Hrdy (2009) has selected for cooperative social interactions on the side of adults and, in the babies, for understanding the intentions of social companions and manipulating their brood care tendencies. The enormous amount of social knowledge needed to achieve this degree of social cooperation may thereby have selected for the development of our extreme brain size.
Acknowledgements I am grateful to Peter Kappeler, Doug Mock and an anonymous referee for many constructive suggestions and comments. My own research on this topic has greatly benefitted from longterm support by the DFG.
Parental care: adjustments to conflict and cooperation
291
References Adrian O, Brockmann I, Hohoff C, Sachser N (2005) Paternal behaviour in wild guinea pigs: a comparative study in three closely related species with different social and mating systems. J Zool Lond 265:97-105 Allainé D, Brondex F, Graziani L, Coulon J, Till-Bottraud I (2000) Male-biased sex ratio in litters of Alpine marmots supports the helper repayment hypothesis. Behav Ecol 11:507-514 Almada VC, Santos RS (1995) Parental care in the rocky intertidal: a case study of adaptation and exaptation in Mediterranean and Atlantic blennies. Rev Fish Biol Fish 5:23-37 Arnqvist G, Rowe L (2005) Sexual Conflict. Princeton University Press, Princeton Asa CS, Valdespino C (1998) Canid reproductive biology: an integration of proximate mechanisms and ultimate causes. Am Zool 38:251-259 Bautista A, García-Torres E, Martínez-Gómez M, Hudson R (2008) Do newborn domestic rabbits Oryctolagus cuniculus compete for thermally advantageous positions in the litter huddle? Behav Ecol Sociobiol 62:331-339 Beach FA, Jaynes J (1956) Studies of maternal retrieving in rats. I. Recognition of young. J Mammal 37:177-180 Becker PH, Dittmann T, Ludwigs J-D, Limmer B, Ludwig SC, Bauch C, Braasch A, Wendeln H (2008) Timing of initial arrival at the breeding site predicts age at first reproduction in a long-lived migratory bird. Proc Natl Acad Sci USA 105:12349-12352 Bell MBV (2008) Strategic adjustment of begging effort by banded mongoose pups. Proc R Soc Lond B 275:1313-1319 Brotherton PNM, Clutton-Brock TH, O’Riain MJ, Gaynor D, Sharpe L, Kansky R, McIlrath GM (2001) Offspring food allocation by parents and helpers in a cooperative mammal. Behav Ecol 12:590-599 Buntin JD (1996) Neural and hormonal control of parental behavior in birds. Adv Stud Behav 25:161-213 Carlson AA, Manser M, Young AJ, Russel AF, Jordan NR, McNeilly AS, Clutton-Brock TH (2006a) Cortisol levles are positively associated with pupfeeding rates in male meerkats. Proc R Soc Lond B 273:571-577 Carlson AA, Russel AF, Young AJ, Jordan NR, McNeilly AS, Parlow AF, Clutton-Brock TH (2006b) Elevated prolactin levles immediately precede decisions to babysit by meerkat helpers. Horm Behav 50:94-100 Clutton-Brock TH (1991) The Evolution of Parental Care. Princeton University Press, Princeton Clutton-Brock TH, Vincent ACJ (1991) Sexual selection and the potential reproductive rates of males and females. Nature 351:58-60 Clutton-Brock TH, Guiness FE, Albon SD (1983) The cost of reproduction to red deer hinds. J Anim Ecol 52:367-383 Clutton-Brock TH, Albon SD, Guinness FE (1989) Fitness costs of gestation and lactation in wild mammals. Nature 337:260-262
292
Fritz Trillmich
Creel S, Creel MN, Mills MGL, Monfort SL (1997) Rank and reproduction in cooperatively breeding African wild dogs: behavioral and endocrine correlates. Behav Ecol 8:298-306 Dahle B, Swenson JE (2003) Factors influencing length of maternal care in brown bears (Ursus arctos) and its effect on offspring. Behav Ecol Sociobiol 54:352358 Dall SRX, Boyd IL (2004) Evolution of mammals: lactation helps mothers to cope with unreliable food supplies. Proc R Soc Lond B 271:2049-2057 Dammann P, Burda H (2006) Sexual activity and reproduction delay ageing in a mammal. Curr Biol 16:R117-R118 Dawkins R, Carlisle TR (1976) Parental investment, mate desertion and a fallacy. Nature 262:131-133 de Jong TR, Chauke M, Harris BN, Saltzman W (2009) From here to paternity: neural correlates of the onset of paternal behavior in California mice (Peromyscus californicus). Horm Behav 56:220-231 Derrickson EM (1992) Comparative reproductive strategies of altricial and precocial eutherian mammals. Funct Ecol 6:57-65 Descamps S, Boutin S, McAdam AG, Berteaux D, Gaillard J-M (2009) Survival costs of reproduction vary with age in North American red squirrels. Proc R Soc Lond B 276:1129-1135 DeWitt TJ, Sih A, Wilson DS (1998) Costs and limits of phenotypic plasticity. Trends Ecol Evol 13:77-81 Dowling DK, Simmons LW (2009) Reactive oxygen species as universal constraints in life-history evolution. Proc R Soc Lond B 276:1737-1745 Drake A, Fraser D, Weary DM (2008) Parent-offspring resource allocation in domestic pigs. Behav Ecol Sociobiol 62:309-320 Drent RH, Daan S (1980) The prudent parent. Energetic adjustments in avian breeding. Ardea 68:225-252 Ebensperger LA (1998) Strategies and counterstrategies to infanticide in mammals. Biol Rev 73:321-346 Eberle M, Kappeler PM (2006) Family insurance: kin selection and cooperative breeding in a solitary primate (Microcebus murinus). Behav Ecol Sociobiol 60:582-588 Elwood RW (1975) Paternal and maternal behaviour in the Monoglian gerbil. Anim Behav 23:766-772 Faulkes CG, Abbott DH (1997) The physiology of a reproductive dictatorship: regulation of male and female reproduction by a single breeding female in colonies of naked mole rats. In: Solomon NG, French JA (eds) Cooperative Breeding in Mammals. Cambridge University Press, Cambridge, pp 302-334 Faulkes CG, Bennett NC (2007) African mole-rats: social and ecological diversity. In: Wolff JO, Sherman PW (eds) Rodent Societies: An Ecological and Evolutionary Perspective. Chicago University Press, Chicago, pp 427-437 Festa-Bianchet M, Gaillard J-M, Jorgenson JT (1998) Mass- and densitydependent reproductive success and reproductive costs in a capital breeder. Am Nat 152:367-379
Parental care: adjustments to conflict and cooperation
293
Fey K, Trillmich F (2008) Sibling competition in guinea pigs (Cavia aperea f. porcellus): scrambling for mother’s teats is stressful. Behav Ecol Sociobiol 62:321-329 Fisher RA (1930) The Genetical Theory of Natural Selection. Oxford University Press, Oxford Forbes S (2002) Pregnancy sickness and embryo quality. Trends Ecol Evol 17:115-120 Francis CM, Anthony ELP, Brunton JA, Kunz TH (1994) Lactation in male fruit bats. Nature 367:691-692 Fraser SA, Keenleyside MHA (1995) Why are larger convict cichlid (Cichlasoma nigrofasciatum) fry sometimes adopted into broods of smaller fry? Behav Ecol Sociobiol 37:343-347 Fraser D, Thompson BK (1991) Armed sibling rivalry among suckling piglets. Behav Ecol Sociobiol 29:9-15 Fuchs S (1982) Optimality of parental investment: the influence of nursing on reproductive success of mother and female young house mice. Behav Ecol Sociobiol 10:39-51 Gilbert AN (1986) Mammary number and litter size in Rodentia – the one-half rule. Proc Natl Acad USA Sci 83:4828-4830 Godfray HCJ (1995) Evolutionary theory of parent-offspring conflict. Nature 376:133-138 Gosling LM (1986) Selective abortion of entire litters in the coypu: adaptive control of offspring production in relation to quality and sex. Am Nat 127:772795 Gruder-Adams S, Getz LL (1985) Comparison of the mating system and paternal behavior of Microtus ochrogaster and M. pennsylvanicus. J Mammal 66:165167 Gubernick DJ, Alberts JR (1989) Postpartum maintenance of paternal behaviour in the biparental California mouse, Peromyscus californicus. Anim Behav 37:656-664 Gubernick DJ, Teferi T (2000) Adaptive significance of male parental care in a monogamous mammal. Proc R Soc Lond B 267:147-150 Gubernick DJ, Schneider KA, Jeanotte LA (1994) Individual differences in the mechanisms underlying the onset and maintenance of paternal behavior and the inhibition of infanticide in the monogamous biparental California mouse, Peromyscus californicus. Behav Ecol Sociobiol 34:225-231 Haig D (1993) Genetic conflicts in human pregnancy. Q Rev Biol 68:495-532 Harshman LG, Zera AJ (2007) The cost of reproduction: the devil in the details. Trends Ecol Evol 22:80-86 Högstedt G (1980) Evolution of clutch size in birds: adaptive variation in relation to territory quality. Science 210:1148-1150 Hofer H, East ML (1993) The commuting system of Serengeti spotted hyaenas: how a predator copes with migratory prey. III. Attendance and maternal care. Anim Behav 46:575-589 Hofer H, East ML (2008) Siblicide in Serengeti spotted hyenas: a long-term study of maternal input and cub survival. Behav Ecol Sociobiol 62:341-351
294
Fritz Trillmich
Holmes MM, Rosen GJ, Jordan CL, de Vries GJ, Goldman BD, Forger NG (2007) Social control of brain morphology in a eusocial mammal. Proc Natl Acad Sci USA 104:10548-10552 Houston AI, Székely T, McNamara JM (2005) Conflicts between parents over care. Trends Ecol Evol 20:33-38 Hrdy SB (1977) The Langurs of Abu: Female and Male Strategies of Reproduction. Harvard University Press, Cambridge/MA Hrdy SB (2009) Mothers and Others: The Evolutionary Origins of Mutual Understanding. Harvard University Press, Cambridge/MA Hudson R, Distel H (1983) Nipple location by newborn rabbits: behavioural evidence for pheromonal guidance. Behaviour 85:260-274 Hudson R, Trillmich F (2008) Sibling competition and cooperation in mammals: challenges, developments and prospects. Behav Ecol Sociobiol 62:299-307 Hussel DJT (1988) Supply and demand in tree swallow broods: a model of parentoffspring food-provisioning interactions in birds. Am Nat 131:175-202 Jensen P, Gustafsson M, Augustsson H (1998) Teat massage after milk ingestion in domestic piglets: an example of honest begging? Anim Behav 55:779-786 Johnstone RA (2004) Begging and sibling competition: how should offspring respond to their rivals? Am Nat 163:388-406 Kedar H, Rodríguez-Gironés MA, Yedvab S, Winkler DW, Lotem A (2000) Experimental evidence for offspring learning in parent-offspring communication. Proc R Soc Lond B 267:1723-1727 Keller L, Genoud M (1997) Extraordinary lifespans in ants: a test of evolutionary theories of ageing. Nature 389:958-960 Kilner RM (1997) Mouth colour is a reliable signal of need in begging canary nestlings. Proc R Soc Lond B 264:963-968 Kilner RM, Hinde CA (2008) Information warfare and parent-offspring conflict. Adv Stud Behav 38:283-336 Kilner RM, Noblet DG, Davies NB (1999) Signals of need in parent-offspring communication and their exploitation by the common cuckoo. Nature 397:667-672 Klopfer PH, Adams DK, Klopfer MS (1964) Maternal ‘imprinting’ in goats. Proc Natl Acad Sci USA 52:911-914 Knott KK, Barboza PS, Bowyer RT (2005) Growth in arctic ungulates: postnatal development and organ maturation in Rangifer tarandus and Ovibos moschatus. J Mammal 86:121-130 Koehler CE, Richardson PRK (1990) Proteles cristatus. Mammal Species 363:1-6 Kölliker M, Richner H (2004) Navigation in a cup: chick positioning in great tit, Parus major, nests. Anim Behav 68:941-948 Kokko H, Jennions MD (2008) Parental investment, sexual selection and sex ratios. J Evol Biol 21:919-948 Kokko H, Johnstone RA, Clutton-Brock TH (2001) The evolution of cooperative breeding through group augmentation. Proc R Soc Lond B 268:187-196 Kokko H, Johnstone RA, Wright J (2002) The evolution of alloparental effort in cooperatively breeding groups: when should helpers pay to stay? Behav Ecol 13:291-300
Parental care: adjustments to conflict and cooperation
295
Künkele J, Trillmich F (1997) Are precocial young cheaper? Lactation energetics in the guinea pig. Physiol Zool 70:589-596 Kunc HP, Madden JR, Manser MB (2007) Begging signals in a mobile feeding system: the evolution of different call types. Am Nat 170:617-624 Kvarnemo C, Ahnesjö I (1996) The dynamics of operational sex ratios and competition for mates. Trends Ecol Evol 11:404-408 Langmore NE, Maurer G, Adcock GJ, Kilner RM (2008) Socially acquired hostspecific mimicry and the evolution of host races in Horsfield’s bronze cuckoo Chalcites byasalis. Evolution 62:1689-1699 Laurien-Kehnen C, Trillmich F (2003) Lactation performance of guinea pigs (Cavia porcellus) does not respond to experimental manipulation of pup demands. Behav Ecol Sociobiol 53:145-152 Lee PC (1987) Allomothering among African elephants. Anim Behav 35:278-291 Lévy F, Keller M (2008) Neurobiology of maternal behavior in sheep. Adv Stud Behav 38:399-437 Lévy F, Keller M, Poindron P (2004) Olfactory regulation of maternal behavior in mammals. Horm Behav 46:284-302 Macy SK (1982) Mother-pup interaction in the Northern fur seal. PhD Thesis, University of Washington, Seattle/WA Madden JR, Kunc HP, English S, Manser MB, Clutton-Brock TH (2009) Calling in the gap: competition or cooperation in littermates’ begging behaviour. Proc R Soc Lond B 276:1255-1262 Malcom JR, Marten K (1982) Natural selection and the communal rearing of pups in African wild dogs (Lycaon pictus). Behav Ecol Sociobiol 10:1-13 Martin RD, MacLarnon AM (1985) Gestation period, neonatal size and maternal investment in placental mammals. Nature 313:220-223 Martínez-Gómez M, Juárez M, Distel H, Hudson R (2004) Overlapping litters and reproductive performance in the domestic rabbit. Physiol Behav 82:629-636 Mas F, Haynes KF, Kölliker M (2009) A chemical signal of offspring quality affects maternal care in a social insect. Proc R Soc Lond B 276:2847-2853 Maynard Smith J (1977) Parental investment: a prospective analysis. Anim Behav 25:1-9 Maynard Smith J (1982) Evolution and the Theory of Games. Cambridge University Press, Cambridge McNamara JM, Gasson CE, Houston AI (1999) Incorporating rules for responding into evolutionary games. Nature 401:368-371 Mock DW, Forbes LS (1992) Parent-offspring conflict: a case of arrested development. Trends Ecol Evol 7:409-413 Mock DW, Parker GA (1997) The Evolution of Sibling Rivalry. Oxford University Press, Oxford Moehlman PD (1979) Jackal helpers and pup survival. Nature 277:382-383 Naguib M, Nemitz A, Gil D (2006) Maternal developmental stress reduces reproductive success of female offspring in zebra finches. Proc R Soc Lond B 273:1901-1905
296
Fritz Trillmich
Neuhaus P, Brussard DR, Murie JO, Dobson FS (2004) Age of primiparity and implications of early reproduction on life history in female Columbian ground squirrels. J Anim Ecol 73:36-43 Neumann ID (2008) Brain oxytocin: a key regulator of emotional and social behaviours in both females and males. J Neuroendocrinol 20:858-865 Nguyen N, van Horn RC, Alberts SC, Altmann J (2009) ‘Friendships’ between new mothers and adult males: adaptive benefits and determinants in wild baboons (Papio cynocephalus). Behav Ecol Sociobiol 63:1331-1344 Numan M, Insel TR (2003) The Neurobiology of Parental Behavior. Springer Verlag, New York Oliveras D, Novak M (1986) A comparison of paternal behaviour in the meadow vole Microtus pennsylvanicus, the pine vole M. pinetorum and the prairie vole M. ochrogaster. Anim Behav 34:519-526 Pettifor RA, Perrins CM, McCleery RH (2001) The individual optimization of fitness: variation in reproductive output, including clutch size, mean nestling mass and offspring recruitment, in manipulated broods of the great tits Parus major. J Anim Ecol 70:62-79 Pfister JF, Cramer CP, Blass EM (1986) Suckling in rats extended by continuous living with dams and their preweanling litters. Anim Behav 34:415-420 Price EC (1990) Infant carrying as a courtship strategy of breeding male cottontop tamarins. Anim Behav 40:784-786 Queller DC (1997) Why do females care more than males? Proc R Soc Lond B 264:1555-1557 Rehling A, Trillmich F (2007) Weaning in the guinea pig (Cavia aperea f. porcellus): who decides and by what measure? Behav Ecol Sociobiol 62:149-157 Rehling A, Trillmich F (2008a) Maternal effort is state dependent: energetic limitation or regulation? Ethology 114:318-326 Rehling A, Trillmich F (2008b) Changing supply and demand by cross-fostering: effects on the behaviour of pups and mothers in guinea pigs, Cavia aperea f. porcellus and cavies, Cavia aperea. Anim Behav 75:1455-1463 Reid JM, Bignal EM, Bignal S, McCracken DI, Monaghan P (2006) Spatial variation in demography and population growth rate: the importance of natal location. J Anim Ecol 75:1201-1211 Reynolds JD, Goodwin NB, Freckleton RP (2002) Evolutionary transitions in parental care and live bearing in vertebrates. Philos Trans R Soc Lond B 357:269-281 Roulin A, Dreiss A, Fioravanti C, Bize P (2009) Vocal sib-sib interactions: how siblings adjust signalling level to each other. Anim Behav 77:717-725 Royle NJ, Hartley IR, Parker GA (2004) Parental investment and family dynamics: interactions between theory and empirical tests. Pop Ecol 46:231-241 Schaal B, Coureaud G, Langlois D, Giniés C, Sémon E, Perrier G (2003) Chemical and behavioural characterization of the rabbit mammary pheromone. Nature 424:68-72 Schradin C (2008) Differences in prolactin levels between three alternative male reproductive tactics in striped mice (Rhabdomys pumilio). Proc R Soc Lond B 275:1047-1052
Parental care: adjustments to conflict and cooperation
297
Schradin C, Scantlebury M, Pillay N, König B (2009) Testosterone levels in dominant sociable males are lower than in solitary roamers: physiological differences between three male reproductive tactics in a sociably flexible mammal. Am Nat 173:376-388 Schubert M, Pillay N, Schradin C (2009a) Parental and alloparental care in a polygynous mammal. J Mammal 90:724-731 Schubert KA, de Vries G, Vaanholt LM, Meijer HAJ, Daan S, Verhulst S (2009b) Maternal energy allocation to offspring increases with environmental quality in house mice. Am Nat 173:831-840 Slattery DA, Neumann ID (2008) No stress please! Mechanisms of stress hyporesponsiveness of the maternal brain. J Physiol 586:377-385 Snowdon CT (1995) Infant care in cooperatively breeding species. Adv Stud Behav 25:643-689 Solomon NG, French JA (1997) Cooperative Breeding in Mammals. Cambridge University Press, Cambridge Stamps J, Clark A, Arrowood P, Kus B (1985) Parent-offspring conflict in budgerigars. Behaviour 94:1-40 Starck JM, Ricklefs RE (1998) Avian Growth and Development: Evolution within the Altricial-Precocial Spectrum. Oxford University Press, New York Stockley P, Parker GA (2002) Life history consequences of mammalian sibling rivalry. Proc Natl Acad Sci USA 99:12932-12937 Sulloway FJ (1996) Born to Rebel: Birth Order, Family Dynamics, and Creative Lives. Pantheon, New York Taborsky M (1985) On optimal parental care – commentary. Z Tierpsychol 70:331-336 Tait DEN (1980) Abandonment as a reproductive tactic – the example with grizzly bears. Am Nat 115:800-808 Tardif SD (1994) Relative energetic cost of infant care in small-bodied neotropical primates and its relation to infant-care patterns. Am J Primatol 34:133-143 Tinbergen N (1963) On aims and methods of ethology. Z Tierpsychol 20:410-433 Trainor BC, Marler CA (2001) Testosterone, paternal behavior, and aggression in the monogamous California mouse (Peromyscus californicus). Horm Behav 40:32-42 Trillmich F (1986) Maternal investment and sex-allocation in the Galápagos fur seal, Arctocephalus galapagoensis. Behav Ecol Sociobiol 19:157-164 Trillmich F (1996) Parental investment in pinnipeds. Adv Stud Behav 25:533-577 Trillmich F, Kooyman GL (2001) Field metabolic rate of lactating female Galápagos fur seals (Arctocephalus galapagoensis): the influence of offspring age and environment. Comp Biochem Physiol 129A:741-749 Trillmich F, Weissing FJ (2006) Lactation patterns of pinnipeds are not explained by optimization of maternal energy delivery rates. Behav Ecol Sociobiol 60:137-149 Trillmich F, Wolf JBW (2008) Parent-offspring and sibling conflict in the Galápagos fur seals and sea lions. Behav Ecol Sociobiol 62:363-375
298
Fritz Trillmich
Trivers RL (1972) Parental investment and sexual selection. In: Campbell B (ed) Sexual Selection and the Descent of Man, 1871-1971. Aldine, Chicago, pp 136-179 Trivers RL (1974) Parent-offspring conflict. Am Zool 11:249-264 van Noordwijk AJ, deJong G (1986) Acquisition and allocation of resources: their influence on variation in life history tactics. Am Nat 128:137-142 Wagner RH, Schug MD, Morton ES (1996) Confidence of paternity, actual paternity and parental effort by purple martins. Anim Behav 52:123-132 Wang Z, Insel TR (1996) Parental behavior in voles. Adv Stud Behav 25:361-384 Weary DM, Fraser D (1995) Calling by domestic piglets: reliable signals of need? Anim Behav 50:1047-1055 Wedell N, Kvarnemo C, Lessels CM, Treganza T (2006) Sexual conflict and life histories. Anim Behav 71:999-1011 Weinandy R, Gattermann R (1999) Parental care and time sharing in the Mongolian gerbil. Z Säugetierkd 64:169-175 Wells JCK (2003) Parent-offspring conflict theory, signalling of need, and weight gain in early life. Q Rev Biol 78:169-202 West-Eberhard MJ (2003) Developmental Plasticity and Evolution. Oxford University Press, Oxford White PA (2008) Maternal response to neonatal sibling conflict in the spotted hyena, Crocuta crocuta. Behav Ecol Sociobiol 62:353-361 Wiesner BP, Sheard NM (1933) Maternal Behaviour in the Rat. Oliver and Boyd, London Wittenberger JF, Tilson RL (1980) The evolution of monogamy: hypotheses and evidence. Annu Rev Ecol Syst 11:197-232 Wynne-Edwards KE, Lisk RD (1989) Differential effects of paternal presence on pup survival in two species of dwarf hamster (Phodopus sungorus and Phodopus campbelli). Physiol Behav 45:465-469 Wynne-Edwards KE (2001) Hormonal changes in mammalian fathers. Horm Behav 40:139-145 Young AJ, Clutton-Brock TH (2006) Infanticide by subordinates influences reproductive sharing in cooperatively breeding meerkats. Biol Lett 2:385-387
Part III Sex and reproduction
Chapter 11
The quantitative study of sexual and natural selection in the wild and in the laboratory WOLF BLANCKENHORN
ABSTRACT I discuss the continuum of approaches that exist when studying sexual or natural selection in the wild and the laboratory. These range from behavioural observations in the laboratory, via experimental manipulations of particular traits or environments, to phenomenological studies in nature. I focus on the study of body size and related life history traits, particularly drawing from our own studies on dung flies as examples. For any given species or phenomenon, ideally all types of studies should be integrated to obtain a complete picture of the evolution of particular traits in terms of mechanisms and function, proximate and ultimate explanations. I particularly advocate the use of standardised selection measures, which are well established in the literature but underused, and which I discuss in the chapter as practical guidance for the general reader. Utilisation of such measures even in experimental, laboratory studies of behavioural mechanisms, which is often possible but rarely done, would greatly facilitate any future meta-analyses of particular traits, species and evolutionary phenomena.
11.1 Introduction Whether studying behaviour, ecology or evolution, Darwin’s (1859, 1871) principle of natural selection is the central paradigm guiding our research. Natural selection is indeed the sole alternative mechanism explaining organic evolution besides the null hypothesis of random genetic drift. Therefore a thorough understanding of the process of natural selection is central to any research in organismic biology, including behaviour. All research in behaviour and ecology originates from observation and description. For example, before investigating the mechanisms of mate choice in the long-tailed widowbird, Andersson (1982) had to understand
302
Wolf Blanckenhorn
and describe the animals’ mating system. A hypothesis potentially explaining the long tail of males was then formulated based on sexual selection: for some reason females prefer to mate with long-tailed males. From this hypothesis predictions could be derived to be tested in an experiment: the mating success of males with artificially enlarged (shortened) tails should increase (decrease) relative to that of un- or mock-manipulated controls, independent of male quality. With such an experiment, sexual selection could be documented for one particular trait in this particular species. In fact, this experiment yielded not only a qualitative demonstration of sexual selection by female choice, but also a quantitative estimate of its strength: by how much did male mating success increase with tail length? However, Andersson (1982) did not calculate this, although he did in a later study on a related bird (Andersson 1989). This simple but clever experiment thus showed that natural selection can be quantified in nature. Why do we want to quantify natural selection? Evolutionary theory and also intuition tells us that the evolutionary change in a given trait X, e.g. tail length in the preceding example, i.e. the evolutionary response to selection R, is proportional to the heritability of the trait h2 and the strength of phenotypic selection S: R = h2S (Falconer 1989). Thus, if we can quantify the heritability of a trait (see Mousseau and Roff 1987) and selection on it, both of which are measurable entities, we can quantitatively predict the response to selection and ultimately the evolutionary change of a trait in a quantitative genetic framework. Although the theory of quantitative genetics was well elaborated by animal and plant breeders during the 20th century, including the methods for estimating genetic variation underlying quantitative traits (Falconer 1989, Lynch and Walsh 1998), it was not until the early 1980s that a handful of seminal papers by Lande and Arnold (1983) and Arnold and Wade (1984a,b; see also Manly 1985) outlined standardised statistical methods for estimating natural selection in nature. This has made possible quantitative comparisons among species, traits and environments at a new level, providing a database for powerful meta-analyses such as those by Endler (1986) or Kingsolver et al. (2001). After all, such meta-analyses of the literature are essential for ultimately evaluating the importance of natural selection in evolution. To give a hypothetical example: if pre-copulatory sexual selection by female choice has been demonstrated in 80 out of 100 study species, while male-male competition only occurs in 50 out of 100, and post-copulatory sperm competition only in 20 out of 100 cases, it can be concluded that pre-copulatory female choice is globally a more important selection mechanism than either male-male or sperm competition. Note that any single species study is only one data point at this level. It is not sufficiently appreciated that standardised selection measures often can
The quantitative study of sexual and natural selection
303
also be calculated for behavioural studies of sexual selection conducted in the field or even at semi-natural or artificial conditions in the laboratory. Unfortunately, this is rarely done. In this chapter I discuss the continuum of approaches that exist when studying sexual or natural selection in the wild and the laboratory. These range from behavioural observations, via experimental manipulations of particular traits or environments, to phenomenological studies in nature. Focus here is on the study of body size and related life history traits, such as growth rate, development time or survival, drawing on particular examples from our own studies on dung flies. I advocate and start with explaining the use of standardised selection measures in this context, as a practical guide for the unfamiliar reader. My major message is to urge researchers studying the behavioural mechanisms underlying sexual selection to calculate standardised selection coefficients whenever possible, as this typically cannot be easily done retrospectively from the data presented in a given paper. Such practice would tremendously broaden the database available for any systematic comparative meta-analyses of particular traits, species and evolutionary phenomena.
11.2 Defining natural selection and fitness In brief, natural selection with regard to a certain trait results when individuals expressing a superior phenotype enjoy greater fitness (defined below), leading to a change in the phenotypic distribution of the trait within a generation. If the trait has a heritable (genetic) component, the selected individuals pass on more genes into the next generation relative to conspecifics expressing an inferior phenotype, leading to changes in the trait distribution over generations, i.e. evolution. Any trait can be selected, for example colouration or body size (morphological traits), the intensity or duration of a mating display (a behavioural trait), immunocompetence (a physiological trait), or even particular alleles (a genetic trait). As selection acts on phenotypes, it merely requires trait and fitness variation, irrespective of the genetic background of the trait. For evolution to result by natural selection, the trait requires a heritable basis. Evolution by random genetic drift only requires (phenotypic) trait variation and trait heritability, fitness (say, mortality) being per definition random, whereas evolution by natural selection additionally requires trait-mediated fitness differences and an identifiable selective cause.
304
Wolf Blanckenhorn
Table 11.1 Hierarchy of fitness estimators, decreasing in precision from top to bottom but at the same time increasing in practicability. Hierarchy of fitness estimators Population (and species) fitness components (expected) time to extinction r: intrinsic rate of increase Individual fitness components number of grand-offspring number of offspring = lifetime reproductive success (R0 = ert) lx (survival) longevity winter survival energy reserves before winter body mass increase food accumulated foraging time
mx (fecundity) offspring/lifetime offspring/season clutch size energy investment/ clutch time investment/clutch
mating success matings per lifetime number of mates/day mating probability mated/not mated once
Most generally, fitness can be defined as the relative contribution of a certain unit of selection (e.g. a species, an individual, a gene, etc.) to the subsequent generation. Strictly speaking, fitness is only defined for a particular class of individuals, but the definition can be easily extended to groups of individuals. There are a multitude of fitness estimators depending on the field, which can be arranged hierarchically in terms of quality, precision, and practicability (Endler 1986; Table 11.1). The (expected) time to extinction of a unit of selection (a species or individual) is arguably the best fitness estimator available, but it is impractical for most biologists except perhaps paleontologists. Ecologists use the intrinsic rate of increase r of a population, as defined by the Euler-Lotka equation, ∑ e-rx lx mx=1, but this is only practical for small, fast-growing organisms such as bacteria, protists or water fleas. Behavioural ecologists commonly consider the individual as the unit of selection, for which lifetime reproductive success is the ideal fitness measure. However, even this is unattainable for most organisms in the field except very large ones (Clutton-Brock 1988). More typically, people estimate at times rather distant sub-components (Table 11.1) of one of the three fitness components of individual reproductive success: survival (the likelihood of reaching a particular stage or age x: lx in the Euler-Lotka equation above), fecundity (i.e. number of offspring:
The quantitative study of sexual and natural selection
305
Selection Natural selection Artificial selection (breeding by humans) Sexual selection Intra-sexual selection (mate competition)
Non-sexual (natural) selection Inter-sexual selection (mate choice)
(b) Stabilising
Fecundity selection
(c) Disruptive
Fitness
Frequency
(a) Directional
Viability selection
Trait (e.g. body size)
Fig. 11.1 Two common classification schemes of natural selection based on the individual fitness components (top) and based on its outcome (bottom).
mx) and, primarily for males, mating success. It should be obvious that male (age-specific) fecundity mx is some product or sum of his mating success (e.g. his number of mates) and his mates’ offspring number. The three sub-components of individual fitness also give rise to a common classification of natural selection (Fig. 11.1, top), so there are viability (or survival), fecundity and sexual selection. Sexual selection can be further subdivided into intra-sexual selection, i.e. competition among members of the same sex for access to the other sex, and inter-sexual selection, largely mate choice of members of one sex by members of the other sex (Fig. 11.1, top). Other synonyms are in use, such as epigamic selection, but the ones presented in Fig. 11.1 are most commonly used. Also, natural selection is sometimes equated with non-sexual selection and opposed to sexual selection (cf. Darwin 1859, 1871; see e.g. Endler 1986). It is best to stick to the precise terms shown in Fig. 11.1. If you subscribe to
306
Wolf Blanckenhorn
the anthropocentric view that sets humans apart from nature, artificial selection can be defined separately (Fig. 11.1, top); if not, such plant or animal breeding orchestrated by humans is natural selection just as well. A second common classification is based on the evolutionary outcome of selection, differentiating between directional, stabilising (or balancing), and disruptive selection (Fig. 11.1, bottom). Again, there are synonyms such as positive (instead of directional) or diversifying (instead of stabilising) selection used by molecular biologists.
11.3 Measuring natural selection In principle, the quantitative assessment of selection is straightforward and based on regression techniques that most behavioural ecologists should be familiar with. Technical descriptions are available in Lande and Arnold (1983), Arnold and Wade (1984a,b), Brodie and Janzen (1996) and Brodie et al. (1995), as well as many evolution textbooks. Generally, any fitness measure (Table 11.1), the dependent variable (Y), is regressed upon one (univariate) or several (multivariate) metric trait(s) (Xi; e.g., body size, mating display intensity, colouration, etc.), the explanatory variables putatively affecting fitness. Selection coefficients can only be calculated if the traits Xi are continuous, ideally normally distributed, while fitness Y can be expressed in various ways. To directly compare the resulting selection coefficients among species, traits and fitness components, however, the Y and X variables must be standardised in a specific way as described below. Confusingly perhaps, there are various selection coefficients (which is the general, non-technical term) used in the literature. I define most of them below (and in BOX 11.1) and explain their relationships. Before starting, two statistical comments are necessary. First, although in principle the regression approach can be universally used, for statistical reasons the preferred method depends on the nature of the dependent (Y) variable. Thus, fitness can be measured in a binary way (dead or alive; mated or not), in which case binary logistic regression must be used. If fitness is instead expressed by a real or ordinal (countable) number (such as number of offspring produced), regular least-squares regression must be used. If only few outcomes are possible, such as when counting the number of mates when mating is a rare event (e.g. 0, 1, 2 or 3 mates), multinomial or loglinear approaches are needed. In modern statistical terms, however, these are all General Linear Models (GLMs) with different error distributions (binary, normal, multinomial, etc.). Second, unless purely descriptive, any statistical method has two elements to it: the estimate and the significance
The quantitative study of sexual and natural selection
307
test. Standard regression thus estimates the slope of Y on X, and the corresponding significance t-test tests whether the slope is different from zero (as the default), but potentially also differences from one or any other a priori prediction. Interestingly, evolutionary biologists and physiologists are often more interested in the estimates, whereas behavioural ecologists traditionally put more emphasis on significance testing, often not even reporting the corresponding estimates or presenting them in a useless form (e.g. unstandardised, scale-dependent regression coefficients instead of standardised (partial) correlation coefficients). It is important to keep in mind that these two statistical elements are equally important and always should come together. The standardised selection coefficients discussed below are the estimates, which come with a statistical test of significance. 11.3.1 Univariate linear selection gradients and differentials It is widely known that larger females of most ectothermic species produce more offspring (Blanckenhorn 2000). As the number of offspring is one of the central fitness measures (Table 11.1), this by itself already constitutes directional selection on (here female) body size. Linear regressions of clutch size on body size (here estimated by head width) for samples from three Swiss populations of the black scavenger or dung fly Sepsis cynipsea are plotted in Fig. 11.2 (left-hand side; data from Blanckenhorn et al. 1999a). If both the fitness (Y) variable and the trait (X) are transformed appropriately, these data yield standardised measures of the strength of fecundity selection for each population generally called selection gradients (Lande and Arnold 1983, Arnold and Wade 1984a,b; Fig. 11.2, right-hand side). The trait X, here head width, is normalised by deducting the population mean (average) from each individual value Xi and dividing by the population standard deviation (SD), to yield a so-called z-score: zi = (Xi – mean(X))/SD(X). This transforms the trait distribution into a standard normal distribution with mean = 0 and SD = 1, which most statistical programs will do automatically for any sample specified. Fitness Y, here estimated by clutch size and generally denoted by w, is transformed differently by dividing each individual value by the population mean to yield the relative fitness: w’ = wi / mean(w). While the slopes of the linear regressions of the raw data on the left in Fig. 11.2 denote the number of additional eggs produced per unit increase in head width for females of each population, the corresponding slopes on the right are dimensionless and denote the (standardised) intensity i of directional fecundity selection favouring larger female body size (because the relationship is positive), in standard deviation units.
308
Wolf Blanckenhorn
BOX 11.1 Calculating univariate linear and non-linear selection coefficients. Univariate selection gradient via regression. To calculate linear and nonlinear selection coefficients using the regression method (i.e. gradients) when only one predictor (x) variable is used (e.g. body size), first produce standardised z-scores for x by subtracting the sample mean from each individual value xi and dividing the difference by the standard deviation: z i xi x / SD x . For binary pairing success or mortality (paired/unpaired; dead/alive), then calculate relative fitness w’ as absolute fitness w, i.e. pairing success or survival (1 or 0), divided by the mean fitness w of the entire, representative sample, which is akin to the operational sex ratio (mated males (= number of mated females)/all males) or the proportion of surviving individuals, respectively: w' wi / w . If necessary, estimate these proportions prior to sampling, take any (non-random) sample, and later adjust according to Blanckenhorn et al. (1999b). The procedure is analogous for any continuous fitness measure such as the number of offspring (clutch size; cf. Fig. 11.2). Use the univariate model of relative fitness on standardised trait size w' c 1 z to estimate the univariate linear selection gradient 1 , and then use the model w' c '1 z 2 z ² to estimate the univariate non-linear (quadratic) selection gradient 2 2 , which quantifies the curvature with the linear component statistically controlled (Arnold and Wade 1984a,b). As a rule, '1 1 . The figure below indicates that, for Bumpus’ (1899) data displayed below, there is no directional viability selection on body size (nonsignificant linear selection gradient 1 ) but instead stabilising selection (significant negative non-linear selection gradient 2 2 ). Univariate selection differential approach if fitness is binary. Calculate zscores as above. Then take only the mean z survive of the 21 surviving birds with absolute fitness 1 with its associated standard deviation SD( z survive ), from which the 95% confidence interval (CI) can be derived as CI = 1.96* SD( z survive )/ n 1 (see light grey underlain numbers in data set below). The resulting selection differential S is the same as 1 above.
Relative surviorship
2.5 2.0 1.5 1.0 0.5 0.0 -3
-2
-1
0
1
Z-score body size
2
3
The non-significant linear viability selection gradient (black line with 95% CI) indicating lack of directional selection for body size, and the significant nonlinear gradient indicating stabilising selection on body size (red; presumably via flight ability), for Bumpus‘ (1899) data on house sparrow (Passer domesticus) adult mortality after a severe storm.
The quantitative study of sexual and natural selection
309
Sample data set: Bumpus’ (1899) mortality of sparrows after a severe storm. Dead/alive Rel. survival 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
Mean SD 95% CI N
0.429
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2.333 2.333 2.333 2.333 2.333 2.333 2.333 2.333 2.333 2.333 2.333 2.333 2.333 2.333 2.333 2.333 2.333 2.333 2.333 2.333 2.333
Body size
Z(body size)
2.987 3.051 3.061 3.100 3.105 3.116 3.129 3.163 3.165 3.169 3.183 3.186 3.186 3.192 3.201 3.201 3.220 3.230 3.232 3.234 3.246 3.248 3.260 3.298 3.300 3.307 3.363 3.379 3.101 3.126 3.143 3.150 3.161 3.161 3.170 3.192 3.193 3.202 3.205 3.208 3.211 3.212 3.222 3.229 3.246 3.252 3.276 3.284 3.289
-2.791 -1.959 -1.818 -1.301 -1.238 -1.100 -0.923 -0.472 -0.441 -0.392 -0.217 -0.172 -0.167 -0.086 0.022 0.028 0.284 0.405 0.439 0.464 0.625 0.645 0.805 1.303 1.340 1.432 2.165 2.374 -1.298 -0.966 -0.734 -0.642 -0.495 -0.495 -0.376 -0.088 -0.075 0.035 0.084 0.118 0.153 0.173 0.306 0.395 0.618 0.703 1.014 1.129 1.186
3.199 0.076 0.021 49
S = 0.036 0.674 0.296 21 Survivors
310
Wolf Blanckenhorn 100 80
2
Luzern
60
1
40
0,5
20 0.8
0.9
1
1. 1
60 40 20
100
0.8
0.9
1
1. 1
1.2
-3
-2
-1
0
1
2
3
2
3
2
3
Obfelden: S = +0.122
1,5 1 0,5 0
-4
-3
-2
-1
0
1
2 Fehraltorf: S = +0.118
Fehraltorf
80
1,5
60
1
40
0,5
20 0 0.7
-4
2
Obfelden
0 0.7
0
1.2
Relative clutch size
Clutch size
0 0.7 100 80
Luzern: S = +0.097
1,5
0.8
0.9
1
1. 1
Head width [mm]
1.2
0
-4
-3
-2
-1
0
1
Z-score head width
Fig. 11.2 Unstandardised relationship of female fecundity (clutch size) with body size (left) and the corresponding standardised fecundity selection differentials S (in standard deviation units; right) for three populations of the black scavenger fly Sepsis cynipsea (from Blanckenhorn et al. 1999a).
Of course, each slope comes with a standard error or confidence interval and a corresponding test of statistical significance. The slopes in Fig. 11.2 slightly differ between the populations, and if we enter population as a grouping factor in the statistical model, the interaction term between population and the trait X tests whether the fecundity selection intensities differ significantly between the populations or not (which is not the case in Fig. 11.2). Note that the significance test does not change due to the transformation performed, i.e. it yields the same result for the raw as for the transformed data, but the estimate crucially does. The data in Fig. 11.2 describe directional selection, because the relationship between fitness and the trait is monotonically increasing and linear, as in Fig. 11.1a, bottom left. Non-linear fitness-trait relationships are of course possible, and it is standard to model stabilising and disruptive selection (Figs. 11.1b, c, bottom) by negative and positive quadratic functions,
The quantitative study of sexual and natural selection
311
respectively. Thus, by adding a quadratic term X2 in the statistical model, as explained in BOX 11.1, we can additionally estimate and test for nonlinear selection. Note that the linear term in the model with the quadratic term will necessarily be different from the linear estimate in the model without the quadratic term. Thus the convention is that directional selection is first estimated using the simple linear model, whereafter non-linear selection is estimated using the model with both the linear and quadratic terms, only paying attention to the quadratic and ignoring the linear estimate (e.g. Fairbairn and Preziosi 1994). What if fitness is not continuous as in Fig. 11.2? If fitness is binary or multinomial, the statistical model for the significance test has to be modified, as stated above. Nevertheless, the same regression method can be applied to produce the estimate. An example is Bumpus’ (1899) famous data set on the mortality of sparrows after a severe storm in relation to their morphology (see BOX 11.1). Of 49 birds, 21 (given absolute binary fitness 1) survived and 28 died (given absolute fitness 0). Thus, assuming this is a random sample, the average fitness mean (w) = 21/49 = 0.429, which is also the proportion of surviving individuals. The two possible relative fitnesses of individuals are 0 or the inverse of mean fitness, 1/0.429 = 2.33. In this case it is immediately obvious that the standardised data produce a steeper relationship between fitness and the trait than the raw, absolute fitness (1/0) data (because 2.33 > 1). While logistic regression needs to be used to test for the statistical significance of the slope (using the raw or standardised data), regular least-squares regression on the standardised data can be used to estimate selection intensity. However, Janzen and Stern (1998) present an equivalent method allowing back-calculation of the selection intensity from the logistic slope estimate. Further and in general, randomisation techniques can, of course, also be used for significance testing (e.g. Manly 1985, Mitchell-Olds and Shaw 1987). Only if fitness is binary, as just discussed, is there a simpler, univariate method originally derived from classical quantitative genetics (Falconer 1989). Assuming the trait X (e.g. body size) is normally distributed and we have truncation selection (dead = not selected = 0 and alive = selected = 1, or mated and not mated, etc.), the selection differential is the mean trait value of the selected proportion of individuals (e.g. the largest ones) minus the mean trait value of the whole sample: S = mean(XSel) – mean(XPop). This value is yet unstandardised and in trait units, but by z-scoretransforming all data as above, standardisation is again achieved. As per definition the population mean(z) is zero, the selection differential is then equal to the mean standardised selected subpopulation mean(zSel), thus becoming identical to the selection gradient derived from regression as described above (see BOX 11.1).
312
Wolf Blanckenhorn 3.43
500 300
400
S = +0.32
300
100
200
Unpaired
200
Paired
Frequency
500
3.53
100
Selection differential
400
100
0
0
100 200 300 400
3.39
500 2.0
2.5
3.0
200 300 400 500
3.5
4.0
4.5
-4
Pairing status 0
-3
-2
-1
0
1
2
3
4
3
Selection gradient
Relative pairing success
1
2
1
S = +0.32
0 2.0
2.5
3.0
3.5
4.0
Male hind tibia length [mm]
4.5
-4
-3
-2
-1
0
1
2
3
Z-score male hind tibia length
4
Fig. 11.3 Unstandardised (left) and standardised (right) (a) frequency distribution of paired (top) and unpaired (bottom) male yellow dung flies (Scathophaga stercoraria) as a function of their body size in Fehraltorf, Switzerland, over 2 years; and (b) the corresponding relationship of absolute (paired = 1, unpaired = 0; left) and relative pairing status (ca. 31% of all males were paired) with body size (data from Jann et al. 2000). Both methods yield the same selection intensity of S = +0.320 (differential top; gradient bottom).
Figure 11.3 illustrates the two procedures to arrive at the same sexual selection intensity estimate for pairing success, using data from Jann et al.’s (2000) longitudinal study of yellow dung flies. I must re-emphasise that in case of binary fitness measures the selection intensity depends crucially on correct estimation of the proportion of mated (or live) vs. unmated (or dead) individuals in the population, because the slope of the regression in Fig. 11.3, bottom right, becomes steeper when this proportion (i.e. mean fitness) decreases. This should be intuitive, as fitness is a relative measure and a particular male should have higher fitness if he out-competes more other males. The sample taken thus needs to truly reflect this proportion (Arnold and Wade 1984a,b). Luckily, the selection estimate can be corrected if the sample does not reflect the true proportion (e.g. when collectors focus on copulating pairs because they are rare and more difficult to collect), but if an independent estimate of the true proportion of mated in-
The quantitative study of sexual and natural selection
313
dividuals is otherwise available (Blanckenhorn et al. 1999b). For the interested reader, Blanckenhorn et al. (1999b), but also e.g. Brodie and Janzen (1996) or Freeman and Herron’s (2007) Evolutionary Analysis textbook, derive the relationships between the different selection coefficients. 11.3.2 Multivariate linear and non-linear selection gradients Two extensions of the regression logic outlined above are obvious. First, selection on several traits Xi can be estimated at the same time as in standard multiple regression. Such multivariate approaches to selection are preferable to simple univariate studies, as quantitative partitioning of selection provides more detailed insights into the precise mechanism of selection. For example, is it larger body size or mass per se that confers an advantage in predator avoidance for a flying insect, or is it the size or shape of the wing relative to body size that does so? Second, the relationship between fitness and the trait may take any non-linear shape. In particular, stabilising and disruptive selection (Fig. 11.1b, c, bottom) can be modeled using negative and positive quadratic functions, respectively. I shall now describe these methods in turn. BOX 11.2 Calculating multivariate linear, non-linear and correlational selection coefficients. Produce standardised z-scores for all traits xi as described in BOX 11.1 by subtracting the sample mean from each value and dividing by the standard deviation: zi xi x / SDx . Calculate relative fitness w’ as absolute fitness w divided by the mean fitness w of the entire, representative sample: w' wi / w . Use the model w' c multi,i zi for multivariate linear selection gradients, and the model w' c ' multi,i z i 0.5 multi,i z i2 i , j z i z j
for multivariate pair-wise correlational, i, j , and non-linear (quadratic) selection gradients, multi,i . While the linear coefficients as calculated in BOX 11.1 reflect the combined effects of direct and indirect selection on body size (Endler 1986), the multivariate coefficients calculated here estimate direct selection on each trait with selection on correlated traits statistically removed.
314
Wolf Blanckenhorn
By assessing several traits at once, selection on, for example, male body size and the duration of his mating display can be estimated simultaneously (BOX 11.2). As in any multiple regression, this yields independent selection coefficients for each trait. By doing so, correlational selection can additionally be estimated (Lande and Arnold 1983, Brodie et al. 1995). Intuitively, if two traits are correlated and both affect fitness, e.g. here if larger males also show longer mating displays, then selection on one trait (e.g. mating display duration by female choice) will produce an indirect, correlated change in the other trait (here body size) even if there is no direct selection on the second trait. This is what is being estimated by correlational selection when entering a product (or interaction) term between two Xi (BOX 11.2). Correlational effects are highly biologically relevant, particularly if selection on two traits that are positively correlated goes in opposite directions. For example, under drought conditions viability selection in the medium ground finch (Geospiza forti) favours deep but narrow beaks with which birds can crack the remaining large and strong seeds best. However, as is typical, both morphological traits are positively genetically correlated, so birds tend to have deeper and wider beaks (Grant and Grant 1995). It should be intuitive that direct selection for narrower beaks (yielding a negative directional selection gradient) will be counteracted by the correlated selection favouring wider beaks (positive correlational selection gradient) that occurs because deeper beaks are favoured by directional selection (positive direct selection gradient). As a result, the response to selection will be constrained until the genetic correlation between the two traits is broken down. Of course, this approach can be extended to incorporate more than two traits as well as quadratic terms estimating stabilising or disruptive selection, as described next. By entering a quadratic term in addition to a linear (and an interaction) term, stabilising and disruptive selection (Fig. 11.1b, c, bottom) can be estimated (BOX 11.2). These two types of selection are mutually exclusive for any given trait, a negative coefficient implying stabilising and a positive coefficient disruptive selection. Furthermore, linear and quadratic terms can both be (independently) significant, thus indicating a combination of linear and non-linear selection, for example asymptotic or accelerating selection (Fig. 11.4). It should be clear that any complex relationship between fitness and a trait is possible. Such relationships are best visualised by non-parametric regression (Phillips and Arnold 1989, Brodie et al. 1995, Blows 2007), e.g. using Schluter’s cubic spline software (http://www.zoology.ubc.ca/~schluter/software.html). Finally, it should be mentioned that historically there are other quantitative measures of selection in the literature that may be relevant in these contexts, such as e.g. the opportunity for selection (Crow 1958, Shuster
The quantitative study of sexual and natural selection Scathophaga stercoraria
315
Sepsis cynipsea
100
Clutch size
80 60 40 20 0
1.5
2
2.5
3
3.5 0.7 Hind tibia length
0.9
1.1
1.3
Fig. 11.4 Unstandardised relationship of female fecundity (clutch size) with body size showing accelerating (left, for the yellow dung fly Scathophaga stercoraria; from Jann et al. 2000) and asymptotic selection (right, for the black scavenger fly, Sepsis cynipsea; from Blanckenhorn et al. 1999a). In both cases the linear and non-linear (quadratic) terms were significant.
and Wade 2003). These are often mathematically related to the aforementioned coefficients but nevertheless different, so the user has to be careful not to confuse the various measures. For the interested reader, further extensions of the statistical approaches described here also exist (Blows 2007, Hunt et al. 2009).
11.4 Study types conducive to estimation of selection coefficients 11.4.1 Phenomenological selection studies in nature Besides the classic phenomenological field studies of selection, standardised selection coefficients can in principle be calculated for a wide variety of studies in behavioural ecology, and this would be useful if only for comparative purposes. These various study types can be loosely categorised as done in Table 11.2, which I shall now discuss, using primarily our own studies on dung flies with an emphasis on body size as examples, although any analogous studies on other taxa or traits would serve just as well. Note that we also did not supply selection coefficients in several of these studies even though we could have.
316
Wolf Blanckenhorn
Table 11.2 Types of behavioural studies principally conducive to calculating selection coefficients for comparative purposes. Study type Experimental unit/ replicate
Fitness component
Phenomenological
Pairing success Field
Non/ Population
Blanckenhorn et al. 1999a
Pairing success Field
None/ season; year
Jann et al. 2000
Pairing success Field
Tail length/ none
Andersson 1982
Survival
Field
None/ season; year
Grant and Grant 1995
Survival
Lab
Predation/ wing damage
Mühlhäuser and Blanckenhorn 2002
Pairing success Lab
Nutrition/ energy depletion
Blanckenhorn et al. 2008
Fecundity; longevity
Mating system/ laboratory line
Martin and Hosken 2003
Pairing success Lab
Sex ratio/ none
Blanckenhorn et al. 2000
Pairing success Lab
Light conditions/parasitism
Milinski and Bakker 1990
Pairing success Lab
None/ species
Abt and Reyer 1993
Pairing success Lab
None/ none
Blanckenhorn et al. 2000
Fecundity; longevity
Lab
None/ copulation number
Blanckenhorn et al. 2000
Fecundity; longevity; pairing success
Lab
Nutrition/ energy depletion
Blanckenhorn et al. 1995
Population
Population- Group based
Individualbased
Pair
Individual
Field/ Manipulation/ lab other factors
Lab
Example
Classic studies document selection as it occurs in the wild and are therefore at the heart of evolutionary ecology. As they are typically not manipu-
The quantitative study of sexual and natural selection
317
lated, they are phenomenological, meaning that fecundity, viability or sexual selection are assessed from field samples without regard to the underlying behavioural mechanisms, e.g. whether mating success is mediated by female choice or male-male competition. In practice a sample of mated and unmated males (e.g. Jann et al. 2000), or a number of live and dead birds (Bumpus 1899, Grant and Grant 1995) are collected, on which any measurements, often relating to morphology but also e.g. colouration, can be taken to investigate which of these traits influence fitness (i.e. here, pairing success or survival). Such studies have been reviewed by Endler (1986), Andersson (1994) and, most recently, by Kingsolver et al. (2001) and Cox and Calsbeek (2009). It must be emphasised that there are fewer such phenomenological selection studies than one might expect, and the existing studies are often incomplete in terms of fitness components and certainly not a random sample. A major reason for the latter is that many species do not occur in sufficiently high numbers in a spatio-temporally aggregated fashion to make such a study practical, as substantial sample sizes are typically required because of large natural variation (Arnold and Wade 1984a,b, Palmer 2000, Kingsolver et al. 2001). For example, if a species is very secretive and mates only rarely and/or for a very short time, sexual selection coefficients will be hard to come by because mating pairs cannot be found. Furthermore, not all fitness components are equally easy to assess in every species. While fecundity selection can be well studied in insects because they lay many eggs (e.g. Fig. 11.2), insect survival in the field is difficult to measure because they are so small (Blanckenhorn et al. 1999a). The reverse is true for larger mammals, which typically have few offspring but can be marked and tracked over long distances and time (Clutton-Brock 1988). Thus, field studies of selection in a given species rarely if ever assess lifetime reproductive success, arguably the best fitness estimate for an individual, but instead make do with more practical but also more distant fitness components lower down in the hierarchy (Table 11.1). Luckily, selection can be studied by a piece-meal or cross-sectional (as opposed to longitudinal) approach (Arnold and Wade 1984b; e.g. Blanckenhorn 2007), whereby the effects of a trait on fitness are investigated for a sample of individuals only at a particular life stage. Several such estimates at various stages, often called selection episodes, for various fitness components can ultimately be integrated, in the ideal case yielding a measure equivalent to lifetime reproductive success. For example, the effect of body size on pairing success would be one such sexual selection episode and, given pairing, whether larger males also mate with larger females, i.e. whether there is assortative mating, is the subsequent selection episode (e.g. Jann et al. 2000). (It should be obvious that both episodes influence
318
Wolf Blanckenhorn
male fitness, because male reproductive success depends on his number of mates and the number of offspring his mate produces with his sperm.) Because fitness is multiplicative, selection differentials are additive, and several selection episodes can so be strung together (Arnold and Wade 1984a,b; see e.g. Blanckenhorn 2007). Cross-sectional estimation of multiple selection episodes and fitness components makes a number of assumptions if it is to correctly reflect overall selection over the entire lifetime of an organism in a variable environment. Most of these assumptions relate to any particular field sample being truly random with regard to various potentially confounding variables. First, it assumes that any field sample correctly reflects the age structure of the population, thus including older and younger individuals of both sexes. Needless to say, the sexes should be assessed separately, although in the juvenile stage this is often not possible. Second, it assumes that there are no systematic effects of age on the fitness component estimated; otherwise early fecundity may systematically overestimate lifetime fecundity if fecundity diminishes with age. Third, selection depends strongly on the environmental conditions at the time. Therefore multiple samples at various times or environmental conditions at more than one place, or in several populations, are necessary to encompass the possibility of spatio-temporal variation in selection for a given species (Istock 1981). Assessment in more than one environment is particularly advised for any experimental estimation of selection in the field or laboratory. Fourth, selection at any life stage is contingent upon the probability of an individual reaching this life stage, so the magnitude of selection has to be adjusted for this probability (Blanckenhorn et al. 1999a, Blanckenhorn 2007). If these assumptions are not fulfilled, biased estimates of selection will result. In phenomenological selection studies, any natural or experimentally manipulated extraneous variable likely producing variation in selection can and should be entered in the statistical model as a factor or covariate to test for variation in selection intensity among treatments or populations via interaction terms, and to arrive at an average estimate of selection over several environments. For example, in Fig. 11.2, fecundity selection gradients, i.e. the slopes, do not differ among the three populations of black scavenger flies, so an average of the values presented for the three populations well represents fecundity selection of the species (Blanckenhorn et al. 1999a). As mentioned in the introduction, Andersson (1982) could have calculated sexual selection coefficients with regard to tail length in the long-tailed widowbird but did not do so. Note that because he manipulated tail length he produced three somewhat discrete tail-length categories (as opposed to continuous tail-length data on the X-axis; cf. Fig. 11.3), al-
The quantitative study of sexual and natural selection
319
Table 11.3 Available sex-specific mean ± 95% CI field estimates of linear sexual, fecundity or viability selection differentials or gradients on any morphological trait for a number of animal species (from Kingsolver et al. 2001 and Blanckenhorn 2007). There is only one available estimate for juvenile viability.
Fecundity or sexual selection
Adult viability selection
Females (N)
Males (N)
+0.127 ± 0.063 (13)
+0.255 ± 0.120 (22)
Differentials (unpaired data)
+0.079 ± 0.114 (8)
+0.333 ± 0.221 (16)
Gradients (unpaired data)
+0.149 ± 0.084 (9)
+0.256 ± 0.139 (9)
Invertebrates1 (paired data)
+0.063 ± 0.155 (6)
+0.239 ± 0.150 (6)
Vertebrates2 (paired data)
0.039 ± 0.113 (9)
+0.042 ± 0.073 (9)
All estimates and species
+0.072 ± 0.078 (9)
Not differentiated by sex
1
Allenomobius socius (Fedorka and Mousseau 2002), Aquarius remigis (Preziosi and Fairbairn 2000), Callosobruchus maculatus (Savalli and Fox 1999), Clibanarius dugeti (Harvey 1990), Gammarus pulex (Ward 1988), Plathhemis lydia (Koenig and Albano 1987), Scathophaga stercoraria (Jann et al. 2000, Blanckenhorn et al. 2003), Sepsis cynipsea (Blanckenhorn et al. 1999a, 2004), Stator limbatus (Savalli and Fox 1998); 2Crocidura russula (Boutellier and Perrin 2005), Carpodacus mexicanus (Badyaev et al. 2000), Geospiza conirostris (Grant 1985), Geospiza fortis (Price 1984), Niveoscineus microlepidates (Olsson et al. 2002), Parus major (Björklund and Lindén 1993)
though this still permits regression to calculate a selection gradient with regard to the number of mates obtained for the whole sample. Some patterns on phenomenological field selection studies emerge from the available data (Blanckenhorn 2000, 2005, 2007, Kingsolver et al. 2001, Cox and Calsbeek 2009). The vast majority of studies (ca. 80%) estimate selection with regard to morphological traits, generally reflecting body size. Selection data for physiological (e.g. Blanckenhorn et al. 2003, 2004) and behavioural traits are scarce in comparison, so I encourage all behavioural ecologists to generate such data. Even a common trait such as body size has been estimated for few species using several fitness components, and for fewer still (9 invertebrates and 6 vertebrates), simultaneous selec-
320
Wolf Blanckenhorn
tion estimates for both sexes exist (paired data in Table 11.3). Sexual or fecundity selection favouring larger male body size is generally stronger than (sexual or) fecundity selection favouring female body size (Table 11.3). Moreover, selection on body size rarely has a different direction in males and females (Cox and Calsbeek 2009). At the same time, adult and especially juvenile viability selection estimates are very rare and typically not different from zero, i.e. survival is largely independent of body size (Table 11.3). According to the differential equilibrium hypothesis of sexual size dimorphism (Blanckenhorn 2007), taken together these patterns would suggest that most species should have male-biased size dimorphism, because sexual selection on males exceeds fecundity selection on females and viability counter-selection is low and does not differ between the sexes. This is inconsistent with the data, as several of the species listed in Table 11.3 have female-biased size dimorphism, thus globally rejecting the hypothesis. 11.4.2 Population selection studies in the laboratory In nature, the scope for manipulations is limited and therefore selection mechanisms are difficult to assess. In such cases animals (such as Drosophila) may be kept and investigated in groups (or populations) in the laboratory in a manner resembling the field situation, although population sizes will necessarily be much smaller (Table 11.2). Thus, similar approaches as in the field can be used to generate selection coefficients. For example, Martin and Hosken (2003a,b) kept several replicate experimental evolution populations of Sepsis cynipsea in the laboratory either at naturally polyandrous conditions or under enforced monogamy, thus manipulating the mating system. Any estimates of, for example, body size dependent sexual, fecundity or viability selection generated with individuals of these populations would yield one selection coefficient (with its associated standard error) per laboratory population replicate. As Martin and Hosken (2003a,b) had three replicate populations per mating system, they could have ended up with 2 times 3 population estimates, thus documenting variation in selection between the mating systems (which was not done). Mühlhäuser and Blanckenhorn (2002) provided a second example. Predation is difficult to observe and manipulate in the field. A number (24) of S. cynipsea individuals of various sizes and two wing damage treatments (wings clipped and unclipped) were exposed to a predator (a yellow dung fly female) in each of 24 replicate containers (= populations; 12 with females and 12 with males). Although body size and behaviour were not measured in this experiment, given that the predator only ate a subset of
The quantitative study of sexual and natural selection
321
the flies each container would have yielded two size-dependent viability selection coefficients (one for the wing-damaged and one for the undamaged subset of flies). The whole experiment would have yielded 12 (males) + 12 (females) such pairs of replicate coefficients, allowing for a test of size-dependent predation with sex and wing-damage as additional factors. Teuschl et al. (2010) adopted a similar approach and calculated replicate selection coefficients. A final example is provided by Blanckenhorn et al. (2008), who simulated mating competition among 9 Scathophaga stercoraria males of different sizes on a dung pat in an enclosure in the laboratory, to which a limited number of females was added. Thus, each replicate container yielded one sexual selection coefficient (for pairing success) with regard to body size. As there was an additional nutrient treatment of the males, again difficult to perform in nature, this laboratory study assessed size-dependent mating success as a function of nutritional state at semi-natural conditions. Note that all the above studies produced replicate selection coefficients per container or population. Although each coefficient comes with its own standard error, this becomes largely irrelevant, as the group/container/population becomes the statistical unit of interest, and a mean selection coefficient with its associated standard error based on the number of group/container/population replicates is being generated (Table 11.2). 11.4.3 Individual-based selection studies in the laboratory In behavioural ecology it is rather common to perform choice experiments where (typically) a female is allowed to choose between a pair of males that may or may not interact, simulating female choice in nature (Table 11.2; e.g. Milinski and Bakker (1990) for sticklebacks; Abt and Reyer (1993) for frogs; Blanckenhorn et al. (2000) for S. cynipsea). Often these males differ in size, although differences in mating display, mating attempts, calling rates or parasitism are sometimes additionally tested. Here the group consists of two individuals only. Nevertheless, a primitive, twoindividual selection coefficient can be calculated for each pair of males, which is equal to the (standardised) deviation of the winner’s (body size, display, etc.) score from the mean of the two males. As the choice tests are replicated, several such coefficients will again yield a mean selection coefficient with respect to body size, behaviour, etc., in principle also allowing multivariate approaches as outlined above if sample sizes are high enough. The simplest situation conceivable consists of laboratory assessment of individuals (Table 11.2). If, for example, a sample of individuals are held singly or in groups and e.g. their fecundity or longevity in the laboratory
322
Wolf Blanckenhorn
GLOSSARY Evolution: A change in gene frequencies over generations affecting any trait Fitness: The relative contribution of a unit of selection (e.g. a species, an individual, a gene, etc.) to the subsequent generation. Best calculated as lifetime reproductive success when studying individuals (cf. Table 11.1) Fitness component: Any (incomplete) subcomponent of fitness only estimating part of fitness (cf. Table 11.1) Heritability h2: The proportion of the total phenotypic variation in a quantitative trait that can be attributed to genetic variation, typically within a given population Natural selection: Cf. Fig. 11.1 Quantitative genetics: A biological field of study of the genetics underlying continuous or quantitative traits, i.e. those that are affected by multiple genes. Traditionally a statistical (phenomenological) approach is used without necessarily identifying all underlying genes Phenomenological selection studies: Typically field studies of natural selection quantifying selection without necessary reference to the underlying mechanism. Sexual selection: Cf. Fig. 11.1 Selection coefficient: A generic term subsuming all terms below Selection differential: A quantitative measure of the strength of selection on a single trait calculated as the difference between the (selected) individuals leaving offspring into the next generation and the overall phenotypic population mean Selection episode: Selection during a single event, point in time or life history stage. Subcomponent of total, lifetime selection Selection gradient: A standardised measure of the strength of selection defined as the covariance between relative fitness and the standardised trait value (cf. Fig. 11.2). Typically estimated as the slope of a uni- or multivariate regression. Selection intensity: The standardised selection differential (see above), calculating by dividing the selection differential by the phenotypic standard deviation (SD) Selection balancing: Selection process whereby both extreme phenotypes have lower fitness (cf. Fig. 11.1, bottom) correlational: In bi- or multivariate selection studies estimating the interactive non-linear selection component between two traits (cf. BOX 11.1 and 11.2) directional: Selection process whereby one of the extreme phenotypes has higher fitness (cf. Fig. 11.1, bottom) disruptive: Selection process whereby both extreme phenotypes have higher fitness (cf. Fig. 11.1, bottom) diversifying: Same as balancing selection (used by molecular biologists)
The quantitative study of sexual and natural selection
323
Selection epigamic: Same as intra-sexual selection fecundity: Selection referring to the fitness component fecundity (number of offspring; cf. Fig. 11.1, top) intra-sexual: Type of sexual selection whereby individuals of the same sex (typically males) compete for access to the other sex. Also called male-male competition inter-sexual: Type of sexual selection whereby individuals of one sex (typically females) choose members of the other sex. Also called female choice non-linear: Selection estimating the non-linear, curvature component indicating stabilising, disruptive (also called quadratic; cf. Fig. 11.1, bottom), asymptotic (cf. Fig. 11.4), or correlational selection (cf. BOX 11.1 and 11.2). linear: Selection estimating the linear, directional component (cf. BOX 11.1 and 11.2) positive: Same as directional selection (as used by molecular biologists) stabilising: Same as balancing selection survival: Selection referring to the fitness component survival or survivorship (the inverse of mortality; cf. Fig. 11.1, top) viability: Same as survival selection
(under any treatment) is investigated, one can obtain fecundity or longevity selection data for the sample. This is how the data in Fig. 11.2 were generated, producing one fecundity or viability selection coefficient per population (Blanckenhorn et al. 1999a; see also Blanckenhorn et al. 1995, 2000 for analogous data sets). If females are supplied with a male (of a given size, performing particular behaviours), this further yields size- or behaviour-dependent pairing success data for males and females, as some females will mate and others not, from which again one sexual selection coefficient can be generated (Blanckenhorn et al. 1995, 2000). Note that in general calculating selection coefficients requires little extra effort besides standardisation, as the statistical models to test for effects are performed anyway.
11.5 Conclusions In this chapter, I described and discussed the available standardised quantitative methods to estimate natural (including sexual) selection in the field and the laboratory. In so doing, the advantages of investigating selection have been addressed, particularly with regard to its underlying behavioural
324
Wolf Blanckenhorn
mechanisms, with a continuum of laboratory and field approaches (Table 11.2). I hope that this treatise helps particularly the unfamiliar readers to familiarise themselves with such approaches, also in practice. My further hope is that these methods become more widely used, especially in the field of behaviour in the context of sexual selection. Although most of my examples treat body size and morphology, as does the available literature (Kingsolver et al. 2001), the methods can be easily transferred to any quantifiable behavioural or physiological trait. In this day and age of metaanalyses the scientific community is seriously discussing data banks for ecological data, similar to those for molecular data, and some do exist already (e.g. http://datadryad.org/repo/handle/10255/dryad.167). As behavioural and ecological data are inherently variable, idiosyncratic and often species and study specific, any available standardisation, such as selection coefficients, would make such an endeavour more feasible. One may hope to see more selection coefficients also in the behavioural literature.
References Abt G, Reyer H-U (1993) Mate choice and fitness in a hybrid frog – Rana esculenta females prefer Rana lessonae males over their own. Behav Ecol Sociobiol 32:221-228 Andersson M (1982) Female choice selects for extreme tail length in a widowbird. Nature 299:818-820 Andersson S (1989) Sexual selection and cues for female choice in leks of Jacksons’s widowbird. Behav Ecol Sociobiol 25:403-410 Andersson M (1994) Sexual Selection. Princeton University Press, Princeton Arnold SJ, Wade MJ (1984a) On the measurement of natural and sexual selection: theory. Evolution 38:709-719 Arnold SJ, Wade MJ (1984b) On the measurement of natural and sexual selection: applications. Evolution 38:720-734 Badyaev AV, Hill GE, Stoehr AM, Nolan PM, McGraw KJ (2000) The evolution of sexual size dimorphism in the house finch. II. Population divergence in relation to local selection. Evolution 54:2134-2144 Björklund M, Lindén M (1993) Sexual size dimorphism in the great tit (Parus major) in relation to history and current selection. J Evol Biol 6:397-415 Blanckenhorn WU (2000) The evolution of body size: what keeps organisms small? Q Rev Biol 75:385-407 Blanckenhorn WU (2005) Behavioral causes and consequences of sexual size dimorphism. Ethology 111:977-1016 Blanckenhorn WU (2007) Case studies of the differential-equilibrium hypothesis of sexual size dimorphism in dung flies. In: Fairbairn DJ, Blanckenhorn WU, Székely T (eds) Sex, Size and Gender Roles: Evolutionary Studies of Sexual Size Dimorphism. Oxford University Press, Oxford, pp. 106-114
The quantitative study of sexual and natural selection
325
Blanckenhorn WU, Preziosi RF, Fairbairn DJ (1995) Time and energy constraints and the evolution of sexual size dimorphism: to eat or to mate? Evol Ecol 9:369-381 Blanckenhorn WU, Morf C, Mühlhäuser C, Reusch T (1999a) Spatiotemporal variation in selection on body size in the dung fly Sepsis cynipsea. J Evol Biol 12:563-576 Blanckenhorn WU, Reuter M, Ward PI, Barbour AD (1999b) Correcting for sampling bias in quantitative measures of selection when fitness is discrete. Evolution 53:286-291 Blanckenhorn WU, Mühlhäuser C, Morf C, Reusch T, Reuter M (2000) Female choice, female reluctance to mate and sexual selection on body size in the dungfly Sepsis cynipsea. Ethology 106:577-593 Blanckenhorn WU, Kraushaar URS, Reim C (2003) Sexual selection on morphological and physiological traits and fluctuating asymmetry in the yellow dung fly. J Evol Biol 16:903-913 Blanckenhorn WU, Kraushaar URS, Teuschl Y, Reim C (2004) Sexual selection on morphological and physiological traits and fluctuating asymmetry in the black scavenger fly Sepsis cynipsea. J Evol Biol 17:629-641 Blanckenhorn WU, Birrer M, Meier CM, Reim C, Teuschl Y, Weibel D (2008) Size-dependent mating success at various nutritional states in the yellow dung fly. Ethology 114:752-759 Blows MW (2007) A tale of two matrices: multivariate approaches in evolutionary biology. J Evol Biol 20:1-8 Bouteiller-Reuter C, Perrin N (2005) Sex-specific selective pressures on body mass in the greater white-toothed shrew, Crocidura russula. J Evol Biol 18:290-300 Brodie ED III, Janzen FJ (1996) On the assignment of fitness values in statistical analyses of selection. Evolution 50:437-442 Brodie ED III, Moore AJ, Janzen FJ (1995) Visualizing and quantifying natural selection. Trends Ecol Evol 10:313-318 Bumpus HC (1899) The elimination of the unfit as illustrated by the introduced sparrow, Passer domesticus. Biol Lect Woods Hole Marine Biol Lab 6:209226 Clutton-Brock TH (1988) Reproductive Success: Studies of Individual Variation in Contrasting Breeding Systems. University of Chicago Press, Chicago Cox RM, Calsbeek R (2009) Sexually antagonistic selection, sexual dimorphism and the resolution of intralocus sexual conflict. Am Nat 173:176-187 Crow JF (1958) Some possibilities for measuring selection intensities in man. Hum Biol 30:1-13 Darwin C (1859) The Origin of Species by Means of Natural Selection. John Murray, London Darwin C (1871) The Descent of Man and Selection in Relation to Sex. John Murray, London Endler JA (1986) Natural Selection in the Wild. Princeton University Press, Princeton
326
Wolf Blanckenhorn
Fairbairn DJ, Preziosi RF (1994) Sexual selection and the evolution of allometry for sexual size dimorphism in the water strider, Aquarius remigis. Am Nat 144:101-118 Falconer DS (1989) Introduction to Quantitative Genetics. Longman, Harlow Fedorka KM, Mousseau TA (2002) Nuptial gifts and the evolution of male body size. Evolution 56:590-596 Freeman S, Herron JC (2007) Evolutionary Analysis. Prentice Hall, Upper Saddle River/NJ Grant BR (1985) Selection on bill characters in a population of Darwin’s finches: Geospiza conirostris on Isla Genovesa, Galapagos. Evolution 39:523-532 Grant PR, Grant BR (1995) Predicting microevolutionary responses to directional selection on heritable variation. Evolution 49:241-251 Harvey AW (1990) Sexual differences in contemporary selection acting on size in the hermit crab Clibanarius digueti. Am Nat 136:292-304 Hunt J, Breuker CJ, Sadowski JA, Moore AJ (2009) Male-male competition, female mate choice and their interaction: determining total sexual selection. J Evol Biol 22:13-26 Istock CA (1981) Natural selection and life history variation: theory plus lessons from a mosquito. In: Denno RF, Dingle H (eds) Insect Life History Patterns: Habitat and Geographic Variation. Springer, Heidelberg, pp 113-126 Jann P, Blanckenhorn WU, Ward PI (2000) Temporal and microspatial variation in the intensities of natural and sexual selection in the yellow dung fly Scathophaga stercoraria. J Evol Biol 13:927-938 Janzen FJ, Stern HS (1998) Logistic regression for empirical studies of multivariate selection. Evolution 52:1564-1571 Kingsolver JG, Hoekstra HE, Hoekstra JM, Berrigan D, Vignieri SN, Hill CE, Hoang A, Gibert P, Beerli P (2001) The strength of phenotypic selection in natural populations. Am Nat 157:245-261 Koenig WD, Albano SS (1987) Lifetime reproductive success, selection and the opportunity for selection in the white-tailed skimmer, Plathemis lydia (Odonata: Libellulidae). Evolution 41:22-36 Lande R, Arnold SJ (1983) The measurement of selection on correlated characters. Evolution 37:1210-1226 Lynch M, Walsh B (1998) Genetics and Analysis of Quantitative Traits. Sinauer Associates, Sunderland/MA Manly BFJ (1985) The Statistics of Natural Selection on Animal Populations. Chapman and Hall, London Martin OY, Hosken DJ (2003a) The evolution of reproductive isolation through sexual conflict. Nature 423:979-982 Martin OY, Hosken DJ (2003b) Costs and benefits of evolving under experimentally enforced polyandry or monogamy. Evolution 57:2765-2772 Milinski M, Bakker TCM (1990) Female sticklebacks use male coloration in mate choice and hence avoid parasitized males. Nature 344:330-333 Mitchell-Olds T, Shaw RG (1987) Regression analysis of natural selection: statistical inference and biological interpretation. Evolution 41:1149-1161
The quantitative study of sexual and natural selection
327
Mousseau TA, Roff DA (1987) Natural selection and the heritability of fitness components. Heredity 59:181-197 Mühlhäuser C, Blanckenhorn WU (2002) The costs of avoiding matings in the dung fly Sepsis cynipsea. Behav Ecol 13:359-365 Olsson M, Shine R, Wapstra E, Ujvari B, Madsen T (2002) Sexual dimorphism in lizard body shape: the roles of sexual selection and fecundity selection. Evolution 56:1538-1542 Palmer AR (2000) Quasireplication and the contract of error: lessons from sex ratios, heritabilities and fluctuating asymmetry. Annu Rev Ecol Syst 31:441-480 Phillips PC, Arnold SJ (1989) Visualizing multivariate selection. Evolution 43:1209-1222 Preziosi RF, Fairbairn DJ (2000) Lifetime selection on adult body size and components of body size in a waterstrider: opposing selection and maintenance of sexual size dimorphism. Evolution 54:558-566 Price TD (1984) Sexual selection on body size, territory and plumage variables in a population of Darwin’s Finches. Evolution 38:327-341 Savalli UM, Fox CW (1998) Sexual selection and the fitness consequences of male body size in the seed beetle Stator limbatus. Anim Behav 55:473-483 Savalli UM, Fox CW (1999) The effect of male size, age, and mating behavior on sexual selection in the seed beetle Callosobruchus maculatus. Ethol Ecol Evol 11:49-60 Shuster SM, Wade MJ (2003) Mating Systems and Strategies. Princeton University Press, Princeton Teuschl Y, Reim C, Blanckenhorn WU (2010) No size-dependent reproductive costs in black scavenger fly (Sepsis cynipsea) males. Behav Ecol 21:85-90 Ward PI (1988) Sexual selection, natural selection, and body size in Gammarus pulex (Amphipoda). Am Nat 131:348-359
Chapter 12
Mate choice and reproductive conflict in simultaneous hermaphrodites NILS ANTHES
ABSTRACT Simultaneous hermaphroditism defines sexual systems in which animals display male and female sex at the same time. Given that each individual now inherently expresses the ‘interests’ of both sexes, this form of gender expression can have profound consequences for the evolution of behavioural reproductive strategies. The outcome of reproductive interactions between two hermaphrodites is likely to vary with (i) intra-individual trade-offs between male and female reproduction, (ii) inter-individual courtship and mate choice between the sexes, (iii) inter-individual competition within the sexes, and (iv) competition with rival individuals in the social group. While earlier work has argued that precopulatory mate choice may only be weakly expressed in simultaneous hermaphrodites, the first section of the chapter documents that, instead, mate choice is prevalent and may include sophisticated mate discrimination based on traits such as body size, mating history, or relatedness. The second section illustrates putative conflicts that individuals may face during copulation, primarily focussing on the decision over mating roles that is central to understand hermaphrodite reproductive behaviour. Available evidence indicates that conditional reciprocity, where individuals accept matings in their disfavoured mating role in order to achieve access to their favoured role, are less widespread than initially though. The final section explores the idea that simultaneous hermaphroditism should enhance selection on postcopulatory mate choice and sperm discrimination mechanisms, including harmful male mating strategies. Support for this prediction remains limited to date, calling for much broader empirical quantifications of the fitness costs and benefits associated with hermaphrodite mating strategies.
330
Nils Anthes
12.1 Introduction Although reproduction represents a generally cooperative act between males and females, there are numerous components of sexual interactions over which the interests of two partners may actually diverge. Sexual conflict is known to occur over traits such as mating frequency, remating with novel mates, the number, size or sex ratio of offspring, and parental care (Arnqvist and Rowe 2005, see also Kempenaers and Schlicht this volume, Schneider and Fromhage this volume). The divergence in evolutionary trait optima underlying such conflicts traces back to anisogamy as the defining difference between the sexes, and may vary with traits such as gamete replenishment rates or the costs and benefits associated with mate search and parental care (Kokko and Jennions 2008). In a very simplistic view, it may appear that sexual conflict occurs because sexual partners (= males and females) inherently pursue different interests. Whilst this logic seems to fit when looking at prime model systems for behavioural
a
b
Courtship & competition
Competition
... & cooperation
Sexual conflict ...
& cooperation
n tio eti mp Co
Sexual conflict
p
Competition
Courtship & competition
Fig. 12.1 Reproductive interactions in separate sex animals (a) and hermaphrodites (b). Shared reproduction between males and females (a) can show components of both sexual conflict and sexual cooperation. The same applies to hermaphrodites (b), but there is additional scope for intrasexual competition between the two male functions (and the two female functions) of both mates. These interactions may further be affected by the intra-individual trade-offs in resource allocation.
Mate choice and reproductive conflict in simultaneous hermaphrodites
331
ecology in mammals, birds or insects, the analogy takes an interesting twist when applied to simultaneous hermaphrodites, where individuals express male and female sex at the same time (BOX 12.1; referred to as ‘hermaphrodites’ throughout). In these animals, mating partners do not differ in their sex (both are hermaphrodites), meaning that mates are more equal to each other than is the case in species with separate sexes. One may argue that this similarity between mates favours mutualistic reproduction, as perhaps indicated by the primarily bi-directional (reciprocal) sperm transfer exhibited by most hermaphrodites (Michiels 1998). Yet, a closer look at hermaphrodite mating reveals that individuals are involved in a rather complicated set of intraand inter-sexual interactions (Fig. 12.1).
Table 12.1 Intrinsic differences between separate sex animals and simultaneous hermaphrodites. This overview focuses on mechanisms that affect reproductive behaviour (modified from Michiels 1998). Mechanism / trait
Separate sex animals
Simultaneous hermaphrodites
Self fertilisation
Inexistent
Facultative, primarily at low densities
Sex-specific gene expression
Prevalent (e.g. via sex chromosomes)
Impossible, restricting sexually dimorphic trait optimisation and ‘masking’ of sexually antagonistic alleles.
Sexual roles during mating
Pre-defined
Preferences for one particular mating role can generate conflict over mating roles.
Paternal care / nuptial gifts
Widespread strategies that increase paternal reproductive success
Largely absent, presumably because investment in own female reproduction pays off more than investment in paternal offspring for which there is no fertilisation guarantee.
Sex allocation
Rare deviations from 1:1 sex ratio (e.g. under local mate competition); Sex ratio adjustments take effect only in next generation
Resource allocation to male and female reproduction can be adjusted ad hoc to environmental variation.
Male mate choice
Present
Perhaps more prevalent: ‘female function’ offers a profitable alternative investment strategy, making ‘sperm dumping’ maladaptive.
332
Nils Anthes
BOX 12.1 Hermaphroditism and its evolution Hermaphroditism defines the expression of male and female sex (i.e., sperm and egg production) in a single individual. Depending on whether both sexes are functional successively or synchronously, we distinguish sequential and simultaneous hermaphrodites, respectively. Sequential hermaphroditism is favoured in systems with substantial sex-differences in the size-fecundity relationship (Ghiselin 1969, Warner 1975). A classic example are haremic fish, where large males can monopolize multiple small females, favouring size-dependent sex change from female to male (Munday et al. 2006). Simultaneous hermaphroditism, being the focus of this chapter, occurs in all major animal clades except insects and vertebrates other than fish (Fig. 12.2; Ghiselin 1969, Michiels 1998, Jarne and Auld 2006). Phylogenetic analyses indicate that simultaneous hermaphroditism represents the ancestral state among animals (Iyer and Roughgarden 2008, but see Ghiselin 1969), followed by repeated transitions between simultaneous hermaphroditism and gonochorism (Eppley and Jesson 2008). Prevailing explanations for the adaptive significance of simultaneous hermaphroditism date back to Tomlinson (1966), Ghiselin (1969), and Charnov et al. (1976), who identified ‘low density’ as a prime condition favouring simultaneous hermaphroditism. Low densities can arise for a variety of reasons, including small or highly structured populations (as in internal parasites), restricted mobility, poor mate-searching capacity, or otherwise rare mate encounters (Puurtinen and Kaitala 2002). In all these cases, individuals benefit if every encounter with a conspecific individual allows outcrossing. Self-fertilisation remains an ‘emergency option’ if no mate is acquired within a reasonable period of time (Charlesworth and Charlesworth 1987, Jarne and Auld 2006), leading to so-called ‘delayed selfing’ (Tsitrone et al. 2003). Under a paradigm of adaptive evolution, one would expect animals to express the reproductive mode that maximises fitness under the current environmental and social conditions. While this type of adaptive flexibility is approached in broadcasting invertebrates with their simple reproductive structures, internal fertilisation and complex reproductive morphologies as present, for example, in gastropods seem to restrict flexibility. Such constraints may explain why whole clades maintain an apparently ‘maladaptive’ reproductive mode, as is the case with simultaneous hermaphroditism under high population densities (Mank et al. 2006, Michiels et al. 2009).
Mate choice and reproductive conflict in simultaneous hermaphrodites
333
Hermaphroditism predominant minority occasional / absent
Fig. 12.2 Schematic view of the distribution of simultaneous hermaphroditism across major animal clades. The tree represents a reduced version of the composite eukaryote phylogenetic tree in Eppley and Jesson (2008). Data modified from Michiels (1998).
334
Nils Anthes
BOX 12.2 Hermaphrodite ‘model systems’ Current knowledge about the evolutionary ecology of hermaphrodite reproductive behaviour has accumulated from a diverse range of organisms. Depending on the research context, a number of animal groups have proven particularly useful study systems, and I briefly allude to those receiving recent emphasis below (Fig. 12.3). Sex allocation theory for simultaneous hermaphrodites tackles the ultimate and proximate factors that influence the proportional division of reproductive resources between male and female function (Charnov 1982). It has stimulated observational and experimental work in a long list of organisms (reviewed in Schärer 2009). The perhaps most profound advances in recent years are due to flourishing research in a small intertidal flatworm, Macrostomum lignano. This species allows non-invasive quantification of sex allocation and provides access to a suite of molecular, developmental and histological techniques (Ladurner et al. 2005). Ongoing research investigates the genetic basis for sex allocation, its connection with mating behaviour (Janicke and Schärer 2009), and its evolutionary trajectories in response to social and environmental variation. The idea that simultaneous hermaphrodites often face conflicts over mating roles (Charnov 1979) has triggered extensive research on ‘egg trading’ in external fertilisers such as serranid fish Serranus and polychaete worms Ophryotrocha (recently Sella and Ramella 1999, Sella and Lorenzi 2000, Petersen 2006, Crowley and Hart 2007) and on ‘sperm trading’ in internal fertilisers such as flatworms, earthworms, and gastropods (recently Anthes et al. 2005, Jordaens et al. 2005, Koene and Ter Maat 2005, Facon et al. 2008). Studies on these and many other species have also tackled questions regarding mate choice criteria, costs and benefits of polyandry, pre- and postcopulatory sexual selection, and physiological partner manipulation (reviews: Leonard 1991, 2006; Baur 1998, Michiels 1998, Jordaens et al. 2007). The option for self-fertilisation is another characteristic specific to simultaneous hermaphrodites. The evolutionary significance of selfing, in addition to factors determining the position of species along the selfing-outcrossing continuum, have been studied primarily in facultatively selfing freshwater molluscs, in particular Biomphalaria glabrata, Physa acuta and Lymnaea spp. (e.g. Escobar et al. 2007, Tian-Bi et al. 2008). The future development of a few of the above-mentioned species into model systems for the evolutionary ecology of hermaphrodite reproduction will provide insights into the underlying mechanisms. At the same time, the field has always drawn from novel insights gained by looking at a great diversity of study systems. To this end, our knowledge is still incomplete for a range of taxonomic groups, calling for further work on currently underrepresented taxa with often intriguing reproductive strategies such as leeches, gastrotrichs, or arrow worms.
Mate choice and reproductive conflict in simultaneous hermaphrodites a)
b)
c)
d)
f)
335
e)
g)
Fig. 12.3 A gallery of classic hermaphroditic study systems: the ‘sex allocation model’ Macrostomum lignano (a, photo © Lukas Schärer), body-piercing earthworms Lumbricus terrestris (b, photo © Nico K. Michiels), the sperm trading sea slug Chelidonura hirundinina (c, photo © Nils Anthes), the penis-fencing flatworm Pseudoceros bifurcus (d, photo © Nico K. Michiels), the dart-shooting garden snail Cornu aspersum (Helix aspersa) (e, photo © Joris M. Koene and Ronald Chase), and two egg traders, the polychaet worm Ophryotrocha diadema (f, photo © Gabriella Sella), and the reef fish Serranus tabacarius (g, photo © Mary K. Hart).
The interplay between individual sex allocation, intra-sexual competition and reciprocal mate choice may in fact generate substantial sexual conflict and favour the evolution of harmful mating strategies even more than is known from separate sex organisms.
336
Nils Anthes
The effect of simultaneous hermaphroditism on the evolution and mechanisms of reproductive behaviour is thus anything but straightforward. In this chapter, I explore how hermaphroditism may lead to sexually antagonistic interactions, and how these can be solved or avoided (Table 12.1). The chapter develops along three basic elements of reproductive behaviour: pre-copulatory mate assessment and choice, sexual interactions during mating, and post-copulatory selection and manipulation. Throughout, I highlight the diversity in hermaphrodite reproductive strategies by referring to findings in a diverse array of study systems (BOX 12.2).
12.2 Pre-copulatory mate assessment and choice Charles Darwin argued that simultaneous hermaphrodites would not exhibit mate assessment or mate choice, primarily because sexual dimorphism cannot be expressed and because ‘lower’ invertebrates would lack the ‘mental powers’ to engage in ‘mutual rivalry’ (Darwin 1871:321). Indeed, frequent mating as seen in many hermaphroditic animals may convey the impression of indiscriminate sexual interactions. For example, Aplysia sea slugs tend to form large mating aggregations where multiple individuals form mating chains in which each individual copulates in both sexual roles with two different partners (Pennings 1991). Yet, frequent mating alone does not prove the absence of mate choice, which can involve very subtle cues to generate non-random mating. The sections below therefore explore the capacity of hermaphrodites to display precopulatory courtship as well as mate choice from both female and male perspectives.
12.2.1 Size-dependent mate choice When the costs of insemination are non-trivial and fecundity increases with size, animals are expected to preferentially inseminate partners of equal or larger body size because small partners will produce fewer (if any) eggs. Substantial variation in adult size, for example in systems with indeterminate growth (e.g. molluscs or flatworms), is thus considered to favour size-dependent mate choice (DeWitt 1996). The size-fecundity relationship, and thus the benefits of size-dependent mate choice, further increase when larger animals invest proportionally more resources into eggs (rather than sperm), as predicted by sex allocation theory (Klinkhamer et al. 1997, Angeloni et al. 2002, Cadet et al. 2004) and confirmed empiri-
Mate choice and reproductive conflict in simultaneous hermaphrodites
337
cally (Vizoso and Schärer 2007). Size-dependent mate choice may be manifested via three pathways, and I briefly review supporting and conflicting evidence below. First, size-dependent mate choice may affect the within-pair decision over mating roles. An agreement over mating roles is primarily necessary in species with unilateral matings, where one individual acts as male and the other as female only. Theory then predicts the larger partner to preferentially take the female role. Mating patterns that conform to this prediction have been found in sea hares Aplysia spp. (Otsuka et al. 1980, Angeloni and Bradbury 1999), freshwater snails Physa spp. (DeWitt 1996, Ohbayashi-Hodoki et al. 2004, but see Dillen et al. 2008) and Helisoma trivolis (Norton et al. 2008), the land snail Achatina fulica (Tomiyama 1996), and the sea slug Chelidonura sandrana (Sprenger et al. 2009). Yet, partner discrimination by body size is all but universal (e.g. SwitzerDunlap et al. 1984, Peters and Michiels 1996a, Koene et al. 2007), and may be absent in particular in species where substantial investment in mate searching makes mate rejection too costly to be advantageous (Baur 1992). Second, in species with bi-directional (= reciprocal) mating, a preference to inseminate larger individuals ultimately results in pair formation between similar-sized individuals. This generates a positive correlation between the body sizes of mating individuals across the population, a pattern known as size-assortative mating. Assortative mating is known from separate-sex animals (Crespi 1989, Rowe and Arnqvist 1996) but should be even more widespread in hermaphroditic populations (Ridley 1983): Here, any preference for larger partners exhibited via one sex function automatically acts reciprocally between partners, whereas both males and females must show a preference for larger partners for size-assortative mating to spread in separate-sex species. Contrary to this prediction, evidence for positive size-assortment in hermaphrodites remains ambiguous: Some studies found positive relationships between partner body sizes in field and laboratory populations of earthworms, limpets, and molluscs (Crozier 1917, Tomiyama 1996, Yusa 1996, Angeloni and Bradbury 1999, Michiels et al. 2001, Angeloni 2003, Angeloni et al. 2003, Monroy et al. 2005, Pal et al. 2006), but most of these correlations were rather weak. Several other studies failed to detect any mating patterns that are consistent with sizeassortative mating (reviewed in Chaine and Angeloni 2005, Koene et al. 2007). Hence, the prevalence and biological relevance of size-assortative mating in hermaphrodites appears lower than expected. Finally, the assessment of a partner’s body size may not affect pair formation per se, but rather lead to prudent male mating effort, where individuals donate larger ejaculates to more fecund partners (Wedell et al. 2002). This effect has been nicely demonstrated in the earthworm Eisenia
338
Nils Anthes
Copulation (mutual penis insertion)
‘Partner screening’
Positioning of gonopores ‘Sandwich posture’
Fig. 12.4 Mating pattern in the flatworm Dugesia gonocephala. Pre-copulatory partner screening and the flattened sandwich posture serve mutual size-assessment. Copulation only follows when partners closely match in size (modified from Vreys and Michiels 1997 with permission from the Royal Society of London).
andrei, where individuals approximately double their ejaculate size when inseminating a partner with twice their body mass (Velando et al. 2008). Similarly, several opisthobranch sea slugs prolong insemination, and thus likely transfer more sperm, when mating with large partners (Angeloni 2003, Michiels et al. 2003, Anthes et al. 2006a). As with the above two mechanisms, prudent male mating should only evolve if this discriminatory behaviour really pays off. For example, if mating rates are low and competition among rival sperm is weak, strategic sperm allocation may not be favoured; this could explain its absence in snails such as Arianta arbustorum and Succinea putris (Baur et al. 1998, Baminger et al. 2000, Jordaens et al. 2005, Dillen et al. 2008). The proximate mechanisms employed by hermaphrodites to assess partner body size have to date received little attention. However, it is known that the parasitic cestode Schistocephalus solidus actively searches large partners using tactile and/or chemical cues, a behaviour that should ultimately also result in size-assortative mating (Lüscher and Wedekind 2002). An intriguing tactile mechanism for size assessment and mate choice has been proposed for the flatworm Dugesia gonocephala (Fig. 12.4): during pre-copulatory contact, prospective mates completely stretch
Mate choice and reproductive conflict in simultaneous hermaphrodites
339
out their body while laying on top of each other (Vreys and Michiels 1997). Even though the receptive pathway remains unknown, this behaviour apparently serves to estimate the partner’s body surface area relative to own body size. Flattening is more likely followed by copulation when partners are similar in body size, whereas dissimilar pairings are interrupted more frequently. 12.2.2 Mate choice for reduced sperm competition Many hermaphrodites are capable of storing allosperm for prolonged periods (Baur 1998), such that sperm from multiple donors may compete for access to unfertilised eggs. The mating history of a putative partner can therefore become a relevant mate choice criterion, in particular from a ‘male’ perspective. A very illustrative example comes from the opisthobranch, Aeolidiella glauca, which deposits spermatophores on the partner’s skin and thus makes recent mating externally visible (Haase and Karlsson 2004). For several days, the presence of a spermatophore reliably signals to putative novel partners that their sperm will be exposed to competition with sperm stored from the previous copulation. In accordance with the expectation that individuals preferentially inseminate previously unmated partners, spermatophore-carrying slugs are rejected more frequently during pre-copulatory interactions than individuals that had the spermatophore experimentally removed (Haase and Karlsson 2004). Most hermaphrodites do not externally deposit spermatophores, but inseminate their partner. As a result, their mating history is not externally visible. Even among such systems, some studies have found individuals to more eagerly copulate with previously unmated partners (Michiels and Bakovski 2000, Anthes et al. 2006a). This indicates the existence of subtle cues that reveal a partner’s mating history, possibly involving tactile receptors in the male copulatory organ that detect the presence of a rival’s ejaculate in the female genital tract. Another option involves chemical cues that could signal previous contact with other mates (Koene and Ter Maat 2007). Clearly more research is needed to reveal the underlying mechanisms. Rather than completely rejecting a previously mated partner, animals may instead strategically adjust their male mating effort to the perceived intensity of sperm competition. Sperm competition models predict that ejaculate sizes should be small when inseminating a virgin partner, reach a maximum when inseminating a partner where the own ejaculate will compete with sperm from a single previous donor, and successively decrease thereafter (Wedell et al. 2002). Concordant with these models, earth-
340
Nils Anthes
worms, Eisenia fetida, approximately double their ejaculate size when inseminating a once mated partner compared to a virgin (Velando et al. 2008). This could be beneficial because mate encounters are frequent in this species and male resources therefore limited. No such adjustment of male mating effort occurs in the landsnail, Arianta arbustorum, where individuals donate sperm independent of partner mating history (Baur et al. 1998) or the actual risk of sperm competition (Locher and Baur 2000). A. arbustorum typically occurs at rather low population densities and only copulates a few times per season, providing a possible explanation for why male choosiness has apparently not evolved. An individual’s mating behaviour may vary also with own mating history. In the freshwater snail, Physa acuta, individuals that obtain a novel mating opportunity after sexual isolation preferentially assume the female mating role (Facon et al. 2007). This is consistent with theory that predicts a preference for the female mating role after periods of sexual isolation because of allosperm depletion. Receiving an ejaculate therefore ensures fertility and maximises immediate fitness benefits (Anthes et al. 2006b). Such ultimate factors may, however, be offset by proximate factors that more directly affect mating propensity. In two pulmonate snails, Lymnaea stagnalis and Succinea putris, it is the male (rather than female) motivation that increases after sexual isolation. In these species, sexual motivation is linked to the filling status of the seminal fluid producing prostate gland (Koene and Ter Maat 2005, Dillen et al. 2008). With the prostate gland depleted after mating, male mating drive remains low for several days, whereas copulations in the female role are still readily accepted despite full allosperm stores. The male motivational effect in these species may have an intriguing consequence for population operational sex ratios: Assuming that male copulations are typically followed by an unreceptive period of several days, whereas female mating motivation is maintained after sperm receipt, populations should on average contain more individuals that are receptive in their female function. The resultant female-biased operational sex ratio could limit access to ‘males’ for receptive ‘females’, possibly leading to sex role reversal as to date only known from separate-sex organisms (e.g. Berglund and Rosenqvist 2003). 12.2.3 Mate choice for relatedness and immune function Inbreeding often confers deleterious effects to offspring through the expression of recessive diseases or reduced genetic diversity at immunerelevant loci (such as MHC). Mate choice for the genetic quality of a partner should therefore be highly beneficial. A corresponding picture emerges
Mate choice and reproductive conflict in simultaneous hermaphrodites
341
from studies in freshwater snails Physa. Individuals from French P. acuta populations increasingly reject mating opportunities along the gradient from cross population, through within population to sib mating (Facon et al. 2006). American P. gyrina discriminate most strongly against outbreeding across populations (McCarthy 2004). Together, these studies indicate a preference for ‘intermediate outbreeding’ (McCarthy and Sih 2008), which provides a sensitive balance between the maintenance of genetic diversity and the disruption of beneficial genotypes. In both species, choosy behaviour regarding relatedness was only observed for matings in the female (but not the male) mating role. The female role is also the one that primarily suffers from the rather substantial inbreeding depression in this species (Jarne et al. 2000). Mate discrimination thus seems to associate with the role that pays the highest cost of ‘wrong choices’. The absence of inbreeding avoidance in other species could have one of several alternative reasons. First, the deleterious effects of sib-mating may be too weak to afford the costs of mate discrimination, and instead be offset by the inclusive fitness benefit that is accrued from incestuous mating (Kokko and Ots 2006). Data consistent with this idea have been reported from the landsnail Arianta arbustorum (Baur and Baur 1997). Second, deleterious alleles may have already been successfully purged, removing the genetic load of inbreeding. Inbreeding may then yield even higher fitness than outbreeding, leading to a preference for sib-matings as documented in the intestinal parasitic cestode Schistocephalus solidus (Schjørring and Jäger 2007). Finally, even in cases where inbreeding is costly, life-history strategies other than mate choice may sufficiently avoid such events. A concordant example comes from the freshwater flatworm Schmidtea polychroa, where efficient dispersal makes encounters between siblings so unlikely that mechanisms for kin recognition and selective mating seem to be obsolete (Peters and Michiels 1996b). In simultaneous hermaphrodites, mate choice for relatedness extends to the option of self-fertilisation as the far end of the ‘relatedness-continuum’ (Jarne and Charlesworth 1993; Jarne and Auld 2006). Selfing offers some intriguing options for the sperm recipient. For example, following mating with a ‘low quality’ partner (say, with an incompatible genetic make-up), the fitness costs of self-fertilisation may be lower than those of outcrossing. Even though not yet tested explicitly, work on the tapeworm Schistocephalus solidus indeed indicates that mate identity affects the degree of selfing, where selfing rates are higher after pairings that involved more conflict between partners (Lüscher and Milinski 2003). Selfing may thus not only be an emergency option when facing allosperm depletion, but can also be considered as a component of an individual’s reproductive strategy whenever inbreeding depression is not too severe. Such ‘strategic selfing’
342
Nils Anthes
would obviously not be in the interest of a previous sperm donor, generating a conflict load over selfing between partners (Bedhomme et al. 2009). Mate discrimination based on genetic traits similarly applies to specific heritable traits such as parasite resistance. Again, mate discrimination primarily relates to the sex function that takes the costs of wrong decisions. For example, genotypes of the snail Biomphalaria glabrata resistant or susceptible to infection with the castrating parasite Schistosoma mansoni mate indiscriminately in both mating roles with uninfected partners, but resistant genotypes refuse matings in the female role with infected partners (Webster et al. 2003, Webster and Gower 2006). Parasites that only weakly depress reproductive success or performance seem to have only limited impact on mating behaviour, as documented for Monocystisinfections of the earthworm Lumbricus terrestris (Field et al. 2003, Field and Michiels 2005). As with body size recognition, we currently have only vague ideas about the mechanisms involved in the detection of relatedness or parasite susceptibility. In the cestode Schistocephalus solidus, mate choice experiments that prevented physical contact between partners implicated chemical cues as informative agents indicating relatedness (Schjørring 2009). Similarly, chemical compounds in the mucous or shell have been suggested to be involved in the detection of resistance status in Biomphalaria glabrata (Webster et al. 2003). Facon et al. (2006) found no evidence that relatedness affected pre-mating behaviour and mucous-trail following in Physa acuta. This indicates that recognition is not associated with chemical cues in the mucous but may rather occur during penis intromission or via other contact signals.
12.3 Conflicts over mating roles and conditional reciprocity While the sexual roles during mating are inherently determined in copulations between males and females, there are three possible combinations for simultaneous hermaphrodites: act in both sex roles, act male only (with the partner acting female), and vice versa. Conflict over mating roles defines situations where two prospective mates disagree over the choice of mating roles for subsequent copulation (Wethington and Dillon 1996, Anthes et al. 2006b). It occurs whenever two individuals prefer incompatible mating roles, for example if both intend to mate in the female but not in the male role (Michiels 1998, Fig. 12.5). Several outcomes of this conflict of interest are conceivable. First, one individual accepts (or is forced into) the less
Insist on ♀ role
Unilateral No conflict
Unilateral No conflict
Conflict over mating roles
Accept ♂ and ♀ role
Unilateral No conflict
Reciprocal No conflict
Unilateral No conflict
Insist on ♂ role
Hermaphrodite 2
Mate choice and reproductive conflict in simultaneous hermaphrodites
Conflict over mating roles
Unilateral No conflict
Unilateral No conflict
Insist on ♂ role
Accept ♂ and ♀ role
Insist on ♀ role
343
Hermaphrodite 1
Fig. 12.5 Scheme illustrating the occurrence of conflicts over mating roles between two prospective hermaphroditic mating partners.
preferred role, resulting in unilateral matings. Second, no mating takes place because no consent is achieved during pre-copulatory ‘negotiation’. Finally, the dilemma is solved if both partners accept mating in the less preferred role and this also guarantees access to their preferred role. Such ‘cooperative’ behaviour would result in balanced reciprocal mating. The last scenario, where individuals reciprocate in the less preferred role in order to obtain access to the preferred role, has been coined trading, or conditional reciprocity (Leonard and Lukowiak 1984). The currency used for trading can be either type of gamete. Egg trading has been experimentally assessed in externally fertilising polychaete worms of the genus Ophryotrocha (Sella 1985, Sella et al. 1997; Fig. 12.3) but to date received most attention in serranid sea basses (details in Fischer 1984, Petersen 1995, 2006; Fig. 12.3). In the final hours before dusk, these hermaphroditic fish engage in alternated bouts of spawning. A first individual releases a small parcel of eggs into the water to be fertilised by its male acting partner. Thereafter, roles are changed repeatedly until both individuals have released and fertilised a balanced number of egg parcels. This behaviour resembles a tit-for-tat game of strategy, where each individual only offers costly eggs when the partner follows suit. The alternative strategy would be very risky: An individual releasing all its eggs in a single go is prone to cheating. Its partner may just fertilise these eggs and leave without offering an own batch of eggs, rather seeking another ‘cheap’ male mating opportunity. Hence, repeated alternation of sex roles assures that
344
Nils Anthes
each partner takes a fair share in both male and female reproduction. Interestingly, egg trading strategies vary strikingly even between closely related species. Evolutionary stable strategy models indicate that this variation may be driven by differences in local conditions, such as mating group size, population density, and predation risk (Crowley and Hart 2007). In sperm trading, it is the male gametes that are exchanged conditionally between partners. Sperm trading is primarily expected in internal fertilisers (Leonard and Lukowiak 1984) where fertilisation is under female control. This makes the ‘fertilisation game’ much more subtle than in egg traders: Only sperm exchange is directly connected to mating and thus verifiable. Eggs, in contrast, are not transferred or offered, such that a male-acting individual has no honest information regarding fertilisation success. Longterm sperm storage, multiple mating, and the presence of sperm digestion organs in many hermaphrodites make male fertilisation success very unpredictable. Hence, even though hermaphrodites are expected to primarily mate in order to donate rather than to receive sperm (Charnov 1979, but see opposite prediction by Leonard 1991), sperm donors should remain prudent about their sperm allocation. By donating sperm only to partners that return this investment, individuals at least (i) ensure own fertility, (ii) obtain a potential ‘repayment’ for their risky ejaculate investment (via resources available for digestion), and (iii) acquire possibly informative signals about the partner’s quality or condition (Landolfa 2002, Anthes et al. 2005). Following the establishment of the concept of sperm trading based on observations in the sea slug Navanax inermis (Leonard and Lukowiak 1984), many follow-up studies found mating patterns that were consistent with this mechanism (reviewed in Anthes et al. 2006b). However, while many reciprocally mating hermaphrodites indeed appear like engaging in a balanced sexual trade, pure behavioural patterns may also occur as a simple by-product of the partners’ mutual willingness to donate and receive sperm and are thus not by themselves sufficient criteria to define conditional reciprocity (Anthes et al. 2006b). For example in the snail, Physa actua, non-random alternation of mating roles is the result of the individual strategy to alternate sex roles between successive matings. Reciprocation then often occurs with novel partners, and does not involve the conditional nature of sex role alternation between two mates that is required for trading (Facon et al. 2007, 2008). Likewise, in the freshwater snail, Lymnaea stagnalis, serial reciprocity with the same partner only occurs when snails had been sexually isolated and thus display elevated male mating motivation (Koene and Ter Maat 2005). This indicates that serial reciprocity is a product of sexual motivation, not of conditionality.
Mate choice and reproductive conflict in simultaneous hermaphrodites a)
345
b)
(ii)
(i)
(iii)
g
T-focal T-cheater
(iv)
C-focal C-partner
p 57 T-pairs
51 C-pairs
Fig. 12.6 Mating cycle (a) and experimental treatment (b) for testing sperm trading in the sea slug Chelidonura hirundinina. Initial body contact (i) is followed by pre-copulatory entwining (ii) and unilateral or reciprocal penis insertion (p) (iii). This cycle is multiply repeated until one partner deserts (iv). In the experiment (b), the sperm groove (violet) transporting ejaculate parcels from the gonopore (g) to the penis was cauterised in imposed ‘cheaters’. All other individuals received a sham-treatment (red dots). The study measured how focal slugs responded to not receiving sperm in the treatment group (T) relative to the control group (C). Reprinted from Anthes et al. (2005) with permission from Elsevier.
Given that sperm trading should ultimately serve to balance the amount of sperm exchanged between partners, between-partner correlations in ejaculate sizes have been considered a second indicator for this mating strategy. A corresponding pattern has been found in the freshwater planarian, Dugesia gonocephala, which closely balances sperm amounts during mutual penis intromission and preparation of the spermatophore (Vreys and Michiels 1998). Interestingly, in the closely related Schmidtea polychroa, sperm amounts are not balanced between partners (Michiels and Bakovski 2000), but instead vary with the size of selfsperm stores of the sperm donor (Michiels and Streng 1998), again indicating individually optimised strategies rather than a conditional ‘agreement’ between partners. Similarly, studies in several molluscs failed to find correlations in ejaculate sizes between partners (Baur et al. 1998, Jordaens et al. 2005), indicating that trading of sperm amounts may in fact be rather rare among simultaneous hermaphrodites. Conditionality as the central component of trading (Leonard and Lukowiak 1984) requires that attempts to cheat (by avoiding the less preferred
346
Nils Anthes
role) are punished by the cheated individual. Recent manipulative studies could confirm that sperm exchange can indeed be conditional in internal fertilisers. In the sea slug Chelidonura hirundinina (Fig. 12.3), multiple bouts of reciprocal and unilateral sperm transfer highly synchronize mating outcomes between partners (Putz et al. 2008) and are suggestive of sperm trading. In an experiment disabling sperm transfer in a subset of individuals to generate ‘cheaters’ in the male mating role (Fig. 12.6), sham-treated focal slugs interrupted matings significantly earlier and after fewer sex role alternations when mated to such cheaters than in matings with shamtreated control partners (Anthes et al. 2005). This shows that in this species sperm donation is indeed conditional upon sperm receipt, and matings are interrupted if the partner does not reciprocate. Interestingly, sperm trading is not universal among closely related species. A congener, Chelidonura sandrana, showed no indications for conditional sperm exchange when exposed to experimental cheaters (Anthes and Michiels 2005). Combined with the above overview on studies failing to provide support for trading, the currently available datasets suggest that trading occurs only in a limited number of systems, rather than being a prevalent mating strategy among simultaneous hermaphrodites as initially expected (Axelrod and Hamilton 1981, Leonard and Lukowiak 1984, Michiels 1998).
12.4 Male harm and post-copulatory partner manipulation 12.4.1 Male harm Male harm occurs when male-male competition gives rise to traits that provide a male fertilisation advantage but also impose collateral or intentional damage upon the female mating partner. Even though widespread among separate sex animals (Johnstone and Keller 2000, Arnqvist and Rowe 2005, Lessells 2006), recent models predict that male harm even more likely evolves in simultaneous hermaphrodites and takes more extreme forms (Michiels and Koene 2006, Preece et al. 2009). The underlying reason is that – according to these models – hermaphrodites can accept matings that are costly for the female function as long as this fitness loss is at least outweighed by the expected paternal success through mating in the male function. Clear evidence for male harm in hermaphrodites is still scarce, and many studies did not detect relevant fitness costs of mating behaviours that look rather damaging at first sight (e.g. dart-shooting: Chase and Vaga 2006 and further details below). Nevertheless, support for manipulative male mating strategies with damaging side-effects for the partner has re-
Mate choice and reproductive conflict in simultaneous hermaphrodites
347
cently begun to emerge. One example is traumatic sperm injection, which often inflicts substantial damage to the female function. This insemination strategy is rare among separate sex organisms (Siva-Jothy 2006), but widespread among hermaphroditic sea slugs, flatworms, or leeches. For example, the externally applied ejaculates of polyclad flatworms (Pseudobiceros bedfordi, Pseudoceros bifurcus, Fig. 12.3) contain aggressive substances that dissolve up to 50% of a receiver’s body tissue while sperm actively travel towards the fertilisation pouches (Michiels and Newman 1998, Arnqvist and Rowe 2005). Evidence for fitness costs of hypodermic injections comes from the sacoglossan sea slug, Alderia willowi. Here, individuals that receive sperm via hypodermic injection produce 30-50% fewer eggs than non-mated individuals that lay unfertilised egg masses (Smolensky et al. 2009). 12.4.2 Physiological partner manipulation A second category of partner manipulation concerns the transfer of manipulative allohormones (Koene 2005), referring to bioactive substances that interfere with postcopulatory processes such as fertilisation, remating, or resource allocation to female function (Michiels 1998, Bedhomme et al. 2009, Schärer and Janicke 2009). Manipulative ejaculate components such as the seminal sex peptides in Drosophila (Chapman et al. 1995, Fricke et al. 2009) are well documented for separate sex organisms. Simultaneous hermaphrodites may have particularly easy access to manipulations of the partner’s reproductive physiology: The genes for male and female regulatory substances are present and expressed in each individual. Hence, active compounds that affect the partner’s reproductive system are inherently available and could easily be applied during mating (Koene 2005). The broad role that such mechanisms may play in hermaphrodite mating systems is indicated by the application of gland secretions during mating in diverse systems, including opisthobranch sea slugs (Anthes and Michiels 2007), land slugs (Reise et al. 2007), land snails, and earthworms. The latter two groups provide the best studied examples to date: The garden snail Cornu aspersum is well-known for its dart-shooting behaviour (Fig. 12.3), where sexual partners initiate copulation by shooting a calcareous dart into the partner’s body. Establishing the dart’s function has attracted a series of experimental studies (Koene and Chase 1998a, Koene and Chase 1998b, Landolfa et al. 2001, Rogers and Chase 2001, Evanno et al. 2005). Only recently, Chase and Blanchard (2006) provided compelling evidence that it is indeed the bioactive compounds delivered with the dart’s mucous that increase a dart-shooters paternity. Interestingly, this effect cannot be gen-
348
Nils Anthes
eralised to all dart-shooting snails, with darts having no effect on sperm delivery in Arianta arbustorum (Baminger et al. 2000). Lumbricus terrestris earthworms follow a similar strategy: During reciprocal copulation and sperm transfer (Fig. 12.3), ~40 copulatory setae pierce into the partner’s body and inject secretions of the setal glands (Grove 1925, Koene et al. 2002). Experimental injections have shown that these products increase sperm uptake and delay remating, both of which are in the interest of the sperm donor but may conflict with the interest of the sperm receiver (Koene et al. 2005). Proteomic analysis of the secretions suggest a role for ubiquitin in the manipulative process (König et al. 2006), but its exact functionality remains to be established. 12.4.3 Costs and benefits of multiple mating Despite the potential costs of matings in the female role, many hermaphrodites do not seem particularly reluctant to accept female matings (Mulvey and Vrijenhoek 1981, Baur 1994, Angeloni et al. 2003, Pongratz and Michiels 2003). This implies that multiple mating not only imposes costs on the female-acting partner, but also confers some kind of direct or indirect benefit (Arnqvist and Nilsson 2000). Some pulmonate land snails such as Arianta arbustorum possess complex sperm storage organs with multiple tubules that could serve differential storage and use of sperm that were received from multiple donors (Bojat and Haase 2002). Such control over fertilisation would indeed benefit female interests, but whether or not controlled fertilisation occurs and is beneficial to the female function awaits experimental confirmation (Chen and Baur 1993, reviewed in Baur 2007). In the sea slug Chelidonura sandrana, egg production decreases steadily with female mating rate (Sprenger et al. 2008b). These mating costs are at least partly offset through polyandry: Multiply mated mothers lay larger eggs that hatch larger veliger larvae than monandrous mothers (Sprenger et al. 2008a). This effect was strongest when experimental slugs were exposed to mating rates matching those experienced in the field (Sprenger et al. 2008a), indicating that in this species it is the female function that maintains mating rates near its optimum. Interestingly, the benefits of polyandry in this species do not depend on male identity: Additive genetic sire (= ‘good gene’) effects were absent, indicating that female benefits do not accrue from the genetic quality of male partners (Sprenger et al. 2010). Instead, variation in offspring traits was largely governed by maternal effects, where mothers more or less actively elevate investment per offspring after multiple mating. These slugs therefore possibly follow a bet-hedging strategy, where the production of genetically diverse offspring could re-
Mate choice and reproductive conflict in simultaneous hermaphrodites
349
duce mortality under the unpredictable environmental conditions that larvae will encounter after settlement (Sprenger et al. 2010).
12.5 Perspectives Our current knowledge on the way sexual selection affects the evolution of hermaphrodite reproductive behaviour primarily suffers from a paucity of explicit quantifications of the sex-specific (lifetime) costs and benefits of the diverse mating strategies. It therefore often remains hard to evaluate whether a given behaviour is an expression of sexual mutualism or sexual antagonism. Closing this gap will be a major goal for the near future. Moreover, given that descriptions of hermaphrodite reproductive behaviour remain often based on anecdotal reports, more extensive experimental research on the mechanisms of mate assessment, mate choice, and cryptic post-copulatory mechanisms will substantially complement our picture of sexual selection in these groups. These goals should greatly benefit from ongoing attempts to establish selected hermaphroditic species as model systems for studying the genetics underlying the variation in reproductive strategies.
Ackowledgements I wish to thank Peter Kappeler, Hanna Kokko, Nico K. Michiels, Dennis Sprenger, and one anonymous referee for constructive comments to this chapter, Stuart Pengelley for linguistic corrections, and Mary K. Hart, Joris M. Koene, Nico K. Michiels, Lukas Schärer, and Gabriella Sella for providing the photos of their study pets displayed in Fig. 12.3.
References Angeloni L (2003) Sexual selection in a simultaneous hermaphrodite with hypodermic insemination: body size, allocation to sexual roles and paternity. Anim Behav 66:417-426 Angeloni L, Bradbury JW (1999) Body size influences mating strategies in a simultaneously hermaphroditic sea slug, Aplysia vaccaria. Ethol Ecol Evol 11:187-195 Angeloni L, Bradbury JW, Charnov EL (2002) Body size and sex allocation in simultaneously hermaphroditic animals. Behav Ecol 13:419-426
350
Nils Anthes
Angeloni L, Bradbury JW, Burton RS (2003) Multiple mating, paternity, and body size in a simultaneous hermaphrodite, Aplysia californica. Behav Ecol 14:554-560 Anthes N, Michiels NK (2005) Do ‘sperm trading’ simultaneous hermaphrodites always trade sperm? Behav Ecol 16:188-195 Anthes N, Michiels NK (2007) Precopulatory stabbing, hypodermic injections and unilateral matings in a hermaphroditic sea slug. Biol Lett 3:121-124 Anthes N, Putz A, Michiels NK (2005) Gender trading in a hermaphrodite. Curr Biol 15:R792-R793 Anthes N, Putz A, Michiels NK (2006a) Hermaphrodite sex role preferences: the role of partner body size, mating history and female fitness in the sea slug Chelidonura sandrana. Behav Ecol Sociobiol 60:359-367 Anthes N, Putz A, Michiels NK (2006b) Sex role preferences, gender conflict and sperm trading in simultaneous hermaphrodites: a new framework. Anim Behav 72:1-12 Arnqvist G, Nilsson T (2000) The evolution of polyandry: multiple mating and female fitness in insects. Anim Behav 60:145-164 Arnqvist G, Rowe L (2005) Sexual Conflict. Princeton University Press, Princeton Axelrod R, Hamilton WD (1981) The evolution of cooperation. Science 211:13901396 Baminger H, Locher R, Baur B (2000) Incidence of dart shooting, sperm delivery, and sperm storage in natural populations of the simultaneously hermaphroditic land snail Arianta arbustorum. Can J Zool 78:1767-1774 Baur B (1992) Random mating by size in the simultaneously hermaphroditic land snail Arianta arbustorum: experiments and an explanation. Anim Behav 43:511-518 Baur B (1994) Multiple paternity and individual variation in sperm precedence in the simultaneously hermaphroditic land snail Arianta arbustorum. Behav Ecol Sociobiol 35:413-421 Baur B (1998) Sperm competition in molluscs. In: Birkhead TR, Møller AP (eds) Sperm Competition and Sexual Selection. Academic Press, London, pp 255305 Baur B (2007) Reproductive biology and mating conflict in the simultaneously hermaphroditic land snail Arianta arbustorum. Am Malacol Bull 23:157-172 Baur B, Baur A (1997) Random mating with respect to relatedness in the simultaneously hermaphroditic land snail Arianta arbustorum. Invert Biol 116:294298 Baur B, Locher R, Baur A (1998) Sperm allocation in the simultaneously hermaphroditic land snail Arianta arbustorum. Anim Behav 56:839-845 Bedhomme S, Bernasconi G, Koene JM, Lankinen A, Arathi HS, Michiels NK, Anthes N (2009) How does breeding system variation modulate sexual antagonism? Biol Lett 5:717-720 Berglund A, Rosenqvist G (2003) Sex role reversal in pipefish. Adv Stud Behav 32:131-167 Bojat NC, Haase M (2002) Sperm storage in the simultaneously hermaphroditic land snail Arianta arbustorum. J Zool Lond 258:497-503
Mate choice and reproductive conflict in simultaneous hermaphrodites
351
Cadet C, Metz JAJ, Klinkhamer PGL (2004) Size and the not-so-single sex: disentangling the effects of size and budget on sex allocation in hermaphrodites. Am Nat 164:779-792 Chaine A, Angeloni L (2005) Size-dependent mating and gender choice in a simultaneous hermaphrodite, Bulla gouldiana. Behav Ecol Sociobiol 59:58-68 Chapman T, Liddle LF, Kalb JM, Wolfner MF, Partridge L (1995) Cost of mating in Drosophila melanogaster females is mediated by male accessory gland products. Nature 373:241-244 Charlesworth D, Charlesworth B (1987) Inbreeding depression and its evolutionary consequences. Annu Rev Ecol Syst 18:237-268 Charnov EL (1979) Simultaneous hermaphroditism and sexual selection. Proc Natl Acad Sci USA 76:2480-2484 Charnov EL (1982) The Theory of Sex Allocation. Princeton University Press, Princeton Charnov EL, Bull JJ, Maynard-Smith J (1976) Why be an hermaphrodite? Nature 263:125-126 Chase R, Blanchard KC (2006) The snail’s love-dart delivers mucus to increase paternity. Proc R Soc Lond B 273:1471-1475 Chase R, Vaga K (2006) Independence, not conflict, characterizes dart-shooting and sperm exchange in a hermaphroditic snail. Behav Ecol Sociobiol 59:732739 Chen X, Baur B (1993) The effect of multiple mating on female reproductive success in the simultaneously hermaphroditic land snail Arianta arbustorum. Can J Zool 71:2431-2436 Crespi BJ (1989) Causes of assortative mating in arthropods. Anim Behav 38:9801000 Crowley PH, Hart MK (2007) Evolutionary stability of egg trading and parceling in simultaneous hermaphrodites: the chalk bass revisited. J Theor Biol 246:420-429 Crozier WJ (1917) Evidence of assortive mating in a nudibranch. Proc Natl Acad Sci USA 3:519-522 Darwin C (1871) The Descent of Man and Selection in Relation to Sex. John Muray, London DeWitt TJ (1996) Gender contests in a simultaneous hermaphrodite snail: a sizeadvantage model for behaviour. Anim Behav 51:345-351 Dillen L, Jordaens K, Dieleman W, Backeljau T (2008) Effects of isolation and body size on the mating behaviour of the hermaphroditic land snail Succinea putris. Anim Behav 75:1401-1411 Eppley SM, Jesson LK (2008) Moving to mate: the evolution of separate and combined sexes in multicellular organisms. J Evol Biol 21:727-736 Escobar JS, Epinat G, Sarda V, David P (2007) No correlation between inbreeding depression and delayed selfing in the freshwater snail Physa acuta. Evolution 61:2655-2670 Evanno G, Madec L, Arnaud J-F (2005) Multiple paternity and postcopulatory sexual selection in a hermaphrodite: what influences sperm precedence in the garden snail Helix aspersa? Mol Ecol 14:805-812
352
Nils Anthes
Facon B, Ravigné V, Goudet J (2006) Experimental evidence of inbreeding avoidance in the hermaphroditic snail Physa acuta. Evol Ecol 20:395-406 Facon B, Ravigné V, Sauteur L, Goudet J (2007) Effect of mating history on gender preference in the hermaphroditic snail Physa acuta. Anim Behav 74:14551461 Facon B, Ravigné V, Goudet J (2008) Gender-role alternation in the simultaneously hermaphroditic freshwater snail Physa acuta: not with the same partner. Behav Ecol Sociobiol 62:713-720 Field SG, Michiels NK (2005) Parasitism and growth in the earthworm Lumbricus terrestris: fitness costs of the gregarine parasite Monocystis sp. Parasitology 130:397-403 Field SG, Schirp HJ, Michiels NK (2003) The influence of Monocystis sp infection on growth and mating behaviour of the earthworm Lumbricus terrestris. Can J Zool 81:1161-1167 Fischer EA (1984) Egg trading in the chalk bass, Serranus tortugarum, a simultaneous hermaphrodite. Z Tierpsychol 66:143-151 Fricke C, Wigby S, Hobbs R, Chapman T (2009) The benefits of male ejaculate sex peptide transfer in Drosophila melanogaster. J Evol Biol 22:275-286 Gascoigne T (1993) Stylets, styles and other cuticular extensions of the male duct in the order Sacoglossa (Gastropoda). Boll Malacol 29:139-146 Ghiselin MT (1969) The evolution of hermaphroditism among animals. Q Rev Biol 44:189-208 Grove AJ (1925) On the reproductive processes of the earthworm, Lumbricus terrestris. Q J Microsc Sci 69:245-290 Haase M, Karlsson A (2004) Mate choice in a hermaphrodite: you won’t score with a spermatophore. Anim Behav 67:287-291 Iyer P, Roughgarden J (2008) Dioecy as a specialization promoting sperm delivery. Evol Ecol Res 10:867-892 Janicke T, Schärer L (2009) Determinants of mating and sperm-transfer success in a simultaneous hermaphrodite. J Evol Biol 22:405-415 Jarne P, Auld JR (2006) Animals mix it up too: the distribution of self-fertilization among hermaphroditic animals. Evolution 60:1816-1824 Jarne P, Charlesworth D (1993) The evolution of the selfing rate in functionally hermaphrodite plants and animals. Ann Rev Ecol Syst 24:441-466 Jarne P, Perdieu M-A, Pernot A-F, Delay B, David P (2000) The influence of selffertilization and grouping on fitness attributes in the freshwater snail Physa acuta: population and individual inbreeding depression. J Evol Biol 13:645655 Johnstone RA, Keller L (2000) How males can gain by harming their mates: sexual conflict, seminal toxins, and the cost of mating. Am Nat 156:368-377 Jordaens K, Pinceel J, Backeljau T (2005) Mate choice in the hermaphroditic land snail Succinea putris (Stylommatophora: Succineidae). Anim Behav 70:329337 Jordaens K, Dillen L, Backeljau T (2007) Effects of mating, breeding system and parasites on reproduction in hermaphrodites: pulmonate gastropods (Mollusca). Anim Biol 57:137-195
Mate choice and reproductive conflict in simultaneous hermaphrodites
353
Klinkhamer PGL, de Jong TJ, Metz H (1997) Sex and size in cosexual plants. Trends Ecol Evol 12:260-265 Koene JM (2005) Allohormones and sensory traps: a fundamental difference between hermaphrodites and gonochorists? Invert Reprod Dev 48:101-107 Koene JM, Chase R (1998a) Changes in the reproductive system of the snail Helix aspersa caused by mucus from the love dart. J Exp Biol 201:2313-2319 Koene JM, Chase R (1998b) The love dart of Helix aspersa Müller is not a gift of calcium. J Mollus Stud 64:75-80 Koene JM, Ter Maat A (2005) Sex role alternation in the simultaneous hermaphroditic pond snail Lymnaea stagnalis is determined by the availability of seminal fluid. Anim Behav 69:845-850 Koene JM, Ter Maat A (2007) Coolidge effect in pond snails: male motivation in a simultaneous hermaphrodite. BMC Evol Biol 7:212 Koene JM, Sundermann G, Michiels NK (2002) On the function of body piercing during copulation in earthworms. Invert Reprod Dev 41:35-40 Koene JM, Pförtner T, Michiels NK (2005) Piercing the partner’s skin influences sperm uptake in the earthworm Lumbricus terrestris. Behav Ecol Sociobiol 59:243-249 Koene JM, Montagne-Wajer K, Ter Maat A (2007) Aspects of body size and mate choice in the simultaneously hermaphroditic pond snail Lymnaea stagnalis. Anim Biol 57:247-259 König S, Mehlich A-M, Bullesbach J, Michiels NK (2006) Allohormones in Lumbricus terrestris? Mass spectrometry of the setal gland product indicates possible role of ubiquitin. Invert Reprod Dev 49:103-112 Kokko H, Jennions MD (2008) Parental investment, sexual selection and sex ratios. J Evol Biol 21:919-948 Kokko H, Ots I (2006) When not to avoid inbreeding. Evolution 60:467-475 Ladurner P, Schärer L, Salvenmoser W, Rieger RM (2005) A new model organism among the lower Bilateria and the use of digital microscopy in taxonomy of meiobenthic Platyhelminthes: Macrostomum lignano, n. sp. (Rhabditophora, Macrostomorpha). J Zool Syst Evol Res 43:114-126 Landolfa MA (2002) On the adaptive function of gamete trading in the black hamlet Hypoplectrus nigricans. Evol Ecol Res 4:1191-1199 Landolfa MA, Green DM, Chase R (2001) Dart shooting influences paternal reproductive success in the snail Helix aspersa. Behav Ecol 12:773-777 Leonard JL (1991) Sexual conflict and the mating systems of simultaneously hermaphroditic gastropods. Am Malacol Bull 9:45-58 Leonard JL (2006) Sexual selection: lessons from hermaphrodite mating systems. Integr Comp Biol 46:349-367 Leonard JL, Lukowiak K (1984) Male-female conflict in a simultaneous hermaphrodite resolved by sperm trading. Am Nat 124:282-286 Lessells CM (2006) The evolutionary outcome of sexual conflict. Philos Trans R Soc Lond B 361:301-317 Lüscher A, Milinski M (2003) Simultaneous hermaphrodites reproducing in pairs self-fertilize some of their eggs: an experimental test of predictions of mixedmating and Hermaphrodite’s Dilemma theory. J Evol Biol 16:1030-1037
354
Nils Anthes
Lüscher A, Wedekind C (2002) Size-dependent discrimination of mating partners in the simultaneous hermaphroditic cestode Schistocephalus solidus. Behav Ecol 13:254-259 Mank JE, Promislow DEL, Avise JC (2006) Evolution of alternative sexdetermining mechanisms in teleost fishes. Biol J Linn Soc 87:83-93 McCarthy TM (2004) Effects of pair-type and isolation time on mating interactions of a freshwater snail, Physa gyrina (Say, 1821). Am Malacol Bull 19:4755 McCarthy TM, Sih A (2008) Relatedness of mates influences mating behaviour and reproductive success of the hermaphroditic freshwater snail Physa gyrina. Evol Ecol Res 10:77-94 Michiels NK (1998) Mating conflicts and sperm competition in simultaneous hermaphrodites. In: Birkhead TR, Møller AP (eds) Sperm Competition and Sexual Selection. Academic Press, London, pp 219-254 Michiels NK, Bakovski B (2000) Sperm trading in a hermaphroditic flatworm: reluctant fathers and sexy mothers. Anim Behav 59:319-325 Michiels NK, Koene JM (2006) Sexual selection favours harmful mating in hermaphrodites more than in gonochorists. Integr Comp Biol 46:473-480 Michiels NK, Newman LJ (1998) Sex and violence in hermaphrodites. Nature 391:647 Michiels NK, Streng A (1998) Sperm exchange in a simultaneous hermaphrodite. Behav Ecol Sociobiol 42:171-178 Michiels NK, Hohner A, Vorndran IC (2001) Precopulatory mate assessment in relation to body size in the earthworm Lumbricus terrestris: avoidance of dangerous liaisons? Behav Ecol 12:612-618 Michiels NK, Raven-Yoo-Heufes A, Kleine Brockmann K (2003) Sperm trading and sex roles in the hermaphroditic opisthobranch sea slug Navanax inermis: eager females or opportunistic males? Biol J Linn Soc 78:105-116 Michiels NK, Crowley PH, Anthes N (2009) Accessory male investment can undermine the evolutionary stability of simultaneous hermaphroditism. Biol Lett 5:709-712 Monroy F, Aira M, Velando A, Domínguez J (2005) Size-assortative mating in the earthworm Eisenia fetida (Oligochaeta, Lumbricidae). J Ethol 23:69-70 Mulvey M, Vrijenhoek RC (1981) Multiple paternity in the hermaphroditic snail, Biomphalaria obstructa. J Hered 72:308-312 Munday PL, Buston PM, Warner RR (2006) Diversity and flexibility of sexchange strategies in animals. Trends Ecol Evol 21:89-95 Norton CG, Johnson AF, Mueller RL (2008) Relative size influences gender role in the freshwater hermaphroditic snail, Helisoma trivolvis. Behav Ecol 19:1122-1127 Ohbayashi-Hodoki K, Ishihama F, Shimada M (2004) Body size-dependent gender role in a simultaneous hermaphrodite freshwater snail, Physa acuta. Behav Ecol 15:976-981 Otsuka C, Rouger Y, Tobach E (1980) A possible relationship between size and reproductive behaviour in a population of Aplysia punctata (Cuvier, 1803). Veliger 23:159-163
Mate choice and reproductive conflict in simultaneous hermaphrodites
355
Pal P, Erlandsson J, Sköld M (2006) Size-assortative mating and non-reciprocal copulation in a hermaphroditic intertidal limpet: test of the mate availability hypothesis. Mar Biol 148:1273-1282 Pennings SC (1991) Reproductive behavior of Aplysia californica Cooper: diel patterns, sexual roles and mating aggregations. J Exp Mar Biol Ecol 149:249266 Peters A, Michiels NK (1996a) Do simultaneous hermaphrodites choose their mates? Effects of body size in a planarian flatworm. Freshwater Biol 36:623630 Peters A, Michiels NK (1996b) Evidence for lack of inbreeding avoidance by selective mating in a simultaneous hermaphrodite. Invert Biol 115:99-103 Petersen CW (1995) Reproductive behavior, egg trading, and correlates of male mating success in the simultaneous hermaphrodite, Serranus tabacarius. Environm Biol Fishes 43:351-361 Petersen CW (2006) Sexual selection and reproductive success in hermaphroditic seabasses. Integr Comp Biol 46:439-448 Pongratz N, Michiels NK (2003) High multiple paternity and low last-male sperm precedence in a hermaphroditic planarian flatworm: consequences for reciprocity patterns. Mol Ecol 12:1425-1433 Preece T, Mao Y, Garrahan JP, Davison A (2009) Harmful mating tactics in hermaphrodites. Am Nat 173:632-639 Putz A, Michiels NK, Anthes N (2008) Mating behaviour of the sperm trading hermaphroditic sea slug Chelidonura hirundinina: repeated sex role alternation balances reciprocity. Ethology 114:85-94 Puurtinen M, Kaitala V (2002) Mate-search efficiency can determine the evolution of separate sexes and the stability of hermaphroditism in animals. Am Nat 160:645-660 Reise H, Visser S, Hutchinson JMC (2007) Mating behaviour in the terrestrial slug Deroceras gorgonium: is extreme morphology associated with extreme behaviour? Anim Biol 57:197-215 Ridley M (1983) The Explanation of Organic Diversity. Oxford University Press, Oxford Rogers DW, Chase R (2001) Dart receipt promotes sperm storage in the garden snail Helix aspersa. Behav Ecol Sociobiol 50:122-127 Rowe L, Arnqvist G (1996) Analysis of the causal components of assortative mating in water striders. Behav Ecol Sociobiol 38:279-286 Schärer L (2009) Tests of sex allocation theory in simultaneously hermaphroditic animals. Evolution 63:1377-1405 Schärer L, Janicke T (2009) Sex allocation and sexual conflict in simultaneously hermaphroditic animals. Biol Lett 5:705-708 Schjørring S (2009) Sex allocation and mate choice of selfed and outcrossed Schistocephalus solidus (Cestoda). Behav Ecol 20:644-650 Schjørring S, Jäger I (2007) Incestuous mate preference by a simultaneous hermaphrodite with strong inbreeding depression. Evolution 61:423-430
356
Nils Anthes
Schmitt V, Anthes N, Michiels NK (2007) Mating behaviour in the sea slug Elysia timida (Opisthobranchia, Sacoglossa): hypodermic injection, sperm transfer and balanced reciprocity. Front Zool 4:17 Sella G (1985) Reciprocal egg trading and brood care in a hermaphroditic polychaete worm. Anim Behav 33:938-944 Sella G, Lorenzi MC (2000) Partner fidelity and egg reciprocation in the simultaneously hermaphroditic polychaete worm Ophryotrocha diadema. Behav Ecol 11:260-264 Sella G, Ramella L (1999) Sexual conflict and mating systems in the dorvilleid genus Ophryotrocha and the dinophilid genus Dinophilus. Hydrobiologia 402:203-213 Sella G, Premoli MC, Turri F (1997) Egg trading in the simultaneously hermaphroditic polychaete worm Ophryotrocha gracilis (Huth). Behav Ecol 8:83-86 Siva-Jothy MT (2006) Trauma, disease and collateral damage: conflict in cimicids. Philos Trans R Soc Lond B 361:269-275 Smolensky N, Romero MR, Krug PJ (2009) Evidence for costs of mating and selffertilization in a simultaneous hermaphrodite with hypodermic insemination, the opisthobranch Alderia willowi. Biol Bull 216:188-199 Sprenger D, Anthes N, Michiels NK (2008a) Multiple mating affects offspring size in the opisthobranch Chelidonura sandrana. Mar Biol 153:891-897 Sprenger D, Faber J, Michiels NK, Anthes N (2008b) Natural female mating rate maximizes hatchling size in a marine invertebrate. J Anim Ecol 77:696-701 Sprenger D, Lange R, Michiels NK, Anthes N (2009) The role of body size in early mating behavior in a simultaneous hermaphrodite, Chelidonura sandrana. Behav Ecol Sociobiol 63:953-958 Sprenger D, Lange R, Michiels N, Anthes N (2010) Sources of phenotypic variance in egg and larval traits in a marine invertebrate. Evol Ecol, doi: 10.1007/ s10682-10009-19300-x Switzer-Dunlap M, Meyers-Schulte K, Gardner EA (1984) The effect of size, age, and recent egg laying on copulatory choice of the hermaphroditic mollusc Aplysia juliana. Int J Invert Repr Dev 7:217-225 Tian-Bi Y-NT, N’Goran EK, N’Guetta S-P, Matthys B, Sangare A, Jarne P (2008) Prior selfing and the selfing syndrome in animals: an experimental approach in the freshwater snail Biomphalaria pfeifferi. Gen Res 90:61-72 Tomiyama K (1996) Mate-choice criteria in a protandrous simultaneously hermaphroditic land snail Achatina fulica (Férussac) (Stylommatophora:Achatinidae). J Moll Stud 62:101-111 Tomlinson J (1966) The advantages of hermaphroditism and parthenogenesis. J Theor Biol 11:54-58 Trowbridge CD (1995) Hypodermic insemination, oviposition, and embryonic development of a pool-dwelling ascoglossan (= sacoglossan) opisthobranch: Ercolania felina (Hutton, 1882) on New Zealand shores. Veliger 38:203-211 Tsitrone A, Duperron S, David P (2003) Delayed selfing as an optimal mating strategy in preferentially outcrossing species: theoretical analysis of the optimal age at first reproduction in relation to mate availability. Am Nat 162:318331
Mate choice and reproductive conflict in simultaneous hermaphrodites
357
Velando A, Eiroa J, Domínguez J (2008) Brainless but not clueless: earthworms boost their ejaculates when they detect fecund non-virgin partners. Proc R Soc Lond B 275:1067-1072 Vizoso DB, Schärer L (2007) Resource-dependent sex-allocation in a simultaneous hermaphrodite. J Evol Biol 20:1046-1055 Vreys C, Michiels NK (1997) Flatworms flatten to size up each other. Proc R Soc Lond B 264:1559-1564 Vreys C, Michiels NK (1998) Sperm trading by volume in a hermaphroditic flatworm with mutual penis intromission. Anim Behav 56:777-785 Warner RR (1975) The adaptive significance of sequential hermaphroditism in animals. Am Nat 109:61-82 Webster JP, Gower CM (2006) Mate choice, frequency dependence, and the maintenance of resistance to parasitism in a simultaneous hermaphrodite. Integr Comp Biol 46:407-418 Webster JP, Hoffman JI, Berdoy M (2003) Parasite infection, host resistance and mate choice: battle of the genders in a simultaneous hermaphrodite. Proc R Soc Lond B 270:1481-1485 Wedell N, Gage MJG, Parker GA (2002) Sperm competition, male prudence and sperm-limited females. Trends Ecol Evol 17:313-320 Wethington AR, Dillon RT Jr (1996) Gender choice and gender conflict in a nonreciprocally mating simultaneous hermaphrodite, the freshwater snail, Physa. Anim Behav 51:1107-1118 Yusa Y (1996) The effects of body size on mating features in a field population of the hermaphroditic sea hare Aplysia kurodai Baba, 1937 (Gastropoda: Opisthobranchia). J Moll Stud 62:381-386
Chapter 13
Extra-pair behaviour BART KEMPENAERS AND EMMI SCHLICHT
ABSTRACT In many socially monogamous species, males and females pursue copulations with individuals other than their social mate. The outcome of this behaviour is that broods often contain offspring of mixed paternity. Here, we first show how the frequency of extra-pair paternity varies among species and among populations of the same species, and we discuss how this variation can be explained. We then examine potential costs and benefits of extra-pair behaviour for males and females. Extra-pair behaviour in both sexes might have evolved because it allows males to produce more offspring. Female extra-pair behaviour could also be favoured by selection because it increases female fitness, for example through increased offspring quality. In the third part of this chapter, we consider some of the evolutionary consequences of the occurrence of extra-pair behaviour. In particular, we evaluate how extra-pair behaviour influences the strength of sexual selection.
13.1 Introduction In many sexually reproducing organisms, a single well-timed copulation would in theory be sufficient to fertilise all the eggs in a clutch. However, in reality males and females often copulate much more frequently and they also often mate with more than one partner during a single bout of reproduction. Although such multiple mating or promiscuity comes with some obvious costs, such as increased risk of predation or increased risk of contracting a sexually transmitted disease, it turns out to be extremely common. Hence, we need an explanation for why multiple mating has evolved. In this chapter, we discuss a special case of promiscuity, which can occur in all species where individuals form pairs for breeding (BOX 13.1).
360
Bart Kempenaers and Emmi Schlicht
BOX 13.1 Pair-living and parenting patterns Pair-living or social monogamy is uncommon and unevenly distributed across the animal kingdom, but it does occur in a wide range of taxa among invertebrates (Lorenzi and Sella 2000, Lombardo et al. 2004, Baeza 2008, Beltran and Boissier 2009) and vertebrates (Sefc et al. 2008, Cohas and Allainé 2009, While et al. 2009a). Birds are unusual in that most avian species are socially monogamous (Bennett and Owens 2002). We define extra-pair behaviour as a special case of promiscuity where copulations occur with more mates than are included in the social mating system. How do behavioural ecologists know which individuals form a social pair? The male and female of a pair have social interactions that are linked to reproduction but go beyond what is required for the act of fertilisation. These interactions lead to an association of pair members in space and time, in particular during the female’s fertile period, that is not observed between unpaired individuals (Westneat et al. 1990). For example, in many birds members of a social pair typically engage in behaviours such as prolonged courtship, mate guarding, territory defence, nest building, incubation of the eggs, feeding or protecting the young, and so on. In birds, parenting patterns often reflect the social mating system (Bennett and Owens 2002) and in the majority of species social monogamy goes hand in hand with biparental care. A male of the socially monogamous American robin (Turdus migratorius) feeding the offspring in his nest. Whether he sired those offspring is another issue. Photo © Bruce E. Lyon
Biparental care may be especially common in birds because eggs and offspring need considerable parental investment to survive (Thomson et al. 1998, Tullberg et al. 2002), and male birds can contribute substantially to all parental activities except egg production. Furthermore, a high mortality cost of caring as compared to competing for mates will lead to selection favouring egalitarian sex roles and hence biparental care (Kokko and Jennions 2008). This comes about because different sex roles can cause sex-specific mortality, which may feedback on the availability of mates. Assume that sex roles have diverged a little bit so that females tend to care more than males
Extra-pair behaviour
361
and males are investing more in competing. Further sex role divergence may now be prevented if caring is the more costly activity. This is because females will become rarer as they suffer the higher risk of mortality due to caring, and the mating pool will become more strongly biased towards males. Hence, it will take deserting males longer to find another mate, and despite the higher mortality cost for caring than for competing, caring may become the better option.
An extra-pair mating can be defined as a copulation with an individual that is not the social partner, and it can lead to extra-pair paternity or mixed paternity within a brood or litter. The study of promiscuity and extra-pair behaviour is interesting, not only in itself, but also because promiscuity has several interesting evolutionary consequences. For example, it can help explain variation in the morphology of reproductive organs, in sperm production, sperm size, and sperm motility, in copulation behaviour, or in patterns of parental care. It may also lead to selection that favours behaviours such as mate guarding or male aggression. Finally, extra-pair behaviour can affect the fitness of an individual and it can dramatically increase the intensity of sexual selection, particularly in socially monogamous species. In this chapter we focus exclusively on birds. In this group of vertebrates, a large variety of mating patterns has been described, but social monogamy with biparental care is by far the most common mating system (BOX 13.1). However, parentage analyses using DNA fingerprinting techniques revealed that social monogamy often goes hand in hand with multiple mating and extra-pair paternity. Studies on birds have played a prominent role in our understanding of the evolutionary causes and consequences of extra-pair mating, partly because bird behaviour is relatively easy to study in the field. Many of the issues discussed here not only apply to birds and are more generally relevant in the context of understanding promiscuous behaviour.
13.2 The occurrence of extra-pair behaviour 13.2.1 Frequency of extra-pair paternity The frequency of extra-pair paternity, as revealed by studies using molecular techniques, varies dramatically among species (Griffith et al. 2002). In some species, extra-pair paternity seems to be absent or extremely rare. For example, in the socially monogamous Lanyu scops owl (Otus elegans
362
Bart Kempenaers and Emmi Schlicht
Y
X
W
A
B
1/7
1
C 1
D
E
4/4
0/2
1
2
1
1/4
0/5
3
1
3
1
5/5
0/7
5/6
5/6
1
0/1
1
4
5
1
1/4
1
3/6
2/6
3/4
2
6/6
1
floater # 1 4
4/5
5
6
7
6/6
1/5
2/5
5 1
2 1
floater # 2
2/5
floater # 3 3/5
2
ST-DI TG-CI
Fig. 13.1 Patterns of extra-pair paternity in a population of tree swallows (Tachycineta bicolor). Each square represents a nestbox. The numbers inside each box refer to the number of extra-pair young and the total number of offspring in the brood. Arrows indicate extra-pair males that sired offspring in a particular nest and the number next to the arrow shows how many offspring they sired. The encircled birds on the right cared for a brood elsewhere, whereas the other three birds were unpaired ‘floaters’ without their own brood. Nestboxes marked with the same colour belonged to one of four socially polygynous males. Reprinted with permission from Kempenaers et al. 2001).
botelensis) only one extra-pair offspring was detected among a total of 200 genotyped offspring from 108 families (Hsu et al. 2006). In other species, extra-pair males sire the majority of offspring. This is for example the case in the socially monogamous tree swallow (Tachycineta bicolor), where 51% of 229 offspring from 49 broods were extra-pair, and extra-pair paternity was found in 75% of all broods (Kempenaers et al. 1999; see Fig.
Extra-pair behaviour
363
13.1). The record holder is found in Australia: in the superb fairy-wren (Malurus cyaneus), a cooperatively breeding bird, extra-group paternity was detected in almost all broods (95% of 40, Mulder et al. 1994), and 61% of 1895 genotyped offspring were sired by males outside the female’s social unit (Double and Cockburn 2003). Species also vary in the distribution of extra-pair young among broods and in the number of fathers within a brood. In many cases, broods show mixed paternity, with some offspring fathered by the social male, and some by an extra-pair male. However, broods that contain exclusively extra-pair young are found in many species (Fig. 13.1). In the superb fairy-wren, this occurred in no less than 48% of the broods (Mulder et al. 1994). Females may also copulate with several extra-pair males, so that each offspring can have a different father (e.g. in the tree swallow; Whittingham et al. 2006, Dunn et al. 2009). There are two important points to be made regarding the frequency of extra-pair paternity. First, one should be aware that multiple paternity in a brood can occur for reasons other than extra-pair mating. These are: (1) rapid switching of social mates (e.g. Mee et al. 2004), (2) sequential polyandry and sperm storage (e.g. Oring et al. 1992), and (3) cooperative breeding with more than one reproductively active male (e.g. Haydock et al. 2001). The second point is that the frequency of extra-pair paternity does not necessarily reflect the frequency of extra-pair behaviour (Brommer et al. 2007, Griffith 2007). Thus, it is possible that extra-pair copulations are rather common, but rarely lead to extra-pair paternity. For example, a study on northern fulmars (Fulmarus glacialis) found no extra-pair paternity although 2.4% of copulations were extra-pair (Hunter et al. 1992). Extensive behavioural observations suggest that the social males may have sired all the offspring because they always obtained the majority of copulations and the last copulation before egg laying. Because observing copulation behaviour is time-consuming, and because extra-pair copulations may be harder to observe than within-pair copulations, it is difficult to link behaviour with paternity. Experimental work with bluethroats (Luscinia svecica) provides further insight. Fossøy et al. (2006) employed a simple device (see photo) to prevent social males from transferring sperm during copulation. Females mated to such males should lay infertile eggs, unless they performed extra-pair copulations. Indeed, Fossøy et al. (2006) showed that most of the experimental pairs had extra-pair offspring in their brood. Because the level of extra-pair paternity in natural broods is much lower, the results suggest that many females that appear truly monogamous are in fact promiscuous. Note that the opposite is also possible: a single, well-timed extra-pair copulation may sire a disproportionate number of offspring (Michl et al. 2002).
364
Bart Kempenaers and Emmi Schlicht
A male bluethroat (Luscinia svecica) with a rubber tube attached around the cloaca to prevent sperm transfer during copulation. Photo © Jan T. Lifjeld (reprinted with kind permission from Springer Science and Business Media; Fossøy et al. 2006).
Extra-pair paternity is not only the outcome of copulation behaviour, but also of post-copulatory processes such as sperm competition and cryptic female choice. The importance of sperm competition was demonstrated in a study on mallards (Anas platyrhynchos): when females were artificially inseminated with equal numbers of sperm from a brother and an unrelated male, differences in fertilisation success could be explained by betweenejaculate differences in average sperm swimming speed and motility, but not by male relatedness to the female (Denk et al. 2005). Evidence for female sperm selection comes from a study on red junglefowl (Gallus gallus): the number of sperm that were counted on the perivitelline membrane of eggs, i.e. the site of fertilisation, was lower when a female was inseminated by a brother compared to an unrelated male (Pizzari et al. 2004). Nonetheless, we still lack a general understanding of whether and how processes such as sperm selection and sperm competition, and factors such as the timing of copulations affect the success of extra-pair copulations.
Extra-pair behaviour
365
13.2.2 Determinants of variation in levels of extra-pair paternity Which factors can explain the observed variation in the frequency of extrapair paternity that occurs between species, populations and individuals? The frequency of extra-pair paternity in a population is the outcome of processes that play at the level of individuals with potentially strong conflicts of interest between males and females (Petrie and Kempenaers 1998, Westneat and Stewart 2003). Thus, to understand variation in extra-pair paternity, we need to consider the costs and benefits for individuals engaging in extra-pair matings (see below). Here, we briefly consider four groups of relevant factors and illustrate their complex interactions with some examples. (1) Species-specific factors and life-history. Comparative analyses have shown that variation in the frequency of extra-pair paternity can be explained by variation in general life-history characteristics of the species (Arnold and Owens 2002). Extra-pair paternity is most frequent in species with high adult mortality (Fig. 13.2) and high annual fecundity, in species where males provide less care (relative to the female), or in species where the effect of male care on offspring fitness is limited. In contrast, extra-pair paternity is generally rare or absent in species that are long-lived and show a low annual fecundity, and in species where male care is more important. Life-history, paternal care, and extra-pair behaviour may be directly linked through the evolutionary response of male behaviour to an increased frequency of cuckoldry. The more common extra-pair paternity becomes, the less it will pay males to care for offspring (BOX 13.2). Extra-pair behaviour and extensive paternal care may then become mutually exclusive and male care in the absence of extra-pair paternity may be the only stable equilibrium for species with slow life-histories. Yet, how exactly slow life-history prevents the invasion of cuckoldry remains unclear. Maybe it is the potential costs of extra-pair matings for females, imposed by the males’ facultative response to their mate’s infidelity (BOX 13.2). Male retaliation in terms of reduced care or divorce after perceived loss of paternity presumably has a stronger negative impact on female fitness in slow life-history species and might thus prevent females from pursuing extra-pair matings. This is also referred to as the ‘constrained female hypothesis’ (Mulder et al. 1994, Gowaty 1996). Alternatively, the association between life-history characteristics and the frequency of extra-pair paternity may be caused by a yet unknown factor.
366
Bart Kempenaers and Emmi Schlicht
BOX 13.2 Multiple paternity and paternal care It is characteristic for birds that males allocate their care to clutches in which other males may have fertilised some or all of the eggs. There is no empirical evidence that males can identify the extra-pair young and theory suggests that the evolution of kin recognition is unlikely in this context (Westneat et al. 1995, Kempenaers and Sheldon 1996, Pagel 1997; but see Johnstone 1997). Female extra-pair behaviour will then not only cause a direct reduction in a male’s fitness, but will also lead to males spending part of their parental investment on unrelated young (Trivers 1972). Should males with reduced paternity – and hence reduced benefits from caring – reduce their care? Intuitively the answer seems ‘yes’, but in fact it depends on the behavioural options available to the male (Grafen 1980). Even when the payoff from paternal care is reduced, it may remain larger than the payoff from alternative behaviours, for instance when chances of survival or remating are remote (Clutton-Brock 1984, Kempenaers and Sheldon 1997). Thus, reduced care is only expected if reallocation to alternative forms of investment (i.e. ultimately to future broods) leads to greater fitness. In general, changes in the level of extra-pair paternity can cause an evolutionary response in the care behaviour of all males or a facultative response in the care of individual males (Westneat and Sherman 1993). On an evolutionary timescale, a population-wide increase in female promiscuity reduces benefits from paternal care for males and increases mating opportunities outside the pair. The first effect alone will not cause selection for reduced male care because males will on average have similar paternity in future broods (Maynard Smith 1978, Grafen 1980, Westneat and Sherman 1993), but due to the second effect – an increased probability of future mating – reduced paternity in a species should lead to a reduction in paternal care (Queller 1997, Houston and McNamara 2002). On the individual level, a male that can assess his paternity in a brood should adjust his level of paternal care so as to maximise his fitness. Depending on the circumstances, he may achieve this by ignoring paternity loss, by reducing his care, or even by increasing his care (Kempenaers and Sheldon 1997, Whittingham and Dunn 2001, Holen and Johnstone 2007). It is not possible to identify a universally optimal male response to paternity loss. This is because (a) the effect of paternal care on the success of the brood may vary among species (Whittingham et al. 1992, Houston 1995), (b) not all males are equal, so that males differ in how their care decisions affect their prospects of survival and future matings (Westneat and Sherman 1993), and (c) the opportunity costs of male care relate to the care decisions of other individuals (Houston and McNamara 2002). For example, whether other males decide to desert or care will influence a male’s extra-pair mating opportunities. It is thus a matter of some intricacy to determine how an individual male should optimally respond when he perceives paternity loss.
Extra-pair behaviour
367
100
Rate of EFP (% of broods)
80
60
40
20
0 0
10
20
30
40
50
60
70
80
Rate of annual adult mortality (%)
Fig. 13.2 The relationship between the frequency of extra-pair paternity and adult mortality rate. Each dot represents one species. Reprinted with permission from Arnold and Owens (2002).
(2) Population-specific factors and genetic diversity. If females mate with extra-pair males to increase the genetic quality of their offspring through ‘good genes’ or ‘compatible genes’, levels of extra-pair paternity may vary depending on the availability of males with corresponding alleles (Kempenaers 2007, Lindstedt et al. 2007). One could then predict a positive relationship between levels of extra-pair paternity and population-wide variation in male genetic quality or genomewide diversity (Petrie et al. 1998). Indirect evidence comes from the observation that levels of extra-pair paternity are generally lower on island populations (Griffith 2000), which may also be less genetically diverse. For example, an island population of house sparrows (Passer domesticus) had both lower levels of extra-pair paternity and reduced genetic diversity compared to several mainland populations (Ockendon et al. 2009). When mainland birds with higher genetic diversity were released on the island, the level of extra-pair paternity strongly increased, as predicted. However, contrary to the idea that females would benefit from mating with immigrant males by maximising the genetic diversity of their offspring, all extra-pair fathers were island males.
368
Bart Kempenaers and Emmi Schlicht
(3) Population-specific factors and ecology. Levels of extra-pair paternity in a population may also vary depending on ecological factors that influence the likelihood of meeting extra-pair partners. For example, the availability of copulation partners may be larger in high-density populations, or in populations with high breeding synchrony (Stutchbury and Morton 1995). Note, however, that high breeding synchrony may also lead to lower levels of extra-pair paternity, if males face a tradeoff between mate guarding and pursuing extra-pair copulations (Westneat et al. 1990, van Dongen and Mulder 2009). Similarly, one could argue that higher levels of extra-pair paternity are expected in low-density populations, if this forces females to settle with nonpreferred males and, hence, to pursue extra-pair copulations more often. Although effects of breeding density and synchrony have been extensively discussed and tested, they rarely seem important (e.g. Kempenaers 1997, Stewart et al. 2006, Lindstedt et al. 2007, Rowe and Weatherhead 2007, but see the experimental study by Charmantier and Perret 2004). Another example is the potential effect of habitat characteristics on extra-pair paternity. Dense vegetation may allow females as well as extra-pair males to hide from guarding males and to sneak extra-pair copulations, whereas open habitats make it easier for territory owners to observe intruding males and may also increase the probability of male retaliation, and thus increase the costs of extra-pair paternity for females (Valera et al. 2003). (4) Individual-specific factors. Only few studies have addressed whether loss or gain of paternity is repeatable for individual males, females or pairs (e.g. Dietrich et al. 2004). At the level of the individual, the question thus remains whether some individuals are more likely to engage in extra-pair behaviour than others (everything else being equal), and what factors play a role. Males or females may intrinsically differ in a variety of ways that influence their propensity to show extra-pair behaviour. For example, individuals may differ in their genetic predisposition to be promiscuous (Forstmeier 2007), or individual extrapair behaviour may depend on maternal effects (e.g. hormone levels in the egg) or on the rearing environment. Males may also differ in quality, as reflected in age, condition, or expression of sexual ornaments, which may influence their capacity to gain extra-pair matings or to avoid losing paternity. One of the more robust findings in studies on extra-pair paternity is that older males are more likely to sire extrapair offspring (e.g. Delhey et al. 2003, Bitton et al. 2007, Bouwman et al. 2007, Schmoll et al. 2007a). Similarly, females may differ in quality, condition, size, or experience (age), which may influence their ability to cope with reduced male investment, and hence the potential
Extra-pair behaviour
369
costs of engaging in extra-pair matings. Alternatively, larger or stronger females might be better at avoiding costly extra-pair copulations and, hence, are less likely to have extra-pair offspring (Rosivall et al. 2009). In reality, it will often be difficult to disentangle the factors that play a role in creating a particular level of extra-pair paternity in a population, unless experiments are conducted. The following examples illustrate how difficult it is to unequivocally interpret results even in carefully designed studies. In the coal tit (Parus ater) Dietrich et al. (2004) showed that the level of extra-pair paternity increased significantly from first to second broods (overall and within pairs). There are several, not always mutually exclusive explanations (see also discussion in Dietrich et al. 2004). (a) Second broods may be less valuable to males so they would invest less in paternity protection strategies. (b) Males whose mates did not lay a second clutch may have invested heavily in extra-pair behaviour causing high paternity loss for males whose mates did produce second broods. (c) Young in second broods may face harsher conditions, so that effects of good or compatible alleles on offspring fitness are more important (Schmoll et al. 2005, Kempenaers 2007), and selection would favour females who engage more often in extra-pair behaviour. (d) Females may invest more in extra-pair behaviour because the environmental conditions have improved so that they are less dependent on male care. (e) Females may have increased opportunities to engage in extra-pair copulations for the second brood because the eggs of the second brood are fertilised when the young of the first brood still require care and males have to trade off mate-guarding with offspring care. The second example concerns studies on the relationship between weather conditions and the level of extra-pair paternity. In a Norwegian population of bluethroats, low temperatures during the peak fertile period resulted in lower levels of extra-pair paternity (Johnsen and Lifjeld 2003), presumably because individuals invested more in self-maintenance during a spell of bad weather. Moreover, it may be harder for males or females to detect suitable extra-pair partners in adverse weather conditions. Finally, when weather conditions are likely to stay bad during the nestling phase, male care may become more important, and this may cause a shift in female behaviour towards less extra-pair behaviour. Similar reasoning can explain why rainfall during the fertile period caused a decrease in levels of extra-pair paternity in the reed bunting (Emberiza schoeniclus: Bouwman and Komdeur 2006). However, in this species, low temperatures led to increased levels of extra-pair paternity, which the authors explained by reduced mate guarding because of investment in self-maintenance when temperatures are low. What can we learn from such conflicting results?
370
Bart Kempenaers and Emmi Schlicht
Clearly, the level of extra-pair paternity is hard to predict, even when information about variation in very specific ecological parameters is available. This is because the level of extra-pair paternity is a population parameter that emerges from behavioural interactions between individuals, and we are still far from understanding the complex dynamics causing population level changes. However, we can focus on particular behaviours or behavioural interactions and use the above results to predict the effect of e.g. weather conditions on mate guarding in male reed buntings or on solicitation of extra-pair copulations in female bluethroats. Ultimately, seemingly contradictory results may not be inconsistent after all. Weather conditions likely affect general activity patterns and may do so more in one sex than in the other or more for particular activities depending on the specific ecological situation and on the species. The final example is an experimental study on song sparrows (Melospiza melodia: MacDougall Shackleton et al. 2006) where food and predator presence was manipulated. Extra-pair paternity was more frequent when the environment was more challenging (no extra food, predators present), and females with extra-pair offspring were more stressed than faithful females. This contradicts the hypothesis that females that are more in need of male help are less likely to engage in extra-pair behaviour. Instead, general activity patterns may again have changed in response to the experimental manipulation, leading also to changes in the exposition to and opportunities for extra-pair mating attempts. For example, hungry females might move around more and, hence, meet more extra-pair males, and females might be less likely to conspicuously resist copulation attempts if predators are around. Arnold and Owens’ (2002) comparative analysis showed that 55% of the interspecific variation in the frequency of extra-pair paternity in birds is explained by the taxonomic classification (family and order). They thus suggested a hierarchical explanation for the variation in extra-pair paternity. Variation among major avian lineages can best be explained by variation in the potential costs and evolutionary consequences of extra-pair behaviour, as explained above. Variation among closely related species, or among populations of the same species, may be better explained by the opportunities to engage in extra-pair copulations and the benefits that can be gained from this behaviour. It would be interesting to find out whether this hierarchical explanation can be extended to other vertebrates. The available data are too scant to allow formal analysis, but indicate that there may be as much variation in levels of extra-pair paternity in other taxa as observed in birds (Sefc et al. 2008, Cohas and Allainé 2009, While et al. 2009a).
Extra-pair behaviour
371
13.3 Evolutionary causes of extra-pair behaviour When the existence of extra-pair behaviour is the result of natural and sexual selection, the fitness benefits an individual derives from acquiring additional mates must be higher than the costs associated with it, at least for some individuals. Costs are not only those that come about directly from performing the behaviour, but also include opportunity costs. These arise from missing the opportunity to perform an alternative behaviour. Extrapair behaviour will trade-off with behaviours such as self-maintenance, mate guarding or parental care. An individual that invests in extra-pair behaviour can only do so at the cost of investing less into such other behaviours, thereby foregoing other fitness benefits. Generally, the reproductive success of male birds is mainly limited by the access to females, because males can produce more gametes than they can obtain eggs to fertilise. Therefore, males should always copulate with additional females, unless there are substantial costs associated with this behaviour. In contrast, female birds usually cannot increase their offspring number by mating with more males and it is therefore not so clear whether they should mate multiply, even when this behaviour is not costly. Due to this initial difference between the sexes, conflicts of interest between the members of a socially monogamous pair (and other individuals) may arise over the level of promiscuity. The observed extra-pair behaviour will be the evolutionary outcome shaped by these conflicts of interest. Here we discuss the costs and benefits of engaging in extra-pair behaviour for males and females separately. 13.3.1 Benefits and costs of extra-pair matings for females 13.3.1.1 Female benefits of extra-pair behaviour Selection can act on females to mate multiply in two ways (Jennions and Petrie 2000). (1) Selection may favour females who increase their number of mates independent of the quality of their social mate. (2) Selection may favour females who improve on the quality of their social mate by ensuring fertilisation by extra-pair males of higher quality. In both cases the fitness increase for multiply mated females can be brought about directly via an increase in female fecundity, in female survival, or in the number or non-genetic quality of the offspring that can be raised (direct benefits). Alternatively, fitness of multiply mated females can increase indirectly through genetic effects on the fitness of offspring. Most likely direct and indirect benefits often occur jointly in the same species (Jennions and Petrie 2000).
372
Bart Kempenaers and Emmi Schlicht
A. Direct benefits Material benefits. The fitness of a female can be enhanced directly via extra-pair behaviour when she gains material benefits in the form of additional male investment such as courtship feeding, nutritional resources in the ejaculate, offspring care, access to additional resources etc. In this context, it is important to note that female multiple mating will reduce the fitness benefit of parental investment for males (BOX 13.2). Also, distributing paternal care among several nests would lead to a reduction in efficiency, especially in territorial species. Selection will therefore favour males who focus their care on the brood(s) where their expected paternity is highest (Souzou and Houston 1994, Iwasa and Harada 1998). This makes it unlikely that females can gain additional male investment such as offspring care from extra-pair mates. Furthermore, when females only seek extra-pair copulations to obtain additional investment, a simple way in which males could reduce multiple mating of their female is to provide her with as much care as possible (cf. Hunter and Davis 1998). Taken together this should concentrate material benefits within the social pair (Akçay and Roughgarden 2007) and inhibit selection for female extra-pair behaviour solely through benefits such as paternal care. In line with this, material benefits from extra-pair copulations are generally thought to be unimportant (e.g. Birkhead and Møller 1992:201-203). Nevertheless, a few studies have found evidence for such benefits and we discuss those cases in more detail below. In the great grey shrike (Lanius excubitor), a socially monogamous species with biparental care, males give food to females immediately before copulation. Tryjanowski and Hromada (2005) showed that extra-pair females are provided with prey items of high energy value that are costly to hunt (Fig. 13.3). Why do males not allocate this investment to their social mate? The benefit for males from this investment is twofold: it not only functions as parental effort but also as mating effort (Møller and Thornhill 1998). Forms of male investment that occur after fertilisation, such as incubation or feeding young, primarily serve to increase offspring fitness and cannot influence mating success anymore (although they might sometimes influence copulation opportunities for future broods, e.g. Freeman-Gallant 1996). In contrast, providing females with courtship gifts may create extrapair opportunities that are otherwise absent. Additional access to fertile females may also explain why male redwinged blackbirds (Agelaius phoeniceus) allow extra-pair mates to forage on their territory (Gray 1997a). Material benefits in the form of foraging opportunities could further be facilitated because males have to defend a territory for their social nest(s) in any case, and the cost of allowing other
Extra-pair behaviour
373
14
Number of prey items
12 10 8 6 4 2 0
Birds
Voles
Lizards
Insects
Without gift
Fig. 13.3 Number of courtship gifts offered by male great grey shrikes (Lanius excubitor) to females in the context of within-pair copulations (open bars) or extrapair copulations (filled bars). Handling time of hunting shrikes is longer for vertebrate prey (birds, voles, lizards) than for insects. Successful copulation attempts are associated with gifts of higher energy content. Reprinted with permission from Tryjanowski and Hromada (2005).
females to forage in their territory may be minimal. Finally, it has been observed that unpaired males in some species provided material benefits to females when they copulated with them (Hunter and Davis 1998, Blomqvist et al. 2005). In this case, the care-providing extra-pair males do not have their own brood to care for. Such a situation shows some resemblance to a cooperative breeding system where several males share in siring offspring and in providing care. Similarly, males may start caring for an ‘extra-pair brood’ after their ‘social brood’ failed (Kempenaers 1993). Insurance benefits. An increase in the number of mates can also lead to higher fecundity because it ensures fertilisation when some males are unable to fertilise a female’s eggs (Sheldon 1994). Even if a male produces functional sperm, he may be unable to fertilise the ova of his social mate due to temporary sperm depletion (Wetton and Parkin 1991) or due to a failure to overcome female barriers against polyspermy (Morrow et al. 2002). There is considerable variation among bird species in hatching success, but no positive relationship with the rate of extra-pair paternity has been found (Morrow et al. 2002). However, such a relationship is not nec-
374
Bart Kempenaers and Emmi Schlicht
essarily expected because the present state may represent an evolutionary response to past selection against infertility (Sheldon 1994), so that species with high levels of extra-pair paternity are now best insured against infertility (Lifjeld 1994). Fertility benefits are difficult to study both for theoretical and practical reasons. First, with observational data it is almost impossible to exclude the hypothesis that females obtain indirect benefits from extra-pair behaviour. Whenever there is some heritable component to an extra-pair male’s ability to fertilise a female’s eggs that her social mate failed to fertilise, genetic benefits are inevitable and it is difficult to quantify the evolutionary importance of one benefit relative to the other (Sheldon 1994, Griffith et al. 2002, Griffith 2007). Second, it may be problematic to ascertain whether eggs have failed due to lack of fertilisation or due to early embryo death (e.g. Kempenaers et al. 1996, Friedl and Klump 2005, but see Birkhead et al. 2008). Temporary sperm depletion is perhaps most likely in polygynous species. Indeed, the strongest evidence for fertility benefits comes from two socially polygynous species (Gray 1997b, Friedl and Klump 2005), whereas evidence from studies of socially monogamous species is relatively weak (Wetton and Parkin 1991, Wagner 1992, Lifjeld 1994, Krokene et al. 1998). Extra-pair behaviour may not only function as an insurance against male infertility but also against mate loss through death of the partner, if it enables multiply mating females to find a new male more quickly (Petrie and Kempenaers 1998). This hypothesis has not been explicitly studied, but interspecific variation in the rate of extra-pair paternity is positively associated with variation in mortality rates (see above, Arnold and Owens 2002). However, such a pattern can easily be explained in other ways because mortality will fundamentally influence the costs and benefits of infidelity in several respects (Mauck et al. 1999, Wink and Dyrcz 1999, Arnold and Owens 2002, Jeschke and Kokko 2008). Insurance benefits could also come into play as a result of genetic pleiotropy when the same genes control the frequency of within- and extrapair copulations (positive genetic correlation; Arnqvist and Kirkpatrick 2005, Forstmeier 2007). It is likely that there is an optimal frequency of within-pair copulations, for example to avoid infertility of eggs, to secure male care, or to strengthen the pair bond. Hence, selection may favour female extra-pair behaviour indirectly because only unfaithful females copulate frequently enough with their social partner to avoid infertility or mate loss. A related benefit of female extra-pair behaviour could lie in mate sampling (Heg et al. 1993) and pair formation (Colwell and Oring 1989). Females in suboptimal pair bonds could assess available males via extra-pair
Extra-pair behaviour
375
behaviour and initiate new social relationships for the following season. In socially monogamous bird species a high divorce rate was positively associated with a high rate of extra-pair paternity (Cézilly and Nager 1995). Again, it is easy to come up with alternative explanations for such an association, because the divorce rate of a species also emerges as a trait from complex interactions between individuals (Cézilly and Nager 1995, Catry and Furness 1997). Diversity benefits. Multiple paternity broods will show a higher genetic diversity. This may directly increase the success of the brood, if it leads to positive interactions among nestlings (Yasui 1998; for tests and discussion see Schmoll et al. 2007b and Dunn et al. 2009). For example, genetic diversity may hinder the transfer of infectious diseases among offspring (Jennions and Petrie 2000). Here it is considered a direct and not an indirect benefit because it is independent of offspring genomic quality itself. It has to be kept in mind, however, that the presence of half-siblings will lead to an increase in sibling-competition as an ecological (Boncoraglio and Saino 2008) or evolutionary (Briskie et al. 1994) response to decreased relatedness among nest-mates. This might be beneficial in some cases when it eliminates genetically inferior competitors quickly (Jennions and Petrie 2000), but in general is expected to be against the parents’ interest (Birkhead and Møller 1992:204). B. Indirect benefits The genetic quality of an offspring will influence its fitness and thus indirectly maternal fitness. Females could therefore benefit from extra-pair behaviour by optimising the genetic quality of their offspring. How females should behave will depend on the information they can obtain about expected fitness returns. It may sometimes be impossible to maximize offspring genetic quality, because the optimal male genotype is uncertain or not readily identifiable. In such a situation genetic bet hedging may be adaptive (Yasui 1998; for tests and discussion see e.g. Schmoll et al. 2007b). Multiple mating produces offspring of variable genetic quality, whereas broods sired by only one male contain young that are more or less of the same (superior or inferior) genetic quality. The average genetic quality of a brood with multiple sires is therefore less likely to be extreme. Hence, increasing genetic diversity by mating multiply causes a reduction in fitness variance between broods. In the long run, this reduction in between-brood variance in offspring quality is associated with increased fitness. This is because over
376
Bart Kempenaers and Emmi Schlicht
evolutionary time, above-average success with one mate cannot compensate similar below-average success with another (the geometric mean is more relevant for long-term fitness than the arithmetic mean; Gillespie 1977, Philippi and Seger 1989). However, it has been convincingly argued that fitness benefits from genetic bet-hedging are usually limited and unlikely to be important in maintaining female promiscuity, except in special cases (Yasui 2001). When females are able to determine the optimal genetic constellation for their offspring, their choice of a paternal genotype should be influenced by two effects: allelic quality and allelic compatibility. The former refers to the absolute, additive effects certain paternal alleles (‘good genes’) have on the fitness of the offspring genotype (Jennions and Petrie 2000, Neff and Pitcher 2005). These will be alleles that increase viability or attractiveness (mating success) and they confer their fitness effects relatively independent of the genetic background in which they happen to occur. Genetic compatibility refers to the effects of interactions within a genome between alleles at the same locus (e.g. heterozygote advantage) or at different loci (epistasis). In the context of mate choice, genetic compatibility issues might arise when the fitness effects of the alleles from the maternal haplotype and other maternal genetic elements depend in a non-additive way on the paternal haplotype they are combined with. This means that the quality of offspring genotypes does not only depend on the sum of the effects of the maternal and paternal alleles, but also on their interaction (Zeh and Zeh 1996, Brown 1997, Neff and Pitcher 2005). Female choice for allelic quality and compatibility are not mutually exclusive (Jennions and Petrie 2000) and it is expected that females trade off one benefit against the other when they are negatively associated (Neff and Pitcher 2005). When female preferences for genetically superior or compatible males drive female extra-pair behaviour, extra-pair copulations are expected only when females can improve on the social mate’s genotype. Thus, females that secured the genetically optimal male as social mate should not engage in extra-pair copulations for genetic benefits. The good genes and the compatible genes hypothesis make different predictions about the congruence among females in their extra-pair mate choice: additive effects lead to agreement about who is the ‘top-quality’ male, whereas non-additive effects lead to a different ranking of males for different females (Zeh and Zeh 1996, Brown 1997, Neff and Pitcher 2005). However, both hypotheses predict that extra-pair young should have higher quality genomes than within-pair young of the same brood (maternal half-sib comparisons; Griffith et al. 2002, Arnqvist and Kirkpatrick 2005, Akçay and Roughgarden 2007). A recent meta-analysis found only small and presumably evolutionary irrelevant effects of paternity status on offspring fitness (Arnqvist and
Extra-pair behaviour
377
Kirkpatrick 2005; see also Akçay and Roughgarden 2007). This suggests that selection on females to pursue extra-pair copulations for genetic benefits is absent. However, the estimates on which this meta-analysis is based can be criticized for three reasons. (1) Estimates of offspring fitness that can be obtained from data in the field and that are reported in studies on extra-pair paternity do not necessarily represent an important component of total fitness, because they often do not give information on residual reproduction or offspring reproduction (Eliassen and Kokko 2008). (2) Differences in genetic quality among offspring within a brood need not transfer into easily measurable differences in fitness when genetic effects explain only a small amount of the variation in offspring fitness (Møller and Alatalo 1999). Yet, they might constitute the most important fitness consequence of a female’s mating decision, which is then shaped by these minor differences because a small fitness benefit can still be selected for over evolutionary time. (3) Parental effects may differ among the young in a brood (Price 1998). This could confound the genetic differences (Griffith et al. 2002) and conceal them when parents invest more into within-pair offspring. Such compensatory allocation (Bluhm and Gowaty 2004) can be very difficult to control for because it can occur already at the stage of egg production (Saino et al. 2002, Bolund et al. 2009; see also Magrath et al. 2009). There is evidence for both good genes and genetic compatibility benefits from studies on a variety of species (e.g. Hasselquist et al. 1996, Blomqvist et al. 2002, Forstmeier et al. 2002, Eimes et al. 2005, Fossøy et al. 2008, Kawano et al. 2009). For example, in a study on the blue tit (Cyanistes caeruleus) extra-pair offspring were more heterozygous than withinpair offspring from the same nest (Fig. 13.4a). Heterozygosity is associated with reproductive success and sexual attractiveness in this species presumably because it reduces the number of recessive deleterious alleles expressed or increases the diversity of gene products synthesized (Foerster et al. 2003, García-Navas et al. 2009). Interestingly, the difference in heterozygosity was only present when extra-pair sires were not close neighbours (Fig. 13.4a). This is because females were generally less related to more distantly breeding males (Foerster et al. 2006). Hence, females that copulated with extra-pair males breeding further away obtained compatibility benefits (Foerster et al. 2003). Further, it could be shown that only close neighbours, but not non-neighbours, were older and larger than the social male they cuckolded (Fig. 13.4b). This suggests that females may have obtained good genes benefits from mating with neighbouring extra-pair males. Thus, in this population the details are more complicated because different females may obtain different genetic
0.10
NS
P
