Carbon Dioxide Populations and Communities

Carbon Dioxide, Populations, and Communities

Carbon Dioxide, Populations, and Communities

This is a volume in the PHYSIOLOGICAL ECOLOGY series Edited by Harold A. Mooney

Carbon Dioxide, Populations, and Cornrnunities Edited by

Christian Korner Botanisches lnstitut der Universitat Basel Basel, Switzerland

Fakhri A. Bazzaz Department of Organismic and Evolutionary Biology Harvard University Cambridge, Massachusetts

Academic Press San Diego

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This book is printed on acid-free paper. Copyright 9 1996 by ACADEMIC PRESS, INC. All Rights Reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher.

Academic Press, Inc. A Division of Harcourt Brace & Company 525 B Street, Suite 1900, San Diego, California 92101-4495

by Academic Press Limited 24-28 Oval Road, London NW1 7DX Library of Congress Cataloging-in-Publication Data Carbon dioxide, populations, and communities / edited by Christian KOrner, Fakhri A. Bazzaz. p. cm.-- (Physiology ecology series) Includes bibliographical references (p. ) and index. ISBN 0-12-420870-3 (alk. paper) 1. Plants, Effect of atmospheric carbon dioxide on. 2. Atmospheric carbon dioxide--Environmental aspects. 3. Plant communities. 4. Plant ecophysiology. I. KSrner, Christian. II. Bazzaz, F. A. (Fakhri) A.) III. Series: Physiological ecology. QK753.C3C38 1996 581.5'222--dc20 96-33959 CIP

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Contents

Contributors Preface xix

xiii

Part Population-Level

I Responses

I. II. III. IV.

Introduction 3 The Genetic Bases for Evolutionary Responses to Climate Change Thermal Sensitivity and Evolutionary Responses to Climate Change Summary 11 References 12

I. II. III. IV.

Introduction 13 Experimental Methods Results and Discussion Conclusions 20 References 21

References

30

15 17

4 7

I. Plant Responses to Environmental Change: Theory and Review of Previous Work 31 II. An Experiment to Test Genotypic Responses to Increased CO2 38 III. Results from the Experiment and Discussion 39 IV. Outlook 47 V. Summary 48 References 49

I. II. III. IV. V. VI.

Introduction 51 54 Genetic Variability in C O 2 Responses Effects of Elevated CO2 on the Selection Process 61 What Characters Will Be Selected? 68 Possible Effects of Evolutionary Changes on Ecosystem Processes Summary 74 References 75

Part I I Commtmity-Level

Responses

I. II. III. IV. V.

Introduction 85 Current Vegetation Changes in Western Europe 86 Plant Functional Types and Response to Elevated CO2 Feedbacks 89 Summary 91 References 91

I. II. III. IV. V.

Introduction 93 Methods 94 Results 96 Discussion 97 Summary 98 References 99

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73

I. II. III. IV.

Introduction 10l Responses at the Level of the Individual 102 Responses at the Level of the Plant Community Conclusions and Recommendations 118 References 119

I. II. III. IV. V.

Introduction 123 The Experimental Designs 124 Species Responses within Community Ecosystem Responses 127 Discussion and Conclusion 131 References 136

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126

Community Microcosms I. II. III. IV. V. VI.

Introduction 139 The Jasper Ridge CO2 Experiment Methods 142 Analysis 144 Results 145 Discussion 151 References 155

140

I. Introduction 159 II. Design of CO2 and Plant Diversity Treatments in Calcareous Grassland Communities 160 III. Response of Calcareous Grassland Communities to Manipulations of CO2 and Plant Diversity 164 IV. Discussion 166 V. Summary 173 References 174

I. II. III. IV.

Introduction 177 CO2 and Vegetation Change Conclusions 188 Summary 189 References 190

I. II. III. IV. V.

Introduction 197 Site Description and Methodology 198 The Response of Primary Producers 200 Other Trophic Levels 203 Conclusions 204 References 205

I. II. III. IV. V.

Introduction 209 Experimental Setup and Methods Results 216 Discussion 221 Summary 226 References 227

I. II. III. IV. V. VI.

Introduction 231 The Role of Fire in Plant Communities 232 CO2 Effects on Vegetation and Fire 235 Predicting High CO2 Effects on Future Fire Cycles Research Priorities 243 Summary 244 References 245

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211

241

Part I I I Interactions

Organismic

I. Introduction 253 II. The Symbiotic N z Fixation: A Highly Flexible Way to Assimilate Nitrogen 254 III. The Link between Plant Growth, Nitrogen Assimilation, and N 2 Fixation 255 IV. The Link between Elevated CO2 and N Availability in the Soil 255 V. The Response of Symbiotic N 2 Fixation to Elevated CO2 in the Field: A Response to Both Increased Legume N Demand and Increased Strength of the Ecosystem N Sink? 258 VI. Model and Conclusion 259 VII. Summary 260 References 261

I. II. III. IV.

Introduction 265 Responses of Symbiotic Fungi to a COz-Enriched Environment Community and Ecosystem Level Consequences 268 Summary 271 References 272

I. Introduction 273 II. Survey of Differential Species Responses within Species Mixtures Exposed to Elevated CO2 275 III. Conclusions 282 References 284

266

I. II. III. IV.

Introduction 287 Materials and Methods Results and Discussion Summary 297 References 298

I. II. III. IV. V. VI. VII. VIII.

288 289

Introduction 301 Theory 301 An Experimental Test 303 Temperature, Phenology, and Competition 311 Species Competitive Abilities 313 Competition and Internal Plant Nutrient Status 314 Longer Term Implications 314 Summary 315 References 316

I. Introduction 319 II. Shade Tolerance of Spruce Seedlings and Some Co-occurring Grasses at Ambient and Elevated CO2 Concentration in Air 320 III. Interaction between Spruce Seedlings and at Ambient and Elevated CO2 327 IV. Conclusions 329 References 330

I. II. III. IV. V.

Introduction 333 Developmental Patterns and Competitive Ability 334 Predicting the Effect of Elevated CO2 on Development 336 Effect of Developmental Patterns on CO2 Responsiveness 341 Summary 344 References 345

I. II. III. IV. V. VI.

Introduction 347 Direct Effects of CO2 349 Interactive Effects: CO2 and Resource Availability 353 Indirect Effects: CO2 and Climate 354 Tritrophic Interactions 355 Predicting Insect Outbreaks: The Functional Attribute Approach 356 VII. Conclusions and Recommendations 357 References 359

I. II. III. IV. V.

Introduction 363 Ruminant Digestion 364 Impact of Elevated CO2 on Forage Quality 366 Impact of Elevated CO2 on Cattle Production in Tallgrass Prairie Conclusions 369 References 370

Part IV Theory, Modeling, Concepts

I. II. III. IV. V. VI.

The Need for Functional Types 375 Methodological Aspects 376 Interspecific Variation 380 Differences between Species at Low N Levels Ecological Aspects 390 Summary 391 References 406

I. Introduction 413 II. Light Interception in Mixed Species Stands

389

414

367

xii

III. Effect of CO2 Elevation on the Canopy Development in Two Annuals 418 IV. Nitrogen Allocation and Optimal Leaf Area Index under Elevated CO2 420 V. Summary and Conclusion 426 References 428

I. II. III. IV. V.

Introduction 431 Extrapolation 432 Reductionism from Below 434 Two Approaches to Research on Elevated CO2 Prediction and Uncertainty 439 References 440

I. II. III. IV. V. VI. VII. VIII. IX.

Index

Introduction 443 Why Study Variance? 444 Genotypic Responses in Populations 445 Responses of Plant Communities 446 Plant-Plant Interactions 449 Plant-Microbe Interactions 451 Plant-Animal Interactions 451 Theory, Modeling, Concepts 452 Ecosystem and Global Consequences 453 References 455 457

436

Contributors

on

D. D. Aekerly (413), Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts 02138 John A. Arnone III (101), Institute of Botany, University of Basel, CH-4056 Basel, Switzerland Lisa M. Auen (363), Department of Agronomy and Department of Animal Science and Industry, Kansas State University, Manhattan, Kansas 66506 F. A. Bazzaz (413, 443), Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts 02138 A. Birrer (31), Institut for Umweltwissenschaften, Universit~it ZOrich, CH8057 Zfirich, Switzerland L. O. Bj6rn (197), Department of Plant Physiology, University of Lund, Lund S-22100, Sweden Herbert Blum (253, 287), Institute of Plant Sciences, Swiss Federal Institute of Technology, 8092 Zfirich, Switzerland T. V. Callaghan (197), Department of Animal and Plant Sciences, The Centre for Arctic Ecology, The University of Sheffield, Sheffield $10 5BR, United Kingdom Bruce D. Campbell (301,375), AgResearch, Grasslands Research Centre, Palmerston North, New Zealand Nona R. Chiariello (139) ,Jasper Ridge Biological Preserve, Stanford University, Stanford, California 94305 Robert C. Cochran (363), Department of Animal Science and Industry, Kansas State University, Manhattan, Kansas 66506 Peter S. Curtis (13), Department of Plant Biology, The Ohio State University, Columbus, Ohio 43210 Paolo De Angelis (209), Department of Forest Environment and Resources, University of Tuscia, 1-01100 Viterbo, Italy Shivcharn Dhillion 1 (123), Centre d'Ecologie Fonctionnelle et Evolutive, Centre de la Recherche Scientifique, F-34033 Montpellier, France Christopher B. Field (139, 443), Department of Plant Biology, Carnegie Institution of Washington, Stanford, California 94305 1 Present Address: Department of Biology and Nature Conservation, Agricultural University of Norway (NLH), .3ts N-1432, Norway.

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Beret Fischer (253), Institute of Plant Sciences, Swiss Federal Institute of Technology, 8092 ZOrich, Switzerland Marco Frehner (253), Institute of Plant Sciences, Swiss Federal Institute of Technology, 8092 Z/irich, Switzerland C. Gehrke (197), Department of Plant Ecology, University of Lund, Lund S-223 62, Sweden; and Abisko Naturvetenskapliga Station, Abisko S98107, Sweden Jan Gloser (319), Department of Plant Physiology, Faculty of Science, Masaryk University, 61137 Brno, Czech Republic J. P. Grime (85), NERC Unit of Comparative Plant Ecology, Department of Animal and Plant Sciences, The University of Sheffield, Sheffield $10 2TN, United Kingdom Jean-Louis Gtdllerm (123), Centre d'Ecologie Fonctionnelle et Evolutive, Centre de la Recherche Scientifique, F-34033 Montpellier, France D. Gwyrm-Jones (197), Department of Animal and Plant Sciences, The Centre for Arctic Ecology, The University of Sheffield, Sheffield S10 5BR, United Kingdom Alan L. Hart (301), AgResearch, Grasslands Research Centre, Palmerston North, New Zealand Ueli A. Hartwig (253, 287), Institute of Plant Sciences, Swiss Federal Institute of Technology, 8092 Z~rich, Switzerland Thomas Hebeisen (253, 287), Institute of Plant Sciences, Swiss Federal Institute of Technology, 8092 Z~rich, Switzerland George R. Hendrey (253, 287), Department of Applied Science, Brookhaven National Laboratory, Upton, Long Island, New York 11973 T. Hirose (413), Biological Institute, Faculty of Science, Tohoku University, Aoba, Sendai 980-77, Japan M. Jasiefiski (51), Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts 02138 U. Johanson (197), Department of Plant Physiology, University of Lund, Lund S-22100, Sweden Hyrum B.Johnson (177), United States Department of Agriculture, Agricultural Research Service, Grassland, Soil & Water Research Laboratory, Temple, Texas 76502 T. Herin Jones (93), NERC Centre for Population Biology, Imperial College at Silwood Park, Ascot, Berks SL5 7PY, United Kingdom Susan Kalisz2 (13), Kellogg Biological Station, Michigan State University, Hickory Corners, Michigan 49060 Joel G. Kingsolver (3), Department of Zoology, University of Washington, Seattle, Washington 98195 Present Address: Department of Biological Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania 15260.

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Dawn Jenkins Klus (13), Kellogg Biological Station, Michigan State University, Hickory Corners, Michigan 49060 Ch. K6rner (159, 443), Institute of Botany, University of Basel, 4056 Basel, Switzerland Elena Kuzminsky (209), Department of Forest Environment and Resources, University of Tuscia, 1-01100 Viterbo, Italy C. Lavigne (31), Institut for Umweltwissenschaften, Universit~it Ziirich, CH8057 ZCtrich, Switzerland Sharon P. Lawler ~ (93), NERC Centre for Population Biology, Imperial College at Silwood Park, Ascot, Berks SL5 7PY, United Kingdom John H. Lawton (93), NERC Centre for Population Biology, Imperial College at Silwood Park, Ascot, Berks SL5 7PY, United Kingdom Paul W. Leadley (159), Botanical Institute, University of Basel, 4056 Basel, Switzerland J. A. Lee (197), Department of Animal and Plant Sciences, The University of Sheffield, Sheffield S10 2UQ, United Kingdom Richard L. Lindroth (347), Department of Entomology, University of Wisconsin, Madison, Wisconsin 53706 Andreas L/iseher (253, 287), Institute of Plant Sciences, Swiss Federal Institute of Technology, 8092 Ziirich, Switzerland Giorgio Matteueci (209), Department of Forest Environment and Resources, University of Tuscia, 1-01100 Viterbo, Italy Herman S. Mayeux (177), United States Department of Agriculture, Agricultural Research Service, Grassland, Soil & Water Research Laboratory, Temple, Texas 76502 Shahid Naeem 4 (93), NERC Centre for Population Biology, Imperial College at Silwood Park, Ascot, Berks SL5 7PY, United Kingdom Marie-Laure Navas 5 (123), Centre d'Ecologie Fonctionnelle et Evolutive, Centre de la Recherche Scientifique, F-34033 Montpellier, France Josef N6sberger (253, 287), Institute of Plant Sciences, Swiss Federal Institute of Technology, 8092 Z/irich, Switzerland Clenton E. Owensby (363), Department of Agronomy, Kansas State University, Manhattan, Kansas 66506 H. Wayne Polley (177), United States Department of Agriculture, Agricultural Research Service, Grassland, Soil & Water Research Laboratory, Temple, Texas 76502 3Present Address: Department of Entomology, Universityof California, Davis, Davis, California 95616. 4Present Address: Department of Ecology, Evolution, and Behavior, Universityof Minnesota, St. Paul, Minnesota 55108. 5Present Address: CEFE and Biologie et Pathologie V6g6tale, ENSA-M,F-34060 Montpellier, France.

• Hendrik Poorter (375), Department of Plant Ecology and Evolutionary Biology, Utrecht University, 3508TB Utrecht, The Netherlands Catherine Potvin (23), Department of Biology, McGill University, Montr6al, Qu6bec H3A 1B1, Canada E. G. Reekie (333), Biology Department, Acadia University, Wolfville, Nova Scotia BOP 1X0, Canada Heather L. Reynolds (273), W. K. Kellogg Biological Station, Michigan State University, Hickory Corners, Michigan 49060 Catherine R0umet (375), Centre d'Ecologie Fonctionelle et Evolutive, Centre National de la Recherche Scientifique-Centre Louis Emberger, 34033 Montpellier, France Jacques Roy (123), Centre d'Ecologie Fonctionnelle et Evolutive, Centre de la Recherche Scientifique, F-34033 Montpellier, France Rowan F. Sage (231), Department of Botany, University of Toronto, Toronto, Ontario M5S 3B2, Canada Ian R. Sanders (265), Institute of Botany, University of Basel, CH-4056 Basel, Switzerland Giuseppe E. Scaraseia-Mugnozza (209), Department of Forest Environment and Resources, University of Tuscia, 1-01100 Viterbo, Italy B. Schmid (31), Institut for Umweltwissenschaften, Universit~it Zfirich, CH8057 ZOrich, Switzerland M. Sonesson (197), Department of Plant Ecology, University of Lund, Lund S-223 62, Sweden; and Abisko Naturvetenskapliga Station, Abisko S-98107, Sweden S. C. Thomas (51), Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts 02138 LindseyJ. Thompson (93), NERC Centre for Population Biology, Imperial College at Silwood Park, Ascot, Berks SL5 7PY, United Kingdom Charles R. Tisehler (177), United States Department of Agriculture, Agricultural Research Service, Grassland, Soil & Water Research Laboratory, Temple, Texas 76502 StephenJ. Tonsor 6 (13), Kellogg Biological Station, Michigan State University, Hickory Corners, Michigan 49060 Denise Tousignant 7 (23), Department of Biology, McGill University, Montr6al, Qu6bec H3A 1B1, Canada Chris Van Kessel (253), Department of Soil Science, University of Saskatchewan, Saskatoon, Saskatchewan S7N 0W0, Canada Present Address: Department of Biological Sciences, Universityof Pittsburgh, Pittsburgh, Pennsylvania 15260. 7 Present Address: Ministere des ressources naturelles, Peponiese St. Modeste, St-Modeste, Quebec J0L 3W0, Canada.

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Jacob Weiner 8 (431), Biological Laboratories, Harvard University, Cambridge, Massachusetts 02138 Richard M. Woodfin (93), NERC Centre for Population Biology, Imperial College at Silwood Park, Ascot, Berks SL5 7PY, United Kingdom SUvia Zanetti (253, 287), Institute of Plant Sciences, Swiss Federal Institute of Technology, 8092 ZCtrich, Switzerland

8 Present Address: Department of Biology, Swarthmore College, Swarthmore, Pennsylvania 19081.

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Preface

In many aspects of biological science, variance is considered a nuisance. Variance makes experimental design difficult, requires much replication and detailed statistical analysis, and may greatly increase the need for expensive research facilities beyond the reach of many investigators. The results of some critical experiments may be statistically insignificant because of low replication. Consequently, many researchers in plant sciences, including those investigating CO2, have attempted to eliminate variance by cloning plants or by working with a small set of individuals and assuming that they represent the species. On the other hand, some researchers consider assemblages of plants and treat whole plant communities as a single "big leaf." In many of these cases, these smooth results and their mean values eliminate variance among individuals in the populations, which is the material for natural selection and evolution. Variance in response among individuals and species may be the most important aspect to consider in predicting the vegetation response to the continued enrichment of the atmosphere with CO2. Because of the speed with which CO2 in the atmosphere is increasing (~1.8 ppm/year), there is little time for the evolution of a new set of genotypes specifically adapted to this new global level of CO2 in the atmosphere. Therefore, it is the current genetic structure of populations that will determine the response of plants to elevated levels of CO2, especially in long-lived woody or clonal plants. Research on the response of a variety of plant species over the past two decades has convincingly shown that species do differ in their response to CO2. These differences can be very large, even among co-occurring species of a community. It is also well established that genotypes within a population differ in their response to CO2 enrichment. Thus, in a changing CO2 environment there may be winner (positively responding) and loser (less responding) individuals or species. This differential response may be underway already. Furthermore, this differential response may determine the genetic structure of future populations, may change the dominance relationship in communities, and thus may alter the importance of some plant functional groups, which may have feedbacks on the functioning of ecosystems. It may also influence biological diversity of some ecosystems. We must remember, however, that under natural conditions, selection by one xix

factor may not be the case, as factors of the physical and the biological environment interact in a variety of ways and may collectively influence the direction and the strength of selection. For example, CO2 enrichment may increase the water-use efficiency of a species or a genotype, providing access to more soil moisture to its otherwise less efficient neighbor, which in turn may offer the preferred food for a butterfly that may be an important pollinator for a third species. Scientists concerned about the global increase in CO2 met in the hills of the SwissJura Mountains in August 1994 and discussed the topics in this volume. They emphasized the need for a better understanding of the differences among individuals and of interactions among themselves a n d with other organisms. They sought to identify critical questions in this research area. This meeting represents one of the major steps in the Global Change and Terrestrial Ecosystems (GCTE) research plan, and its outcome is intended to complement that of the preceding workshop on ecosystem response to elevated CO2, the results of which appeared last year in this series. We gratefully acknowledge the support of the Swiss National Science Foundation, the Swiss Academy of Sciences, the United States Electric Power Research Institute (EPRI), and the United States National Science Foundation. The Leuenberg Conference Center near Basel provided a charming environment for this workshop. CH. KORNER

F. A. BAZZAZ

I Population-Level Responses

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1 Physiological Sensitivity and Evolutionary Responses to Climate Change

The global changes in C O 2 and climate expected to occur during the coming decades are but one of many types of environmental changes resulting from human activities during the past century. The ecological and evolutionary consequences of pollution, pesticides, heavy metals, and other environmental insults during the past 40 years have been well documented. It is natural to ask whether and how the lessons we have learned from such studies may be used to anticipate the evolutionary consequences of future climate change for populations and species. In this chapter I will argue that the evolutionary consequences of climate change may differ importantly from those documented by field studies of pesticides and many other environmental toxins for a rather simple reason: pesticides represent an abrupt step-change in the environment, whereas climate change represents a progressive, directional alteration of environmental conditions. To illustrate this point, I will suggest and defend two conjectures about the evolutionary consequences of climate change: 1. The evolutionary responses of populations and species to climate change will involve polygenic, not monogenic, genetical responses. 2. Species whose individuals have broad physiological tolerances to climatic conditions will be less able to adapt evolutionarily to rapid and

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Copyright 9 1996 by Academic Press, Inc. All rights of reproduction in any form reserved.

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climate change than those species whose individuals have intermediate tolerances. For the sake of discussion, I will argue these points with greater confidence than is perhaps warranted. My goal, however, is to show how lessons learned from the evolution of pesticide resistance and from quantitative genetic models of physiological sensitivity may provide some useful guidelines for evolutionary studies of climate change.

Most discussions of the biological consequences of climate change have downplayed any potential role for evolution, arguing that the predicted rapid rate of climate change will preclude evolutionary responses: species will either adjust ecologically or become extinct. It is certainly true that the relatively long generation times and small effective population sizes of many trees and large vertebrates make evolutionary responses to future climate change, which may occur on time scales of one to several decades, ineffective. However, the long history of studies of the evolution of resistance to pesticides and heavy metals clearly demonstrates that evolutionary responses to environmental changes can be rapid indeed in species of interest to humans. It is more useful to ask in what cases rapid evolution is likely to be important. First, rapid evolution is most likely in populations with large population sizes (e.g., >105-106), with short generation times (e.g., 0.5/generation). Thus, evolutionary responses to climate change may be quite likely in pest species. Second, rapid evolution is more likely when migration and dispersal are geographically restricted. Thus, evolutionary adaptation to climate change may be of importance in nature reserves and on other habitat islands, where the diluting effects of gene flow are reduced and where range shifts into new areas may be constrained.! geographically. Studies of the evolution of insecticide resistance in insect pests provide some useful insights into the possible genetic bases for evolutionary responses to climate change. A key question is whether evolutionary adaptation to climate change is more likely to involve a few major gene loci of large effect (monogenic), or many gene loci each of small effect (polygenic). Although the genetic basis for insecticide resistance has been intensively studied since the 1950s (Crow, 1957), the early studies appeared to be conflicting. Only in the last decade has a clear pattern in this literature been suggested: most laboratory studies, in which artificial selection is used

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to select for resistance from an initially susceptible population, indicate a polygenic basis for resistance. Conversely, many field studies, in which resistant genotypes are sampled from a population that has experienced frequent heavy insecticide doses, indicate a monogenic basis for resistance (Roush and McKenzie, 1987). The example of diazinon resistance in sheep blowflies is instructive (McKenzie and Batterman, 1994). Diazinon was widely used in Australia to control sheep blowflies, which rapidly evolved resistance to this insecticide. Genetic studies showed that this resistance was the result of the same allelic substitution at a single locus in different populations; and this resistant genotype was maintained near fixation during two decades of routine application of diazinon in the field. Subsequently, four populations of resistant blowflies were established in the laboratory and subjected to artificial selection for further increases in resistance. Within eight generations, more highly resistant strains had been developed, and genetic analyses showed that the increased resistance was due to multiple loci on at least four chromosomes. Thus, while two decades of field selection resulted only in monogenic evolutionary changes, laboratory selection led quickly to polygenic responses (McKenzie and Batterman, 1994). What causes these differing evolutionary responses both in the laboratory and in the field? The best current explanation is that the evolutionary response may depend on the intensity of selection (Roush and McKenzie, 1987; McKenzie and Batterman, 1994). Consider a laboratory population undergoing artificial selection for increased resistance to an insecticide (Fig. 1, top). During artificial selection, the intensity of selection (i.e., the fraction of the population killed by selection) must be chosen such that surviving individuals form a population sufficiently large to avoid substantial inbreeding and subsequent drift. Typically the insecticide dosage is chosen to achieve a selection intensity less than 80-90%, even for relatively large laboratory populations (103-104). As a result, selection occurs within the range of existing genetic variation in resistance in the population, which is often the result of many loci. The situation in the field is quite different. Here frequent and heavy doses are traditionally used to eliminate the entire pest population, and selection in this case could exceed 99% or more (Fig. 1, bottom). Even in large pest populations, only the rare individual with a mutant allele of large effects on resistance would be likely to survive. Because these rare alleles would only appear initially in heterozygotes, such alleles would need to be partially or fully dominant to be expressed. Such resistant alleles frequently have deleterious pleiotropic effects in the absence of insecticides, hence their initial rarity. Thus the very high insecticide doses, and hence the high selection intensity, typical of the field situation may have selected for resistance caused by one or a few alleles of larger effect.

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Figure I (Top) The distribution on the left (BEFORE) represents the distribution ot susceptible phenotypes within a population of insects before selection. When an insecticide dosage (Selection intensity, dashed line) is applied, only those individuals with resistances greater than the applied dosage (to the right of the dashed line) will survive. After repeated generations of selection, the distribution of phenotypes in the population will shift to the right as a result of evolution (AFFER). These selective conditions, typical of artificial selection studies in the laboratory, may preferentially select for a polygenic response. (Bottom) The distribution on the left (BEFORE) represents the distribution of susceptible phenotypes within a population of insects before selection. When a high insecticide dosage (Selection intensity, dashed line) is applied, only those individuals possessing mutations with large effects on resistance to the insecticide will survive. After repeated generations of selection favoring rare mutants of large effect on insecticide resistance, the distribution of phenotypes in the population will shift far to the right as a result of evolution (AFTER). These selective conditions, typical of insecticide applications in the field, may preferentially select for a monogenic response. Adapted from McKenzie and Batterman (1994), Fig. 1. T a b a s h n i k (1995) a r g u e s t h a t this d i c h o t o m y b e t w e e n m o n o g e n i c field r e s i s t a n c e a n d p o l y g e n i c l a b o r a t o r y r e s i s t a n c e is t o o simplistic. H e s u g g e s t s t h a t t h e e v i d e n c e t h a t r e s i s t a n c e typically h a s a m o n o g e n i c basis in t h e field is e q u i v o c a l a n d t h a t s o m e o f t h e m o s t t h o r o u g h s t u d i e s o f r e s i s t a n c e d o n o t fit n e a t l y i n t o e i t h e r t h e m o n o g e n i c o r p o l y g e n i c e x t r e m e s . F o r o u r p u r p o s e s , h o w e v e r , t h e p o i n t is t h a t m o r e g r a d u a l s e l e c t i o n is m o r e likely to s e l e c t o n e x i s t i n g q u a n t i t a t i v e v a r i a t i o n in r e s i s t a n c e in a p o p u l a t i o n a n d t h a t t h e c o n d i t i o n s o f s e l e c t i o n c a n i n d e e d i n f l u e n c e t h e g e n e t i c basis of resistance.

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What might this suggest for evolutionary responses to climate change? One characteristic of global climate change is that it will not occur in an abrupt step, but as a gradual, directional increase in CO2 and temperature. To those organisms most likely to respond evolutionarily--those with relatively short generation times and large population sizes--such gradual changes are likely to generate selection intensifies per generation more similiar to laboratory artificial selection regimes than to the extremes seen in field insecticide applications. Thus we might predict that the evolutionary responses to climate changes will involve primarily polygenic, not monogenic, control. One implication of this suggestion is that experimental studies exploring evolutionary responses to climate change need to consider the type of environmental change and the selection intensity imposed on the study population. In particular, studies that utilize abrupt step-changes in CO2 or temperature may affect the type of genetic responsesmpolygenic or m o n o g e n i c - - t h a t occur, in ways that do not accurately reflect the rates of change predicted from global climate change (see Tousignant and Potvin, Chapter 3). Again, the key issue is whether or not the imposed environmental change falls within the range of the existing genetic variation in the population. The notion that step-changes and progressive directional changes in the environment may yield qualitatively different responses has not received much attention. To further explore the importance of these differences, I will briefly discuss some recent models that address the question how does the physiological tolerance of individuals in a population affect the population's evolutionary response to selection?

One useful way to characterize the effects of temperature or other physical factors on the performance or fitness of an individual organism is in terms of a which maps environmental conditions onto physiological or ecological performance (Fig. 2). (For convenience I will focus on temperature effects throughout this secdon, but the basic ideas should apply to most other physical factors.) Performance initially increases with temperature, reaches some "optimal" temperature for performance, then declines rapidly as it approaches upper lethal levels. Frequently one can characterize the performance curve in terms of three parameters: optimal temperature (Z), the temperature at which performance is maximum; performance breadth (~r), the breath or width of the performance curve; and the maximum performance (Rmax), the level of performance at

Rmllx

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Z ENVIRONMENTALTEMPERATURE Thermal performance curves illustrating the relationship between an individual's performance (assumed directly proportional to fitness) and the environmental temperature it experiences. For each individual, there is an optimal temperature (Z) at which performance is maximized (Rmax).Performance curves are given for two individuals with identical optimal temperature (Z) and maximal performance (Rmax),but that differ in thermal performance breadth (tr). Adapted from Huey and Kingsolver (1989).

the optimal t e m p e r a t u r e (Fig. 2). We shall assume that the measure of p e r f o r m a n c e chosen is directly related to fitness. O n e natural question is how do the values of these parameters affect the ecological and evolutionary response to climate change (e.g., climate warming) ? Suppose we consider two individuals with identical Z and Rmax, but that differ in p e r f o r m a n c e breadth t r m t h a t is, one is a thermal " specialist" (small tr), the other a thermal "generalist" (large tr) (Fig. 2). Suppose the environmental t e m p e r a t u r e 0 is initially the same as Z, but then 0 increases somewhat. Obviously the reduction in p e r f o r m a n c e (and hence the reduction in fitness) of the thermal generalist is less (Fig. 2). Similarly, a population of thermal generalists will suffer a smaller decline in m e a n fitness than a population of thermal specialists in the face of a small increase in environmental temperature. Clearly, thermal generalists are at an ecological advantage in the face of climate warming. But how does thermal p e r f o r m a n c e breadth affect the evolutionary response of a population to sustained, directional climate warming? We have recently e x a m i n e d this question (Huey and Kingsolver, 1993), modifying a quantitative genetic m o d e l developed by Lynch and Lande (1993) (see Fig. 3). The p e r f o r m a n c e curve identifies the optimal t e m p e r a t u r e (Z) and thermal p e r f o r m a n c e breadth (tr) of each individual (Fig. 2). Suppose that optimal t e m p e r a t u r e Z is now a polygenic trait with some constant phenotypic and genetic variation in the population, but that all individuals

1.

9

Diagram illustrating the effect of thermal performance breadth on a population's evolutionary response to climate warming. Here f(Z) is the frequency distribution of phenotypic trait Z, the optimal temperature for performance. In each panel, the solid line represents the change in environmental temperature (0), and the dashed line represents the change in the population mean value of Z with time. As time proceeds, a lag develops between the environmental optimum and the population mean phenotype. For populations with large thermal performance breadths (top), this lag will be greater than for populations with small performance breadths (bottom). From Huey and Kingsolver (1993), Fig. 5.

in the p o p u l a t i o n (with fixed, constant, effective p o p u l a t i o n size) have identical p e r f o r m a n c e b r e a d t h (t r) a n d m a x i m u m p e r f o r m a n c e (Rma~). Initially the e n v i r o n m e n t a l t e m p e r a t u r e 0 is at t h e m e a n o p t i m a l t e m p e r a ture Z o f the p o p u l a t i o n ; 0 t h e n increases at a c o n s t a n t m e a n rate, b u t with s o m e stochastic ( r a n d o m ) variation. Given this situation, t h e m e a n o p t i m a l t e m p e r a t u r e Z o f t h e p o p u l a t i o n will evolve toward increasingly h i g h e r values, b u t will lag b e h i n d the e n v i r o n m e n t a l t e m p e r a t u r e (Fig. 3). m

0 If the rate of climate warming is too rapid, the population's lag will become too great, its mean fitness will approach zero, and extinction will occur. Hence one can identify a critical rate of climate change above which population extinction will quickly occur (Fig. 3). Using this model, we can address how performance breadth affects the critical rate of climate change that a population can sustain. Consider the simplest case in which the genetic variation in optimal temperature Z in the population is constant with rime and independent of performance breadth. The model then predicts that the critical rate of climate change will initially increase with increasing performance breadth, quickly reach a maximal value, and then decline with increasing performance breadth (Fig. 4). Thus the model predicts that populations with intermediate performance breadths will be able to sustain the highest rates of climate c h a n g e - that populations of thermal generalists are more likely to become extinct in the face of rapid climate change. Stochastic variation in climate decreases the critical rate of change and increases the performance breadth at which the rate is maximal, but does not alter the qualitative result (Fig. 4). Interestingly, these results do not depend on the existence of tradeoffs between specialists and generalists (Huey and Kingsolver, 1993). What produces this apparently paradoxical result? The key once again is the importance of the intensity of selection. For a population of thermal

~0

"-2".

0.4

o. r

0

2

.,'> 0.05) from the distribution of response ratios across 155 species reported by Poorter (1993). In order to partition variation in CO2 responses into within and between species components, the minimal data requirement would be growth analyses of genotypes within some sample of plant species. Ideally, such data should also encompass a range of environments for each species, so as to allow an evaluation of the relative importance of"environmental" variation in CO2 responsiveness. Unfortunately, no such data set yet exists. Existing data do give some indication that genetic variation in CO2 responsiveness is actually large, relative to variation among species. Table I lists the conventional "response ratios" for genotypes in four studies investigating genetic

60

F i g u r e 3 Distributions of CO2 growth " e n h a n c e m e n t ratios" (biomass at 700 p p m / b i o m a s s at 350 ppm) for 8 genotypes of pooling 7 weekly measurements and 2 density treatments (top), and 155 plant species compiled by Poorter (1993) (bottom). The 2 distributions do not differ significantly (G test for homogeneity: P > 0.050).

variation in CO2 responses in annual plants. Table II gives the result of a mixed model analysis of variance that partitions variance in response ratio within and among species, and among environmental states. For each

Species

Env.

Genotypes

Range of response

Reference

2 nutr. 2 nutr. 1 only

4 6 5

0.47-2.37 0.25-1.37 0.93-1.39

Wulff and Alexander, 1985 Fajer 1992 Curtis 1994

2 dens.

8

0.30-1.40

Thomas manuscript in preparation

a Responses are calculated as the ratio of plant performance at 700/350 ppm for the most proximate fitness characteristic measured. The ranges reported are pooled across environments in studies for which measurements were made under different environmental treatments.

61

5.

Effect

d.f.

SS

MS

F

P

Species Environment Genotype Error Total

2 1 16 21 40

0.120788 0.377143 3.80075 2.31536 6.83487

0.060394 0.377143 0.237547 0.110255

0.25424 3.4206 2.1545

0.7786 0.0785 0.0502

For this analysis environmental treatments were classified as "good" (high nutrient or low density) vs "poor" (low nutrient or high density).

species the most proximate fitness measure was used (i.e., either final total reproductive or vegetative biomass). Also, in three of the four studies multiple environmental states were measured. For the purposes of the analysis, these were scored as "favorable" (high nutrients or low density) or "unfavorable" (low nutrients or high density). This preliminary analysis suggests that intraspecific variation exceeds interspecific variation: 56% of total variance in response ratio is explained by genotype, approximately 6% is explained by environmental state, and less than 2% is explained by species. The genotype term approaches significance at the P < 0.05 level, while the environment term is also marginally significant. Existing data thus suggest that intraspecific variation in responses to elevated CO2 is very substantial, perhaps even greater in magnitude to interspecific variation. However, we emphasize that this preliminary analysis does not take into account the important issue of ontogenetic changes in growth enhancement. Additionally, models that incorporate CO2 effects in the context of local resource competition would be necessary to rigorously evaluate the relative importance of genetic change versus change in species composition under rising CO2.

A. A Quantitative Genetic Framework Quantitative genetic models represent a potentially powerful tool for understanding the evolutionary dynamics under global change (e.g., Lynch and Lande, 1993). A central assumption of these models is that phenotypic traits of interest are determined by many genes of small effect (MitchellOlds and Rutledge, 1986; Falconer, 1989). However, there are important cases of evolutionary responses to anthropogenic disturbance in which

62

single locus changes have very large effects (such as copper tolerance in (MacNair, 1977, 1991). It is within the range of possibility that single genes could also have large effects on CO2 responses. For example, Musgrave (1986) examined CO2 responses in pea hybrids differing in the presence vs. absence of the cyanide-resistant respiratory pathway. Presence of the pathway was associated with a very low growth response to CO2, the explanation offered being that carbohydrate production was respired in hybrids possessing the pathway. Many metric traits display a right-skewed distribution of gene effects, with some degree of "major gene" influence as well as many genes of small effect (Hill and Caballero, 1992). It seems likely that CO2 responses would have a similar distribution of gene effects; however, studies addressing the genetic basis of CO2 responses in natural plant populations are entirely lacking. In the simplest quantitative genetic models of selection, the rate of change in fitness is a product of the heritability of fitness, and the relative variation in fitness [Eq. (2a)]. The response of some trait correlated with fitness may be estimated by substituting the product of fitness heritability and the covariance of the trait with fitness in this expression [Eq. (2b)]. The "Chicago school" multivariate quantitative genetic models of selection essentially extend this expression to predict selection on a set of traits, incorporating a genetic variance-covariance matrix in the place of the heritability term (Lande, 1979, 1982; Arnold and Wade, 1984) h2 h2

(2a)

2 2.

(2b)

Here R or R' is the selection rate on fitness or on a correlated trait, respectively; h2 is narrow sense heritability, V~ is variance in fitness, W is mean absolute fitness before selection, and ~ is the covariance of a given 2 is simply the square of the trait with fitness. Note that the term coefficient ofvariance of fitness (cf. Thomas and Bazzaz, 1993). The product h2 2 is sometimes called the "opportunity for selection" (denoted I), and has been used as a measure ofevolvability (Crow, 1958; Houle, 1992). Elevated CO2 may potentially affect the selection process by systematically altering some or all of the variables in these expressions, namely, the relative variance in fimess within local populations, the heritability of fitness-related traits, and the genetic covariance of particular traits of interest with fitness. In the subsequent sections, these parameters are addressed in turn.

B. Phenotypic Variability Rising C O 2 may affect the selection process simply by altering the degree of phenotypic variability in fitness related traits. One mechanism by which this could occur is the acceleration of size differences due to enhanced

63

5.

overall growth. In the exponential phase of plant growth, small differences in growth rates among individuals result in exponential increases in size differences. Over time an even-aged set of plants that displays a normal distribution of seedling sizes will show increasing relative variation (Koyama and Kira, 1956; Uchmafiski, 1985). The addidon of any resource is expected to accelerate this process. By this reasoning, one would expect greater phenotypic variability in size in plant populations under elevated CO2. However, the sigmoidal nature of plant growth modifies this expectation. Plants grown at higher resource states may reach asymptotic sizes earlier, which could potentially result in decreased variability in asymptotic size or reproductive output under high resource conditions. A second mechanism by which elevated CO2 could influence phenotypic variability in plant size and reproductive output is by accelerating competitive interactions for other plant resources. In general, size variability increases through stand ontogeny in even-aged plant monocultures (e.g., Thomas and Weiner, 1989), and monocultures growing at higher densities display greater variability in plant size (Weiner and Thomas, 1986). Addition of nutrients and other resources often results in greater variation in size and reproductive output (Weiner, 1985; Rice, 1990). Elevated CO2 might similarly result in increased size variability. Morse and Bazzaz (1994) specifically addressed this issue in experiments with stands of two annual plants. Their results provide some evidence that elevated CO2 may accelerate size hierarchy formation and self-thinning. However, from an evolutionary perspective, it is of greatest interest to examine variability in reproductive output, rather than in size. Table III

C.V. of final total seed mass

Opportunity for selection (I)

Broad-sense heritability (H 2)

Response to selection (R)

350 p p m

0.557

Individually grown 0.31

0.052 ,

0.016

700 p p m

0.400

0.16

0.236

0.038

350 p p m

1.442

H i g h density 2.08

0.050

0.104

700 p p m

1.752

3.07

0.104

0.320

Statistical significance of differences were tested using a boot-strapping approach (cf. Thomas and Bazzaz, 1993), with 2000 iterations for each test. * Indicates pairwise comparison is significant at P > 0.05. Based on Bazzaz 1995. a

64

3,1.

presents data from the experiment. The data are consistent with the hypothesis that enhanced competition results in higher variability in fitness under elevated CO2: a significant difference in the coefficient of variation of final seed mass was found at high density, though not for individually grown plants. Not all species show such a pronounced response, however (S. C. Thomas, M. Jasiefiski, and F. A. Bazzaz, unpublished data).

C. Heritability The heritability of fimess-related traits is expected to be close to zero, as selection will operate to remove genetic variance for such traits (Fisher, 1930). Nonzero heritabilities may commonly be maintained by negative genetic correlations among a set of fitness-related traits. However, if traits are expressed in an evolutionarily novel environment in which selection has had no opportunity to act, then heritabilities may be much higher even in the absence of "trade-offs" among fitness components (e.g., Service and Rose, 1985). This raises the central issue of whether or to what degree elevated atmospheric CO2 (i.e., in the 350-700 ppm range) constitutes an evolutionarily novel environment. From a very long-term paleoecological perspective, CO2 levels were considerably higher in the geological past (B6ger, 1980; Spicer and Corfield, 1992). However, the past 160,000 years have been a period of relatively low atmospheric CO2 levels (Barnola 1987). Life spans of terrestrial plants vary in general from less than 1 year to several hundred years (Harper and White, 1974). Because the majority of plant species are iteroparous, generation times are generally much shorter. If changes in CO2 concentrations have directly or indirectly resulted in even modest selective effects (e.g., selection coefficients of order 0.00010.01), then there has almost certainly been sufficient time for preindustrial low CO2 levels to have eroded genetic variance related to earlier evolutionary processes driven by high CO2. The idea that rising CO2 constitutes an evolutionarily novel environment also depends on the nature of the selective regime generated. As noted above, the selective impact of rising CO2 may generally be expressed indirectly, particularly by exacerbating competitive interactions for other resources (as well as through the indirect effects of CO2-forced climatic change). In a review that briefly addresses this issue, Roose (1991) suggests that "these secondary effects of increased CO2 do not create novel environments, but rather environments which already occur elsewhere" (p. 122). There are several strong arguments against this view. First, almost any "novel" selective pressure is novel only locally, not globally. To take the paradigmatic example, mining activities expose heavy-metal-rich soils of a sort that generally already occur elsewhere; yet this does not alter the fact that local populations colonizing mine-spoils may have high genetic variance in fitness components due to a lack of previous heavy-metal expo-

5.

65

sure. Second, competitive regimes generated by altered C O 2 levels may indeed be qualitatively novel. For example, if plant monocultures are able to sustain a higher leaf area index under elevated CO2, then this could generate a qualitatively novel light environment under the canopy of a given species. Along these lines, one study detected substantial effects of CO2 on red-far red ratios of light transmitted through a canopy (Arnone and K6rner, 1993). Rising CO2 could also act as a novel evolutionary environment through its effects on plant development. Two general classes of developmental effects may be of importance in this regard. First, CO2 has known biochemical interactions in plants that are not mediated by the carboxylase activity of rubisco. For example, CO2 is directly involved in the regulation of ethylene biosynthesis (e.g., Horton, 1985; Cheverry 1988). Also, CO2 binds to rubisco to create the active form of the enzyme, and also regulates the activity of rubisco activase (for a review see Bowes, 1991). Second, elevated CO2 may have important novel effects on plant development that arise from increased carbon accumulation. One notable example is changes in nonstructural carbohydrate chemistry. For example, wheat shows a qualitatively different pattern of fructan accumulation under elevated CO2, with large amounts synthesized very early in ontogeny (Smart 1994). Completely novel carbohydrates are synthesized by certain conifer species at elevated CO2 (H. Lee, personal communication). Such quantitative and qualitative changes in carbohydrate chemistry may have important and novel effects on plant morphogenesis. One possible example of such an effect is dramatic changes in leaf form seen in (Fig. 4). Under elevated CO2 plants produced exaggerated "sun-leaf" morphologies, with significant changes in leaf length and degree of dentition. An alternative perspective on fitness heritabilities under rising CO2 derives from studies of genotype-specific performance under varying competitive regimes. A variety of studies indicate that competition in plant populations is often asymmetric with respect to size: large individuals usurp resources at the expense of small individuals (Lomnicki, 1988; Weiner, 1990). This phenomenon has the potential to greatly amplify small differences in size among individuals in a population, particularly in even-aged stands. Differences in size early in plant ontogeny may generally be largely due to microenvironmental heterogeneity. The amplification of early size differences may therefore act to enhance environmental variation in plant performance. This reasoning leads to a prediction of lower heritabilities for size under conditions of enhanced competition, such as at high density (Thomas and Bazzaz, 1993). Higher resource levels would also be expected to result in earlier and more intense competitive interactions. By this reasoning, one might expect reduced heritabilities for fitness-related traits under elevated CO2.

66

o 350 ppm 9700 ppm

1.4

o

9

1.2

~

O-'"""

-"~ o

9

1.0

.."

9

1 " ~ ~

~-~176 ~

0.8 ~~

0.6

~176176 o*~

0

0.2

014

016

018

110

1;2

1;4

1J6

1;8

i

Log leaf area (cm 2 ) 4 Effects of elevated CO2 on leaf shape in Altered patterns of plant development under rising CO2 may result in qualitatively novel phenotypes. From Thomas and Bazzaz, 1995. Figure

To summarize these arguments, there is strong reason to believe that increasing CO2 levels could act as an evolutionarily novel environment, perhaps most importantly through effects on plant developmental processes. This is expected to be associated with increased genetic variability in fitness-related traits at elevated CO2. However, accelerated competitive interactions may under some conditions act to increase the importance of small-scale environmental sources of variation in plant performance. This effect may act to reduce genetic variability in fitness-related traits at elevated CO2. Do trait heritabilities actually respond to elevated CO2? Data from the experiment indicate a consistent pattern of higher heritabilities at elevated CO2 than at ambient CO2 for final seed mass (Table III). This pattern is most pronounced for the individually grown plants, although high-density plants show a nonsignificant trend in this direction. Heritabilities at either CO2 level are also generally lower at high density. The overall pattern is consistent with the idea that accelerated competitive interactions may enhance the role of "environmental noise" in determining plant performance (cf. Thomas and Bazzaz, 1993). There is thus some evidence

5.

67

that both "evolutionary novelty" and "environmental noise" may play important roles in determining heritabilities of fitness-related traits under elevated CO2. D. Genetic Correlation Structure

Responses of a given trait to selection depend on the covariance of that trait with fitness. More generally, the response to selection of any set of phenotypic characteristics will depend on the overall genetic variancecovariance structure (Lande, 1982; Falconer, 1989). An ultimate task, however, is to establish a connection between quantitative-genetic estimates of variation and covariation of traits, developmental processes, and functional relationships of traits (Riska, 1989). Only then will we be able to provide mechanistic explanations of the evolution of suites of traits in novel environments (Chapin 1993). Such limitations notwithstanding, quantitative genetics of covariances among traits continues to be a basic framework for evolutionary considerations. The verdict is still out, however, as to the feasibility of using phenotypic correlations among traits in lieu of, more difficult to obtain, genetic correlations (Cheverud, 1988; Willis 1991; Roff, 1995). Although genetic variance-covariance structure is often treated as constant in quantitative genetic models, it is not fixed. There is a substantial literature that examines changes in genetic correlation structure with environmental conditions (e.g., Giesel 1982; Itoh and Yamada, 1990; Wilkinson 1990). (Although genetic covariances are directly used in calculating selection effects, comparative analyses are often conducted with genetic correlations.) In plants, changes in genetic correlation structure have been best documented with respect to changes in local density (Geber, 1990; Mazer and Schick, 1991; Thomas and Bazzaz, 1993; but see Shaw and Platenkamp, 1993; see also Young 1994). A body of theoretical work exists regarding expected changes in genetic variance-covariance structure under selection and drift (Crow and Kimura, 1970, pp. 236-239; Avery and Hill, 1977, 1979; Turelli, 1988). However, less attention has been given to possible effects of environmental changes, novel or otherwise. The statement has even been made that " . . . theory cannot predict whether the environmental changes that select for new phenotypes will change environmental or genetic covariances" (Turelli, 1988, p. 1344). One possible basis for prediction may, however, stem from observations that functionally or developmentally related traits generally show high (positive or negative) genetic correlations (e.g., Clark, 1987; Cowley and Atchley, 1990). One might predict in a novel environment of any sort that functionally related genetic correlation structure would tend to weaken. Similarly, environmental changes altering developmental processes could result in an overall lowering of absolute values of genetic

correlations. Another possibility is that changes in genetic variance in fitness could affect relationships between fitness correlates and other traits simply by altering overall phenotypic variance. Specifically, given some underlying genetic relationship, an increase in variance in one trait could result in increased genetic covariance with another trait. The sign of such covariance, however, is hard to predict, especially in traits whose phenotypic expression depends on the allocation of a single resource (van Noordwijk and deJong, 1986; de Jong and van Noordwijk, 1992). The empirical data on allow for a preliminary analysis of effects of elevated CO2 on genetic correlation structure (Fig. 5). In spite of the relatively small sample size (in terms of numbers of genotypes), both statistically significant genetic correlations and statistically significant differences between CO2 treatments are detected. At both ambient and elevated CO2 there are high positive genetic correlations between final size metrics: namely, height, leaf area, and biomass. Also in both treatments there is a high negative genetic correlation of these characteristics with seed size (mass). However, while at ambient CO2 initial relative growth rate shows a strong positive genetic correlation with final size characteristics, this correlation is very weak at elevated CO2. Genetic correlations of any of the traits examined to the most proximate fitness measure (final fruit mass) do not attain statistical significance (P < 0.05) for either COz level. However, there is a suggestive negative genetic correlation of final plant height with fruit mass that is considerably higher at elevated CO2. Overall, genetic correlations appear to be somewhat weaker under elevated CO2 conditions. These observations suggest surprisingly large effects of CO2 on genetic correlation structure; however, we emphasize that in this preliminary analysis we have not performed a conservative pooled test for the entire character matrix (cf. Shaw, 1991b). Long-term responses to selection may often be determined by fitness differentials, rather than genetic correlation structures, unless genetic correlations are very high (e.g., Via, 1987; Zeng, 1988). This point is of some interest from the perspective of evolutionary responses to a relatively sudden environmental change such as rising CO2. Although fitness maximization may prevail over the long term, it is likely that effects of genetic correlation structure will be especially pronounced over the first several generations of selection. This points to the importance of further studies aimed at elucidating genetic correlation structure and its consequences of evolution under rising CO2.

It has commonly been assumed that traits directly involved in physiologi cal responses to C02 may respond evolutionarily to rising C02. Thus, a priori

5.

69

Effects of elevated CO2 on genetic correlation structure in Data are for individually grown plants. Black bars indicate significant positive genetic correlations; white bars indicate significant negative correlations. Hatched bars indicate nonsignificant positive correlations; stippled bars indicate nonsignificant negative correlations. Genetic correlations were calculated as Pearson product-moment correlations between genotypic means. Bar width is proportional to the absolute value of the correlation.

predictions regarding expected evolutionary responses may be derived from considerations of optimal allocation patterns. For example, one might e x p e c t e v o l u t i o n a r y r e s p o n s e s involving c h a n g e s in n i t r o g e n a l l o c a t i o n f r o m r u b i s c o to e i t h e r d a r k cycle e n z y m e s i n v o l v e d in R U B P o r p h o s p h a t e

70

8.

regeneration (Bowes, 1991,1993; Stitt, 1991 ) or to light-harvesting molecules such as chlorophyll. However, there is presently a complete absence of studies addressing genetic correlations of such physiological traits with reproductive output under elevated CO2. Similarly, it is not clear that evolutionary responses ofstomatal density will match developmental responses of individual plants (see Beerling and Chaloner, 1993). Reported long-term trends in stomatal density (e.g., Woodward, 1987; Pefiuelas and Matamala, 1990) may or may not involve genetic change. It also cannot be assumed that either net photosynthesis orvegetative growth responses to CO2 will necessarily increase as plants evolve under rising CO2. For example, there is a negative genetic correlation offruit production with final plant height observed in the population under elevated CO2 (Fig. 5). The predicted short-term selective response would thus be for plants of smaller final stature. If rising CO2 levels generally act to exacerbate competitive interactions within and among plant species (Bazzaz and McConnaughay, 1992), one might expect CO2 to favor traits that are also favored under conditions of high density or high productivity. Such traits may include early germination, rapid early growth, delayed reproduction, and increased stem allocation, among others (e.g., Thomas and Bazzaz, 1993). A second a priori hypothesis is that selection under elevated CO2 will often involve amelioration of "nonadaptive" plastic responses. Consider, for example, species that show strong developmental effects, such as altered reproductive timing (cL Reekie 1994). Genots, pes that retain a flowering schedule more closely matched to their current seasonal pattern might be strongly favored under rising CO2. Similarly, forms of that do not develop exaggerated sun leaves under elevated CO2 (see Fig. 4) may be differentially favored. Future studies should be cognizant of possible indirect selective pressures brought about by enhanced competitive interactions and also by developmental effects of rising CO2. The potential for evolutionary change in plant traits can also be explored through an analysis of their covariance structure during ontogeny (Kirkpatrick 1994). In the case of per-plant leaf area measured in at six points in time, the eigenfunction associated with the dominant eigenvalue did not change sign in high-density populations, at either CO2 level (Fig. 6; M. Jasiefiski, S. C. Thomas, and F. A. Bazzaz, manuscript in preparation). This means that selection for an increase (or decrease) in leaf area at one age has the same effect at every point during ontogeny. A similar effect was found in the case of plants grown individually, although much smaller fraction of total variance in growth trajectories was concentrated in the first eigenvalue (i. e., 60% of variance, rather than over 90%, as in high-density plants). In the low-density plants, the second eigenfunctions changed signs (Fig. 6), indicating possible trade-offs in responses to selection for early versus late leaf area; e.g. selection for an increase in leaf area

71

5.

700 ppm CO2

350 ppm CO2

1st eigenfunction

High density

o.eoj

/

~

o.1o

0.05 ~

0.05

30

40

50

60

70

80

30

40

50

60

70

80

1st eigenfunction 0.15

0.15

0.10

0.10

0.05

0.05

Low

density

2nd eigenfunction 0.2

0.2

0.1

0.1

0.0 ~ , J 3 0

-0.1[

40

50

'

'

0.0

-0.1 Time since germination (d)

Figure 6 Effectsof elevated CO2 and density on the covariance structure of leaf area during growth in Line thickness of the eigenfunction corresponds to the fraction of variance associated with its eigenvalue. In high-densityplants, second eigenvalues accounted for less than 5% of total variance and are not shown. From M. Jasiefiski, S. C. Thomas, and F. A. Bazzaz, manuscript in preparation. of young plants will lead to decreases in leaf area of older plants, and vice versa. Density of plants had a stronger direct effect than CO2 on the potential for evolutionary modifications in growth trajectories: selection on leaf area in plants grown without competition had m o r e possible outcomes than selection in high-density populations. This result points again to density as an i m p o r t a n t proxy for CO2 effects. A recent selection e x p e r i m e n t on (see Tousignant and Potvin, Chapter 3) provides virtually the only direct experimental evidence

regarding traits favored under rising C O 2. Following eight generations of truncation selection for reproductive output (under a regime of increasing CO2, temperature, and temperature variation), selected lines exhibited increased biomass, but reduced allocation (in both absolute and relative terms) to reproduction. One possible explanation for these results is that plants under elevated CO2 were effectively under a selective regime of increased aboveground competition. A variety of life history models predict increased size and decreased reproductive allocation under such conditions (e.g., Gadgil and Bossert, 1970). However, the inclusion of the temperature increases and heat shock episodes in the experimental design make these experimental results difficult to interpret unambiguously. Inbreeding effects could also have resulted in the observed reproductive declines. One earlier study attempted to select lettuce for high growth response to elevated CO2 (Maxon-Smith, 1977). No significant response was detected after eight generations of selection; however, the author suggests that the experiment may have been compromised by poor control of CO2 and temperature levels. Some intriguing physiological responses to selection under very low CO2 conditions have been documented in a series of experiments with doubled haploid lines of (Delgado and Medrano, 1991; Delgado, 1992a,b, 1993). Lines selected for survival at CO2 levels near the CO2 compensation point (60 ppm) were found to display increased vegetative growth under both field and laboratory conditions. However, this was not associated with either increased leaf-level photosynthesis or decreased photorespiration. Rather, selected lines showed increased rates of leaf production and lower respiration rates (Delgado 1992b, 1993). Additionally, leaves of selected lines possessed smaller mesophyll cells than did controls, which may have decreased mesophyll limitation of CO2 diffusion under low CO2 conditions. The implications of these findings to selection under high CO2 are not entirely clear. However, it is of some interest that screening of genotypes under low CO2 levels has previously been used as a strategy to select for high photosynthetic rates and growth potential in crop species (see also Cannell 1969; Menz 1969). One potentially important source of direct evidence regarding traits favored under rising CO2 is a comparison between populations of plants growing near naturally high CO2 environments with populations under ambient levels. Unfortunately, no systematic study of this nature has yet been attempted. However, one obscure and very early study addressing the ecology of crater plants on the island of Java contains some suggestive observations on possible effects (Von Faber, 1925, 1927). Von Faber's attention was initially drawn to CO2 vents by the presence of extremely green leaves of plants in the immediate vicinity of the vents. He later documented that these plants did in fact show exceptionally high chloro-

5.

phyll content. Von Faber also speculated that high C O 2 levels could compensate for very low light levels, facilitating the evolution of extreme shade plants in such environments (Schimper, 1935, p. 146). In summary, at present no strong a priori theory exists allowing for predictions of what traits will be favored under rising CO2. Two speculative hypotheses are advanced: first, selection may act largely through enhanced local competition, thus favoring suites of traits enhancing fitness under high density or high productivity environments; and second, in cases where CO2 has pronounced effects on plant developmental processes, selection may operate to ameliorate such effects. Definitive empirical studies aimed at identifying traits favored under rising CO2 are presently lacking. A variety of approaches, including selection experiments, quantitative genetic investigations, and comparative studies of populations exposed to naturally high CO2 levels are necessary to make progress in this area.

There are well-documented examples in which genetic change in populations can have profound impacts on ecosystem function. In the case of a heavily contaminated mine spoil, ecosystem properties such as carbon and nitrogen flux may be entirely contingent on patterns ofintraspecific genetic variability (Antonovics 1971; Shaw, 1991). If no tolerant genotypes were available to colonize heavily contaminated areas, then no carbon fixation by any autotrophic organism would exist. The evolutionary implications of a resource increase are, however, less clear at the ecosystem level. Some bounds on potential evolutionary effects on ecosystem function might be derived from selection experiments which monitor both ecosystem properties and genetic composition. The data from the experiment provides some preliminary data on this issue. Using quantitative genetic projections [Eq. (2)], we calculated a < 1% per generation increase in net primary productivity in either high or low density populations (Bazzaz 1995). This result was primarily due to a low correlation between reproductive and vegetative growth enhancement, in spite of relatively high values for the total response to selection. Since data regarding traits selectively favored under rising CO2 are very scant, predictions regarding consequences of evolutionary change to ecosystem processes are largely premature. However, such lack of information does not mean that evolutionary processes could not potentially play an important role in determining future trends in ecosystem function. For example, enhanced root turnover or root exudate production (for reviews see Stulen and den Hertog, 1993; Rogers 1994) may not result in

74

enhanced plant performance. Physiological characteristics that provide the basis for these responses could thus be rapidly selected out of plant populations, depending on genetic variability and fitness consequences. If plants do indeed generally exhibit greatly enhanced levels of belowground carbon release under elevated COs, the evolutionary implications for soil microbes may be very large. In this case, short generation times could facilitate very rapid evolutionary responses, perhaps favoring the ability to rapidly utilize newly available fluxes of belowground carbon. It would be remarkable indeed if a doubling of the primary substrate for the world's most abundant enzyme did not have profound evolutionary implications for the world's autotrophic organisms. The few existing studies documenting genetic variation in plant responses to elevated COs have consistently found that not all genotypes respond positively (cf. Wulff and Alexander, 1985; Curtis 1994; Bazzaz 1995; Wayne and Bazzaz, 1995). In this regard, we may confidently predict, both on the basis of general theory and existing data, that selection under elevated COs will involve some loss of genetic variability in plant populations. This may or may not have long-term repercussions to community composition or ecosystem function. However, because COs-related selection affects all plant populations throughout the globe, such a threat to global genetic resources should be examined in earnest. Even considering massive anthropogenic changes in land use patterns and atmospheric pollutants, globally rising COs could well be the single most profound selective agent affecting our planet's autotrophic organisms.

Recent empirical work has documented substantial intraspecific genetic variation in plant growth responses to elevated CO2. thus raising the issue of selective responses to elevated CO2 in plant populations. In contrast to the well-studied case of selection for heavy-metal tolerance, selection under rising CO2 is likely to be density dependent and contingent on local availability of other plant resources. The component processes of natural selection, namely, the expression of phenotypic variation in fitness, the degree to which this variation is heritable, and genetic covariance of other traits with fitness, may each respond in predictable ways to rising COs conditions. Each of these parameters is examined, with specific reference to reaction norm experiment investigating the responses of genotypes of to population density and COs. Phenotypic variation within plant populations may be enhanced by elevated COs: for example, variation in size-related traits may increase due to accelerated divergence in growth a n d / o r accelerated competitive interactions. Heritabilities of fitness-related

5.

traits m a y o f t e n b e e x p e c t e d to b e h i g h e r , b e c a u s e e l e v a t e d C O 2 c o n s t i t u t e s a n o v e l e n v i r o n m e n t a l state n o t p r e s e n t in t h e r e c e n t selective h i s t o r i e s o f m o s t p l a n t species. G e n e t i c c o r r e l a t i o n s t r u c t u r e m a y also b e a l t e r e d , p e r h a p s d u e to a d i s r u p t i o n o f f u n c t i o n a l i n t e g r a t i o n o f p l a n t d e v e l o p m e n t . E x i s t i n g d a t a s u g g e s t t h a t r i s i n g CO2 levels will h a v e p r o f o u n d selective c o n s e q u e n c e s o n p l a n t p o p u l a t i o n s . H o w e v e r , t h e r e is very little d a t a availa b l e to s u g g e s t w h a t p h e n o t y p i c c h a r a c t e r i s t i c s will u l t i m a t e l y b e s e l e c t e d . T h e c o n s e q u e n c e s o f s u c h s e l e c t i o n o n c o m m u n i t y a n d e c o s y s t e m level p r o c e s s e s a r e also p r e s e n t l y u n c l e a r , a l t h o u g h s e l e c t i o n u n d e r r i s i n g CO2 will n e c e s s a r i l y r e s u l t in s o m e loss o f g e n e t i c v a r i a t i o n a m o n g p l a n t p o p u l a tions.

We thank F. A. Bazzaz for collaboration on the experiment reported here, and for inspiration and discussions of the ideas presented. This work was supported by a grant from the U.S. Department of Energy (DEFGO2 ER 60257).

Ackerly, D. D., and Bazzaz, F. A. (1995). Plant growth and reproduction along C O 2 gradients: Non-linear responses and implications for community change. 1, 199-208. Antonovics, J. (1978). The population genetics of mixtures. "Plant Relations in Pastures" (J. R. Wilson, ed.), pp. 233-252. CSIRO, Melbourne. Antonovics, J., Bradshaw, A., and Turner, R. G. (1971). Heavy-metal tolerance in plants. Res. 7, 1-85. Arnold, S.J., and Wade, M.J. (1984). On the measurement of natural and sexual selection: Theory. 38, 709-719. Arnone, J. A., and K6rner, C. (1993). Influence of elevated CO2 on canopy development and red:far-red ratios in two-storied stands of 94, 510-515. Avery, P.J., and Hill, W. G. (1977). Variability in genetic parameters among small populations. 29, 193-213. Avery, P.J., and Hill, W. G. (1979). Variance in quantitative traits due to linked dominant genes and variance in heterozygosity in small populations. 91, 817-844. Baker, A.J. (1987). Metal tolerance. 106 (Suppl.), 93-111. Barnola, J. M., Raynaud, D., Korotkevich, Y. S., and Lorius, C. (1987). Vostok ice core provides 160,000-year record of atmospheric CO2 329, 408-414. Bazzaz, F. A., and McConnaughay, K. D. M. (1992). Plant-plant interactions in elevated CO2 environments. 40, 547-563. Bazzaz, F. A., Garbutt, K., Reekie, E. G., and Williams, W. E. (1989). Using growth analysis to interpret competition between a C3 and a C4 annual under ambient and elevated CO2. 79, 223-235. Bazzaz, F. A., Bassow, S. L., Berntson, G. M., and Thomas, S. C. (1996). Elevated CO2 and terrestrial vegetation: Implications for and beyond the global carbon budget. "Global

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Change in Terrestrial Ecosystems" (B. Walker and W. Steffen, eds.), pp. 43-76. Cambridge University Press, Cambridge. Bazzaz, F. A., Jasiefiski, M., Thomas, S. C., and Wayne, P. (1995). Microevolutionary responses to elevated CO2 environments in experimental populations of plants: Parallel results from two model systems. 92, 8161-8165. Beerling, D. J., and Chaloner, W. G. (1993). Evolutionary responses of stomatal density to global COs change. 48, 343-353. B6ger, P. (1980). The Os/COscycle: Development and atmospheric consequences. "Biochemical and Photosynthetic Aspects of Energy Production" (A. San Pietro, ed.), pp. 175-190. Academic Press, New York. Bowes, G. (1991 ). Growth at elevated CO2: Photosynthetic responses mediated through rubisco. 14. 795-806. Bowes, G. (1993). Facing the inevitable: Plants and increasing atmospheric COs 44, 309-332. Bradshaw, A. D., and McNeilly, T. (1991). Evolutionary response to global climate change. 67 (Suppl. 1), 5-14. Cannell, R. Q., Brun, W. A., and Moss, D. N. (1969). A search for high net photosynthetic rate among soybean genotypes. Sc/. 9, 840-841. Causton, D. R., and Venus, J. C. (1981). "The Biometry of Plant Growth." Arnold, London. Ceulemans, R., and Mousseau, M. (1994). Effects of elevated atmospheric COs on woody plants. 127, 425-446. Chapin, F. S. I., Autumn, K., and Pugnaire, F. (1993). Evolution of suites of traits in response to environmental stress. 142, $78-$92. Cheverry, J. L., Sy, M. O., Puliqueen J., and Marcellin, P. (1988). Regulation by CO2 of 1aminocyclopropane-l-carboxylic acid conversion to ethylene in climacteric fruits. 72, 535-540. Cheverud, J. M. (1988). A comparison of genetic and phenotypic correlations. 42, 958-968. Clark, A. G. (1987). Genetic correlations: The quantitative genetics of evolutionary constraints. "Genetic Constraints on Adaptive Evolution" (V. Loeschcke, ed.), pp. 25-45. SpringerVerlag, Berlin. Coleman, J. S., and Bazzaz, F. A. (1992). Effects of COs and temperature on growth and resource use of co-occurring C3 and C4 annuals. 73, 1244-1259. Cook, S. C., Lefebvre, C., and McNeilly, T. (1972). Competition between metal tolerant and 26, 366-372. normal plant populations on normal soil. Cowley, D. E., and Atchley, W. R. (1990). Development and quantitative genetics of correlation structure among body parts of 135, 242-268. Crow, J. F. (1958). Some possibilities for measuring selection intensities in man. 30, 1-13. Crow, J. F., and Kimura, M. (1970). "Introduction to Population Genetics Theory." Burgess, Minneapolis, MN. Cure, J. D., and Acock, B. (1986). Crop response to carbon dioxide doubling: A literature survey. 38, 127-145. Curtis, P. S., Snow, A. A., and Miller, A. S. (1994). Genotype-specific effects of elevated CO2 on fecundity in wild radish 97, 100-105. Davies, M. S., and Snagdon, R. W. Rapid population differentiation in a mosaic environment. III. Measures of selection pressures. 36, 59-66. de Jong, G., and van Noordwijk, A.J. (1992). Acquisition and allocation of resources: Genetic (co)variances, selection, and life histories. 139, 749-770. Delgado, E., and Medrano, H. (1991). Field performance and leaf characteristics of L. genotypes selected by low COs survival. 25, 313-322.

5.

77

Delgado, E., Parry, M. A. J., Vadell, J., Lawlor, D. W., Keys, A.J., and Medrano, H. (1992a). Effects of water stress on photosynthesis, leaf characteristics, and productivity of field-grown L. genotypes selected for survival at low CO2 43, 1001-1008. Delgado, E., Azc6n-Bieto, J., Aranda, X., Palaz6n, J., and Medrano, H. (1992b). Leaf photosynthesis and respiration of high CO2-grown tobacco genotypes selected for survival in a low CO2 atmosphere. 98, 949-954. Delgado, E., Parry, M. A.J., Lawlor, D. W., Keys, A.J., and Medrano, H. (1993). Photosynthesis, ribulose-l,5-bisphosphate carboxylase, and leaf characteristics of L. genotypes selection by survival at low CO2 concentrations. J. 44, 1-7. Enoch, H. Z., and Honour, S.J. (1993). Significance of increasing ambient CO2 for plant growth and survival, and interactions with air pollution. "Interacting Stresses on Plants in a Changing Climate" (M. B. Jackson and C. R. Black, eds.), pp. 51-76. SpringerVerlag, Berlin. Fajer, E. D., Bowers, M. D., and Bazzaz, F. A. (1992). The effect of nutrients and enriched CO2 environments on production of carbon-based allelochemicals in A test of the carbon/nutrient balance hypothesis. 140, 707-723. Falconer, D. S. (1952). The problem of environment and selection. 86, 293-298. Falconer, D. S. (1989). "Introduction to Quantitative Genetics," 3rd ed. Longman, London. Farnsworth, E. J., and Bazzaz, F. A. (1995). Inter- and intra-generic differences in growth, reproduction, and fitness of nine herbaceous annual species grown in elevated CO2 environments. 104, 454-466. Fisher, R. A. (1930). "The Genetical Theory of Natural Selection." Clarendon, Oxford. Gadgil, M., and Bossert, W. H. (1970). Life historical consequences of natural selection. 104, 1-24. Garbutt, tC, and Bazzaz, F. A. (1984). The effects of elevated CO2 on plants. III. Flower, fruit and seed production and abortion. 98, 433-446. Geber, M. A. (1990). The cost of meristem limitation in Negative genetic 44, 799-819. correlations between fecundity and growth. Geber, M. A., and Dawson, T. E. (1993). Evolutionary responses of plants to global change. "Biotic Interactions and Global Change" (P. M. Kareiva, J. G. Kingsolver, and R. B. Huey, eds.), pp. 179-197. Sinauer, Sunderland, MA. Giesel, J. T., Murphy, P. A., and Manlove, M. N. (1982). The influence of temperature on genetic interrelationships of life history traits in a population of What tangled data sets we weave. 119, 464-479. Gomulkiewicz, R., and Kirkpatrick, M. (1992). Quantitative genetics and the evolution of reaction norms. 46, 390-411. Harper, J., and White, J. (1974). The demography of plants. 5, 419-463. Hartnett, D. C. (1990). Size-dependent allocation to sexual and vegetative reproduction in four clonal composites. 84, 254-259. Hickey, D. A., and McNeilly, T. (1975). Competition between metal tolerant and normal plant populations: A field experiment on normal soil. 29, 458-464. Hill, W. G., and Caballero, A. (1992). Artificial selection experiments. 23, 287-310. Holsinger, K. E., and Pacala, S. W. (1990). Multiple-niche polymorphisms in plant populations. 135, 301-309. Horton, R. F. (1985). Carbon dioxide flux and ethylene production in leaves. "Ethylene and Plant Development" (J. A. Roberts and G. A. Tucker, eds.), pp. 37-46. Butterworths, London. Houghton, J. T., Callander, B. A., and Varney, S. K. (1992). "Climate Change 1992: The Supplementary Report to the IPCC Scientific Assessment." Cambridge Univ. Press, Cambridge,UK. Houle, D. (1992). Comparing evolvability and variability of quantitative traits. 130, 195-204.

Itoh, Y., and Yamada, Y. (1990). Relationships between genotype x environment interaction and genetic correlation of the same trait measured in different environments. 80, 11-16. Kawano, S., Hayashi, S., Aria, H., Yamamoto, M., Takasu, H., and Oritani, T. (1989). Regulatory mechanisms of reproductive effort in plants. III. Plasticity in reproductive energy allocation and propagule output of two grass species, cv. Akihikarai and cultivated at varying densities and nitrogen levels, and the evolutionary-ecological implications. 4, 75-99. Kimball, B. A. (1983). Carbon dioxide and agricultural yield: An assemblage and analysis of 430 prior observations. 75, 779-788. Kirkpatrick, M., and Lofsvold, D. (1989). The evolution of growth trajectories and other complex quantitative characters. 31, 778-783. Kirkpatrick, M., and Lofsvold, D. (1992). Measuring selection and constraint in the evolution of growth. 46, 954-971. Kirkpatrick, M., Lofsvold, D., and Bulmer, M. (1990). Analysis of the inheritance, selection, and evolution of growth trajectories. 124, 979-993. Kirkpatrick, M., Hill, W. G., and Thompson, R. (1994). Estimating the covariance structure of traits during growth and aging, illustrated with lactation in dairy cattle. 64, 57-69. Koyama, H., and Kira, T. (1956). Intraspecific competition among higher plants. VIII. Frequency distribution of individual plant weight as affected by the interaction between plants. D 7, 73-94. Lande, R. (1979). Quantitative genetic analysis of multivariate evolution, applied to brain: Body size allometry. 33, 402-416. Lande, R. (1982). A quantitative genetic theory of life history evolution. 63, 607-615. Eomnicki, A. (1988). "Population Ecology of Individuals." Princeton Univ. Press, Princeton, NJ. Lynch, M., and Lande, R. (1993). Evolution and extinction in response to environmental change. "Biotic Interactions and Global Change" (P. M. Kareiva, J. G. Kingsolver, and R. B. Huey, eds.), pp. 234-250. Sinauer, Sunderland, MA. MacNair, M. R. (1977). Major genes for copper tolerance in 268, 428-430. MacNair, M. R. (1991). The genetics of metal tolerance in natural populations. "Heavy Metal Tolerance in Plants: Evolutionary Aspects" (A. J. Shaw, ed.), pp. 235-253. CRC Press, Boca Raton, FL. MacNair, M. R., Smith, S. E., and Coumbes, Q.J. (1993). Heritability and distribution of variation in degree of copper tolerance in at Copperopolis, California. 71, 445-455. Maxon-Smith, J. W. (1977). Selection for response to CO2-enrichment in glasshouse lettuce. 17, 15-22. Mazer, S. J., and Schick, C. T. (1991). Constancy of population parameters for life-history and floral traits in L. II. Effects of planting density on phenotype and heritability estimates. 45, 1888-1907. McLauglin, S. B., and Norby, R.J. (1991). Atmospheric pollution and terrestrial vegetation: Evidence of changes, linkages, and significance to selection processes. "Ecological Genetics and Air Pollution" (G. E. Taylor, L. F. Pitelka, and M. T. Clegg, eds.), pp. 61-102. Springer-Verlag, Berlin. McNeilly, T. (1968). Evolution in closely adjacent plant populations. III. tenuis on a small copper mine. 23, 99-108. Menz, K. M., Moss, D. N., Cannell, R. Q~, and Brun, W. A. (1969). Screening for photosynthetic efficiency. 9, 692-694.

5.

79

Mitchell-Olds, T., and Rutledge,J.J. (1986). Quantitative genetics in natural plant populations: A review of the theory. 127, 379-402. Morse, S. R., and Bazzaz, F. A. (1994). Elevated COz and temperature alter recruitment and size hierarchies in C3 and C4 annuals. 75, 966-975. Musgrave, M. E., Strain, B. R., and Siedow, J. N. (1986). Response of two pea hybrids to CO2 enrichment: A test of the energy overflow hypothesis for alternative respiration. 83, 8157-8161. Namkoong, G., Bishir, J., and Roberds, J. H. (1993). Evolutionary effects of density-dependent selection in plants. 62, 57-62. Noordwijk van, A.J., and de Jong, G. (1986). Acquisition and allocation of resources: Their influence on variation in life history tactics. 128, 137-142. Pefiuelas, J., and Matamala, R. (1990). Changes in N and S leaf content, stomatal density and specific leaf area of 14 plant species during the last three centuries of CO2 increase. 41, 1119-1124. Poorter, H. (1993). Interspecific variation in the growth response of plants to an elevated ambient CO2 concentration. 104/105, 77-97. Reekie, J. Y. C., Hicklenton, P. R., and Reekie, E. G. (1994). Effects of elevated CO2 on time 72, 533-538. of flowering in four short-day and four long-day species. Rice, K.J. (1990). Reproductive hierarchies in Effects of variation in plant density and rainfall distribution. 71, 1316-1323. Riska, B. (1989). Composite traits, selection response, and evolution. 43, 1172-1191. Roff, D. A. (1995). The estimation of genetic correlations from phenotypic correlations: A test of Cheverud's conjecture. 74, 481-490. Rogers, H. H., Cure, J. D., Thomas, J. F., and Smith, J. M. (1984). Influence of elevated CO2 24, 361-366. on growth of soybean plants. Rogers, H. H., Runion, G. B., and Krupa, S. V. (1994). Plant responses to atmospheric CO2 enrichment with emphasis on roots and the rhizosphere. 83, 155-189. Roose, M. L. (1991). Genetics of response to atmospheric pollutants. "Ecological Genetics and Air Pollution" (G. E. Taylor, L. F. Pitelka, and M. T. Clegg, eds.), pp. 111-126. Springer-Verlag, Berlin. Samson, D. A., and Werk, K. S. (1986). Size-dependent effects in the analysis of reproductive effort in plants. 127, 667-680. Schimper, A. F. W. (1935). "Pflanzengeographie auf physiologischer Grundlage," 3rd ed. Fischer, Jena. Schmalhausen, I. I. (1949). "Factors of Evolution: The Theory of Stabilizing Selection." Univ. Chicago Press, Chicago. Service, P. M., and Rose, M. R. (1985). Genetic covariation among life-history components: The effect of novel environments. 39, 943-945. Shaw, A.J., ed. (1991a). "Heavy Metal Tolerance in Plants: Evolutionary Aspects." CRC Press, Boca Raton, FL. Shaw, R. G. (1991b). The comparison of quantitative genetic parameters between populations. 45, 143-151. Shaw, R. G., and Platenkamp, G. A.J. (1993). Quantitative genetics of response to competitors in 47, 801-812. Smart, D. R., Chatterton, N. J., and Bugbee, B. (1994). The influence of elevated CO2 on nonstructural carbohydrate distribution and fructan accumulation in wheat canopies. 17, 435-442. Spicer, R. A., and Corfield, R. M. (1992). A review of terrestrial and marine climates in the Cretaceous with implications for modelling the 'Greenhouse Earth.' 129, 169-180.

Stitt, M. (1991). Rising CO2 levels and their potential significance for carbon flow in photosynthetic cells. 14, 741-762.

80

Strain, B. R. (1991). Possible genetic effects of continually increasing atmospheric CO2. "Ecological Genetics and Air Pollution" (G. E. Taylor, L. F. Pitelka, and M. T. Clegg, eds.), pp. 177-202. Springer-Verlag, Berlin. Strain, B. R., and Cure, J. D. (1985). "Direct Effects of Increasing Carbon Dioxide on Vegetation." United States Dept. of Energy, Carbon Dioxide Research Division, DOE/ER 0238, Office of Energy Research, Washington, DC. Stulen, I., and den Hertog, J. (1993). Root growth and functioning under atmospheric CO2 enrichment. 104/105, 99-115. Tans, P. P., Fung, I. Y., and Takahashi, T. (1990). Observational constraints on the global atmospheric CO2 budget. 247, 1431-1438. Thomas, S. C., and Bazzaz, F. A. (1993). The genetic component in plant size hierarchies: Norms of reaction to density in a species. 63, 231-249. Thomas, S. C., and Bazzaz, F. A. (1996). Elevated CO~ and leaf shape: Are dandelions getting toothier? 83, 106-111. Thomas, S. C., and Weiner, J. (1989). Growth, death and size distribution change in an population. 77, 524-536. Tolley, L. C., and Strain, B. R. (1984). Effects of CO2enrichment on growth of and seedlings under different irradiance levels. 14, 343-350. Tremmel, D. C., and Patterson, D. T. (1994). Effects of elevated CO~ and temperature on development in soybean and five weed. 74, 43-50. Turelli, M. (1988). Phenotypic evolution, constant covariances, and the maintenance of additive variance. 42, 1342-1347. Uchmafiski, J. (1985). Differentiation and frequency distributions of body weights in plants and animals. 310, 1-75. Via, S. (1987). Genetic constraints on the evolution of phenotypic plasticity. "Genetic Constraints on Adaptive Evolution" (V. Loeschcke, ed.), pp. 47-71. Springer-Verlag, Berlin. Via, S., and Lande, R. (1985). Genotype-environment interaction and the evolution of phenotypic plasticity. 39, 505-522. Von Faber, F. C. (1925). Untersuchungen fiber die Physiologie der javanischen SolfatarenPhflanzen. 18/19, 89. Von Faber, F. C. (1927). Die Kraterpflanzen Javas in physiologisch-tkologischer Beziehung. no. 1. Wade, M.J. (1985). Soft selection, hard selection, kin selection, and group selection. 125, 61-73. Wallace, B. (1968). Polymorphism, population size, and genetic load. "Population Biology and Evolution" (R. C. Lewontin, ed.), pp. 87-108. Columbia Univ. Press, New York. Walters, M. B., Kruger, E. L., and Reich, P. B. (1993). Growth, biomass distribution and CO2 exchange of northern hardwood seedlings in high and low light: Relationships with successional status and shade tolerance. 94, 7-16. Wayne, P. M., and Bazzaz, F. A. (1995). Seedling density modifies the growth response of yellow birch maternal families to elevated carbon dioxide. 1,315-324. Weiner, J. (1985). Size hierarchies in experimental populations of annual plants. 66, 743-752. Weiner, J. (1988). The influence of competition on plant reproduction. "Reproductive Ecology of Plants: Patterns and Strategies" (J. Lovett-Doust and L. Lovett-Doust, eds.), pp. 228-245. Oxford Univ. Press, New York. Weiner, J. (1990). Asymmetric competition in plant populations. 5, 360-364. Weiner, J., and Thomas, S. C. (1986). Size variability and competition in plant monocultures. 47, 211-222. Wilkinson, G. S., Fowler, K., and Partridge, L. (1990). Resistance of genetic correlation structure to directional selection in 44, 1990-2003.

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01

Willis, J. H., Coyne, J. A., and Kirkpatrick, M. (1991). Can one predict the evolution of quantitative characters without genetics? 45, 441-444. Wilson, J. B., and Levin, D. A. (1986). Some genetic consequences of skewed fecundity distributions in plants. 73, 113-121. Woodward, F. I. (1987). Stomatal numbers are sensitive to increases in COzfrom pre-industrial levels. 327, 617-618. Wulff, R. D., and Alexander, H. M. (1985). Intraspecific variation in the response to COz enrichment in seeds and seedlings of 66, 458-460. Young, H.J., Stanton, M. L., Ellstrand, N. C., and Clegg, J. M. (1994). Temporal and spatial variation in heritability and genetic correlations among floral traits in wild radish. 73, 298-308. Zeng, Z.-B. (1988). Long-term correlated response, interpopulation covariation, and interspecific allometry. 42, 363-374. Ziska, L. H., and Teramura, A. H. (1992). Intraspecific variation in the response of rice (Oryza to increased COzmPhotosynthetic, biomass and reproductive characteristics. 84, 269-276.

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II Community-Level Responses

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The Changing Vegetation of Europe: What Is tile Role of Elevated Carbon Dioxide?

Although there is no doubt that atmospheric carbon dioxide concentrations are rising rapidly (Keeling 1982) and will continue to do so (IPCC, 1992), there is considerable uncertainty with regard to the consequences for plant communities and ecosystems (Korner, 1993). The difficulties in predicting the impact of elevated CO2 first become evident in the laboratory or growth chamber and multiply as we move outdoors and begin to consider large-scale processes operating over extended periods of time. From laboratory studies we know that plant species differ in responsiveness to elevated CO2 (Hunt 1991; Poorter, 1993) and we may be certain that patterns of response detected under controlled conditions will be subject, in more natural habitats, to the modifying effects of other environmental factors, some of which (temperature, rainfall, UV-B) are themselves implicated in global environmental change. At this point in the analysis it is tempting to conclude that the task of predicting the ecological impacts of rising CO2 falls almost exclusively in the domain of plant physiology (e.g., Schulze and Mooney, 1993). Little doubt remains that physiological insights are needed for a mechanistic and predictive understanding of vegetation responses to elevated CO2. However, in this chapter I shall argue that the most urgent requirement is to place CO2 research in the context of other global and regional changes in vegetation driven by more powerful forces. and

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Copyright 9 1996 by Academic Press, Inc. All rights of reproduction in any form reserved.

At the present time, the most potent forces for change acting on vegetation are the effects of land use. These arise from the direct effects of human activity (habitat modification by agriculture, forestry, industry, human settlements, overgrazing) and indirect effects (eutrophication through groundwater and atmospheric pollutants, and phytotoxicity resulting from aerial and soil contamination). Reviewed on a world scale, the most consistent effect of these phenomena is the inexorable replacement of mature, often species-rich ecosystems by early successional states in which the vegetation is composed of recently established, fast-growing clonal herbs and ephemeral species. This process has two important implications for studies which seek to predict the impacts of rising CO2. The first is the notion that vegetation is already experiencing such radical processes of change that impacts of CO2 are perhaps most appropriately analyzed as a fine-tuning of the rates and trajectories of changes which are already well advanced and are driven by land use. The second implication arises from the faster growth rates and reduction in the average life span in the constituent species of vegetation arising from modern forms of intensive or disruptive land use (Grime 1988). Later in this chapter we will examine evidence that these expanding species are more responsive to elevated CO2. Moreover, the higher rates of population turnover characteristic of the vegetation of disturbed and intensively exploited landscapes create conditions in which the plant cover is likely to respond more quickly to selection driven by elevated CO2 either by permitting more invasions and extinctions or by allowing rapid genetic changes within component populations. Hence land use is likely to be an essential factor in any calculations of the direction and rate of vegetation responses to elevated CO2. In order to explore further the interaction between changing land use and CO2 responses, let us now look at recent evidence of floristic change in Western Europe.

In a comparative discriminant analysis of the functional traits of increasing and decreasing species in the vascular plant floras of the British Isles, The Netherlands, and West Germany (Thompson, 1994), three main conclusions have been drawn: 1. A key measure discriminating between increasing and decreasing species is S radius. S radius is a measure of proximity to the stress-tolerant corner of a CSR strategic triangle of plant functional types (Grime, 1974; Grime 1988); a large S radius is correlated with low growth rate, low rates of tissue turnover, and low mineral nutrient requirements. In densely

6.

populated England, the Netherlands, and to a lesser extent, West Germany, decreasing species are stress-tolerators (large S radius), whereas increasing species are fast-growing and typical of eutrophic, disturbed habitats. 2. In the sparsely populated northern and western regions of the British Isles differences between "winners" and "losers" are very slight. 3. Surprisingly, regenerative attributes (seed weight, seed persistence in soil, wind dispersal) are very poor predictors of success and failure in the modern northwest European landscape. The same sources are used in Fig. I to plot the mean Sradius of increasing and decreasing species against human population density in seven European countries. Thompson's (1994) interpretation of these results accords with an earlier hypothesis of Hodgson (1986a,b) in suggesting that in the densely populated countries of Western Europe, land use is increasingly polarizing the flora into two parts. The successful, fast-growing part is tolerant of human activities and is ecologically attuned to intensively managed grassland, arable fields, road verges, gardens, spoil, and urban waste-

Figure 1 Relationship between mean S radius of increasing and decreasing species and h u m a n population density in seven European countries. S radius of the two groups is not significantly different in Scotland, N. Ireland, or Wales. The two groups are significantly different in Republic of Ireland (P = 0.049), England, western Germany, and The Netherlands (all P < 0.001).

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j. t'. ~ m e

land. Because these habitats are common, and because soils, seeds, and plant fragments are moved freely between them by human agencies, these plants are highly mobile, rapidly colonizing new sites as they become available. Species of this type will have little difficulty in migrating in response to land use change. In contrast, the slow-growing, stress-tolerant part of the flora, typical of unimproved grassland, lowland heath and old woodland, is increasingly excluded from the wider landscape. How will rising COs influence these vegetation changes resulting from land use? Has responsiveness to COs concentration already played a significant role in the promotion of fast-growing, resource-demanding species in intensively developed landscapes? To address these questions it is necessary to consider our present understanding of how different types of plants respond to elevated COs.

Over the period from 1987 to 1994 a comprehensive screening program (Integrated Screening Programme, ISP) was conducted at Sheffield (with links to other centers) to compile standardized information on the laboratory characteristics of a large number of common herbaceous vascular plants of the British Isles. As part of the ISP a series of CO2 screening experiments were carried out at Horticulture Research International's site at Littlehampton (Hunt 1991, 1993, and 1995). These experiments covered 36 different species; many of them were later restudied to provide confirmation. Strong responses to elevated CO2 were recorded when plants were held at 18~ In some species there was a 27% increase in biomass after only 8 weeks' growth. However, such levels of response mainly occurred in robust, fast-growing perennials (e.g., of the kind which often dominate vegetation in productive and undisturbed habitats, such as river banks and recently abandoned farmland and gardens. These plants exhibit sustained vegetative growth and develop large roots, shoots, and storage organs prompting the hypothesis that responsiveness to elevated COs may be related to possession of rapidly expanding carbon sinks. This interpretation is supported by the observation (Hunt 1995) that the benefit of elevated COs to the fast-growing ephemeral, is not sustained beyond the early vegetative phase of development. A consistent feature of the ISP results has been the low level of response by slowgrowing evergreen species of unproductive habitats (i.e., high S radius plants). These results suggest that the capacity to respond strongly to elevated COs is prominent among the species that are currently expanding in abundance in the more intensively developed landscapes of heavily populated countries of Western Europe.

89

6.

The need for caution in extrapolating from the responses of individual potted plants in growth chambers to the dynamics of communities of plants in the field is self-evident. The majority of laboratory studies (including the ISP) are designed to standardize conditions and facilitate comparison and interpretation. Realism is sacrificed to the extent that the complexities of season, weather, soil microbiology, decomposition, nutrient dynamics, interspecific competition, and plant-animal interactions are excluded. Some insights into the complications that can arise when attention is turned to "real" systems are evident in Fig. 2 (A,B), which presents results from an experiment (Diaz 1993) in which early-successional plant communities were allowed to reassemble from natural seed banks and soils removed to

Shoot biomass n

s

Cover

~

~ n s

Dominance Carbohydrates Nitrogen SOIL 9

Microbial N ..

-40

-30

-20

-10

0

10

20

30

MicrobialC 40

% change under doubling CO2 Figure 2 (A) Responses of and soil microflora grown in microcosms to a doubling of atmospheric CO2 (700 ppm) as compared to controls at 350 ppm. Vegetation was allowed to develop for 84 days by natural recruitment from seed banks in soils removed from a tall herb community in Derbyshire and placed in microcosms (6 replicates per treatment) in cabinets without nutrient addition. Shoot biomass was measured as milligram dry weight, cover as n u m b e r of touches in a point-quadrat analysis, dominance as biomass of R. total community biomass, carbohydrates (starch + glucose + sucrose) as milligram/gram fresh weight and nitrogen as milligram/gram dry weight of fully expanded young leaves, microbial C and N as milligram/gram dry soil; ns, nonsignificant; *, P < 0.05; **, P < 0.01 (ANOVA). (B) Effects of atmospheric doubling of CO2 concentration (ppm) and fertilizer addition on foliar N content of grown in microcosm for 60 days. Deionized water (control) and full-strength Rorison solution (fertilized) were added throughout the experiment as 100 ml per microcosms every 4 days. Bars designated by the same letter are not different at P < 0.05 (ANOVA).

90

j.P. Gr/me 25 o l

2 0 ow

15 o l

Q ~

10~

z

5 --

0

~ 350 ppm

700 ppm

Continued

laboratory microcosms providing ambient and elevated

CO

2 concentra-

tions.

In the example shown in Fig. 2A the potentially responsive showed leaf stunting when exposed to elevated CO2. These symptoms coincided with carbohydrate accumulation and reduced levels of foliar nitrogen. From soil analyses, circumstantial evidence showed that deficiency had been induced by export of carbohydrate from roots to soil and subsequent sequestration of nitrogen in a massively expanded soil microflora. This hypothesis was supported by the results of a second experiment (Fig. 2B) in which the leaf nitrogen content of plants grown at elevated CO2 did not increase when additional mineral nutrients were added to the soil. These results are a useful reminder of the feedbacks that can occur in response to elevated CO2. Species responses within ecosystems are likely to be determined by factors such as soil microbiology, which are additional to those (e.g., sink strength) that emerge as key factors in simple laboratory assays.

6.

91

This chapter assembles circumstantial evidence that the types of herbaceous plants which are currently expanding in a b u n d a n c e in heavily populated countries of Western Europe are also strongly responsive to elevated concentrations of carbon dioxide. This evidence suggests that responses to carbon dioxide may be contributing to the recent success of these species. An attractive feature of this hypothesis is the observation that the responsive species occupy habitats in which other essential resources are relatively a b u n d a n t and are unlikely, therefore, to limit the stimulatory effect of carbon dioxide enrichment. There are several reasons why we should treat this interpretation with caution. The data comparing responses to elevated CO2 are based on simplified laboratory conditions and refer mainly to herbaceous plants grown for short periods of time with nonlimiting supplies of moisture and mineral nutrients. It may be especially i m p o r t a n t to recognize that on natural soils responses to CO2 may be limited by n u t r i e n t stress arising from microbial sequestration of mineral nutrients. In attempts to u n d e r s t a n d the interactions between land use and elevated CO2 it may be essential to differentiate between short and long cycles of secondary succession. Where vegetation destruction and mineral n u t r i e n t release occurs frequently, it seems likely that selection associated with elevated CO2 may act in parallel with eutrophication in p r o m o t i n g fast-growing clonal herbs. However, it can be argued that where the intervals between major disturbance events are longer (coppiced woodlands, plantations, long-rotation grasslands, b u r n e d heathlands), elevated CO2 could accelerate succession by favoring plants that develop m o r e slowly but provide m o r e substantial sinks for carbon and mineral nutrients. These hypotheses require experiments of sufficient scale and duration to allow rigorous tests of the effects of CO2 e n r i c h m e n t on successional processes.

This chapter draws on information collected with colleagues at UCPE as part of the Integrated Screening Programme and the Terrestrial Initiative in Global Environmental Research, both of which are supported by the Natural Environment Research Council.

Diaz, S., Grime,J. P., Harris,J., and McPherson, E. (1993). Evidence of a feedback mechanism limiting plant response to elevated carbon dioxide. 364, 616-617.

Grime, J. P. (1974). Vegetation classification by reference to strategies. 250, 26-31. Grime, J. P., Hodgson, J. G., and Hunt, R. (1988). "Comparative Plant Ecology: A Functional Approach to Common British Plants." Unwin Hyman, London. Hodgson, J. G. (1986a). Commonness and rarity in plants with special reference to the Sheffield flora. I. The identity, distribution, and habitat characteristics of the common and rare species. 36, 199-252. Hodgson, J. G. (1986b). Commonness and rarity in plants with special reference to the Sheffield flora. II. The relative importance of climate, soils, and land use. 36, 254-274. Hunt, R., Hand, D. W., Hannah, M. A., and Neal, A, M. (1991). Response to COz enrichment in 27 herbaceous species. 5, 410-421. Hunt, R., Hand, D. W., Hannah, M. A., and Neal, A. M. (1993). Further responses to CO2 enrichment in British herbaceous species. 7, 661-668. Hunt, R., Hand, D. W., Hannah, M. A., and Neal, A. M. (1995). Temporal and nutritional influences on the CO2 response in selected British grasses. 76, 207-216. International Panel on Climate Change Report (1992). "Climate Change 1992: The Supplementary Report to the IPCC Scientific Assessment." Cambridge Univ. Press, Cambridge, UK. Keeling, C. D., Bacastow, R. B., and Whorf, T. P. (1982). Measurements of the concentration of carbon dioxide at Mauna Loa Observatory, Hawaii. "Carbon Dioxide Review" (W. C. Clark, ed.). Korner, C. H. (1993). CO2 fertilization: The great uncertainty in future vegetation development. "Vegetation Dynamics and Global Change" (A. M. Solomon and H. H. Shugart, eds.), pp 53-70. Chapman and Hall, London. Poorter, H. (1993). Interspecific variation in the growth response of plants to an elevated ambient CO2 concentration. 104/105, 77-97. Schulze, E. D., and Mooney, H. A., eds. (1993). "Design and Execution of Experiments on CO2 Enrichment." Commission of the European Communities, Brussels. Thompson, K. (1994). Predicting the fate of temperate species in response to human disturbance and global change. "NATO Advanced Research Workshop on Biodiversity, Temperate Ecosystems, and Global Change" (T. J. B. Boyle and C. E. B. Boyle, eds.), pp. 6176. Springer Verlag, Berlin.

7 Changing Community Composition and Elevated CO2

Anthropogenic forcing of biogeochemical cycles, such as the global carbon cycle, can potentially alter community composition (e.g., Bazzaz and Carlson, 1984; Bazzaz and Fajer, 1992; Melillo 1990; Gates, 1994). Likewise, alterations in the species composition of communities can alter ecosystem processes (Tilman and Downing, 1994; Naeem 1994a, 1995; Schulze and Mooney, 1993). Together these interactions describe a potential feedback between changing levels of biotic diversity and changing levels of CO2. This potential feedback between biotic diversity and the carbon biogeochemical cycle may be significant on a global scale. Ecosystems worldwide are simultaneously experiencing both anthropogenic alterations in diversity (e.g., Wilson and Peter, 1988; Soul~, 1991; Ehrlich and Wilson, 1991; Groombridge, 1992; Sisk 1994) and anthropogenic increases in atmospheric CO2. Such feedbacks between biotic factors and biogeochemical cycles are important for modeling global change (Lashof, 1989; Schneider, 1992). Empirical evidence for the feedback between diversity and carbon cycling is limited. We present, however, evidence from two mesocosm experiments using a controlled environmental facility referred to as the "Ecotron" 93

Copyright 9 1996 by Academic Press, Inc. All rights of reproduction in any form reserved.

94 (Lawton 1993) which support the possibility of interactions between community composition and C02 flux through an ecosystem (biomass accumulation) and the possible feedback between them. In the first experiment, henceforth the "biodiversity experiment," community composition was manipulated and ecosystem biomass accumulation was measured as a response variable. In the second, henceforth the "elevated C02 experiment," C02 levels were manipulated and community composition and biomass accumulation were measured as response variables. We discuss the implications of these results for global-change research on elevated C02.

A. The Biodiversity Experiment The Ecotron is described in both Lawton (1993) and Thompson (1993). The materials, methods, and results concerning the association between biodiversity and ecosystem functioning (the biodiversity experiment) can be found in Naeem (1994a,b, 1995). Briefly, in this experiment plant and animal species composition within model terrestrial communities were experimentally manipulated to produce 3 levels of diversity: low (4 replicates), intermediate (4 replicates), and high diversity (6 replicates) mesocosms (see Table I for a list of species). The Ecotron consists of 16 chambers which are divided into 2 banks of 8 chambers each. Because each bank is serviced by separate environmental regulating machinery, random assignment of treatments to chambers was statistically blocked by bank to test for block effects. Diversity was manipulated in all trophic levels (Table I). CO2 flux was measured continuously throughout the experiment after Day 120 (total experiment duration was 210 days), but only data collected over 48-hour periods, on a biweekly basis, when chambers were closed and undisturbed by the activities of researchers, were used for statistical analyses. B. The Elevated CO2 Experiment This experiment conducted in the Ecotron consisted of one bank of chambers with eight replicate mesocosms exposed to ambient levels of CO2 and eight replicates of the second bank exposed to ambient +200 ppm CO2. CO2 flux was measured as above, but data used for statistical analyses were collected weekly. C. Differences between the Two Experiments Although the edaphic, daily temperature and humidity conditions were the same for both experiments, the elevated CO2 experiment differed from the biodiversity experiment in several significant ways. First, more light

Biodiversity Species

Low

Int.

High

C02

Plants

u

Animals Mollusk

Earthworm W o o d louse Collembola

cf. cf. Insect herbivores

Parasitoids

a Note similarities in community composition between intermediate (Int.) diversity treatment and the current COs experiment.

96 (18% full sunlight) was provided in the elevated C O 2 experiment (10% full sunlight was provided for the biodiversity experiment). Second, though trophic complexity and number of species were similar between the elevated CO2 experiment and the intermediate-diversity treatment of the biodiversity experiment, some species substitutions were made (Table I). Third, unlike the biodiversity experiment, the Ecotron does not permit random assignment of atmospheric treatments, such as ambient versus elevated CO2, to replicate mesocosms. This results in a pseudoreplicated design which necessitates a follow-up experiment in which treatments to banks (enhanced and ambient CO2) are reversed (currently running, but not reported here). Fourth, injection of augmented CO2 into the atmospheric stream servicing the elevated CO2 communities occasionally resulted in spurious levels of recorded CO2 exhausts in five of the eight chambers during the period of measurement reported here (the problem has since been rectified). We therefore estimated COz flux using only the chambers (chambers 3, 5, and 6) whose CO2 flux readings were not suspect. Finally, periodic harvests were conducted for standing biomass estimation. This practice periodically reduced net CO2 flux.

The biodiversity experiment showed that manipulating community composition alters biomass accumulation, as measured by CO2 flux (Fig. 1). In our model system, higher diversity assemblages sequestered more carbon, a result that is robust for other combinations of plant species (Naeem 1994a, 1995). Although communities rarely differed within intervals, over the duration of the experiment a repeated measures analysis of variance (RMANOVA) showed that higher diversity communities sequestered more carbon than lower diversity communities (RMANOVA; among group = 2, 8; F = 4.5; P < 0.05; interaction = 22, 88; F = 2.7; P < 0.001). Results from the CO2 experiment show that overall levels of biomass accumulation (as measured by COz flux) are statistically different between ambient and elevated CO2 communities of intermediate diversity (RMANOVA; = 26, 1; F = 5.6; P < 0.001, Fig. 1). Note that this statistic was obtained by the conservative method of comparing weekly mean CO2 fluxes of elevated CO2 communities with the weekly mean COz fluxes of ambient CO2 communities. Periodic harvests, estimates of community composition, and additional analyses reveal that a complex number of ecological changes over the course of the experiment are associated with these results. These results are still in a preliminary form and will be reported in detail elsewhere.

7.

97

Figure 1 CO~ flux (mol m -2 d -x) in the biodiversity and elevated experiments. Time is measured in weeks from start of experiment. For the purposes of comparison, this figure shows only a partial set (that which corresponds temporally to the shorter sequence in the biodiversity experiment) of the data from the elevated CO2 experiment. Arrows indicate harvest dates ("winters") in which most of the vegetation is removed and the system is allowed to recover. The top graph (a) plots results from the elevated COs experiment. The lower graph (b) plots results from the biodiversity experiment. Note that negative values indicate sequestered carbon whereas positive values indicate greater microbial, invertebrate, and plant respiration than photosynthetic activity. Note also the different scales and note the greater negative values for the elevated CO2 experiment are partly the result of additional light provided in this experiment. Error bars represent one SE. AMB, ambient CO2; ELEV, elevated CO2; HI, high diversity; INT, intermediate diversity; LOW, low diversity.

Results from these experiments suggest that declining diversity within an ecosystem can decrease biomass accumulation and, conversely, that elevated CO2 can change the biomass accumulation of an ecosystem. Interpreted more broadly, our results suggest that ecosystem response to elevated CO2 is a function of both diversity and CO2 levels.

Though biomass accumulation may be trivially a function of the species found within an ecosystem, the response of biomass accumulation to random declines in diversity is not a trivial problem. For example, neither theory nor experiments in intercropping provide steadfast rules for how diversity and yield (biomass accumulation) might be associated in even simple agroecosystems (Vandermeer, 1989; Swift and Anderson, 1993). Our biodiversity experiment suggested that if a decline in plant diversity is associated with decreasing interception of light by the canopy, then CO2 sequestration by an ecosystem may decline. Our elevated CO2 experiment, however, suggests that changes in ecosystem biomass accumulation generated by elevated COz could compensate for such a loss of carbon sequestration. Although we cannot readily extrapolate from these simple experimental systems to larger more complex naturally occurring systems, these experiments point to an often neglected possibility that understanding how ecosystems will respond to elevated COz will be a function of how diversity changes over the next few decades. Our results suggest that manipulating both CO2 and community composition may improve our understanding of global change. Most research on the ecological consequences of elevated CO2 has been conducted using, on average, 550-700 ppm CO2, or levels likely to occur 50-60 years from now (Houghton 1990) and this research has rarely manipulated community composition. By the time these 50-60 years pass, changing COz, in addition to many other globally changing factors (e.g., N fertilization and habitat fragmentation) (Vitousek, 1994), may have already changed community composition. Indeed, some authors (e.g., K6rner, Chapters 11 and 28; Polley 1994, and Chapter 12) have argued that some of these effects have already occurred. Even without the effects of elevated CO2, the community composition of most ecosystems is likely to be substantially altered in the near future (e.g., Wilson and Peter, 1988; Soul6, 1991; Ehrlich and Wilson, 1991; Groombridge, 1992; Sisk 1994; Lawton and May, 1995). Understanding the interactions and feedbacks between ecosystem processes and community composition and how human impacts contribute to these processes will prove useful for predicting and understanding the effects of elevated CO2 on global change.

Current research on the ecological consequences of elevated C O 2 supports two direct interactions between communities and atmospheric CO2. First, altering levels of CO2 can change the relative abundance of species in communities. Second, altering the species composition of communities can change the ecosystem's ability to absorb CO2 (accumulate biomass).

7.

99

T h e s e two d i r e c t i n t e r a c t i o n s c o n s t i t u t e a f e e d b a c k b e t w e e n c h a n g i n g diversity a n d c h a n g i n g CO2 levels. Results f r o m two e x p e r i m e n t s c o n d u c t e d in a c o n t r o l l e d e n v i r o n m e n t a l facility ( t h e E c o t r o n ) s u p p o r t t h e e c o l o g i c a l bases f o r t h e s e i n t e r a c t i o n s . S i n c e virtually all e c o s y s t e m s a r e c u r r e n t l y b e i n g s i m u l t a n e o u s l y e x p o s e d to b o t h a n t h r o p o g e n i c a l l y i n d u c e d d e c l i n e s in diversity a n d i n c r e a s e d CO2, s t u d i e s t h a t m a n i p u l a t e b o t h CO2 a n d diversity as e x p e r i m e n t a l f a c t o r s will p r o v i d e m o r e p o w e r f u l i n s i g h t s i n t o g l o b a l c h a n g e t h a n single f a c t o r s t u d i e s c a n p r o v i d e a l o n e .

Bazzaz, F. A., and Carlson, R. W. (1984). The response of plants to elevated C O 2 . I. Competition among an assemblage of annuals at different levels of soil moisture. 62, 196-198. Bazzaz, F. A., and Fajer, E. D. (1992). Plant life in a CO2-rich world. 266, 68-74. Ehrlich, P. R., and Wilson, E. O. (1991). Biodiversity studies: Science and policy. 253, 758-762. Gates, D. M. (1994). "Climate Change and Its Biological Consequences." Sinauer, Sunderland, MA. Groombridge, B. (1992). "Global Biodiversity: Status of the Earth's Living Resources." A report compiled by the World Conservation Monitoring Centre. Chapman & Hall, London. Houghton, J. T., Jenkins, G. J., and Ephraums, J. J. (1990). "Climate Change: The IPPC Scientific Assessment." Cambridge Univ. Press, Cambridge, UK. Lashof, D. A. (1989). The dynamic greenhouse: Feedback processes that may influence future concentrations of atmospheric trace gases and climatic change. 11, 7-31. Lawton, J. H., and May, R. M. (1995). "Extinction Rates." Oxford Univ. Press, Oxford, UK. Lawton, J. H., Naeem, S., Woodfin, R. M., Brown, V. K., Gange, A., Godfray, H. C.J., Heads, P. A., Lawler, S., Magda, D., Thomas, C. D., Thompson, L. J., and Young, S. (1993). The Ecotron: A controlled environmental facility for the investigation of population and ecosystem processes. 341, 181-194. Melillo, J. M., Callaghan, T. V., Woodward, F. I., Salati, E., and Sinha, S. K. (1990). Effects on ecosystems. "IPCC, Climate Change, The IPCC Scientific Assessment" pp. 282-310. Cambridge Univ. Press, Cambridge, UK. Naeem, S., Thompson, L.J., Lawler, S. P., Lawton,J. H., and Woodfin, R. M. (1994a). Declining biodiversity can alter the performance of ecosystems. 368, 734-737. Naeem, S., Thompson, L. J., Lawler, S. P., Lawton, J. H., and Woodfin, R. M. (1994b). Biodiversity loss in model ecosystems: A reply to Andr6 371, 565. Naeem, S., Thompson, L.J., Lawler, S. P., Lawton, J. H., and Woodfin, R. M. (1995). Empirical evidence that declining species diversity may alter the performance of terrestrial ecosystems. 347, 249-262. Polley, H. W., Johnson, H. B., and Mayeux, H. S. (1994). Increasing CO2: Comparative responses of the C4 grass and grassland invader 75, 976-988. Schneider, S. H. (1992). The climate response to greenhouse gases. 22, 1-32. Schulze, E. D., and Mooney, H. A. (1993). "Biodiversity and Ecosystem Function." SpringerVerlag, New York. Sisk, T. D., Lauder, A. E., Switky. K. B., and Ehrlich, P. R. (1994). Identifying extinction 44, 592-604. threats. Soul6, M. E. (1991). Conservation: Tactics for a constant crisis. 253, 744-750.

1

Swift, M.J., and Anderson, J. M. (1993). Biodiversity and ecosystem function in agricultural systems. "Biodiversity and Ecosystem Function" (E. D. Schulze and H. A. Mooney, eds.), pp. 15-41. Springer-Verlag, New York. Thompson, L.J., Thomas, C. D., Radley, J. M., Williamson, S., and Lawton, J. H. (1993). The effect of earthworms and snails in a simple plant community. 95, 171-178. Tilman, D., and Downing, J. A. (1994). Biodiversity and stability in grasslands. 367, 363-365. Vandermeer, J. (1989). "The Ecology of Intercropping." Cambridge Univ. Press, Cambridge, UK. Vitousek, e. (1994). Beyond global warming: Ecology and global change. 75,1861-1902. Wilson, E. O., and Peter, F. M. (1988). "Biodiversity." National Academy of Science, Washington, DC.

Predicting Responses of Tropical Plant Communities to Elevated C02: Lessons from Experiments with Model Ecosystems

Tropical ecosystems and plant communities contain an enormous proportion of the world's known species and represent about 42% of the world's biomass carbon reserves (Brown and Lugo, 1982; Olson 1983). Furthermore, these ecosystems are expected to be among the most responsive to the direct effects of rising atmospheric carbon dioxide concentrations (Long, 1991; Hogan 1991; Lugo, 1992). Despite the inevitable importance of tropical ecosystems to global species conservation and to the world's C balance, no experimental data exist on the response of native tropical plant communities to elevated atmospheric CO2! Our knowledge to date is based on a total of seven actual experiments conducted using moist tropical plant species either grown under conditions of nonlimiting nutrient supply as individuals (Oberbauer 1985; Reekie and Bazzaz, 1989; Ziska 1991) or in competitive arrays in model communities (Reekie and Bazzaz, 1989), or in model plant communities with varying degrees of nutrient limitation (Ktrner and Arnone, 1992; Arnone and Ktrner, 1993; Arnone and Ktrner, 1995; and Arnone 1995). In order to improve our chances at accurately predicting the responses of the tropical biome, it is essential to more accurately represent the predominantly low to moderately low soil fertilities found in these regions (e.g., Whittaker, 1975; Sfmchez, 1976). For example, 63% of the soils in the moist tropics is represented by Oxisols and Ultisols (Vitousek and Sanford, 1986). Perhaps a 1 01

Copyright 9 1996 by Academic Press, Inc. All rights of reproduction in any form reserved.

more critical deficit is the complete lack of data on the responses to elevated CO2 of dry tropical vegetation and communities (savannas and scrub vegetation) and even tropical seasonal forests. These terrestrial systems may be among the most responsive to rising atmospheric CO2 because high CO2 reduces leaf stomatal conductance and can reduce plant water use, at least in the short term (e.g., Strain and Cure, 1985; Jackson 1994; see Chiarello and Field, Chapter 10). Despite these deficits in our knowledge and although studies conducted in native tropical systems are desperately needed, we have gained substantial insights into the range of possible responses of native tropical plant communities to elevated CO2 as a result of the diverse data sets generated by these seven experimental studies. Perhaps the most significant finding is that nutrient supply plays a pivotal role in determining the magnitude and speed of responses of various species in a community to elevated CO2. The objective of this chapter is to synthesize our current understanding of how, and through which mechanisms, tropical plant communities will likely respond to rising atmospheric CO2. I particularly emphasize results from the studies with multispecies plant assemblages in which intra- and interspecific competition for above- and belowground resources was incorporated into the experimental design. The reason for this focus stems from the recognition that responses at the community level often cannot be reliably predicted from responses seen in individually grown plants (e.g., Bazzaz and Carlson, 1984; Zangerl and Bazzaz, 1984; Bazzaz and McConnaughay, 1992; K6rner, 1995). However, I attempt to integrate results from pot and model community studies in this synthesis. I would also like to refer the reader to earlier syntheses on the responses of multispecies model communities to elevated CO2 (Bazzaz 1985; K6rner, 1995; Bazzaz, 1990), as well as to works on the potential response of native vegetation (Strain and Bazzaz, 1983; Bazzaz, 1990; Hogan 1991) to high CO2. In addition, K6rner (1993) reviewed the utility of model ecosystems in CO2 research.

Hogan (1991) reviewed the results of the only three experiments to be conducted on individually grown (i.e., potted) tropical plants, and then speculated on the potential responses which might occur at the levels of the plant population, community, and ecosystem. These studies by Oberbauer (1985), Reekie and Bazzaz (1989), and Ziska (1991) have shown that a variety of species from the moist tropics respond both physiologically and in terms of growth to elevated atmospheric CO2. How-

8.

ever, the results from these studies paint a picture that is far from consistent. The responses of the six C~, one C4, and two CAM species observed by Ziska were the most consistent with results typically reported for a wide range of agricultural plants and other temperate species growing under ample nutrient supply (cf. Strain and Cure, 1985). Oberbauer reported a substantial increase in biomass accumulation under elevated CO2 in seedlings of both species tested, but actually measured decreases in leaf-level photosynthesis. Reekie and Bazzaz observed no CO2 effect on biomass or photosynthesis of individually grown plants but did measure decreases in stomatal conductance. Hogan and Ziska attributed the discrepancies among these studies to the negative effects of pot size on sink strength and the potential to respond to elevated CO2 (Ziska used relatively large pots, whereas Oberbauer and Reekie and Bazzaz used relatively small pots) (cf. Thomas and Strain, 1991). Berntson (1993) refuted this claim by showing that the effects of small pot size can be eliminated by increasing nutrient additions. Certainly both pot size and the actual amount of nutrients available to the plant can affect plant growth. Furthermore, all three of these experiments were conducted under unnaturally high nutrient conditions indicating that the species responses to elevated C O 2 observed may be quite untypical. Undoubtedly, the interpretation of C02 responses of potted individuals is confounded by extremes in pot size and by relatively large additions of fertilizer.

A. Species Shifts Although still artificial, model plant communities allow us to assess the responses of species to elevated atmospheric CO2 in an environment which, in most cases, more closely reflects natural competitive conditions than those represented by isolated plants (K6rner 1993). The four experiments with model communities of moist tropical plant species completed to date demonstrate some significant common responses to high CO2 as well as some important differences. All of these studies began with the establishment of replicate plant communities containing either several to many species planted in relatively homogeneous substrates (but all containing some amount of native soil) or, in Arnone and K6rner (1993), a twostoried monoculture in which the responses of overstory and understory plants were compared (Table I). Aside from the number of species used, experimental conditions differed dramatically, especially between the Atnone and K6rner studies and that of Reekie and Bazzaz (1989). Ground area, substrate depth, and average volume of substrate available per individual plant were in some cases orders of magnitude different. Planting density

Substrate

Species Reekie and Bazzaz (1989) 5 species

Functional groups

Moist tropical

Tree Tree Tree Tree Tree KOrner and Arnone (1992) "Experiment I" 15 species Moist tropical

Pioneer tree Tree Shrub Shrub Climbing vine Climbing vine Climbing vine G r o u n d vine G r o u n d vine Herb. m o n c o t Herb. m o n c o t Herb. m o n c o t Herb. m o n c o t Herb. m o n c o t

Planting density (m -s)

400

Ground area (m -s)

0.075

0.30 0.45 0.75 0.30 0.30 0.30 0.30 0.90 0.45 0.30 0.30 0.60 0.30 0.60 0.45

soil: turface (1:1) Fertilizer 4 • ?

11

Vol. (liters)

8

CO2 levels (/~11 -~)

300 525 700

111

340 610

94

LAI

NPP equivalent ( g m - S y r -1)

6.65

sand: vermiculite (1:1) + compost-soil layer Fertilizer 20 g m -s Osmocote NPK and micro. Tot. N equiv, of 400 kg N ha -~

1300

Shift in Biomass spp. abund. response at harvest ~ at harvest (A % rel. to (% of c o n t r o l ) c o n t r o l [COs])

n.s.

n.s.

n.s.

12.3 b 11.9 b 11.4 b

1875 1840 1940

control -2 +3 at 525, 700 +40 +100 +122 +115 -40 -45 +55 +60 -30 +15

6.9 6.6

P = 0.09 2780 3377

P = 0.10 control +11 at 610 +10 +1 +20 +13 +22 -17 + 4 0 (*) +5 +15 +47 (*) +17 +23 - 9 (*) +5 +8

Peter's NPK m Very high: "nonlimiting"

80 80 80 80 80

6.6

Type

Depth (cm)

Effective trt. period (d)

significant

33.0 35.4 at 525, 700 +1.8 +1.6 +4.1 +5.3 -8.0 -17.7 +10.6 +8.5 -8.5 +2.3 P = 0.10

n.s.

13.4 at 610 +0.06 - 5 . 2 3 (*) -0.19 +0.16 +0.74 +0.16 +1.99 (*) -0.08 -0.15 +0.69 (*) +0.12 +2.76 -0.88 -0.15 0.00

Number of communities (n)

Arnone and K6mer (1993) "Experiment II" 1 species Moist tropical (two-storied canopies) Over-/understory

5.7

6.65

same as K6rner & Arnone (1992) Tot. N equiv, of ca. 360 kg N ha -t

3.0/2.7

20

1300

340 610 340

21

Arnone and K6rner (1995) "Experiment HI"

Moist tropical

Tree Tree G r o u n d vine dcot. G r o u n d vine mcot. Herb. m o n c o t Herb. m o n c o t Herb. moncot

a Shifts in species contribution

n.s.

11.6

6.65

0.30 0.45 0.90 0.45 0.30 0.60 0.30

to t o t a l c o m m u n i t y

bIncludes foliage which extended

sand and tropical soil inoculum top layer (1 cm) and dried ground plant material Fertilizer 129 g m -~ NPK and micro. Total N equiv, of 118 kg N ha -~ yr -~

aboveground

beyond the ground

25

1700

340 610

530

4.0 3.9

b i o m a s s ; * * P < 0.01, * P < 0.05, (*) P < 0.15.

area of the tubs (most probably).

cIncludes leaf litter and standing necromass, but excludes root litter.

P = 0.02 375 c

P = 0.02 +18"

n.s. (% understory)

47O ~

1.75/ 0.11 1.73/ 0.08

610

7 species

n.s. 1.86 1.81

+ 1 8 " / + 1 6 n.s.

n.s.

n.s.

n,s. (sig. by spp. groups) 20.4

-18 +35 +136 0 +9 -40 -18

-4.4 +6.4 +0.9 0 +2.9 -4.1 -1.7

815 ~ 910 c

106 was also lower (6.6-11.6 versus 400 individuals per square meter) as was the a m o u n t of nutrients supplied/available in the Arnone and K6rner experiments. The following is a relative ranking of the nutrient availabilities of the four studies: Reekie and Bazzaz (1989)~>)K6rner and Arnone, 1992 > Arnone and K6rner 1993 ~> Arnone and K6rner, 1995. Furthermore, the starting size of individuals used in each experiment varied. Reekie and Bazzaz began with very small seedlings, Arnone and K6rner (1993 and 1995) with larger (30-70 cm tall) but still relatively small stamred individuals, and K6rner and Arnone (1992) with larger (up to 1 m tall) individuals in order to create a highly structured stand from the start which enabled the analysis of the CO2 effects on various life-forms occupying different positions along the vertical light gradient. Finally, the duration of these experiments varied considerably ranging from 21 to 530 days (Table I), and Reekie and Bazzaz were able to include four replicate communities per CO2 treatment, instead of the two used in the Arnone and K6rner studies. Despite the significant increases in community biomass accumulation observed under both ambient and elevated CO2 over the course of all of these experiments, significant CO2-induced shifts in species dominance (or in composition of overstory versus understory plants) were reported for only two of them (Table I). Reekie and Bazzaz (1989) found highly significant and substantial shifts in the contribution of individual tree species to community aboveground biomass with increasing CO2 concentration in stands planted with equal densities of each species. For example, increased in abundance while decreased at elevated CO2. Perhaps most striking is that these shifts occurred even though CO2 level had no effect on overall community aboveground biomass or on leaf area index (LAI). The authors showed that the success of a species was positively related to its mean canopy height measured at harvest. In much more nutrient-poor systems, Arnone and K6rner (1995, Experiment III) reported significant changes in the abundance of groups of species under elevated CO2 but no significant shifts in any single species (Table I). The magnitude of the CO2-induced shifts Arnone and K6rner observed over 530 days were considerably less than those observed by Reekie and Bazzaz (1989). The contribution of a pioneer species, to community biomass was reduced over the course of the experiment and this shift was slightly (n.s.) enhanced under elevated CO2 (Fig. 1). In contrast, the slower-growing and the understory monocot increased in abundance in all communities, with a trend toward even greater increases u n d e r elevated CO2. No significant changes in biomass accumulation or LAI were observed u n d e r elevated CO2. Although no significant overall species shifts were observed in the relatively fast-growing nutrient-rich systems of Experiment I (K6rner and Arnone, 1992), showed a substantial 5% mean decrease in its share of community aboveground

8.

107

Figure 1 Mean changes in the contribution of the seven species of moist tropical plants to communitybiomass (including coarse root biomass) over 530 daysin Experiment III in systems maintained at ambient and elevated atmospheric CO2 concentrations.

biomass (P = 0.11) u n d e r elevated C O 2 measured at harvest, while two other and species showed marginally significant increases in their share of community aboveground biomass (P = 0.14 and 0.08, respectively, Table I). The success of at elevated CO2 u n d e r one set of competitive experimental conditions and its relative failure at elevated CO2 u n d e r another set of conditions does, however, point to the difficulty of predicting species-specific responses to elevated CO2 based on results from model systems alone. Thus, it appears that the most reliable prediction is that some level of shifts in species dominance will take place in native moist tropical communities in a CO2-rich world, and shifts may occur more rapidly in nutrient-rich systems containing very young individuals than in nutrient-poorer systems or in those containing older plants. However, we are unable to predict with any degree of certainty which species will win and which will lose.

B. Individually Grown Versus Competitively Grown Plants How well do the responses of individually grown plants extrapolate to their responses when grown u n d e r competition? Generally, existing data support the notion of a poor correspondence between responses in individually grown plants and competitively grown plants. Reekie and Bazzaz (1989) report correlations between some autecological morphological traits and responses to elevated CO2 in their tropical plants growing u n d e r competitive conditions. However, they found no correlations for other morphological and physiological traits. Perhaps their most interesting finding was that mean canopy height and shape (leaf area profiles) were strongly influ-

108

enced by competition and C O 2 level. Bazzaz and McConnaughay (1992) use data from an experiment by Williams (1988), with serpentine grassland species, to illustrate the pronounced mismatch between projections of community species composition derived from CO2 responses of isolated individuals and their actual success in heterospecific stands. Likewise, the experiments of Arnone and K6rner with model communities of tropical plant species indicate a relatively poor correspondence between prognostications made based on single-plant experiments (Hogan 1991) and responses of plants in multispecies stands. For example, Arnone and K6rner found no uniform increase across all species in leaf area per plant under competitive conditions in any of their three experiments, as is implied by Hogan (1991) and predicted from models (e.g., Oikawa, 1990). Moreover, in none of the three community experiments did Arnone and K6rner find the often predicted CO2-induced increase of LAI (Eamus andJarvis, 1989; Nijs 1989). Even under nonlimiting nutrient conditions, Reekie and Bazzaz (1989) found no effect of CO2 concentration on leaf area per plant of either individuals or plants grown in model communities. When nutrients were supplied at near natural levels, LAI even tended to decrease under elevated CO2 (K6rner and Arnone, 1992; Arnone and K6rner, 1993, 1995). This was associated with higher leaf mortality in a number of species at high CO2 (Fig. 2). These leaf area responses are remarkably consistent over a wide range of nutrient conditions, species mixes, plant life-forms, overall LAIs, and durations of experiments, further exemplifying the danger of simple extrapolation from singleplant responses obtained under unlimited nutrient supply to responses under competition and more realistic nutrient regimes. C. Effects of Plant Morphology on Competitive Performance: Biomass Allocation Patterns and Plant Life-form

In tropical plant species growing competitively in model communities in Experiment III (Arnone and K6rner, 1995), the effects of elevated CO2 on patterns of biomass allocation were similar to those observed in a very large number of other species grown as individual plants (e.g., Strain and Cure, 1985; Rogers 1994; Poorter, 1993). These patterns include greater (initial) enhancement of root growth than shoot growth under elevated CO2 (Fig. 3) and consequently increased allocation to root biomass. These changes are commonly associated with greater root:shoot ratios, lower leaf weight ratios (LWR), and leaf area ratios (LAR) (e.g., Norby 1992) but may not be so pronounced when mineral nutrients are abundant (Oberbauer 1985; Reekie and Bazzaz, 1989; Ziska 1991). For instance, Ziska and coworkers (1991) only found increases in root:shoot ratio in two of nine species, and lower LWRs in half of the C3 species studied.

8.

-

+t I-

E

v m

[~ Arab0~ I

_.1

Time courses of leaf area index (LAI) development in Experiments I, II, and III for communities maintained at ambient (open symbols) and elevated (filled symbols) atmospheric CO2 concentrations (mean _+ SE of two communities per CO2 level).

LWR appears to explain the relative competitive success of the seven species in Experiment III (Arnone and K6rner, 1995). They found that the greater the LWR of a species the larger the positive shifts observed in species dominance within the plant community over the 530-d experiment (Fig. 4). Since no CO2-induced changes were observed in specific leaf area (SLA) for any of the species (Arnone 1995), this relationship also holds true for LAR. This effect was independent of CO2 treatment, however, and the relationship appears to reverse itself if the very high

-2'o o Relative effects of growth under elevated CO2 on LAI, biomass accumulation of various organs, and on production of aboveground necromass in Experiments I, II, and III (difference between mean ambient and elevated values expressed as a percentage of the ambient mean; a, senescing leaves; **, P < 0.01; *, P < 0.05; (*), P < 0.15).

110

o

0-

ffl

Ct

Relationship between leaf weight ratios (LWR, including coarse roots) measured for each of the seven species at the start of the 530-day Experiment III and their competitive outcomes as measured by the change in a species' contribution to total Community biomass over the course of the experiment. Each point represents one species in one of the four communities. Each curve represents a second-order polynomial fitted either to all points (longer curve, r z = 0.52) or to all but the four data points from (shorter curve, r 2 = 0.48). Curves fitted separately to ambient and elevated CO2 points were not different, so the curve shown was fitted to the entire set of points (save Species key: Ct = Ce = Ep = He = E1 = Fib = Fip =

a g r o u n d - c r e e p i n g vine, were i n c l u d e d in the analysis. R e e k i e a n d Bazzaz (1989) u s e d p r i n c i p l e c o m p o n e n t analysis a n d stepwise r e g r e s s i o n to evaluate which m o r p h o l o g i c a l a n d physiological characteristics o f individually g r o w n plants o f five tropical p l a n t species w o u l d best e x p l a i n t h e i r success w h e n g r o w i n g in c o m p e t i t i v e arrays. T h e two m e a s u r e s w h i c h e x p l a i n e d almost 75% o f the variation in c o m p e t i t i v e success were m o r p h o l o g i c a l traits: m e a n c a n o p y h e i g h t a n d leaf a r e a ratio. N e t leaf-level p h o t o s y n t h e s i s e x p l a i n e d less t h a n 9% o f the variability in the data. I n d e e d even in p o t t e d tropical plants, O b e r b a u e r (1985) f o u n d t h a t b i o m a s s a c c u m u l a t i o n was g r e a t e r in plants g r o w n u n d e r elevated CO2 even t h o u g h leaf-level p h o t o s y n t h e s i s was lower in these plants! All o f these o b s e r v a t i o n s g e n e r a l l y suggest t h a t CO2-induced alterations in p l a n t m o r p h o l o g y a n d p l a n t d e v e l o p m e n t may be m o r e useful p r e d i c t o r s o f species' c o m p e t i t i v e success t h a n c h a n g e s in t h e i r p h o t o s y n t h e t i c p e r f o r m a n c e . Biomass allocation p a t t e r n s are closely tied to p l a n t life-form in t h a t c e r t a i n life-forms e x h i b i t various d e g r e e s o f m o r p h o l o g i c a l plasticity in r e s p o n s e to e n v i r o n m e n t a l stimuli a n d to c o m p e t i t i o n . Thus, m o r p h o l o g i -

8.

111

cal constraints can profoundly affect the type and magnitude of response to atmospheric CO2 level (Table I). Once one begins to think in this vein one must consider constraints imposed on a species' resource (light and nutrients) capturing ability conferred on it by both its lateral and vertical space occupancy in the canopy and in the soil. Indeed, Reekie and Bazzaz (1989) showed the importance of differences in canopy height and architecture in determining the success of tropical tree seedlings u n d e r elevated CO2. In Experiment III, Arnone and K6rner also found that plant lifeform could help explain its response in model communities. For example, herbaceous monocots such as were able to proliferate rapidly in lateral directions but could not grow significantly in height, whereas tree species such as and were not able to grow laterally very quickly but could grow in height (Arnone and K6rner, 1995; see also Hunt 1991). the pioneer with its short-lived leaves and rapid growth in open stands, gained an early advantage in all communities. In contrast, the slower growing tree species with its long-lived leaves and its continuous occupation of the soil with its roots allowed it to gradually increase in dominance in all communities, but more so u n d e r elevated CO2. Within the herbaceous monocots, the success of (20% of start biomass and 38% of harvest biomass at ambient CO2, and 41% at elevated CO2) and the relative failure of (39% at the start, 12% and 8%, respectively at harvest) was largely due to the relative slowness of leaf and lateral filler proliferation in more rapid proliferation of new tillers in Furthermore, root systems of were more extensive than those of

D. The Vertical Dimension: Interactive Effects of LAI, Light, and Light Quality Plants growing in competitive arrays shade themselves and each other and create gradients of decreasing light availability from the top to the bottom of the canopy. As LAI increases, light transmittance in the stand decreases. These changes are known to have variable effects on different plant species depending on their position in the community. Under conditions of elevated atmospheric CO2 it has often been hypothesized that LAIs should increase (e.g., Nijs et al., 1989; Eamus and Jarvis, 1989). One reason that this could occur is through an increased production and retention of leaves of understory plants growing in deep shade. Greater leaf retention u n d e r very low photon flux densities (PFDs) u n d e r elevated CO2 could result from improved leaf carbon balance (Pearcy and Bj6rkmann, 1983) afforded by CO2-induced reductions in light compensation point and by increases in q u a n t u m use efficiency (e.g., Ehleringer and Bj6rkmann, 1977). In all three of the Arnone and K6rner experiments and in the study of Reekie and Bazzaz (1989) no evidence in support of this hypothesis was

observed (Table I). In fact, as a consequence of the unchanged LAIs under elevated CO2 (Fig. 2; Reekie and Bazzaz, 1989), no differences in light transmittance within stands has been observed. Accordingly, we found no CO2-induced shifts in vertical leaf area distribution for any of the 15 species growing in the communities in Experiment I (Fig. 5). Thus, LAI appears to be relatively insensitive to atmospheric CO2 concentration. In Experiment II, Arnone and K6rner (1993) specifically examined the responses to elevated CO2 ofunderstory plants growing in two-storied monospecific stands of the extremely fast-growing tropical species Both understory and overstory plants in all communities increased significantly in size over the 21-d CO2 treatment. However, they observed no differences in LAI of either the overstory or understory plant canopies between ambient and elevated CO2 communities (Fig. 3). They also found no enhancement of biomass accumulation in understory plants in high CO2 communities, as was hypothesized, but did observe significantly greater (17%) height growth and internode length of understory plants growing in communities maintained at elevated CO2 (Fig. 3). These growth responses are typical of shade avoidance reactions in response to reductions in the red:far-red ratio (e.g., Smith, 1982), and suggested that elevated CO2 may alter properties of leaves such that they absorb more red light a n d / o r reflect more far-red light (e.g., Ballar6 1987). Indeed, Arnone and K6rner measured significantly lower R:FR ratios beneath overstory leaves produced under elevated CO2 than under leaves produced under ambient CO2. Although these results do not rule out other possible direct effects of elevated CO2 on understory plant behavior, they do suggest that CO2-induced alterations in light quality within a community could eventually have a pronounced effect on plant-plant interactions and competitive outcomes. For example, recruitment patterns and species composition of later successional stages in tree-fall gaps may be affected by shifts in R:FR ratios and variable inherent sensitivities to reductions in R:FR ratio of gapcolonizing species.

250]

Meanleaf area profiles of each of the 15 species growing in model communities in Experiment I after 94 days of exposure to ambient (open symbols) and elevated (filled symbols) atmospheric CO2 concentrations.

8.

E. Photosynthetic Performance as a Determinant of Species' Competitive Success

M. Gruber (unpublished data) measured whole-shoot CO2 exchange of the most dominant species in Experiment III in order to evaluate species' contributions to ecosystem CO2 flux and to test how well shootlevel physiology would correspond to species' competitive performance. Measurements were made in the last third of the experiment with an openIRGA system by enclosing individual shoots from each species in each community in transparent polyethylene bags. During this phase of the experiment relatively pronounced "successional" shifts in species dominance were underway in all communities, however no obvious CO2 treatment effects were seen. Net shoot CO2 flux on each individual was measured at the growth CO2 concentration for about 16 hours, which included the latter half of the photoperiod and most of the dark period. In Experiment III, Gruber found greater shoot assimilation rates under elevated CO2 in all of the four species evaluated (Table II). In and these increases were marginally significant (P < 0.15) and amounted to 53% and 123% of the rates measured at ambient CO2, respectively. Higher assimilation rates under elevated CO2 in may have

Shoot dark respiration

S h o o t assimilation (/~mol CO2 m -2 leaf s -1) Species

Amb. CO 2 2.57 1.41 0.99 0.77

_+ _+ + _+

Elev. CO2

0.39 0.14 0.08 0.20

2.85 2.16 1.04 1.71

+ + _+ _+

0.16 0.27 0.08 0.17

(/~mol CO2 m -2 leaf s -1) Diff. Diff. (%) +11 + 5 3 (*) +6 + 1 2 3 (*)

A m b . COz 0.69 0.24 0.12 0.09

+ +_ +_ _+

0.10 0.04 0.03 0.02

Elev. CO2 0.76 0.27 0.09 0.04

+_ +_+ _+

0.01 0.02 0.02 0.04

(%) +10 +12 -25 -55

a.f ANOVA

CO 2

1

Results

Resid.

2

Species

3

Sp. • C O 2 Residual

3 6

n.s.

n.s.

(*)

Levels of statistical significance: ** = P < 0.01; * = P < 0.05; (*) = P < 0.15. a All parameters were measured at growth CO2 concentrations. Mean net assimilation rates measured on individual leaves on Day 305 were 72% greater (P = 0.03) under elevated CO2 (13.6 _+ 0.2 /~mol CO2 m -s leaf s-1) than under ambient COs (7.9 _+ 1.1 /.~mol COs m -2 leaf s-l). The values in the table are means _+ SE with n = 2 communities per COs level.

114 contributed to its relative greater gains in these communities than in communities maintained at ambient CO2 (Table I). on the other hand, suffered marginally greater losses under elevated CO2 despite its greater shoot assimilation rates and its reduced dark respiration rates. Likewise, the 25% lower (n.s.) shoot dark respiration rates measured in may have conferred a substantial advantage to this species over time and facilitated its relative greater expansion in elevated CO2 communities. Species such as which had similar shoot CO2 assimilation and dark respiration under both ambient and elevated CO2, but surprisingly 72% greater leaf-level photosynthesis (see legend of Table II), tended to lose a greater share in community biomass by the end of the experiment. This again illustrates the unreliability of using physiological traits alone to predict competitive outcomes. Thus it can be argued that physiological performance with respect to shoot C O 2 balance may have contributed to competitive outcome in some species but may have been relatively unimportant determinants of success in other species. The same held true for the connections between leaf stomatal conductance and species competitive outcome in Experiment III. In the latter third of this experiment, A. Kocyan (unpublished data) measured substantial decreases in leaf diffusive conductance under elevated CO2 in the five most dominant species, but only small reductions (5%) in whole ecosystem evapotranspiration. It is unclear how lower water consumption by any of the species would confer any particular competitive advantage since water was not limiting in this experiment. No differences in leaf stomatal conductance between ambient and elevated CO2 were found in Experiment I, and this corresponded well with the absence of differences in ecosystem evapotranspirational water losses. Due to the 75 % greater LAI in this experiment (--- 7), relative to Experiment III (~- 4), air humidity was higher and may have precluded stomatal responses to CO2.

F. Belowground Interactions among Plants' and Species' Competitive Success Under elevated atmospheric CO2 levels, competition for nutrients (e.g., phosphorus) should increase as a result of greater root growth, greater allocation of carbon to root systems, and maintenance of larger fine root populations of many or all plant species within a community. Thus the importance of interactions among roots and between roots and soil organisms would also be expected to increase in a CO2-rich world, but these have not been quantified. However, qualitative observations on the timing and extent of root growth and proliferation of various species in model communities confirm the major role they play in determining competitive outcome regardless of CO2 effects. For example, Bazzaz (1990) attributed the relatively successful outcome of higher atmospheric CO2 concentrations

8.

115

(see Reekie and Bazzaz, 1989) to its greater allocation to roots and ultimately to its rapid occupation of the soil volume early in the experiment. Arnone and K6rner (1995) observed a similar p h e n o m e n o n in their Experiment III under relatively nutrient-poor conditions. Early in the experiment (first 100 d), the pioneer species quickly occupied the entire top several centimeters of the soil with its fine roots and grew equally rapidly in height under both ambient and elevated CO2. As the experiment progressed, root systems and shoots of the understory herbaceous monocots (especially and the relatively slow growing trees began to compete strongly with its growth. By the end of the experiment (530 days) in all communities had lost tremendous share in its contribution to community leaf area and biomass, especially. Belowground competitive pressure from a species with leaves unable to shade those of appeared to be the main cause for the severe suppression of growth in all communities, and this effect tended to increase at high CO2. In another experiment embedded in Experiment III (J. Arnone, unpublished data), abilities of species to exploit nutrient-rich soil microsites in an otherwise "nutrient-limited" system were investigated. A pronounced increase in proliferation of fine roots (-3 years) of UV-B radiation per se on the same heathland vegetation, Johanson (unpublished) has found increases in flavonoids. The effects of UV-B x CO2 on flavonoid accumulation will be investigated in future seasons. Little is known about the energy cost of producing and maintaining protective pigments in the plant. Increased investment in these compounds at enhanced UV-B may be at the expense of growth, although such loss of energy to photoprotection may not be as great at elevated CO2 because plant maintenance costs are often reduced (Reuveni and Gale, 1985; Bunce, 1990; Bunce and Caulfield, 1990). Studies to date have concentrated mainly on the effects of UV-B and CO2 on aboveground growth and development of the dwarf shrubs, because studies of the rhizosphere in the current system have presented difficulties. However, some of the aboveground responses observed may be partially mediated through changes occurring in the rhizosphere. A review by Rogers, Brett Runion, and Krupa (1994) extensively discussed the effects of elevated CO2 belowground processes, but our knowledge on UV-B effects are limited. The heathland surface soil horizon is dominated by the roots of the ericaceous dwarf shrub which may be indirectly and directly influenced by such perturbations. Individual studies on decomposition (Gehrke 1995), soil water relations (Gwynn-Jones and Pantis, unpublished) and carbon exudation from roots (Norby 1987) all suggest that there

202

could be major effects of these perturbations on the rhizosphere. Any process that influences the availability of soil nutrients may be of particular importance within the heathland.

B. Grasses (Minor Canopy Species) Grass species contribute only a small proportion of total plant cover within the heathland, hence experiments on the effects of UV-B and CO~ on grasses have been carried out in controlled environments. The predominant grass species within the heathland are and Experiments on these species have addressed the individual rather than the interactive effects of these two perturbations. Of particular interest in these species is the nonlinear damage response observed with increasing levels of UV-B radiation. A 40% decrease in dry weight was observed following 60 d exposure to enhanced UV-B radiation representing a 15% ozone depletion (cf. natural level) while no effects were observed at a higher UV-B dosage (representing 25% ozone depletion) (Gwynn-Jones andJohanson, unpublished). Damage caused by UV-B radiation could be overcome at higher levels via stimulation of tillering. Such tillering could have been stimulated at the higher UV-B level by the direct effect of auxin which may control apical dominance. shows a characteristic increase in growth following exposure to elevated concentrations of CO2 (Parsons, unpublished). Given the responses observed individually at enhanced UV-B and elevated CO2 it is difficult to make predictions as to the response of this species to simultaneous exposure. From the positive responses observed, it could be hypothesized that combined effects of these two variables may increase the significance of grasses in the heathland. However, there are no apparent changes in the importance of grasses within our main field site, which remain at low densities following two full seasons of exposure.

C. Cryptogams (Understory Species) showed increased shoot growth at elevated CO2 but no effects of UV-B were apparent after 2 years' exposure. Results suggest that the effect was more p r o n o u n c e d in previous year shoots (c + 1) than in those developed during the current year (c). It could be hypothesized that the influence of CO2 on dwarf shrubs may be partially responsible for changes in the growth of these mosses (see Section III A in this chapter). Mosses such as initiate their highest growth rates when deciduous canopy species are leafless--at the beginning and end of each growing season (Karlsson, 1987). Changes in V. phenology may have been partly responsible for the increased shoot growth of due to increased exposure to photosynthetically active radiation. This would emphasize the importance of studying plant responses to environmental per-

13.

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203

turbation within natural communities as opposed to short-term, singlespecies experiments.

A. Decomposition Experiments at Abisko to date have concentrated on I.W-B effects on decomposition although material has been collected to study the decomposition of tissue previously exposed to simultaneous UV-B and CO2 exposure. The decomposition rate of leaf litter was found to be reduced overall under enhanced I_W-B levels due to both direct and indirect influences (Gehrke 1995). Direct impacts were due to a reduction in the n u m b e r of active microorganisms at enhanced UV-B which was reflected by a reduced microbial respiration. Indirect effects of UV-B were expressed as changes in leaf litter quality, where increases in phenolic (e.g., tannin) substances were apparent following field exposure of species to enhanced I_W-B. Such phenolic compounds complexing with proteins may cause decreased digestibility to microorganisms (Richards, 1987) thus slowing the rate of decomposition. Leaf tissue quality is also influenced by exposure to elevated CO2 as the C : N ratio is commonly increased (see review by Woodward, 1992). However, such marked effects on tissue quality may not necessarily influence the rate of decomposition as this will be dependent on the populations and activities of both microflora and fauna within the ecosystem. It could be predicted that the combination of enhanced UV-B and elevated CO2 may result in reductions in the rate of litter decomposition. Such a response over sequential growing season may result in reduced soil fertility, lower primary production, and greater storage of soil carbon.

B. Herbivory Changes in leaf quality as a result of plant exposure to elevated CO2 and UV-B may also influence the degree of insect herbivory in the subarctic heathland. Bazzaz and Fajer (1992) showed that the Buckeye butterfly was adversely affected by high CO2 as caterpillars would grow more slowly, feeding on plantain grown at elevated CO2. Exposure to I.W-B radiation may also influence leaf tissue quality (Teramura, 1983; Hatcher and Paul, 1994) and hence the success of herbivores. Indeed, Hatcher and Paul (1994) found increases in the levels of leaf phenolics in pea plants exposed to enhanced levels of I.W-B radiation under laboratory conditions. Feeding the leaves of these plants to larva of the moth L. had no deleterious effects on growth rates as the level of nitrogen had also increased following exposure to I.W-B radiation.

204 Further studies are needed to fully understand such relationships and these should be performed in the field and not under artificial laboratory conditions. A field-based project was commenced during the summer of 1995 to look at the direct and indirect effects of UV-B and COz on the moth which feeds predominantly on birches and deciduous dwarf shrubs.

Results from our experiments based in a subarctic heathland suggest that vegetation responses to UV-B and CO2 are species-specific. The deciduous dwarf shrub V. was found to be most sensitive to the perturbations showing both CO2 and UV-B responses during the period of exposure. Responses to elevated CO2 included changes in photosynthesis, phenology, and growth, which were only observed during the first season of exposure. However UV-B responses were apparent during the second season of exposure where the flowering and berry yield of this species was stimulated at e n h a n c e d UV-B. The other dwarf shrub species present within the heathland appeared to be unresponsive to these environmental perturbations in aspects of physiology, demography, and growth during the two seasons of exposure. Compared to many laboratory investigations, the dose simulating a 15% reduction in the ozone layer is fairly modest. This, combined with the fact that all the plants studied are long-lived perennials, suggests that small, potentially cumulative damage may be occurring. O u r evidence for field responses of cryptogam to UV-B and CO2 is limited, although we have observed some stimulation of growth in the moss H. at elevated COz during the second season of exposure. Further field studies are required to understand the long- and short-term sensitivity of the understory species (including lichens and other moss species) to such environmental perturbation. An understanding of the effects of global climate change on seminatural ecosystems must be u n d e r p i n n e d by realistic and long-term experimentation. The experiment described in this chapter is one attempt to do so. O u r ecosystem approach is diagramatically illustrated in Fig. 1. It shows the breadth of our approach and the interdependence of trophic levels addressed. Responses observed in the first 2 years are fairly modest. It is probable that the ecological interest will increase with time. This should allow, for example, a thorough investigation not only of cumulative plant-specific responses to perturbations, but also a full evaluation of the effects on other ecosystem components and, in particular soil processes.

13.

on

~ / structureI Figure

1 Diagram showing the relationship between the ecosystem as a whole and the environmental perturbations addressed.

We are grateful to the CEC for financial support and to the Abisko Naturvetenskapliga Station (Abisko, N. Sweden) for allowing these experiments to be conducted and providing excellent technical and administrative support.

Baker, J. T., and Allen, L. H., Jr. (1994). Assessment of the impact of rising carbon dioxide and other climate changes on vegetation. 83, 223-235. Bazzaz, F. A., and Fajer, E. D. (1992). Plant life in a CO2-rich world. 1, 18-24. Bj6rn, L. O., and Murphy, T.M. (1985). Computer calculations of solar ultraviolet radiation at ground level. 23, 555-561. Bornman, J.F., and Teramura, A. H. (1993). Effects of ultraviolet-B radiation on terrestrial plants. "Environmental Photobiology" (]. Young, ed.), pp. 427-471. Plenum, New York. Bunce, J. A. (1990). Short- and long-term inhibition of respiratory carbon dioxide efflux by elevated carbon dioxide. 65, 637-642. Bunce,J. A., and Caulfield, F. (1990). Reduced respiratory carbon dioxide efflux during growth at elevated carbon dioxide in three herbaceous perennial species. 67, 325-330. Drake, B. G., and Leadley, P. W. (1991). Canopy photosynthesis of crops and native plant communities exposed to long-term elevated CO2. 14, 853-860. Eamus, D., and Jarvis, P. G. (1989). The direct effects of increases in the global atmospheric CO2 concentrations on natural and commercial temperate trees and forests. 19, 2-55. Emanuelsson, U., and Callaghan, T. V. (1994). Population structure and process of tundra plants and vegetation. "The Population Structure of Vegetation" (J. White, ed.), pp. 399-439. Junk of Bodstricht press. Farman, J. C., Gardiner, B. G., and Shanklin, J. D. (1985). Large losses of total ozone in Antarctica reveal seasonal C1Ox/NOx interaction. 315, 207-210.

206 Farrar, J. F., and Williams, M. L. (1991). The effects of increased atmospheric carbon dioxide and temperature on carbon partitioning, source-sink relations, and respiration: Commissioned review. 14(8), 819-831. Frederick, J. E., and Snell, H. E. (1988).Ultraviolet radiation levels during the Antarctic spring. 241, 438-440. Gehrke, C., Johanson, U., Callaghan, T., Chadwick, D. and Robinson, C. H. (1995). The impact of enhanced ultraviolet-B radiation on litter quality and decomposition processes in leaves from the sub-arctic. 72, 213-222. Gleason, J. F., Bhartia, P. K., Herman, J. R., McPeters, R., Newman, P., Stolarski, R. S., Flynn, L., Labow, G., Larko, D., Seftor, C., Wellemeyer, C., Komhyr, W. D., Miller, A., and Planet, W. (1993). Record low global ozone in 1992. 290, 523-526. Hatcher, P. E., and Paul, N. P. (1994). The effects of elevated UV-B radiation on herbivore of pea by Autographa gamma. 71 (3), 227-233. Hoffman, D.J., and Deshler, T. (1991). Evidence from balloon measurements for chemical depletion of stratospheric ozone in the Arctic winter of 1989-1990, 349, 300-305. Johanson, U., Gehrke, C., Bj6m, L. O., Callaghan, T. V., and Sonesson, M. (1995a). The effects of enhanced UV-B radiation on a sub-arctic heath ecosystem. 24, 106-111. Johanson, U., Gehrke, C., Bj6rn, L. O., and Callaghan, T. V. (1995b). The effects of enhanced UV-B radiation on the growth of dwarf shrubs in a sub-arctic heathland. 9(5), 713-719. Karlsson, P. S. (1987). Niche differentiation with respect to light utilization among coexisting dwarf shrubs in a sub-arctic woodland. 8, 35-39. Kerr, R. A. (1993). The ozone hole reaches a new low. 262, 501. Krupa, S., and Kickert, R. N. (1989). The greenhouse effect: Impacts of ultraviolet-B (UVB), carbon dioxide (CO2), and ozone (03) on vegetation. 61, 263-293. Newton, P. C. D. (1991). Direct effects of increasing carbon dioxide on pasture plants and communities. 34, 1-24. Norby, R., O'Neill, E. G., Hood, W. G., and Luxmoore, R.J. (1987). Carbon allocation, root exudation, and mycorrhizal colonization of seedlings grown under CO2 enrichment. 3, 203-210. Oechell, W. C., Hastings, S.J., Vourlitis, G., Jenkins, M., Riechers, G., and Grulke, N. (1993). Recent change of Arctic tundra ecosystems from a net carbon dioxide sink to a source. 261 (6412), 520-523. Proffitt, M. H., Margitan, J. J., Kelly, K. K., Loewenstein, M., Podolske, J. R., Jones, and Chan, K. R. (1990). Ozone loss in the Arctic polar vortex inferred from high-altitude aircraft measurement. 347, 31-36. Reuveni,J., and Gale,J. (1985). The effect of high levels of carbon dioxide on dark respiration and growth of plants. 8, 623-628. Richards, B. N. (1987). "The Microbiology of Terrestrial Ecosystems." Longman, New York. Rogers, H. H., Brett Runion, G., and Krupa, S. V. (1994). Plant responses to atmospheric CO2 enrichment with emphasis on roots and the rhizosphere. 83, 155-189. Rozema, J., Lenssen, G. M., and van de Staaij, J. W. M. (1990). The combined effects of increased atmospheric COs and I.W-B radiation on some agricultural and salt marsh species. "The Greenhouse Effect and Primary Productivity in European Agroecosystems" (J. Goudriaan., H. van Keulen, and H. H. van Laar, eds.), pp. 68-71. Pudoc Wageningen. Sonesson, M., and Lundberg, B. (1974). Late quaternary forest development in Tornetr/isk area, northern Sweden. I. Structure of modern forest ecosystems. 25, 121-133. van de Staaij,J. W. M., Lenssen, G. M., Stroetenga, M., and Rozema, J. (1993). The combined effect of elevated COs levels and UV-B radiation on growth characteristics ofElymus 104/105, 433-439. Stewart, J. D., and Hoddinot, J. (1993). Photosynthetic acclimation to elevated atmospheric 88, 493-500. carbon dioxide and UV irradiation in

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Sullivan, J. H., and Teramura, A. H. (1992). The effects of ultraviolet-B radiation on loblolly pine. II. Field-grown seedlings. 6, 115-120. Sullivan, J. H., and Teramura, A. H. (1994). The effects of UV-B radiation on loblolly pine. III. Interaction with CO2 enhancement. 17, 311-317. Teramura, A. H. (1983). Effects of UV-B radiation on the growth and yield of crop plants. 58, 415-427. Teramura, A. H., Sullivan, J. H., and Lewis (1990). Interaction of elevated UV-B radiation and COs on productivity and photosynthetic characteristics in wheat, rice and soybean. 94, 470-475. Tissue, D. T., and Oechell, W. C. (1987). Response of to elevated COs and temperature in the Alaskan tussock tundra. 68, 401-410. United Nations Environment Program (UNEP) (1994). Effects of increased solar ultraviolet radiation on terrestrial plant. "Environmental Effects of Ozone Depletion--1994 Assessment," pp. 49-65. Nairobi, Kenya. Watson, R. T., Rodhe, H., Oeschger, H., and Siegenthaler, U. (1990). Greenhouse gases and aerosols. "Climate Change--IPCC Scientific Assessment" (J. T. Houghton, G.J.Jenkins, and J. J. Ephramus, eds.), pp. 1-40. Cambridge Univ. Press, Cambridge, UK. Woodward, F. B. I. (1992). Predicting plant responses to global environmental change. New 122, 239-251. Ziska, L. H., and Teramura, A. H. (1992). CO2enhancement of growth and photosynthesis in rice (Oryza Modification by increased ultraviolet-B radiation. 99, 473-481.

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1 Carbon Metabolism and Plant Growth under Elevated C02 in a Natural Quercus ilex L. "Macchia" Stand

Mediterranean-type woodland communities represent slightly more than 10% of the total forest surface of the world (Walter, 1985), and they make up the natural vegetation of some of the most populated and economically active areas of the globe. At the same time, the Mediterranean biome represents the intermediate vegetation between the desert zone and the temperate forests. It is, therefore, crucial to be able to anticipate the possible effects of environmental changes on these plant communities given their essential role on protecting lands that are under a strong pressure by man and climate. In Mediterranean-type ecosystems, the two main factors limiting primary productivity are water and nutrient availability (Specht, 1973; Debano and Conrad, 1978). Additionally, the frequency of disturbances is high due to the occurrence of wildfires during the summer dry season, harvesting of biomass, and animal grazing. Many plant species of the Mediterranean regions are evergreen sclerophyll shrubs and trees adapted to low water and nutrient availability, and also able to rapidly recover after disturbance by resprouting from protected buds (Naveh, 1974). L. (holm oak) is the dominant tree species of most mature communities over large areas of the Mediterranean basin (Romane and Terradas, 1992). This species avoids the damaging effects of summer 209

Copyright 9 1996 by Academic Press, Inc. All rights of reproduction in any form reserved.

210

water deficits through mechanisms that maintain positive turgor during periods of reduced water availability (Rhizopoulou 1989; Rhizopoulou and Mitrakos, 1990; Terradas and Say6, 1992), by means of stomatal closure (Romane and Terradas, 1992), and through morphological adaptations that improve the efficiency of the plant hydraulic system (Rambal, 1993). Predictions on the effects of increasing CO2 concentrations on natural communities of trees and herbs have been traditionally inferred from short-term studies conducted on plants raised under controlled conditions (Cure and Acock, 1986; Sengupta and Sharma, 1993; Ceulemans and Mousseau, 1994). Hence, a large wealth of information has been accumulated regarding the physiology of photosynthesis and transpiration (Sfitt, 1991; Eamus, 1991), stomatal activity (Idso, 1991; Bunce, 1993), leaf anatomy (Radoglou andJarvis, 1990), and biomass growth and distribution into components (Bazzaz, 1993; Luo 1994). However, according to Cipollini (1993) concern has arisen over the validity of extrapolations from short-term, small-scale experiments. Only a few long-term experiments at the community and ecosystem level have been conducted worldwide (Oechel and Riechers, 1986; Drake 1989) although a number of CO2 exposure experiments in natural conditions were recently initiated, in particular within the European ECOCRAFI' research network on "The likely impact of rising [CO2] and temperature on European forests." Critical questions that should be solved by experiments in natural habitats are (i) which plant functional type will be successful in a future double CO2 world, particularly in a drier environment; (ii) whether photosynthesis undergoes down-regulation adjustments over long-term exposure (Sage 1989); and in case of no major acclimating effects, (iii) how the excess of organic carbon is utilized by plants, particularly woody species, trees, and shrubs. Evidence exists about the increase of nonstructural carbohydrates in plants under elevated CO2, particularly in leaves (Wullschleger 1992), but also about the increment of some tree biomass components as woody stem and roots (K6rner and Arnone, 1992). The objective of our research has been, therefore, to examine the impact of long-term exposure to elevated CO2 concentration in a natural Mediterranean community dominated by (high "macchia"). Emphasis is placed on measurements of carbon metabolism and light energy utilization by the leaves in order to assess the physiological responses that subtend growth rather than just trying to measure short-term biomass increments at the tree level alone.

14.

A. The Experimental Site This study capitalizes on a long-term research conducted over the past 5 years aimed at understanding the interactions between structure, functions, and microclimate in a woody plant community, representing the natural vegetation of the Mediterranean, coastal sand dunes. The site is located near Montalto di Castro (Viterbo), along the Thyrrenian coast, 100 km northwest of Rome, at the E.N.E.L. (National Agency of Electric Energy) reservation (Lat. 42 ~ 22' N, 11 ~ 32' E). The vegetation is a Mediterranean evergreen " m a c c h i a " ecosystem, 4 - 6 m tall, dominated by trees, with a dense shrub layer made up of L., and L. Toward the seashore, this Br. B1. community is substituted by a dense belt of Caneva; toward the interior, beyond the last sand dune, the vegetation becomes a 15 m tall, deciduous forest composed of spp., and spp. trees (Fig. 1). Within the intermediate belt of high total aboveground biomass is 35 Mg ha -1 of dry matter, vegetation covers about 80% of the g r o u n d surface, and leaf area index (LAI) ranges from 3 to 4. H o l m oak

Vegetationdistribution along a profile from the coast to the interior at the Montalto di Castro experimental site.

212

trees represent 34% of total n u m b e r of woody plants, 53% of aboveground biomass, and 62% of LAI of the forest community; total aboveground productivity is around 2.5 Mg ha -1 year -1 with the oak contributing far more than one-half (Matteucci, 1991). The climate in this area is typically temperate-Mediterranean, with a mean annual temperature of 15~ the m a x i m u m temperature in s u m m e r can be greater than 35~ and the m i n i m u m winter temperature can be less than -5~ The total annual rainfall is around 610 mm; its distribution during the year typically peaks in February and in late September; consequently, the dry season lasts from May until early September (Fig. 2). B. The Experimental Setup Within this " m a c c h i a " stand, six open-top chambers (OTCs) have been installed to test the effect of atmospheric CO2 e n r i c h m e n t on clumps of natural, Mediterranean vegetation, starting from early spring 1992. The OTCs are made of an aluminium frame, coated with a transparent sheet of PVC "Cristal," 0.4 m m thick. The size of the OTCs is 4 m in diameter and 6 m in height. The airflow rate of 12,000 m 3 hr -1 inside the OTCs changes the air three to four times per minute in order to maintain the microclimate inside the chambers similar to outside. The air temperature inside the OTCs (Fig. 3) was, on average, 1.1~ higher than outside as measured continuously over a 2-year period with a CR-10 data logger (Campbell-USA). On the contrary, relative humidity was, on average, not significantly affected. The light environment inside the OTCs was affected

Climatediagram of the experimental site, according to Walter and Lieth scheme (Walter, 1985); thin and thick line are, respectively, monthly mean temperature (1 division, 10~ and monthly mean precipitation (1 division, 20 mm).

14.

[ o u t s i d e

E

1

10.0

2.0 ~:

1'2 Figure 3 Air temperature variation during the experimental period and differences between the temperatures inside and outside the OTCs. The temperature is calculated as the mean over a 10-day period.

by the PVC cover in relation to the solar elevation angle; at solar angles > 5 0 ~ the r e d u c t i o n of PPFD was b e t w e e n 0 a n d 10%, while at lower solar elevations a 30% o f r e d u c t i o n was observed. T h e CO2 c o n c e n t r a t i o n of the air inside the OTCs is either a m b i e n t or a m b i e n t plus 3 5 0 / x m o l mo1-1. In each O T C the woody vegetation c l u m p (about 30 years of age) is m a d e up, o n the average, by trees a n d by four a n d seven shrubs. T h e m e a n stem d i a m e t e r of is 7 _+ 0.8 (-+SE) cm and canopy height reaches 3.7_+0.35 m. C o r r e s p o n d i n g values for 4 _+ 0.7 a n d 2.4 -+ 0.11, a n d for 3 -+ 0.13 a n d 1.7 _+ 0.19. C. M e t h o d s

1. D u r i n g the third year of C O 2 e x p o s u r e (1994), the r e s p o n s e of n e t assimilation to the CO2 c o n c e n t r a t i o n s (A/Ci curves) was m e a s u r e d in the spring season, w h e n the water supply did n o t limit photosynthesis. C a r b o n dioxide a n d water vapor e x c h a n g e s of leaves

214 (two samples X two OTCs) were measured in the field on each of the three species with the Compact Minicuvette System (CMS, Heinz Walz GmbH, Germany), a portable, temperature and water vapor controlled, open-path, gas-exchange system. The rate of leaf photosynthesis and transpiration, as well as conductance and intercellular concentration of CO2 were calculated according to the equations of von Caemmerer and Farquhar (1981). Air temperature and air vapor pressure deficit inside the cuvette were maintained constant (25~ and VPG ---13 hPa) during measurements of steady state A/Ci curves (Table I). The cuvette was m o u n t e d on a tripod to reach sunlit branchlets; an artificial light source was utilized (HQI-Osram) to obtain about 1200/.tmol m -2 sec -~ of incident PPFD in the PAR region; measurements were taken at steady state only, about every 40 min. The response of A to Ci was fitted by nonlinear regression methods (SY STAT 5.0), with a nonrectangular hyperbola (Eq. 5 of the Table 4.1 reported by Thornley, 1976).

2. Fluorescence emission from the leaves was measured with a modulated fluorometer (PAM 101, Heinz Walz GmbH, Germany) on dark-adapted leaf samples detached from the plants of the three woody species enclosed in the OTCs (three samples x two OTCs). Fluorescence measurements were made over a 2-year period (from 1992 through 1993) in different seasons and at different times of the day to derive m i n i m u m daily values of the photochemical efficiency of PSII (Butler, 1978; Demmig-Adams 1989). For each measurement, leaf disks were collected from the upper part of the plants and were dark adapted in an aluminium container for 15 rain. With this time length the relaxation of the fast c o m p o n e n t of nonphotochemical quenching is reported to occur (Krause and Weis, 1991). Photochemical efficiency of PSII was then estimated by where is the maximum fluorescence intensity emitted from a leaf disk on application of a saturating light pulse,

Species

Treatment

Ta a

m.s.d.

PPFD

m.s.d.

VPG

m.s.d.

Ambient Elevated

25.3 25.0

0.08 0.07

1100 1113

26.0 92.8

14.2 13.4

0.48 0.36

Ambient Elevated

25.0 25.1

0.07 0.12

1137 1063

21.5 24.3

12.3 12.1

0.68 0.43

Ambient Elevated

25.1 25.0

0.01 0.01

1341 1354

8.7 11.5

12.7 14.6

0.12 0.05

"Ta, cuvette air temperature (~ PPFD, incident photon flux density (/zmol quanta m -~ s-l); VPG, vapour pressure gradient (hPa); m.s.d., mean values of the standard deviations of the A/Ci curves.

14.

215

while F0 is the m i n i m u m fluorescence intensity emitted in response to a negligible level of actinic light. As reported in the literature, this ratio is a measure of photoinhibition of photosynthesis (Ogren, 1991). During natural daily courses, generally decreases with minimum values at midday; this reduction can be related to two broad processes: an increase of nonradiative thermal deactivation and an increase of damage and repair of PSII reaction centers (Demmig-Adams and Adams, 1992; Long 1994). 3. End-products of carbon metabolism, pigments concentration, and nitrogen content were analyzed in the leaves of the three woody species in the same period as the gas-exchange measurements. Total nonstructural carbohydrates (TNC) were analyzed from leaf disks (two samples x two OTCs) collected in the morning at 9:00 AM after about 3 hr of daylight. The material was sampled from the u p p e r part of the canopy of trees and of and shrubs, included in the OTCs. Leaf disks were frozen directly in the field u n d e r liquid N2 and later stored at -80~ Sugars were extracted from disks dried for 2 min in a microwave oven and boiled for 30 min in distilled water (Wong, 1990; K6rner and Miglietta, 1994). Soluble sugars were then analyzed spectrophotometrically using the Boehringer M a n n h e i m Biochemicals kit 716260 (Germany). Starch was determined according to H u b e r and Israel (1982) and Rufty and H u b e r (1983). Chlorophyll extraction from the leaf disks (four samples x two OTCs) was carried out by dimethylformamide (DMF) whereas chlorophylls a and b content was d e t e r m i n e d spectrophotometrically, on the resulting solution, according to Moran (1982). Nitrogen content of leaves (two samples x two OTCs) was determined by Kjeldhal digestion followed by distillation in vapor of ammonia and titration. 4. Anatomical observations were carried out, in the s u m m e r 1994, on mature leaves from the southern part of the upper crown collected from one plant per species in each OTC. Two transverse sections per leaf were analyzed microscopically at five different point locations (four samples X two OTCs) for thickness of the epidermis, the palisade layer, and the spongy mesophyll. 5. The Mediterranean " m a c c h i a " species enclosed in the OTCs are considered slow-growing plants. In fact, Bruno (1977) observed a mean annual increment of the basal area of trees, comparable in size to our plants, of about 1.4 c m 2 y r -] (

0 0

0 0

e-

.-~ 7-

1.3

(A) Box plots of the observed relative changes in the growth parameters RGR, NAR (net assimilation rate), LAR (leaf area ratio), SLA (specific leaf area) and LWR (leaf weight ratio), as observed for 63 different C~ species. (B) Idem for 8 C4 species. For further information see Fig. 2. Data are from Badger (1992), Baxter (1994), Bowler and Press (1993), Callaway (1994), Carter and Peterson (1983), Chu (1992), Coleman and Bazzaz (1992), Collins (1976), DeLucia (1994), Den Hertog (1993), Hocking and Meyer (1991), Hurd and Thornley (1974), Musgrave and Strain (1988), Pettersson and McDonald (1992), Poorter (1993), Roumet (1993), Rozema (1993), Ryle (1992a,b), Van de Staaij (1993), Wong (1992), Wong (1993), and Wyse (1980) as cited in this reference list; and data from Bazzaz (1989), Bhattacharya (1985), Bunce (1990), Cure (1987, 1988),Jansen (1986),Jolliffe and Ehret (1985), Marks and Clay (1990), Mauney (1978), Neales and Nicholls (1978), Overdieck (1988), Patterson (1986), Patterson and Flint (1980, 1982), Patterson (1988), Peet (1986), Poorter (1988), Rogers (1984), Sionit (1983), Sionit (1982), Thomas (1991), and Wong (1990) as cited in the reference list from Poorter (1993).

384

(e.g., Wong, 1990). Although there is some variation in LWR values, the mean response of these relatively well-nourished plants is nil (cf. Stulen and Den Hertog, 1993). It should be noted that in quite a number of cases the first harvest of the growth analysis started after the onset of CO2 enrichment. As most of the growth response to elevated CO2 occurs in the first 10-20 days, changes in RGR and NAR may have been underestimated to some extent. A limited number of growth analyses have been carried out with C4 species. Generally, the responses are much smaller (Fig. 3B). Although the number of species in this group that is investigated (n = 8) does not allow much of a generalization, it is remarkable to see that the results seem to mirror those of the C~, with decreases in RGR and NAR, and increases in SLA.

B. Within C3 Species Sink strength has been put forward as a main modulator of the response of C3 species. As such, within the group of C3 species three main categories can be discerned. First, crop species, which have been selected to grow vigorously and thus may have a large sink strength during development. Second, the wild herbaceous species, where human selection pressure to increase sink strength generally has been much smaller. And third, woody species, which are generally slow-growing and morphologically and physiologically quite different from the first two groups anyway. On average, the crop species are the strongest in responding, at least in the vegetative growth period, with a mean dry weight increase of 58% (Fig. 2A, The response of wild herbaceous species and trees is smaller, as far as their growth stimulation is concerned (42 and 44%, respectively). However, given the larger time scale of the experiments with trees than with herbs, there is a distinction between the average stimulation in RGR of herbaceous and woody species (Fig. 2B). Generally, growth stimulation by high CO2 in herbaceous species is only temporary. Because few time trends have been analyzed for trees, it remains speculative whether they will be stimulated over a longer time period (but see Bazzaz 1993). In a comparative growth analysis of tree seedlings and a grass species, Gloser (Chapter 21) found the tree seedlings to be stimulated throughout the season in contrast with the grass species. Unfortunately, our insight into the time dependency of the growth stimulation is still fragmentary.

C. Within Wild Herbaceous C3 Species The most clear-cut difference we found in our analysis was when wild herbaceous C~ species were categorized in fast-growing, intermediate, and slow-growing species (Fig. 4). There is a general trend that fast-growing species respond much stronger than slow-growing species (60% versus

25. 3.0

~'~ n,'

Figure 4 (A) Box plots of the observed weight ratios of C3 species of the categories inherently slow-growing (n = 42), intermediate (n = 36), and fast-growing (n = 30) wild herbaceous C3 species, to the left side, and for evergreen (n = 40) and deciduous (n = 43) woody species, to the right side. (B) Idem for the absolute RGR stimulation of those categories. For further information see Fig. 2.

27%). Using these categories, 18% of the total variation in the weight ratios of Appendix 2 could be explained, and 22% in the variation in RGR stimulation. These values in themselves are not particularly high. However, given the large variability that can be expected for weight ratios (see Section IIB), this fraction of explained variance is probably at the high side of what could be achieved anyway. The grouping was carried out on the basis of a number ofmsubjectivem criteria (see Poorter, 1993). Therefore, it is good to compare these results with literature. In Fig. 5 we compiled the available data on experiments where different plant species were grown at elevated CO2 and where RGR

386

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mS""~ ~

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RGR c (rag g-1 day-l) Relationship between the absolute RGR stimulation due to high CO2 and the observed RGR at control levels of CO2. Each line represents a linear regression through literature data of different plant species grown in the same experiment. Continuous lines indicate experiments with herbaceous species, dotted lines are shown for experiments with woody plants. Data for the herbaceous plants are of Baxter (1994; 1), Bowler and Press (1993; 2), Campbell (1993; 3) and Gamier (unpublished; 4), Gobin (unpublished; 5), Mortensen (1985; 6); Musgrave and Strain (1988; 7), Overdieck (1988; 8), Poorter (1993; 9), Roumet (unpublished; 10), Tremmel and Patterson (1993; 11), and Wong (1993; 12). Data for woody species are from Lindroth (1993; a), Mortensen (1994a; c), (1994b; d), Tolley and Strain (1984; e), Wiggins (unpublished; f) and Wong (1992; g). In the experiment indicated with a *, a herb and a tree were compared Chapter 21). In those cases where the first harvest of the growth analysis occurred after the start of the CO2 enrichment, RGR stimulation was calculated according to Appendix 1.

values were d e t e r m i n e d . A l t h o u g h n o t e a c h of these r e p o r t s gave positive, significant relationships b e t w e e n the growth rate of a species a n d its RGR stimulation at h i g h CO2, the average t r e n d is a positive one. A striking result of c o m b i n i n g the data f r o m all the e x p e r i m e n t s is the e m e r g e n c e o f a clear r e l a t i o n s h i p b e t w e e n the RGR of plants at c o n t r o l levels a n d their r e s p o n s e to CO2 (Fig. 5). I n d e p e n d e n t of w h e t h e r RGR was low b e c a u s e the species u n d e r investigation were tree seedlings ( d o t t e d lines in Fig. 5) or b e c a u s e h e r b a c e o u s plants were grown over p r o l o n g e d p e r i o d s o f time a n d t h e r e f o r e showed low RGR's (like the e x p e r i m e n t s n u m b e r e d 1 a n d 4), the growth stimulation does n o t e x c e e d the 10 m g g-1 day-1. For the fast-growing h e r b a c e o u s species m e a s u r e d over relatively s h o r t p e r i o d s stimulation t u r n e d o u t to be at least twice as high. T h e large r e s p o n s e o f c r o p species in the vegetative stage, as discussed in Section IIIB, fits into this picture, as they will generally be i n t e r m e d i a t e to fast-growing as well.

387

25.

An alternative hypothesis to explain the pattern of variation in wild C~ species has been put forward by H u n t (1991, 1993). In a combined analysis of three experiments conducted in 3 consecutive years, with a total n u m b e r of 36 species, they found that the response of species was best characterized by their position in the strategy triangle of Grime (1979). The further the species were away from the C-point of the triangle (the "competitive" strategy), the less they did respond. We have several reasons why we think the relationship as observed by H u n t is not a general one. First, we were not able to reproduce this relationship when we tried to do so for 37 New Zealand grassland species (data not shown). Second, the negative relationship as given in H u n t (1993, Fig. 2) seems to be caused mainly by two outlying values, one of which is the average of an extremely high and a below-average weight ratio. Given the relatively high values in the standard deviations of In-transformed dry weights for at least some species (0.4 and 0.6 as derived from Fig. 2 of H u n t 1991), we suggest that these outliers are most likely caused by variability in their plant material (cf. Section IIB). The third and most important reason to question the relationship is a methodological one. Stated somewhat simplified, the C-radius theory expects that competitors (sensu Grime, 1979) will respond strongly to high CO2, whereas species with a ruderal or stress-tolerating strategy will not. Given that there were very few ruderals in the experiment of H u n t it is likely that the negative relationship is determined to a large extent by the competitors and stress tolerators only. In our opinion, it would be more appropriate to test for the differences between the groups of competitors, stress tolerators, and ruderals explicitly. When we use the full information of our data base, for all the species that have been classified by Grime (1988), we find that stress tolerators do respond significantly less than competitors and ruderals, and that no significant differences can be detected between the two latter groups (Table I). Therefore, the differences reduce to a contrast between the slow-growing species (stress tolerators) and fast-growing ones (ruderals and competitors). Such a division seems to make more sense, given the differences in physiology

Strategy Stress tolerators Competitors Ruderals

WH/Wc

RGRH-RGRc (mg g-1 day-l)

n of species

1.23 1.56 1.64

5.1 13.6 17.2

12 6 8

Plants categorized into the middle part of the triangle (CSR, CS, SR, or CR) were not included.

and morphology in the vegetative stage between stress tolerators on one side, and ruderals and competitors on the other side (cf. Poorter and Remkes, 1990; Poorter 1990; Garnier, 1992). However, if the analysis would be extended to the reproductive phase, it is possible that ruderals and competitors would respond in quite different ways. If ruderals start to flower and stop increasing in vegetative biomass when they reach a certain size, the difference that shows up early in life may disappear later. We made some other a posteriori analyses within the group of wild herbaceous species. No consistent differences were observed between monocotyledonous and dicotyledonous species (Fig. 6). Species that are capable

l

, i

I

I I ..............i..............• ............................[ ............i ..............

(A) Box plots of the observed weight ratios of monocotyledonous (n = 56) and dicotyledonous (n = 74) herbaceous C3-species, to the left side, and those species that potentially can fix N2 in symbiosis (n = 20) and those that cannot (n = 112), to the right side. (B) Idem for the absolute RGR stimulation of those categories. For further information see Fig. 2.

25.

389

of symbiotically fixing N2 did respond somewhat more strongly than the other herbs, though not significantly. However, given the high N availability in most of these experiments, nodulation is likely to have been inhibited, making the comparison somewhat obsolete. Direct evidence comparing the two groups of species is scarce. In the data set of Campbell (1993), with 12 leguminous species/cultivars and 20 nonleguminous ones, no significant difference between the groups was found either, although the tendency was similar as in Fig. 6. See also LOscher (Chapter 19).

D. Within Woody Species A large amount of data has been published in recent years about the response of woody species. These experiments were mainly on tree seedlings, and the median duration of these experiments is 110 days only (see Appendix 2). Thus, most research has focused on only a very limited time span of the total life cycle of these species (cf. K6rner, 1993b). Within the group of tree species, we could envisage a difference between deciduous and evergreen species, similar to the difference between fastand slow-growing species observed above. Although deciduous species do have a slightly higher RGR stimulation, this difference does not show up in the weight ratio (Fig. 4, the difference is not consistent, some direct experiments are required to obtain more insight into this problem. For a more detailed analysis of the physiological performance of tree species see Ceulemans and Mousseau (1994).

The above literature survey comprises experiments in which the availability of nutrients will have been relatively high compared to what plants generally encounter in nature. To what extent will this affect the weight ratios? Evidence is conflicting, with some reports showing weight ratios to decrease with diminishing nutrient availability, and others where the weight ratio is constant or even increases. We could imagine that this may partly coincide with the severity of the applied nutrient stress. I n some reports the low N treatment hardly caused any growth reduction (e.g., Larigauderie 1994), whereas in others the low N plants weigh only a small fraction of the control. To allow for this variation, we plotted the weight ratio (weight of high CO2 relative to those of control levels) against the relative reduction in size of the plants at control levels of CO2 due to the low nutrient treatment, for both trees and herbaceous C~ species (Fig. 7). The observed relationship shows a lot of scatter, as expected (Section IIB). A way to correct for this is to consider the data of each species and experiment separately. We did so by calculating regression lines through all the points

o

9

0.0

9

o

o

o

o

o

0',

9

;.0

Wc,Iow NU / Wc,high NU Figure 7 Weight ratios of plants grown at high and low nutrient availability. The x-axis values indicate the severity of the nutrient stress, calculated as the weight of the plants at low nutrient availability divided by the total plant weight at the highest nutrient availability. The circles pertain to observations on herbaceous Ca species, the squares to observations on woody species. The continuous and broken line indicate the average response of herbaceous and woody species, respectively. Values are from Bassow (1994), Bazzaz and Miao (1993), Bowler and Press (1993), Coleman (1993), E1 Kohen and Mousseau (1994), E1 Kohen (1992), Griffin (1993), Hocking and Meyer (1985), Johnsen (1993), Kerstiens and Hawes (1994), Larigauderie (1994), McConnaughay (1993), Norby and O'Neill (1991), Radoglou and Jarvis (1992), Silvola and Alholm (1992, 1993), Wilkins (1994), Wong (1990), and Wong (1992), as listed in the References, and from Cure (1988), Goudriaan and De Ruiter (1983), Larigauderie (1988), Marks and Clay (1990), Oberbauer (1986), and Patterson and Flint (1982), as cited in the references from Poorter (1993).

o f Fig. 7 that p e r t a i n e d to o n e species in o n e e x p e r i m e n t . T h e m e a n slope o f all these regression lines is positive (P < 0.01), indicating that the average g r o w t h r e s p o n s e of plants to h i g h CO2 d e c r e a s e s w h e n n u t r i e n t availability decreases. This applies to woody a n d h e r b a c e o u s C3 species to the same extent, as can be seen f r o m the regression lines in Fig. 7. For b o t h g r o u p s of species the r e s p o n s e is almost nil at e x t r e m e l y limiting conditions. It s h o u l d be realized t h a t the r e s p o n s e s h e r e are analyzed in a relative way. It is clear t h a t the growth stimulation at low N levels is m u c h lower anyway, w h e n the absolute r e s p o n s e s are c o n s i d e r e d ( K t r n e r , 1993b).

As m e n t i o n e d above, the data listed in A p p e n d i x 2 have b e e n o b t a i n e d o n individually grown plants, at relatively h i g h availabilities of water a n d

25.

391

nutrients. To what extent this information can be extrapolated to the natural field situation, with its myriad of interactions and feedbacks between a wide range of organisms is unknown. As far as such extrapolations are permitted, there are two points that deserve attention. First, one should realize that a high weight ratio does not imply that the high-CO2 plants have increased in "functional size" to the same extent. This is due to the fact that the higher dry weight is caused partly by an increased accumulation ofnonstructural carbohydrate in the leaves. Thus, in a competitive situation, where light interception, and thus total leaf area, is of more importance than leaf weight, differences between types of species will be smaller than expected on the basis of the analysis of Section III. Second, responses of biomass to CO2 in natural environments will generally be less than in these compiled experiments, due to a lower nutrient availability (Field 1992; Section IV; but see Gifford, 1994). Let us make a simple contrast of inherently slow-growing species growing in low-nutrient (low-resource) environments and inherently fast-growing species in nutrient-rich (highresource) environments (cf. Grime, 1979; Poorter and Remkes, 1990). Given the low nutrient availabilities in the habitats of the inherently slowgrowing species, and the very modest response of those species anyway (Fig. 4), we do not expect much of a change in biomass in such environments. A somewhat larger response can be anticipated of the faster-growing species growing in their nutrient-richer habitat (say, an increase in biomass of ---25%). We doubt whether this by itself will have a large impact on the vegetation. Indeed, in the experiments in natural vegetations under way, generally very small responses in biomass are observed (K6rner Chapter 28). A somewhat different question is whether the floristic composition of the vegetation will alter. Up to now, we have assumed that all species within a functional group will respond more or less similarly. However, if there is considerable variation between species within the functional types discerned, this may still affect the floristic composition of the vegetation, even if the total a m o u n t of biomass does not change that much. Also at this point the available evidence is scarce (Bazzaz, 1990). Intended more as a provocative statement than a conclusion we suggest that, given these considerations, the effect of an increase in the atmospheric CO2 concentration on the growth of plants in natural vegetations is relatively small, and that any changes in the ecosystem are more likely to occur via an increased water use efficiency or via changes in the chemical composition of the plants, rather than via a biomass response.

In this chapter we discussed aspects of the growth response of plants to elevated CO2. A simple way to express the stimulation is to calculate the

392 ratio between the biomass of high-CO2-and control-CO2-grown plants, the weight ratio. A major problem with weight ratios is that their variability is high, even when relatively large numbers of plants are harvested. Another weak point of this ratio is that it does not include a time effect. Alternatively, the absolute stimulation in relative growth rate may be used. The amount of information required for this analysis cannot be obtained from a single experiment, and therefore results of 250 plant species from a large number of experiments have been compiled in order to calculate the average response of groups of plants. Basically, the conclusions are similar to those of Poorter (1993). C3 plants were found to be more responsive (47% increase in weight) than those with the C4 and CAM photosynthetic pathway. However, on average C4 species also respond significantly to elevated CO2 (10%). There is insufficient insight into the causes of this stimulation. Also within the C~ group of species differences were found between functionally different types of species. On average, potentially fast-growing wild species and crop species show relatively strong growth responses to high CO2 (58 and 60% increase in weight, respectively), whereas the response of inherently slow-growing species is only half of that (27%). Woody species have an intermediate response when final weights are considered (44%), but are far less responsive when the longer time span in those experiments is taken into account. When the growth response of plants to high CO2 is analyzed at a low nutrient availability, on average a lower weight ratio is found, with no growth stimulation at all at severely limiting conditions. As far as these results of plants grown individually can be extrapolated to natural vegetations, this is one of the reasons that we expect the growth response in the field to be small.

We thank Eric Garnier,Jan Gloser, Kevin Griffin, Marilyn Ball, and Olivier Gobin for providing us with as yet unpublished data. Hans Lambers and Adrie van der Werf made helpful suggestions on an earlier draft of the manuscript.

Assume that plants have a weight W1 at time tl and that they grow with a constant RGR over the time interval tl to t2. Assume that plants are separated into two groups at time h, high-CO2-grown plants (H) and control plants (C). The weight of the control plants at time t2 is then given by

393

25. Wc --

W1 9 e RGRc (t2-tl)

(1)

and that of the high CO2 plants by W H --

W 1 " e RGRH (t'2-tl).

(2)

The weight ratio at time t2 is then given by WH

Wc

W1 9 eRGRH (t2-t 1)

=

W~ 9e~e~ (~-,,/

(3)

and thus - - e(RGRH -RGRc) (t~-tl).

(4)

Wc Consequently, the absolute average stimulation of RGR over time can be calculated as

w~ ln~ Wc A RGR = . t2-tl

(5)

Note that it is the absolute difference in RGR over a certain time period that is of interest, rather than the relative response, as RGR is a relative p a r a m e t e r itself already. From Eq. 4 one can derive that it is an absolute difference in RGR that causes a certain relative difference in plant weight over a given time span. Equation (4) can be rewritten as WH

Wc

"- e

(k-l) r (t2-tl)

where r = RGRc and = RGRH. By definition, potentially fast-growing species have higher r than slow-growing species. If high CO2 would have the same relative effect k on the RGR of both fast- and slow-growing species, then (k - 1)r would be higher for the fast-growing species, and, consequently, the weight ratio of these species. In physiological terms, this could be the case if the leaf a r e a : p l a n t weight ratio is higher for the fast- than for the slow-growing species, and photosynthesis is stimulated in all species to the same extent.

A compilation of the ratio of total weight of plants grown at a high (60-80 Pa) and at a control concentration (30-40 Pa) of CO2. Data are of various literature sources and comprise 503 observations on a total of 256

394

species. Final yield was taken when plants remained vegetative. In other cases plant weight before flowering or fruiting was used. In those cases where mean relative growth rates were given, these values were used for the calculation of the weight ratio, as they summarize data of more than one harvest. For each species and reference, the n u m b e r of days that the experiment lasted (n days), and the total n u m b e r of plants harvested per treatment on which the ratio is based (n plants), are given. Previous no. indicates the n u m b e r of references in Poorter (1993) for the same species. These references are not repeated here, but those data are also used to calculate the mean weight ratio per species. Mean values per species and per category are backtransformed values of averaged log-transformed ratios, to correct for the intrinsically skewed nature of ratios. For the C~ wild species it is indicated whether they are potentially slow-growing (s), intermediate (i), or fast-growing (f). For each category, the median value of the weight ratio, the duration of the experiment, and the n u m b e r of plants harvested per treatment are given. n n days plants

Species

Mean Previous weight no. ratio

Reference

A. C3 crop species

1.43

20

10

1.51

35

5

1.93 1.80 2.08

18 32 30

12 12 4

Gobin

(unpublished)

Tremmel and Patterson (1993) Rogers (1992) Rufty (1994) Thomas (1993)

1

1.08

0 1 1 1 13

1.43 1.56 1.83 2.10 1.71

1.82 1.64

3.91 1.42 1.79 2.13 2.23 2.29 1.65

20 28 28 28 20 28 31

10 10 10 10 10 10 ?

1.75 2.01 2.75

35 35 28

3 3 10

Gobin (unpublished) Campbell (1993) Campbell (1993) Campbell (1993) Gobin (unpublished) Campbell (1993) Stanghellini and Bunce (1993) Ziska and Bunce (1993) Ziska and Bunce (1994) Campbell (1993)

2.04 1.82

1.38 1.93

395

25.

n

Species

n

days plants 1.51

9

9

1.19

113

20

1.20

113

10

1.33

113

20

1.62

113

10

1.30

29

6

1.61

60

3

1.34 1.41 1.41 1.58

28 40 40 28

4 14 14 ?

1.06

45

6

Reference Sicher et

(1994)

Ziska and Teramura (1992b) Ziska and Teramura (1992a) Ziska and Teramura (1992b) Ziska and Teramura (1992a) Radoglou and Jarvis (1992)

Retuerto and Woodward (1993) Billes (1993) Nicolas (1993) Nicolas (1993) Rozema (1993) Radoglou and Jarvis (1993)

Mean weight ratio

0

1.51

2

1.37

0

1.30

4 5 0

1.36 1.64 1.61 1.47

1.46 1.23 1.45 1.80

u Median values (n = 97)

Previous no.

1.58

28

8

1.24 1.33

28 50

6 5

1.55

35

5

1.68 1.35

40 150

? 5

B. C3 wild species Dippery (1995) Coleman and Bazzaz (1992) Tremmel and Patterson (1993) Coleman (1993) Downton and Grant (1994)

1.43

1.35 1.71

1.59 2.00

58 79

6 7

Bowler and Press (1993) Baxter (1994)

1.57 1.82

396

n

Species

days plants 2.20

28

Previous no.

n

10

Reference Campbell

Mean weight ratio

(1993) 1

1.10

1 0

1.40 1.38

1

1.21

Ferris and Taylor (1993)

0

0.96

1

1.50

1

1.35

1 1

1.13 1.15

0 1

1.21 1.00

0 2

1.27 1.46

1 0 1

3.60 1.03 1.66

1.00 1.92 1.21

49 28 52

8 10 8

Hunt Campbell Hunt

(1993) (1993) (1993)

0.96

100

5

1.14 2.53 1.67

52 20 63

8 10 10

Hunt (1993) Gobin (unpublished) Johnson and Lincoln (1991)

1.12 1.19 1.21 1.00

100 25 20 52

16 11 10 8

Lenssen (1993) Lenssen (1993) Gobin (unpublished) Hunt (1993)

1.27 1.19 1.73

49 20 144

8 10 4

Hunt (1993) Gobin (unpublished) Gamier et a/. (unpublished)

1.03 1.34 1.37

20 20 180

10 10 4

Gobin (unpublished) Gobin (unpublished) Garnier (unpublished)

1.49

20

10

Gobin

(unpublished)

1.16 1.49 2.92 2.57 1.04 1.72 1.41

1.81 2.16

28

10

Campbell

(1993)

?

Gloser and Bartok (1994)

1.69 2.16

397

25.

Species

n

n

days

plants

Previous no.

Reference

1.37

35

5

1.90 1.18

21 49

10 8

Tremmel and Patterson (1993) Gobin (unpublished) Hunt (1993)

1.51

21

10

Gobin

(unpublished)

Mean weight ratio

1

1.30

1 1 1

1.13 1.10 1.48 1.90 1.18

1.51 1.59

1.25

52

8

Hunt

(1993)

2.14 1.26

1.74

28

10

Campbell

(1993)

1.74 1.67

2.22

28

10

Campbell

(1993)

2.22

1.27 1.56 1.63 1.74

52 28 56 35

8 10 3 3

Hunt (1993) Campbell (1993) Ziska and Bunce (1994) Ziska and Bunce (1993)

2.31

1.72 1.28 1.30 1.16 1.25

49

8

1.06 1.29 1.31 1.36 1.40 1.64 1.64 1.67

71 29 65 34 23 65 65 35

18 15 12 15 17 12 14 5

Hunt

(1993)

Lenssen (1993) Lenssen (1993) Lenssen (1993) Lenssen (1993) Lenssen (1993) Lenssen (1993) Van de Staaij (1993) Tremmel and Patterson (1993)

1.25 1.33 1.37

1.67

n

Species

days plants 1.12

52

Mean Previous weight no. ratio

n

8

Reference Hunt

Campbell

(1993)

1.11

1

1.19

0

1.30

2 1 0 0 1

1.44 1.00 0.42 1.23 1.00

1.30

28

10

1.24 0.42 1.23

58 189 52

4 6 8

1.76 2.67

28 20

10 10

Campbell Gobin

(1993) (unpublished)

1 0

1.68 2.67

1.63

20

10

Gobin

(unpublished)

0

1.63

1

1.02

1

O.78

1 0

1.46 1.03

0

1.61

0

1.26

Hunt Baxter Hunt

Hunt

(1993)

1

(1995) (1994) (1993)

1.03

49

8

(1993)

1.57 1.66 1.26

28 28 20

10 10 10

Campbell Campbell Gobin

1.61 1.00 1.75 2.11 1.93

20 49 100 28 28

10 8 5 10 10

Gobin (unpublished) Hunt (1993) Ferris and Taylor (1993) Campbell (1993) Campbell (1993)

(1993) (1993) (unpublished)

(wild) 1.61 1.55

1.93 1.57

1.27

146

4

1.31

146

4

Garnier (unpublished) Garnier (unpublished)

1.27 1.31 1.17

spec?

0.92

399

25.

n

Species

Mean Previous weight no. ratio

n

days plants

1.22 1.00

62 49

6 8

1.94

28

10

Reference

2

1.36

Bowler and Press (1993) Hunt (1993)

0 0 1

1.22 1.00 1.32

Campbell

1

1.67

1 0 1 2

2.72 2.09 1.02 1.28

3 0 0 1 0 1 1

1.48 0.90 1.30 1.23 2.09 1.03 1.48

0

1.65

1

0

1.31 2.08

0

1.92

1 1

1.46

(1993)

2.09

28

10

Campbell

(1993)

1.38

28

10

Campbell

(1993)

0.90 1.30 1.50 2.09

100 105 28 28

5 6 10 10

Ferris and Taylor (1993) Baxter (1994) Campbell (1993) Campbell (1993)

1.65

62

15

Lenssen (1993)

2.08

28

10

Campbell

1.92

100

5

(1993)

Ferris and Taylor (1993)

1.70

2.30

28

10

Campbell

(1993)

0

2.30

1.76

28

10

Campbell

(1993)

0

1.76

1.70

28

10

Campbell

(1993)

0

1.70

1.77 1.83 2.16 2.24 2.31 2.66 0.86

28 42 28 28 28 28 28

10 8 10 10 10 10 10

Campbell (1993) Ryle (1992a) Campbell (1993) Campbell (1993) Campbell (1993) Campbell (1993) Campbell (1993)

1.77 2.00

1.24

400

Previous no.

Mean weight ratio

10

Van der Eerden (1993) Gobin (unpublished)

0

1.61

21

10

Gobin

0

1.32

1.16 1.73

52 28

8 10

Hunt Campbell

(1993) (1993)

4 0

1.45 1.73

1.44

38

8

1.76

365

20

Samuelson and Seiler (1992)

0

1.76

1 1

1.40 1.21

0

1.25

0

1.38

1

1.60

0

2.20

n

n

days

plants

1.78

40

?

1.61

21

1.32

Species

Median values (n = 174)

Reference

(unpublished)

C. C3 woody species

1.11 1.20 1.47 1.07 1.20 1.42 1.58 1.03 1.44 1.66 2.67 4.68 2.20

70 210 900 60 900 210 70 35 60 51 100 140 100

4 6 6 10 6 6 5 5 7 3 10 6 5

1.02 1.03 1.32 1.94

210 900 79 90

6 6 4 10

2.15

90

10

Bassow (1994) Bazzaz and Miao (1993) Bazzaz (1993) Bazzaz (1990) Bazzaz (1993) Bazzaz and Miao (1993) Bunce (1992) Reid and Strain (1994) Lindroth (1993) Bunce (1992) Bazzaz (1990) Tschaplinski (1995) Wiggins (unpublished)

Bazzaz and Miao (1993) Bazzaz (1993) Bassow (1994) Rochefort and Bazzaz (1992) Rochefort and Bazzaz (1992)

1.44 1.73 4.13 1.28

2.15 0.90

401

25.

n

n

days

plants

1.24 1.57

60 90

10 10

1.18 1.58

37 122

16 4

1.67

38

3

3.07 0.99 1.21 1.21 1.44 2.44

34 900 66 210 79 90

20 6 9 6 4 10

1.01 1.20 1.26

540 150 150

4 16 24

1.27

180

18

1.66 1.20 2.01 1.30

270 63 63 100

10 30 30 5

Species

Previous no.

Reference Bazzaz (1990) Rochefort and Bazzaz (1992) Mortensen (1994b) Silvola and Ahlholm (1995) Pettersson and McDonald (1992) Pettersson (1993) Bazzaz (1993) Miao (1992) Bazzaz and Miao (1993) Bassow (1994) Rochefort and Bazzaz (1992) Rouhier (1994) E1 Kohen (1993) E1 Kohen and Mousseau (1994) E1 Kohen (1992)

Mean weight ratio

0

1.39

0

1.76

0

1.39

1

1.23

1.14 Kaushal (1989) Cruz (1993) Cruz (1993) Wiggins (unpublished)

1.66 1.55 1.30

1.61 2.11 3.44 1.57 3.90

42

4

Conroy

(1992)

2.03 1.45 1.32 2.56 1.19

402

Species

n

n

days

plants

Previous no.

Reference

1.50 1.83 1.62

70 60 150

6 10 22

Reid and Strain (1994) Bazzaz (1990) E1 Kohen (1993)

1.38 1.51

210 900

6 6

Bazzaz and Miao (1993) Bazzaz (1993)

1.25 1.38

81 82

54 54

1.42

128

6

1.16

850

10

Mortensen (1994a) Mortensen (1994a) Tschaplinski Norby

(1995) (1992)

Mean weight ratio

1

2.74

0

1.66

0 1 0

1.62 1.10 1.44 1.26 1.25 1.38 0.90 1.52 1.42 2.35 1.32

1.12 1.61

59 126

5 10

Bunce (1992) Berryman

(1993)

1.12 1.61 0.92

1.32

90

4

Downton and Grant (1994)

1.46 1.17 1.79 1.30

1.07 1.14 1.23 1.35 1.35 1.44

111 49 111 110 401 112

90 16 90 90 16 20

1.47 1.30 1.50

115 155 112

90 48 20

1.65

305

80

Mortensen (1994a) Mortensen (1994b) Mortensen (1994a) Mortensen (1994a) Mortensen (1994a) Yakimchuk and Hoddinott (1994) Mortensen (1994a) Johnsen (1993) Yakimchuk and Hoddinott (1994) Samuelson and Seiler (1994)

1.22

1.46

1.40

1.70

403

25.

n

n

days

plants

1.75

152

40

1.16 1.24 1.43

115 390 300

90 45 10

1.82

112

20

1.02

112

90

1.04 1.29 1.67 1.26 1.48

112 270 120 60 166

90 10 12 16 8

1.76

407

3

1.20 1.03 1.09 1.21 1.28 1.40 1.59 1.79

100 112 112 112 100 120 177 172

10 90 90 90 5 48 5 10

1.82

166

8

1.63

126

6

Species

Previous no.

Reference Samuelson and Seiler (1993) Mortensen (1994a) Lee (1994) Stewart and Hoddinott (1993) Yakimchuk and Hoddinott (1994) Mortensen (1994a) Mortensen (1994a) Kaushal (1989) Guehl (1994) Callaway (1994) Griffin (unpublished) Johnson (1995) Bazzaz (1990) Mortensen (1994a) Mortensen (1994a) Mortensen (1994a) Griffin (1993) Lewis (1994) Thomas (1994) Larigauderie (1994) Griffin (unpublished) Tschaplinski

(1995)

spec. x

spec.

1.49

158

5

1.26

70

34

Curtis and Teeri (1992)

1.34 0.64 0.65 1.23 1.48

152 195 195 195 60

24 5 5 5 7

Zak (1993) Ceulemans (1994) Ceulemans (1994) Ceulemans (1994) Lindroth (1993)

Curtis

(1995)

Mean weight ratio

0

1.20

0

1.62

0 2 0 0 0 0

1.02 1.38 1.04 1.29 1.67 1.49

1.35 1.20 1.17

1.45

1.15 1.13 2.13 1.65 1.58 1.30

1.06

1.48

n

n

days

plants

1.41

180

16

1.81 1.33 1.03 1.06 1.36 2.00 2.81

540 60 450 116 450 90 90

3 10 6 90 6 9 10

Species

2.37 0.89 1.17 1.25 1.46 2.21 3.72

120 64 198 210 900 60 520

12 5 14 6 6 7 13

Previous no.

Reference Kerstiens and Hawes (1994) Wilkins (1994) Bazzaz (1990) Gorissen (1995) Mortensen (1994) Gorissen (1995) Condon (1992) Condon (1992)

Guehl (1994) Bunce (1992) Vivin (1995) Bazzaz and Miao (1993) Bazzaz (1993) Lindroth (1993) SeegmOller and Rennenberg (1994)

Mean weight ratio

0

1.59

0 1

1.33 1.11

0 0 1

2.00 2.81 1.43

1.20 1.78 2.37 0.89 1.17 1.59

1.17 1.07 1.32

x

1.46

120

4

3.27

120

3

Silvola and Ahlholm (1992) Silvola and Ahlholm (1993)

1.46 3.27 1.19 2.64 1.21

Median values (n = 174):

1.40

100

10

1.40

112

8

Bazzaz

(1990)

1.40

D. C4 species 1.26 1.02 0.90

28

6

Dippery

(1995)

1.26

405

25.

Species

n

n

days

plants

1.14

35

5

1.27

50

5

1.39

40

?

1.37 0.94

76 28

8 10

Previous no.

Reference

Mean weight ratio

Tremmel and Patterson (1993) Coleman and Bazzaz (1992) Coleman (1993)

Morgan

(1994)

Campbell

(1993)

1

0.63

1

1.14

1

1.30

1

1.06

1

1.23

5

1.37

3 1

1.11 1.45

1

1.22

0.95

28

10

Campbell

(1993)

0

0.95

1.15

28

10

Campbell

(1993)

0

1.15

1

1.21

2 0

1.11 0.88

0.88

28

10

Campbell

(1993)

1.73 1.52 1.09

35

5

Tremmel and Patterson

1.10

(1993)

Median values (n = 49)

0.80 0.90 0.95 0.83

58 58 57 28

28 14 35 10

0.87 1.14

?

?

30

8

Lenssen (1993) Lenssen (1993) Lenssen (1993) Campbell (1993)

Rozema (1993)

0.88

0.83 0.94 1.09

n n days plants

Species

Mean Previous weight no. ratio

Reference

E. CAM species

Median values (n=9) All species Median values (n = 503)

1.10

126

4

Nobel

(1994)

1.34 1.44

161 84

5 5

Cui (1993) Cui and Nobel (1994)

1.15

161

5

1.42

49

8

1

1.36

1 1

1.22 1.08

1 1

0.90 1.14

1

1.22

Badger, M. (1992). Manipulating agricultural plants for a future high CO~ environment. 40, 421-429. Barnett, V., and Lewis, T. (1978). "Outliers in Statistical Data." John Wiley, Chichester. Bassow, S. L., McConnaughay, K. D. M., and Bazzaz, F. A. (1994). The response of temperate tree seedlings grown in elevated CO2 to extreme temperature events. App. 4, 593-603. Baxter, R., Ashenden, T. W., Sparks, T. H., and Farrar, J. F. (1994). Effects of elevated carbon dioxide on 3 montane grass species. I. Growth and dry matter partitioning. 45, 305-315. Bazzaz, F. A. (1990). The response of natural ecosystems to the rising global CO2 levels. 21, 167-196. Bazzaz, F. A., and Miao, S. L. (1993). Successional status, seed size, and responses of tree seedlings to CO2, light, and nutrients. 74, 104-112. Bazzaz, F. A., Coleman,J. S., and Morse, S. R. (1990). Growth responses of major co-occurring tree species of the northeastern United States to elevated COz. 20,1479-1484. Bazzaz, F. A., Miao, S. L., and Wayne, P. M. (1993). CO2-induced growth enhancements of co-occurring tree species decline at different rates. 96, 478-482. Berryman, C. A., Eamus, D., and Duff, G. A. (1993). The influence of CO2 enrichment on growth, nutrient content, and biomass allocation of 41, 11-21.

25.

407

Billes, G., Rouhier, H., and Bottner, P. (1993). Modifications of the carbon and nitrogen allocations in the plant L.) soil system in response to increased atmospheric CO2 concentration. 157, 215-225. Bowes, G. (1991). Growth at elevated CO2: Photosynthetic responses mediated through rubisco. 14, 795-806. Bowler, J. M., and Press, M. C. (1993). Growth responses of 2 contrasting upland grass species to elevated CO2 and nitrogen concentration. 124, 515-522. Bunce, J. A. (1992). Stomatal conductance, photosynthesis and respiration of temperate deciduous tree seedlings grown outdoors at an elevated concentration of carbon dioxide. 15, 541-549. Callaway, R. M., DeLucia, E. H., Thomas, E. M., and Schlesinger, W. H. (1994). Compensatory responses of CO2 exchange and biomass allocation and their effects on the relative growth rate of ponderosa pine in different CO~ and temperature regimes. 98, 159-166. Campbell, B. D., Laing, W. A., and Newton, P. C. D. (1993). Variation in the response of pasture plants to carbon dioxide. "Proceedings of the XVII International Grassland Congress," pp. 1125-1126. Carter, D. R., and Peterson, K. M. (1983). Effects of a CO2-enriched atmosphere on the growth and competitive interaction of a C3 and C4 grass. 58, 188-193. Ceulemans, R., and Mousseau, M. (1994). Effects of elevated atmospheric CO2 on woody plants. 127, 425-446. Ceulemans, R., Perez-Leroux, A., and Shao, B. Y. (1994). Physiology, growth and development of young poplar plants under elevated CO~. "Vegetation Modelling and Climate Change Effects" (F. Veroustrate and R. Ceulemans, eds.), pp. 81-98. SPB Academic Publishing, The Hague, The Netherlands. Chu, C. C., Coleman,J. S., and Mooney, H. A. (1992). Control ofbiomass partitioning between roots and shoots: Atmospheric CO2 enrichment and the acquisition and allocation of carbon and nitrogen in wild radish. 89, 580-587. Coleman, J. S., and Bazzaz, F. A. (1992). Effects of CO2 and temperature on growth and resource use of co-occurring C3 and C4 annuals. 73, 1244-1259. Coleman, J. S., McConnaughay, K. D. M., and Bazzaz, F. A. (1993). Elevated CO2 and plant nitrogen-use--Is reduced tissue nitrogen concentration size-dependent? 93, 195-200. Collins, W. B. (1976). Effect of carbon dioxide enrichment on growth of the potato plant. 11, 467-469. Condon, M. A., Sasek, T. W., and Strain, B. R. (1992). Allocation patterns in two tropical vines in response to increased atmospheric CO2. 6, 680-685. Conroy, J. P., Milhat, P.J., and Barlow, E. W. R. (1992). Effect of nitrogen and phosphorus availability on the growth response of to high CO2. 15, 843-847. Cruz, C., Lips, S. H., and Martins-Lougao, M. A. (1993). The effect of nitrogen source on photosynthesis of carob at high CO2 concentrations. 89, 552-556. Cui, M., and Nobel, P. S. (1994). Gas-exchange and growth responses to elevated CO~ and light levels in the CAM species 17, 935-944. Cui, M., Miller, P. M., and Nobel, P. S. (1993). COz exchange and growth of the crassulacean acid metabolism plant under elevated CO2 in open-top chambers. 103, 519-524. Curtis, P. S., and Teeri, J. A. (1992). Seasonal responses of leaf gas-exchange to elevated carbon dioxide in 22, 1320-1325. Curtis, P. S., Vogel, C. S., Pregitzer, K. S., Zak, D. R., and Teeri, J. A. (1995). Interacting effects of soil fertility and atmospheric CO2 on leaf area growth and carbon gain physiology x (Dode) Guinier. 129, 253-263. in

408 DeLucia, E. H., Callaway, R. M., and Schlesinger, W. H. (1994). Offsetting changes in biomass allocation and photosynthesis in ponderosa pine in response to climate change. 14, 669-677. Den Hertog, J., Stulen, I., and Lambers, H. (1993). Assimilation, respiration and allocation of carbon in affected by atmospheric CO2 levels. 104/105, 369-378. Dippery, J. K., Tissue, D. T., Thomas, R. B., and Strain, B. R. (1995). Effects of low and elevated CO2 on C3 and C4 annuals. I. Growth and biomass allocation. 101, 13-20. Downton, W. J. S., and Grant, W. J. R. (1994). Photosynthetic and growth responses of variegated ornamental species to elevated COs. 21, 273-279. E1 Kohen, A., and Mousseau, M. (1994). Interactive effects of elevated COs and mineral nutrition on growth and COs exchange of sweet chestnut (Castanea 14, 679-690. E1 Kohen, A., Rouhier, H., and Mousseau, M. (1992). Changes in dry weight and nitrogen partitioning induced by elevated COs depend on soil nutrient availability in sweet chestnut Mill.). 49, 83-90. E1Kohen, A., Venet, L., and Mousseau, M. (1993). Growth and photosynthesis of two deciduous forest species at elevated carbon dioxide. 7, 480-486. Ferris, R., and Taylor, G. (1993). Contrasting effects of elevated COs on the root and shoot growth of 4 native herbs commonly found in chalk grassland. 125, 855-866. Field, C. B., Chapin, F. S., Matson, P. A., and Mooney, H. A. (1992). Responses of terrestrial ecosystems to the changing atmosphere: A resource-based approach. 23, 201-235. Gamier, E. (1992). Growth analysis of congeneric annual and perennial grass species. 80, 665-675. Gifford, R. M. (1994). The global carbon cycle: A viewpoint on the missing sink. 21, Gloser, J., and Bartak, M. (1994). Net photosynthesis, growth rate and biomass allocation in a rhizomatous grass grown at elevated COs concentration. 30, 143-150. Gorissen, A., Kuikman, P.J., and Van de Beek, H. (1995) Carbon allocation and water use in juvenile Douglas fir under elevated COs. 129, 253-263. Griffin, K. L., Thomas, R. B., and Strain, B. R. (1993). Effects of nitrogen supply and elevated 95, carbon dioxide on construction cost in leaves of (L.) seedlings. 575-58O. Grime, J. P. (1979). "Plant Strategies and Vegetation Processes." Wiley, Chichester. Grime, J. P., Hodgson, J. G., and Hunt, R. (1988). "Comparative Plant Ecology: A Functional Approach to Common British Species." Unwin Hyman, London. Guehl, J. M., Picon, C., Aussenac, G., and Gross, P. (1994). Interactive effects of elevated COs and soil drought on growth and transpiration efficiency and its determinates in two European forest tree species. 14, 707-724. Hocking, P.J., and Meyer, C. P. (1985). Responses of noogoora burr Bertol.) to nitrogen supply and carbon dioxide enrichment. 55, 835-844. Hocking, P.J., and Meyer, C. P. (1991). Effects of COs enrichment and nitrogen stress on growth, and partitioning of dry matter and nitrogen in wheat and maize. 18, 339-356. Hunt, R., Hand, D., Hannah, M. A., and Neal, A. M. (1991). Response to COs enrichment in 27 herbaceous species. 5, 410-421. Hunt, R., Hand, D. W., Hannah, M. A,, and Neal, A.M. (1993). Further response to COs enrichment in British herbaceous species. 7, 661-668. 9 Hurd, R. G., and Thornley, J. H . M. (1974). An analysis of the growth of young tomato plants in water culture at different light integrals and COs concentrations. I: Physiological aspects. . . . . .... 38, 375-388.

25.

409

Johnson, D. W., Ball, T., and Walker, R. F. (1995). Effects of elevated CO2 and nitrogen on nutrient uptake in ponderosa pine seedlings. 168/169, 535-545. Johnson, K. H. (1993). Growth and ecophysiological responses of Black Spruce seedlings to elevated CO2 under varied water and nutrient additions. 23, 1033-1042. Johnson, R. H., and Lincoln, D. E. (1991). Sage brush carbon allocation patterns and grasshopper nutrition: The influence of CO2 enrichment and soil mineral nutrition. 87, 127-134. Kaushal, P., Guehl,J. M., and Aussenac, G. (1989). Differential growth response to atmospheric carbon dioxide enrichment in seedlings of and ssp. Laricio var. Corsicana. J. For. Res. 19, 1351-1358. Kerstiens, G., and Hawes, C. V. (1994). Response of growth and carbon allocation to elevated CO2 in young cherry (Pmnus L.) saplings in relation to root environment. 128, 607-614. K6rner, C. (1993a). Scaling from species to vegetation: The usefulness of functional groups. "Biodiversity and Ecosystem Functioning" (E. D. Schulze, and H. A. Mooney, eds.), pp 118-140. Springer-Verlag, Berlin. K6rner, C. (1993b). CO2 fertilization: The great uncertainty in future vegetation development. "Vegetation Dynamics and Global Change" (A. M. Solomon and H. H. Shugart, eds.), pp. 53-70. Chapman & Hall, New York. Lambers, H., and Poorter, H. (1992). Inherent variation in growth rate between higher plants: A search for physiological causes and ecological consequences. 23, 188-261. Larigauderie, A., Reynolds, J. F., and Strain, B. R. (1994). Root response to CO2 enrichment and nitrogen supply in loblolly pine. 165, 21-32. Lee, H. S.J., Muray, M., Evans, L., Pettersson, R., Leith, I., Barton, C. V. N., and Jarvis, P. G. (1994). Effects of elevated CO2 on Sitka spruce seedlings. 104/105, 458-459. Lenssen, G. M. (1993). "Response of C3 and C4 Species from Dutch Salt Marshes to Atmospheric CO2 Enrichment." Thesis, Free University, Amsterdam. Lenssen, G. M., Lamers, J., Stroetenga, M., and Rozema, J. (1993). Interactive effects of atmospheric COz enrichment, salinity and flooding on growth of C3 and C4 salt marsh species. 104/105, 379-388. Lewis, J. D., Thomas, R. B., and Strain, B. R. (1994). Effect of elevated CO2 on mycorrhizal colonization of loblolly pine (Pinus L.) seedlings. 165, 81-88. Lindroth, R. L., Kinney, K. K., and Platz, C. L. (1993). Responses of deciduous trees to elevated atmospheric COz~Productivity, phytochemistry, and insect performance. 74, 763-777. McConnaughay, K. D. M., Berntson, G. M., and Bazzaz, F. A. (1993). Limitations to CO2 induced growth enhancement in pot studies. 94, 550-557. Miao, S. L., Wayne, P. M., and Bazzaz, F. A. (1992). Elevated CO2 differentially alters the responses of co-occurring birch and maple seedlings to a moisture gradient. 90, 300-304. Morgan, J. A., Knight, W. G., Dudley, L. M., and Hunt, H. W. (1994). Enhanced root system C-sink activity, water relations and aspects of nutrient acquisition in mycotrophic subjected to CO2 enrichment. 165, 139-146. Mortensen, L. M. (1985). Nitrogen oxides produced during CO2 enrichment. II. Effects of different tomato and lettuce cultivars. 101, 411-415. Mortensen, L. M. (1994a). The influence of carbon dioxide or ozone concentration on growth and assimilate partitioning in seedlings of nine conifers. 44, 157-163. Mortensen, L. M. (1994b). Effects of carbon dioxide concentration on assimilate partitioning, photosynthesis and transpiration of Roth. and (L.) Karst. seedlings at two temperatures. 44, 164-169.

410 Musgrave, M. E., and Strain, B. R. (1988). Response of two wheat cultivars to CO2 enrichment under subambient oxygen conditions. 87, 346-350. Nicolas, M. E., Munns, R., Samarakoon, A. B., and Gifford, R. M. (1993). Elevated CO2 improves the growth of wheat under salinity. 20, 349-360. Nobel, P. S., Cui, M. Y., Miller, P. M., and Luo, Y. Q. (1994). Influences of soil volume and an elevated CO2 level on growth and CO2 exchange for the crassulacean acid metabolism plant 90, 173-180. Norby, R.J., and O'Neill, E. G. (1991). Leaf area compensation and nutrient interactions in CO2-enriched seedlings of yellow poplar (Liriodendron L.). 117, 515-528. Norby, R. J., Gunderson, C. A., Wullschleger, S. D., O'Neill, E. G., and McCracken, M. K. (1992). Productivity and compensatory responses of yellow poplar trees in elevated CO~. 357, 322-324. Overdieck, D., Reid, C., and Strain, B. R. (1988). The effects of preindustrial and future CO2 concentration on growth, dry matter production and the C/N relationship in plants at low nutrient supply: (cowpea), (okra) and (radish). 62, 119-134. Pettersson, R., and McDonald, A.J.S. (1992). Effects of elevated carbon dioxide concentration on photosynthesis and growth of small birch plants Roth.) at optimal nutrition. 15, 911-919. Pettersson, R., McDonald, A.J.s., and Stadenberg, I. (1993). Response of small birch plants Roth) to elevated CO2 and nitrogen supply. Poorter, H. (1989). Plant growth analysis: Towards a synthesis of the classical and the functional approach. 75, 237-244. Poorter, H. (1993). Interspecific variation in the growth response of plants to an elevated CO2 concentration. 104/105, 77-97. Poorter, H., and Remkes, C. (1990). Leaf area ratio and net assimilation rate of 24 wild species 83, 553-559. differing in relative growth rate. Poorter, H., Remkes, C., and Lambers, H. (1990). Carbon and nitrogen economy of 24 wild species differing in relative growth rate. 94, 621-627. Poorter, H., Gifford, R. M., Kriedemann, P. E., and Wong, S. C. (1992). A quantitative analysis of dark respiration and carbon content as factors in the growth response of plants to elevated CO2. 40, 501-513. Potvin, C., and Strain, B. R. (1985). Effects of CO2 enrichment and temperature on growth of two C4 weeds, and 63, 1495-1499. Radoglou, K. M., and Jarvis, P. G. (1992). The effects of CO2 enrichment and nutrient supply on growth, morphology, and anatomy of L. seedlings. 70, 245-256. Radoglou, K. M., and Jarvis, P. G. (1993). Effects of atmospheric CO2 enrichment on early growth of a plant with large cotyledons. 16, 93-98. Reid, C. D., and Strain, B. R. (1994). Effects of CO2 enrichment on whole-plant carbon budget of seedlings of and 98, 31-39. Retuerto, R., and Woodward, F. I. (1993). The influence of increased CO2 and water supply on growth, biomass allocation, and water-use efficiency of L. grown under different wind speeds. 94, 415-427. Rochefort, L., and Bazzaz, F. A. (1992). Growth response to elevated CO2 in seedlings of 4 co-occurring birch species. 22, 1583-1587. Rogers, H. H., Peterson, C. M., McCrimmon, J. N., and Cure,J. D. (1992). Response of plant roots to elevated atmospheric carbon dioxide. 15, 749-752. Rouhier, H., Billes, G., E1Kohen, A., Mousseau, M., and Bottner, P. (1994). Effect of elevated CO~ on carbon and nitrogen distribution within a tree (Castanea Mill) soil system. 162, 281-292.

25.

411

Roumet, C., Bel, M. P., Jardon, F., Salager, J. L., and Roy, J. (1993). Diversite de la response de graminees ~tune augmentation de la teneur en CO2 atmospherique. 18, 35-44. Rozema, J. (1993). Plant responses to atmospheric carbon dioxide enrichment: Interactions with some soil and atmospheric conditions. 104/105, 173-190. Rufty, T. W., Thomas, R. B., Cure, J. D., and Cure, W. W. (1994). Growth response of cotton 91, 503-509. to CO2 enrichment in differing light environments. Ryle, G.J.A., Powell, C. E., and Davidson, I. A. (1992a). Growth of white clover, dependent on Nz fixation, in elevated CO2 and temperature. 70, 221-228. Ryle, G.J.A., Powell, C. E., and Tewson, V. (1992b). Effect of elevated CO2 on the photosynthesis, respiration and growth of perennial ryegrass. J. 43, 811-818. Sage, R. F. (1994). Acclimation of photosynthesis to increasing atmospheric COz: The gas exchange perspective. 39, 351-358. Samuelson, L. J., and Seiler, J. R. (1992). Fraser fir seedling gas exchange and growth in response to elevated CO2. 32, 351-356. Samuelson, L.J., and Seiler, J. R. (1993). Interactive role of elevated CO2, nutrient limitations, and water stress in the growth responses of Red Spruce seedlings. For. Sc/. 39, 348-358. Samuelson, L.J., and Seiler, J. R. (1994). Red Spruce seedling gas exchange in response to elevated CO~, water stress and soil fertility treatments. 24, 954-959. SeegmCdler, S., and Rennenberg, H. (1994). Interactive effects of mycorrhization and elevated carbon dioxide on growth of young pedunculate oak L.) trees. 167, 325-329. Sicher, R. C., Kremer, D. F., and Rodermel, S. R. (1994). Photosynthetic acclimation to elevated COz occurs in transformed tobacco with decreased ribulose-l,5-bisphosphate carboxylase/ oxygenase content. 104, 409-415. x grown at Silvola, J., and Ahlholm, U. (1992). Photosynthesis on willows different CO2 concentrations and fertilization levels. 91, 208-213. Silvola,J., and Ahlholm, U. (1993). Effects of CO2 concentration and nutrient status on growth, growth rhythm and biomass partitioning in a willow, 67, 227-234. Silvola, J., and Ahlholm, U. (1995). Combined effects of CO2 concentration and nutrient status on the biomass production and nutrient uptake of birch seedlings (Betula 168/169, 547-553. Stanghellini, C., and Bunce, J. A. (!993). Response of photosynthesis and conductance to light, CO2, temperature and humidity in tomato plants acclimated to ambient and elevated 29, 487-497. CO2. Stewart, J. D., and Hoddinott, J. (1993). Photosynthetic acclimation to elevated atmospheric carbon dioxide and UV irradiation in 88, 493-500. Stulen, I., and Den Hertog, J. (1993). Root growth and functioning under atmospheric COz enrichment. 104/105, 99-115. Thomas, R. B., Reid, C. D., Ybema, R., and Strain, B. R. (1993). Growth and maintenance components of leaf respiration of cotton grown in elevated carbon dioxide partial pressure. 16, 539-546. Thomas, R. B., Lewis, J. D., and Strain, B. R. (1994). Effects of leaf nutrient status and photosynthetic capacity in loblolly pine L.) seedlings grown in elevated atmospheric CO~. 14, 947-960. Tolley, L. C., and Strain, B. R. (1984). Effects of CO2 enrichment on growth of and seedlings under different irradiance levels. 14, 343-350. Tremmel, D. C., and Patterson, D. T. (1993). Responses of soybean and 5 weeds to CO~ enrichment under 2 temperature regimes. 73, 1249-1260. Tschaplinski, T.J., Stewart, D. B., Hanson, P.J., and Norby, R.J. (1995). Interactions between drought and elevated CO2 on growth and gas exchange of seedlings of three deciduous tree species. 129, 63-71.

412 Van der Eerden. L., Dueck, T., and Ptrez-Soba, M. (1993). Influence of air pollution on carbon dioxide effects on plants. "Climate Change: Crops and Terrestrial Ecosystems" (S. C. van de Geijn, J. Goudriaan, and F. Berendse, eds.), pp 59-70. CABO-DLO, Wageningen. Van de Staaij,J. W. M., Lenssen, G. M., Stroetenga, M., and Rozema, J. (1993). The combined effects of elevated CO2 levels and UV-B radiation on growth characteristics ofElymus (= 104/105, 433-439. Vivin, P., Gross, P., Aussenac, G., and Guehl, J. M. (1995). Whole plant CO2 exchange, carbon partitioning and growth in seedlings exposed to elevated COs. 33, 201-211. Wilkins, D., Van Oosten, JJ, & Besford, R. T. (1994) Effects of elevated COs on growth and chloroplast proteins in 14, 769-779. Wong, S. C. (1990). Elevated COs and plant growth. II. Nonstructural carbohydrate content and its effect on growth parameters. 23, 171-180. Wong, S. C. (1993). Interaction between elevated atmospheric concentration of COs and humidity on plant growth: Comparison between cotton and radish. 104/105, 211-221. Wong, S. C., Kriedemann, P. E., and Farquhar, G. D. (1992). COs X nitrogen interaction on seedling growth of four species of 40, 457-472. Wyse, R. (1980). Growth of sugarbeet seedlings in various atmospheres of oxygen and carbon dioxide. 20, 456-458. Yakimchuk, R., and Hoddinott, J. (1994). The influence of ultraviolet-B light and carbon dioxide enrichment on the growth and physiology of seedlings of 3 conifer species. J. For. Res. 24, 1-8. Zak, D. R., Pregitzer, K. S., Curtis, P. S., Teeri, J. A., Fogel, R., and Randlett, D. L. (1993). Elevated atmospheric COs and feedback between carbon and nitrogen cycles. 151, 105-117. Ziska, L. H., and Bunce, J. A. (1993). Inhibition of whole plant respiration by elevated COs as modified by growth temperature. 87, 459-466. Ziska, L. H., and Bunce, J. A. (1994). Increasing growth temperature reduces the stimulatory effect of elevated CO2 on photosynthesis or biomass in 2 perennial species. 91, 183-190. Ziska, L. H., and Teramura, A. H. (1992a). Intraspecific variation in the response of rice to increased CO2--Photosynthetic, biomass and reproductive characteristics. 84, 269-276. Ziska, L. H., and Teramura, A. H. (1992b). COs enhancement of growth and photosynthesis in rice (Oryza Modification by increased ultraviolet-B radiation. 99, 473-481.

2 CO2 Elevation and Canopy Development in Stands of Herbaceous Plants

Atmospheric C O 2 concentrations have strong direct effects on plant physiology and growth, due to changes in photosynthetic carbon assimilation and allocation of assimilate among various components of growth. Studies of plants grown individually under a variety of environmental conditions have contributed much to our understanding of such changes, and have formed the basis for considerable speculation about potential responses of plant communities in a changing climate. However, a variety of experimental studies demonstrate that plant responses to rising CO2 concentrations may be altered considerably when plants are growing in monospecific stands or mixed species communities (Bazzaz and McConnaughay, 1992). One of the direct consequences of growth in dense stands is the increased intensity of competition for light. Under such conditions, the effects of changing CO2 concentrations (or levels of other resources) may be critically mediated .by alterations in canopy structure and the costs and benefits of leaf placement in different strata of the community. For example, Reekie and Bazzaz (1989) studied seedlings of five tropical tree species growing in experimental stands at different CO2 concentrations, and found that shifts in competitive success were best explained by alterations in canopy architecture and the deployment of leaves at different canopy heights. Changes in the location of canopy leaves among neighboring individuals will have significant effects on competitive interactions and may influence and Communities

413

Copyright 9 1996 by Academic Press, Inc. All rights of reproduction in any form reserved.

414

the biological diversity of natural communities. Additionally, at the ecosystem level, models of plant productivity are critically dependent on the distribution of leaf area, and consequent light interception, across communities and the potential changes in these parameters are fundamental to an understanding of the natural carbon cycle (Field, 1991). Understanding how species interact in elevated CO2 environments and other global change conditions is critical to evaluate the potential impact of global change on populations and communities. In this chapter, we address three questions regarding canopy structure in elevated CO2 communities: (i) What is the relative efficiency of light capture by dominant and subordinate members of a plant community? (ii) Is the efficiency of light capture in experimental stands of competing species modified by atmospheric CO2 concentrations? and (iii) Based on a theoretical model of nitrogen allocation and photosynthesis in relation to the attenuation of light through a canopy, is the optimal leaf area index of a plant stand modified by atmospheric CO2 concentrations?

Natural plant communities are composed of a variety of species with a broad range of plant heights and abundances. The variation in plant height, and in the placement of leaf area, has important implications for the capture of light (photosynthetic photon flux density, PPFD), the most important energy source for plant growth. Leaves in the upper layer of the canopy overshade the leaves in the lower layer and thus a gradient of light climate develops within a canopy (Monsi and Saeki, 1953). When a plant community is composed of a range of species with different plant heights, a hierarchy of individuals and species can be established in the canopy with respect to the availability of PPFD (Weaver and Clements, 1929; Keddy and Shipley, 1989; Weiner, 1990). Species that are able to grow tall can place their leaves in upper layers of the canopy. Such species intercept greater fractions of available PPFD and dominate in the stand. Shorter, subordinate species occupy lower layers in the canopy and receive smaller fractions of the available PPFD, nevertheless coexisting with taller species. Thus dominant and subordinate species in a plant community can be differentiated along this light gradient (Grime, 1987). What mechanisms are involved in the coexistence of these species in a plant community? Hirose and Werger (1995) presented a model, based on leaf area distribution and the cost and efficiency of light capture, to analyze canopy structure in multispecies communities and applied it to an herbaceous plant community on a floating fen.

26.

415

A. T h e M o d e l

Attenuation of PPFD through the canopy is assumed to follow Beer's law (Monsi and Saeki, 1953): I = I0 e x p ( - / ~ ,

(1)

where Fis the cumulative leaf area index (LAI) from the top of the canopy, I0 and I are PPFD on a horizontal level above the canopy and within the canopy at depth F, respectively, and K is the coefficient of light extinction. PPFD intercepted by the leaves of species i in the jth layer in the canopy (~bij) is given by (Aj~/[~;A~),

(2)

where -A/j is the a m o u n t of PPFD absorbed in layer j and Aj~ is the leaf area of species/in layer j. Since = A/JAFj and from Eq. (1), A / j = -K/0 exp(-KFj), Eq. (2) is rewritten as ~bij= K/0 e x p ( - / ~ j )

9Afj,

(3)

where Fj is the cumulative LAI at layer j. Thus ~bijcan be determined from K and the distribution of leaf area of each species in the canopy. Total PPFD absorbed by species i (~) is given by = ]Lj~bii.

(4)

Because photons are intercepted by leaves, a positive correlation is expected between photon absorption and leaf area. A power equation is fitted to the relationship between total photon absorption (~) and leaf area (A): b,

(5)

where 9 and A are defined for each species in a stand and a and b are positive constants. To achieve high photon absorption (~), plants need not only to develop a large leaf area, but also have to place their leaves at relatively higher positions in the canopy, or in more open locations to avoid direct shading from above; such plants may invest a large fraction of biomass in supporting tissues such as stems, petioles, or heavier leaf venation. Then we expect a positive correlation between 9 and the aboveground biomass (M) as well: d,

(6)

where cand dare positive constants. Dividing both sides of Eq. (5) by A gives (I)area --" ~ / A

= aA b-1.

(7)

(I)area is the photon flux absorbed per unit leaf area which is defined for each species. Likewise, dividing both sides of Eq. (6) by M gives

416

(8)

(I)mass :

(I)mass is the photon flux absorbed per unit aboveground biomass and defined for each species. IfMis considered as the investment cost to absorb photons, is the benefit gained for that investment. T h e n (I)mass as a ratio of the benefit to the cost indicates an efficiency of aboveground biomass use to absorb photons. The following relationship holds between (I)mass and ~area: (IDmass --" ALAR"

(I)area ,

(9)

where ALAR (aboveground leaf area ratio) is the ratio of leaf area per unit a m o u n t of aboveground dry mass (not total dry mass as in conventional growth analysis). ALAR is further analyzed as: AIAR = A L M R . SLA,

(10)

where ALMR (aboveground leaf mass ratio) is the ratio of leaf dry mass to the aboveground dry mass and SLA (specific leaf area) is the leaf area per unit leaf dry mass. Hirose and Werger (1995) hypothesized that tall dominant species have higher ~area than shorter subordinate species because the former develops their foliage in the upper layers of the canopy. They further hypothesized that (I)mass of the tall dominant species is not necessarily higher than that of short subordinate species because the former should invest more biomass to supporting tissues.

B. Partitioning of Photons among Species in a Plant Community The above hypothesis was tested in a tall herbaceous plant community (Thelypterido-Phragmitetum) on a floating fen at the time of peak standing crop (Hirose and Werger, 1995). There were 11 species coexisting in an area of 0.5 X 1 m. Total aboveground standing dry mass was 407 g / m 2. Three taller dominant species, and accounted for 94.6% in dry mass and 8 subordinate species for the rest of 5.4%. The green LAI was 3.42, of which the 3 tall dominant species accounted for 93.4% and 8 subordinate species for the rest of 6.6%. Ofincident PPFD, 77.5% was intercepted by the photosynthetic tissue of the canopy and 8.0% by the dead leaves. The rest (14.5 %) reached ground level. The 3 dominant species intercepted 75% of the incident PPFD and the 8 subordinate together 2.5%. Power equations fitted to the relationships between photon absorption (@) and leaf area (A) over 11 species and between photon absorption (@) and total aboveground biomass (M) were: @ = 0.40 A H9 (r ~ = 0.988) and @ = 0.74 34TM (r 2 = 0.968). Photon absorption increased more than proportionately with increasing leaf area (b > 1) and less than proportionately with increasing biomass (d < 1, though not significant). Dividing both sides of these two equations by A and M, respectively, gave:

26. (~area -- 0 . 4 0

417 A~

(I)mass --" 0.74 M -~176

(I)area increased significantly with increasing A (P < 0.01; Fig. la), while (I)mass t e n d e d to decrease with M (not significant; P > 0.1; Fig. lb). The a m o u n t of PPFD absorbed per unit leaf area ((I)area) was large in tall, d o m i n a n t species high in the canopy, whereas the a m o u n t of photons absorbed per unit aboveground mass ((I)mass) was not higher in those species. (I)mass is a p r o d u c t of ALAR and (I)area (Eq. 9). There was a trade-off relationship between ALAR and (I)area , leading to relatively constant values of ~ma~s. Similar tradeoffs were r e p o r t e d by Givnish (1982), who showed that taller species, which invest m o r e resources in supporting tissues to remain mechanically stable, display lower proportional allocation to foliage. To obtain a high p h o t o n flux per unit leaf area, plants should place their leaves at higher positions in the canopy. Such plants have to invest a large fraction ofbiomass in supporting tissues. Tall species a p p e a r e d to have an advantage over subordinate species in receiving a large fraction of incident PPFD, whereas subordinate species have an advantage in efficiently using their biomass to capture PPFD. Both ALMR and SLA contributed to larger ALAR (see Eq. 10) of subordinate species, though the contribution of SLA was m u c h larger. Light use efficiency (photosynthetic return per unit a m o u n t of absorbed PPFD) d e p e n d s both on species and on the level of PPFD

1.0

0.1 0.01

01

10 Leaf area

100

0.1

1

10

100

Total mass

1 Relationship (a) between photon absorption per unit leaf area (ordinate) and leaf area (abscissa) and (b) between photon absorption per unit aboveground dry mass (ordinate) and aboveground dry mass (abscissa) for 11 species in the canopy of the Thelypterido-Phragmitetum, Both axes are in relative values (total lead area, 100; total aboveground dry mass, 100, and total photon absorption, 100). (Redrawn from Hirose and Werger, 1995, with permission). Figure

418

absorbed (Bj6rkman, 1982). If higher light use efficiencies at lower levels of PPFD are taken into account, the efficiency of biomass use for dry mass production is even higher in subordinate species. However, we may hypothesize that species maintaining a certain level of (I)m~sis a necessary condition for their coexistence in a plant community.

Canopy consequences of CO2 elevation are difficult to predict, because component species respond to CO2 elevation differently from each other and competition may change their response to CO2 elevation (Bazzaz, 1990). If taller dominant species expand relatively more leaf area under elevated CO2 conditions, (I)area of shorter subordinate species would be reduced. Consequently, CI)massof the latter species would decrease and would not maintain themselves in the canopy unless their ALAR would increase with COs elevation to counterbalance the decrease in (I)area. Using two co-occurring annual species, and we carried out an experiment to see if COs elevation alters canopy development (Hirose unpublished). Both species were from disturbed environments in the American Midwest. These species were selected because they both produce few lateral branches, while having different distinct patterns of leaf display along the primary axis; leaves of increase in size at upper nodes, whereas those of decrease prior to production of a terminal inflorescence. We established mono- and mixed stands of these species at two growth stages (39 and 53 days since planting) under ambient (350/~1/1) and elevated (700/xl/1) COs conditions in the glasshouse with natural light conditions. Temperature was maintained at 25~ day and 20~ night. Lighting was supplemented by halogen bulbs. developed leaf area faster but stopped development earlier than did and no significant difference was found in leaf area between the two species at the later growth stage (Fig. 2a). Neither COs nor interference had significant effects on leaf area development. Averaged over the two COs levels, stand LAI increased from 0.76 to 2.29 in the stand, from 1.15 to 2.16 in the stand, and from 1.02 to 2.25 in the mixed stand. distributed its leaves to lower layers, whereas developed its leaves mainly in upper layers. Although and had similar leaf areas and plant heights in the mixed stand, intercepted a much larger fraction of available photons than due to the difference in leaf placement (Fig. 2b). CO2 elevation had little effect on photon absorption. Averaged over the COs levels, 57, 69, and 68% of incident PPFD were intercepted on Day 39, and 83, 89, and 86% were

26.

419

(a) Leaf area per plant, (b) photon absorption per plant ( in relative units), (c) photon absorption per unit leaf area, and (d) aboveground dry mass in response to CO2 for mono- and mixed stands of and on Days 39 and 53 after emergence. Error bars show _+1 SE of the mean (for details of experimental methods and calculation of photon absorption see Hirose manuscript in preparation).

i n t e r c e p t e d o n Day 53 by and monospecific stands a n d the m i x e d stand, respectively. P h o t o n a b s o r p t i o n p e r unit leaf area ( ~ .... ) d e c r e a s e d with growth (Fig. 2c), reflecting increasing m u t u a l shading particularly w h e n a m o n g leaves. h a d h i g h e r (I~area than the two species were grown in mixture. T h e r e was a significant effect of CO2 elevation o n the a b o v e g r o u n d dry mass (Fig. 2d). O n average, biomass increased with CO2 elevation by 6 - 2 9 % at the y o u n g e r stage a n d by 2 9 - 3 6 % at the later growth stage. Because t h e r e was n o significant difference in leaf area d e v e l o p m e n t a n d light i n t e r c e p t i o n u n d e r two CO2 conditions (Figs. 2 a - 2 c ) , this increase in biomass should be ascribed to h i g h e r n e t assimilation rates (biomass production p e r unit leaf area) u n d e r the elevated CO2 c o n c e n t r a t i o n . This result is s o m e w h a t different f r o m earlier studies. T h e biomass increase in the

420 present study was comparable to 33-37% increase in yield due to doubling CO2 averaged from diverse crops and wild species (Kimball, 1983; Cure and Acock, 1986; Poorter, 1993; Poorter Chapter 25). However, earlier studies showed that the increase in biomass was attributable to increased leaf area as well as increased photosynthetic activity of leaves. Coleman and Bazzaz (1992), studying the effect of COs and temperature on growth of two annuals, and suggested that the effects of CO2 elevation on growth were primarily due to changes in leaf area production and loss, and to a lesser degree to effects on photosynthesis, nitrogen, and water use efficiency. In competition, however, exhibited a relative enhancement in performance at elevated CO2, apparently due to increased net assimilation rates late in growth (Bazzaz 1989). K6rner and Arnone (1992) also found no significant difference in leaf area development in artificial tropical ecosystems established in glasshouses under ambient and elevated COs conditions. These results suggest that enhancement of net assimilation rate may be a particularly important component of COs responses in competitive conditions, where plant-plant interference and self-shading may constrain the deployment of leaf area. However, this does not contradict the importance of leaf display (e.g., Reekie and Bazzaz, 1989), because net assimilation rates depend on both the amount of light intercepted (i.e., the relative positions of leaves in the canopy), and the efficiency of light utilization in photosynthesis. In the last section, we approach this problem from a different perspective using an optimality model for stand level carbon gain to assess the potential COs responses of leaf area index in dense stands.

The effects of elevated C O 2 o n carbon gain in a dense stand depend on the changes in leaf photosynthetic parameters throughout the canopy. At the leaf level, the quantum yield of photosynthesis under light-limiting conditions is higher in plants grown in elevated COs atmospheres (Long and Drake, 1991). The increase in quantum yield lowers the light compensation point of instantaneous and diurnal carbon assimilation in elevated COs. Based on this leaf level response, an increase in leaf area index might be expected in closed stands, because additional leaves with positive carbon balance could be maintained in the shaded, lower canopy layers. However, this prediction does not take into account the distribution of leaf nitrogen and photosynthetic potential through the canopy. In particular, COsinduced changes in rates of photosynthesis a n d respiration will alter the relative value of leaves in different canopy layers. Here we investigate a

26.

421

model that incorporates potential changes in leaf photosynthetic parameters due to elevated CO2 in relation to the allocation of nitrogen through the canopy. The model determines the joint optimum of the number of leaf layers (leaf area index) and the distribution of nitrogen among those layers that maximizes stand level carbon gain, given a fixed supply of nitrogen for the entire stand. The model was parameterized using data from our experiment on and (see Section III above), supplemented with information obtained from the literature as necessary. Preliminary analysis of the model presented below suggests that optimal leaf area index is only slightly higher in elevated CO2, though total carbon gain is greatly enhanced. Furthermore, the predictions of the model appear to be more sensitive to changes in respiration rates, relative to leaf nitrogen and CO2 concentration than to the small changes in quantum yield observed in elevated CO2 atmospheres. Carbon gain at the whole plant or stand level depends on the number of leaves or leaf layers, and the distribution of incident light availability and photosynthetic potential (i.e., leaf nitrogen) among these leaves. Daily leaf-level nitrogen use efficiency of photosynthesis (PNUE, diurnal carbon gain per unit leaf nitrogen) is higher in high-light environments, but it declines as leaf nitrogen increases. For a plant with a given number of leaves in a range of light environments, total carbon gain is maximized when the marginal returns in carbon gain relative to nitrogen concentration in any particular leaf are equal for all leaves (Field, 1983). As a result, carbon gain is maximized when leaf nitrogen concentrations are higher in leaves in high light conditions; observed nitrogen allocation patterns closely parallel these predicted optima, though the mechanisms underlying these distributions are still not understood (Field, 1983; Hirose and Werger, 1987; Traw and Ackerly, 1995; see Chen 1993 for an alternative approach to nitrogen distribution patterns). Previous analyses of optimal nitrogen allocation have assumed that the number and size of leaves are fixed; if these are allowed to vary, the optimal nitrogen distribution and maximum attainable carbon gain will change correspondingly, and a joint optimum may be found that maximizes shoot level carbon gain in relation to all of these parameters. Formally, the joint optimum is the set of values of leaf nitrogen concentration (N, per unit area), leaf number (L), and individual leaf area (m) that maximize canopy level carbon gain and satisfy two constraints:

dN~

= m,c~

~m~N~ = NT, i=1

(11)

(12)

422

where c~ is a constant and is the total nitrogen in all leaves. In contrast to Field (1983), Eq. (11) includes leaf size on the right-hand side because we are considering leaf nitrogen concentration per unit area (not per leaf) and the reallocation of a fixed a m o u n t of nitrogen will alter Nconcentration in two leaves in proportion to their relative sizes. When both leaf size and n u m b e r are allowed to vary, the optimal (and somewhat trivial) solution for a plant is to produce a single large leaf in the uppermost canopy position with a leaf nitrogen concentration that maximizes leaf level PNUE. If leaf n u m b e r (L) is held constant, the model predicts that optimal leaf size will be larger in response to low ambient light levels or increased nitrogen availability (Ackerly, 1993). The result relative to light availability is of interest as it suggests that the decrease in leaf size in high light may enhance nitrogen use efficiency, in addition to improved regulation of leaf energy balance and water loss. Here, we investigate the question of optimal leaf area index by specifying a total nitrogen supply per unit of ground area (g/mS), setting a fixed leaf size of 0.1 m s, and solving for values of c~ and L that maximize carbon gain; leaf area index is then calculated as Following Hirose and Werger (1987), we utilized a nonrectangular hyperbola to characterize the light response of photosynthesis. The nitrogen dependence of lightsaturated photosynthetic capacity and dark respiration rates were based on data obtained for in ambient and elevated COs concentrations (Hirose unpublished data). The nitrogen dependence of quantum yield (0) and the curvature parameter (0) were based on an earlier study of (Hirose and Werger, 1987). For elevated COs, the intercept of the regression of quantum yield on leaf nitrogen concentration was increased by 0.01 u n d e r elevated COs (cf. Long and Drake, 1991). These equations are summarized in Table I. Midday PPFD levels at the top of the canopy were set at 1800/zmol m -s s -1 and the daily course of PPFD was modeled following a sine square curve (Hirose and Werger, 1987). Light attenuation in successive layers of the canopy followed Eq. 1, with k = 0.7 for both ambient and elevated COs concentrations (Hirose unpublished data). Leaf-level daily carbon assimilation was calculated for light environments corresponding to successive leaf layers u n d e r ambient or elevated COs concentrations and for a range of leaf nitrogen concentrations from 0.6 to 4 g N/mS; values of calculated numerically for use in Eq. (11). We analyzed this model to determine optimal leaf area index and nitrogen allocation, in relation to the total nitrogen supply in the canopy. This comparison eliminates differences between ambient and elevated COs stands due to differences in overall growth rates (cf. Coleman 1994), and standardizes the comparisons relative to the total amount of nitrogen available for deployment in the entire canopy. Optimal leaf area index and

26.

Regression on leaf nitrogen concentration ( g / m 2) Parameters (/zmol m -2 sec -1) Pm~ Pm~ Rd P~ 4) 4) 0

CO2 level (tzl/liter)

Slope

Intercept

350 700 350 700 350 700 Both

15.44 21.37 1.381 1.333 0.0188 0.0188 -0.251

-- 1.436 - 3.852 --0.141 0.0514 0.0211 0.0311 1.1

Values for Pmaxand R~ were obtained from measurements of (Hirose unpublished data) and values for quantum yield (~b) and the curvature parameter (0) were obtained from Hirose and Werger (1987).

stand-level carbon gain both increase sharply with increases in total foliar nitrogen, while mean leaf nitrogen concentrations show a less dramatic response (Figs. 3a-3c). As total nitrogen availability increases, optimal LAI is also slightly higher in elevated CO2 environments, and leaf nitrogen concentrations are correspondingly lower (cf. Hilbert 1991). Stand level carbon gain is consistently enhanced by about 45% under elevated CO2 at all levels of nitrogen availability. [Oikawa (1986) obtained a similar result in a model of forest productivity, predicting an increase in optimal leaf area index from about 6.3 to 6.6, in response to a doubling of CO2 concentration, while overall productivity increased by over 50%.] The optimal nitrogen allocation gradient, measured as the difference between the upper and lowermost leaves, increases with total nitrogen supply, due to increases in the predicted nitrogen levels of the upper leaves (Fig. 3d). The gradient is less steep in elevated CO2, based on comparisons at similar LAI or total nitrogen availability. Based on the photosynthetic parameters used in the model, the daily light compensation points for the lower leaves in the canopy (with predicted leafN concentrations of 1 g / m 2) are approximately 6 and 5 mol m -2 day -1 for ambient and elevated CO2, respectively. Based on a light extinction coefficient of 0.7, these values correspond to leaf area indices of 2.64 and 2.95 for the two environments. Thus on the basis of light compensation points alone, a higher LA/ is predicted for elevated CO2. However, a greater LA/was also predicted for lower nitrogen supply levels, where the lowermost leaves will be well above their light

424 c 1.8 -1

~-, 1.4

* [

t

0.8.

A- 0.7. ~.~ 0.6. 9

;~,~ 0 " 8 ~ .

~

e

HighCO2

I ~0"3"~,~

0.6

0.2 1

2

!

2

3

b

3

4.0

1.9

r

0.5.

~

1.8 3.0

..,

Top layer

1.7

o o

1.6

9

"3 1.5

~

2.0

,

"3 1.0 "- 1.4 N

Bottom layer

1.3

~ 1

2

3

Total stand leaf nitrogen (g/m2 ground area)

0

2 3 Total stand leaf nitrogen (g/m2 ground area)

(a) Predicted optimal leaf area index (LAI) that maximized canopy level carbon gain, in relation to total canopy nitrogen supply (g/m 2 of ground area) and atmospheric CO2 concentrations (ambient, 350 /~l/liter; elevated, 700 /~l/liter. (b) Predicted canopy level carbon gain at optimal LAI and optimal distribution of nitrogen among canopy layers. Across all nitrogen levels the enhancement due to elevated CO2 is about 45%. (c) Mean leaf nitrogen concentration at optimal LAI. (d) Nitrogen allocation gradient in relation to nitrogen supply, shown as the leaf nitrogen concentrations of the uppermost and lowermost leaf layers in the canopy.

compensation points. Thus the enhancement of LAI under elevated CO2 predicted by the model is due to the maximization of nitrogen use efficiency throughout the canopy, not simply to a change in the light compensation point of the lowest layer. The predictions of this model, regarding optimal leaf area index, were tested by plotting LAI versus total leaf nitrogen for the experimental stands of and grown under two CO2 concentrations, and harvested at two different ages (as described in Section III above). Leaf area

26.

425

index was positively correlated with total nitrogen, except for at elevated CO2, and the observed values were slightly higher than those predicted by the model (Fig. 4). Most importantly, though, there were no significant differences in this relationship between CO2 concentrations. What are the possible explanations for this discrepancy? First, the predictions of the model are very sensitive to the relationship between the photosynthetic light response curves and leaf nitrogen concentration, and to the shifts in that relationship u n d e r elevated CO2. In particular, shifts in the nitrogen dependence of respiration rates may strongly influence the results, as the relative costs of nitrogen in different leaf layers is strongly affected. The response of respiration to elevated CO2 continues to be one of the most poorly understood components of plant carbon balance (Amthor, 1996). For this analysis we were not able to obtain all of the parameters for the light response curves directly from plants in the experimental stands, so it is impossible to say whether the functions we used accurately reflect the changes observed in these stands. We emphasize that this is a preliminary analysis of this model, as there are a large n u m b e r of variables that require additional empirical validation, and further research on physiological responses is critical to achieve more confident predictions regarding stand level responses. Additionally, it is very important to recognize that any tests of optimality models d e p e n d on the validity of the optimality criterion. In this case, we assume that a stand of plants will be structured to maximize stand level carbon gain. Any criterion of this sort is an implicit evolutionary statement

oc 9o

9

0

0

1

2

3

0

1

2

3

4

Total stand leaf nitrogen (g/m2 ground area) Relationship between leaf area index (LAI) and total canopy nitrogen content in (a) and (b) (Hirose unpublished data). Open symbols, 350/zl/liter; solid symbols, 700/~l/liter.

426

with several important components, i.e., (i) maximization of short-term carbon gain is correlated with lifetime fitness; (ii) sufficient genetic variation in the characters underlying carbon gain (e.g., the processes regulating nitrogen allocation and leaf area index) has been available to selection; (iii) selection has been an important factor shaping plant responses under the conditions we are studying (this is particularly problematic when considering responses to changing environmental conditions); and (iv) we have identified the most important causal pathway linking these characters with overall performance, such that the optimality criterion we identify is the strongest selective factor. In addition to these conditions, optimality models applied to stand level properties assume either that the individuals in the stand exhibit optimal behavior, which is manifest as optimal properties at the stand, level as well, or that there has been selection on properties at the stand level (e.g., due to genetic relatedness of neighbors). The latter condition will certainly not be met in mixed-species stands; in this case, game theory models of individual behavior, and the consequences for population properties (e.g., Iwasa 1984), will be a more appropriate theoretical approach to problems such as the optimal leaf area index under different environmental conditions. However, even if these such conditions are not all met, the analysis of this model provides important insights into the sensitivity of carbon gain to different aspects of leaf function and stand structure.

In this chapter we first showed a model to analyze the canopy structure of plant communities with many species (Section II). The model assumed that PPFD attenuates exponentially through the canopy and that PPFD is intercepted by constituent species in proportion to their leaf area. It was applied to an herbaceous plant community, Thelypterido-Phragmitetum, which contained 11 species with different plant heights. Tall species in the canopy received higher PPFD averaged over leaf area ((I)area),whereas PPFD absorbed per unit aboveground biomass (~m~s) of tall species was not higher than that of the subordinate species. This is because tall species invested larger fractions of their biomass to supporting tissues. It was suggested that species maintaining a certain level of (I)mass is a necessary condition for their coexistence in the plant community. To examine if CO2 elevation alters canopy development and competitive interactions, we established mono- and mixed-species stands of Abutilon and at two growth stages under ambient and elevated CO2 conditions (Section III). distributed its leaves to lower layers, while developed its leaves mainly in upper layers. Although and

26.

427

had similar leaf areas in the mixed stand, occupying upper layers in the canopy absorbed a much larger fraction of available photons than At the later growth stage, reduced (I)mass and increased (])mass when they were mixed, indicating a competitive advantage in the latter species. However, the present experiment did not indicate that CO2 elevation significantly changed the competitive relationships of these species. Analysis of a model of optimal leaf area index and nitrogen allocation, in relation to stand level carbon gain, indicated that elevated CO2 levels should lead to only slight enhancements in LAI, compared to stands in ambient CO2 with similar total foliar nitrogen. However, carbon gain of these stands is greatly enhanced due to the large e n h a n c e m e n t in assimilation rates and nitrogen use efficiency. In contrast to these predictions, the stands of and exhibited no effect of CO2 concentration on leaf area index, relative to canopy nitrogen levels. Currently, more detailed studies of photosynthetic responses to light and nitrogen u n d e r ambient and elevated CO2 are needed to improve models of canopy level responses. In particular, predicted canopy responses are quite sensitive to CO2 effects on respiration rates. Several studies suggest that respiration declines in elevated CO2, in parallel with a decline in leaf nitrogen concentrations. However, the effect of CO2 concentration on the relationship of respiration to leaf nitrogen concentrations has received little attention (Amthor, 1996), and is critical in this context. These studies suggest several critical areas of future research on canopy structure and function in relation to global change. First, in order to scale from leaf level processes to stand level carbon gain, we need a much better understanding of the combined effects of light, leaf nitrogen, and atmospheric CO2 on leaf level photosynthesis. Much research has, understandably, focused on CO2 response of photosynthesis (i.e., A-C~ curves) u n d e r nonlimiting light conditions. As we have demonstrated above, the responses of leaf photosynthesis in the shaded, lower layers of the canopy are the critical determinants of potential changes in canopy structure. These shaded leaves also contain less nitrogen, so the d e p e n d e n c e of light curve parameters must be established across a range of leaf nitrogen concentrations. Secondly, if, as we suggest, elevated CO2 enhances biomass accumulation, but has little effect on leaf area index, where does the biomass go? For determinate annuals (such as it is possible that the entire life cycle will be completed more rapidly, leading to phenological shifts in the importance of different species during the growing season (cf. Reekie and Bazzaz, 1991). For indeterminate species, such as forest communities, there may be increased biomass sequestration belowground a n d / o r more rapid turnover of the canopy. The latter possibility would imply a reduction in leaf lifespan and a more rapid turnover of nitrogen through the plant

428

canopy. Will nitrogen be recycled more efficiently within the plant canopy, increasing long-term nitrogen use efficiency, or will it be taken up and returned to the soil more rapidly, leading to short-term depletion of available nitrogen in the soil? The effects of elevated CO2 on canopy functioning must be considered in a broader context in relation to the functioning of the entire ecosystem. Finally, in large, closed-canopy stands (such as forests) changes in the distribution of leaf area may alter the light availability in different strata of the community. If growth of dominant species is enhanced, and leaf area index in the upper canopy increases, understory light levels may be reduced. In a single-species stand this might simply result in the loss of a layer of leaves, or mortality of suppressed individuals. In mixed-species stands, however, a decline in understory light levels could eliminate less shade-tolerant species and reduce biological diversity of the community. Alternatively, increased C O 2 concentrations may allow these species to survive under lower light levels, mitigating these effects. Resolution of these questions will require detailed studies of the effects of atmospheric CO2 concentrations on leaf and whole-plant carbon balance under low light levels. Further study of these issues is particularly important, as the CO2 responses of productive plant communities with high leaf area indices and high biological diversity play a particularly important role in the global carbon budget.

We thank Christian K6rner for comments and discussion that improved the manuscript. Special thanks are also due to Brian Traw and Reiko Yambe for help with experiments and nitrogen analyses. This study was partly supported by a grant-in-aid of the Japan Ministry of Education, Science and Culture to T.H. (06454007) and by US-NSF grants to D.D.A. and F.A.B.

Ackerly, D. D. (1993). "Phenotypic Plasticity and the Scale of Environmental Heterogeneity: Studies of Tropical Pioneer Trees in Variable Light Environments." Ph. D. Thesis, Harvard University, Cambridge, MA. Amthor,J. S. (1996). Plant respiratory responses to elevated CO2 partial pressure. "Advances in Carbon Dioxide Effects Research" (L. H. Allen, Jr., M. B. Kirkham, D. M. Olszyk, and C. Whitman, eds.), in press. American Society of Agronomy, Madison, WI. Bazzaz, F. A. (1990). Response of natural ecosystems to the rising CO2 levels. 21, 167-196. Bazzaz, F. A., and McConnaughay, K. D. M. (1992). Plant-plant interactions in elevated CO2 environments. 40, 547-563. Bazzaz, F. A., Garbutt K., Reekie, E. G., and Williams, W. E. (1989). Using growth analysis to interpret competition between a C3 and a C4 annual under ambient and elevated CO2. 79, 223-235.

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Bj6rkman, O. (1982). Responses to different quantum flux densities. "Physiological Plant Ecology. I. Encyclopedia of Plant Physiology (O. L. Lange, P. S. Nobel, C. B. Osmond, and H. Ziegler, eds.), Volume 12A, pp. 57-107. Springer-Verlag, Berlin. Chen, J.-L., Reynolds, J. F., Harley, P. C., and Tenhunen, J. D. (1993). Coordination theory of leaf nitrogen distribution in a canopy. 93, 63-69. Coleman, J. S., and Bazzaz, F. A. (1992). Effects of CO2 and temperature on growth and resource use of co-occurring C3 and C4 annuals. 73, 1244-1259. Coleman, J. S., McConnaughay, K. D. M., and Ackerly, D. D. (1994). Interpreting phenotypic variation in plants. 9, 187-191. Cure, J. D., and Acock, B. (1986). Crop responses to carbon dioxide doubling: A literature survey. 38, 127-145. Field, C. B. (1983). Allocating leaf nitrogen for the maximization of carbon gain: Leaf age as a control on the allocation program. 56, 341-347. Field, C. B. (1991). Ecological scaling of carbon gain to stress and resource availability. "Response of Plants to Multiple Stresses" (H. A. Mooney, W. E. Winner, and E.J. Pell, eds.), pp. 35-65. Academic Press, San Diego. Givnish, T.J. (1982). On the adaptive significance of leaf height in forest herbs. 120, 353-381. Grime, J. P. (1987). Dominant and subordinate components of plant communities: Implications for succession, stability, and diversity. "Colonization, Succession and Stability" (A. J. Gray, M.J. Crawley, and P.J. Edwards, eds.), pp. 413-428. Blackwell Sci. Oxford. Hilbert, D. W., Larigauderie, A., and Reynolds, J. F. (1991). The influence of carbon dioxide and daily photon-flux density on optimal leaf nitrogen concentration and root: shoot ratio. 68, 365-376. Hirose, T., and Werger, M.J.A. (1987). Maximizing daily canopy photosynthesis with respect to the leaf nitrogen allocation pattern in the canopy. 72, 520-526. Hirose, T., and Werger, M.J.A. (1995). Canopy structure and photon flux partitioning among species in a herbaceous plant community. 76, 466-474. Iwasa, Y., Cohen, D., and Leon, J. A. (1984). Tree height and crown shape, as results of competitive games. J. 112, 279-297. Keddy, P. A., and Shipley, B. (1989). Competitive hierarchies in herbaceous plant communities. 54, 539-550. Kimball, B. A. (1983). Carbon dioxide and agricultural yield: An assemblage and analysis of 430 prior observations. 75, 779-789. K6rner, Ch., and Arnone, J. A., III (1992). Responses to elevated carbon dioxide in artificial tropical ecosystems. 257, 1672-1675. Long, S. P., Drake, B. G. (1991). Effect of the long-term elevation of CO2 concentration in the field on the quantum yield of photosynthesis of the C3 sedge, 96, 221-226. Monsi, M., and Saeki, T. (1953). l]ber den Lichtfaktor in den Pflanzengesellschaften und seine Bedeutung f~r die Stoffproduktion. 14, 22-52. Oikawa, T. (1986). Simulation of forest carbon dynamics based on a dry-matter production model. III. Effects of increasing CO2 upon a tropical rainforest ecosystem. 99, 419-430. Poorter, H. (1993). Interspecific variation in the growth response of plants to an elevated and ambient CO2 concentration. 104/105, 77-97. Reekie, E. G., and Bazzaz, F. A. (1989). Competition and patterns of resource use among seedlings of five tropical trees grown at ambient and elevated CO2. 79, 212222. Reekie, E. G., and Bazzaz, F. A. (1991). Phenology and growth in four annual species grown in ambient and elevated CO2. 69, 2475-2481.

430 Traw, M. B., and Ackerly, D. D. (1995). Leaf age, light levels and nitrogen allocation in five species of rain forestpioneer trees. 82, 1137-1143. Weaver, J. E., and Clements, F. E. (1929). "Plant Ecology." McGraw-Hill, New York. Weiner, J. (1990). Asymmetric competition in plant populations. 5, 360-364. Woodrow, I. E. (1994). Optimal acclimation of the C3 photosynthetic system under enhanced C02. 39, 401-412.

27 Problems in Predicting the Ecological Effects of Elevated CO

The rising level of atmospheric CO2 is a major global anthropogenic change that we can track and predict with great confidence. We know that atmospheric CO2 has increased, and we can make relatively good predictions of the levels we can expect to see in the near future. But the ecological effects of this rising COz are not as easy to predict, and this is exactly what scientists are being asked to do by policy makers. Indeed, from the policy makers' point of view, the need for predictions of global change is the for research on elevated CO2. How good is our ability to make reasonable predictions, and how can we best improve such predictions? Most would agree that the answer to the first question is " n o t very good" at this point in time. This makes the second question even more important. The difficulty in making predictions of the ecological effects of rising COz levels stems from two basic problems. First, ecology is a young science that does not have a body of widely accepted theory applicable to the questions of global change. There is no short-term solution to this problem, and the longer term solution is to promote the development of the science of ecology. As I will argue later in this chapter, research on the effects of elevated CO2 can perhaps make a significant contribution to this longer-term goal. The second major problem in making reliable predictions about the ecological effects of elevated CO2 is that while scientists are being asked 431

Copyright 9 1996 by Academic Press, Inc. All rights of reproduction in any form reserved.

to make predictions at the community, ecosystem, and biosphere level, most of the available information exists at lower levels (K6rner, 1993). Figure 1 shows the traditional hierarchy of the levels of organization in biology, although the point here would apply to alternative hierarchical schemes (e.g., O'Neill 1986) as well. The predictions that are most needed concerning the effects of elevated CO2 are at the top three levels, but most of our information about the effects of CO2 are from experiments conducted at lower levels. For example, there are numerous experiments looking at the effects of elevated CO2 on leaf-level photosynthesis, whole growth, and development of individual plants (see reviews by Bazzaz [1990], Mooney [ 1991], and Woodward [ 1991] ), but because of costs and logistical constraints, we are just beginning to see longer-term experiments on populations and communities in the field. One solution that has been proposed to this problem of making predictions at higher levels of organization is scaling up from the lower levels (Ehleringer and Field, 1993). But what exactly does "scaling up" mean? I find two very different meanings of this term in recent literature: (1) Extrapolation within one level of organization; or (2) Actual prediction of higher level phenomena using information from a lower level. I will discuss them both in turn.

Extrapolation usually means simply extending a quantitative relationship beyond the range of the data on which the relationship is based. Extrapolation is certainly possible and reasonable in many cases. For example, if one

1 Levelsof organization in biology.

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could accurately measure NPP in many randomly placed 1-m 2 quadrats within a grassland, one can extrapolate to get a good estimate of NPP over a larger a r e a . T h e issues here are purely practical, not scientific. Extrapolating a specific quantitative relationship entails m u c h more risk, as can be seen clearly in a simple example from population growth. Figure 2 shows a simple computer-generated logistic growth curve with r a n d o m normal noise added. If we have data from only one part of the curve, we would not be able to extrapolate very successfully, because we would not have any information on the overall shape of the relationship If we have information only from the beginning of the curve, we would be inclined to conclude that growth is exponential (geometric growth). If we have information on the central part of the curve, growth would appear to be approximately linear (arithmetic growth). If we have data on the right-hand part of the curve, we would likely conclude that the growth rate is continuously decreasing, such as in a simple saturating function. Extrapolating any of these trends to the other regions of the curve would lead to major errors. One needs either data over the whole range of the relationship, or huge sample sizes to provide the statistical power to see subtle changes in the derivatives over smaller ranges. As another general example of this problem, one can point to the development and use of systems analysis models in ecosystem ecology (Patten, 1983). These "black box" models are often developed to predict some specific ecosystem processes, and calibrated using empirical data. Such models are often pretty good at predicting new combinations of variables within the range of the data used to calibrate them, but these same models are often very poor at making predictions outside the range of the data with which they are calibrated. The reason is similar to the

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80 Logistic growth curve with random normal variation.

434 example of the logistic growth curve: the characterization of quantitative relationships is usually good enough for interpolating within the range of the calibrating data, but this characterization is not good enough to make predictions far beyond the range of the data. The same issue arises in statistical models. In conclusion, extrapolation can be dangerous, but it is certainly possible and reasonable in some cases. It is important to note, however, that extrapolation does not usually involve a change in the level of organization in question. Rather, it usually refers to questions of scale within one level of organization.

I call the second meaning of scaling up which I found in the literature "reductionism from below," meaning the actual prediction of higher level p h e n o m e n a from lower level information. I call it "from below" because reductionism is usually from above, i.e. it starts with the higher level phenomenon. In scaling up our starting point is information at the lower level. It is my contention here that this type of scaling up generally fails. For example, there is no basis for assuming that responses of a system to an environmental factor at a higher level of organization will be similar to responses at a lower level, and this has been documented in elevated CO2 research (Reynolds and Acock, 1985; Reynolds 1993). Short-term regulatory responses of leaves to elevated CO2 (i.e., an increase in the rate of photosynthesis) does not predict whole-plant biomass accumulation or acclimatory responses (Mooney and Koch, 1994). On the contrary, acclimatory responses often damp out regulatory response (Bazzaz, 1990). Similarly, the performance of plants grown singly at elevated CO2 may not be a good predictor of their performance when competing. (Bazzaz and Garbutt, 1988; Bazzaz and McConnaughay, 1992). Evolutionary responses to elevated CO2, which we have a strong basis to expect (see Chapters 1-5), present the most difficult problems for prediction. There is no basis for assuming that the plastic response of an organism to an environmental factor will be similar or even in the same general direction as evolutionary responses to that same factor. For example, a plant may respond to shade by etiolating, but natural selection may favor slower growth and shorter stature in the shade (as we see in understory herbs). Similarly, Woodward (1987) presented evidence that plants respond to increasing COs by decreasing the number of stomata (although this conclusion has been disputed [K6rner, 1988]). Even if we assume that plants do develop fewer stomata in a COs-enriched environment, I see no reason why we should expect evolutionary responses to be in

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the same direction. Simply put, evolutionary responses may damp out effects of elevated CO2 (as populations evolve in an environment of elevated CO2), or evolutionary responses may amplify short-term effects, as competitive relationships are altered and species evolve in different ways. There is no way to predict the long-term outcome at this point. The problems of scaling up are not limited to evolutionary change. For example, CO2 is a resource, and there has been significant progress in theories of resource utilization and limitation (Tilman, 1986; Bloom 1985; Chapter 28). These theories could provide some reasonable predictions concerning the effects of elevated CO2 as a resource. Evidence is accumulating, however, that developmental effects of CO2 on plants (e.g., Reekie and Bazzaz, 1991; Loehle, 1995) may be more important than resource-mediated effects. Since elevated CO2 is a novel environment, developmental effects will not be predictable. Several species seem to show increased reproductive output in high CO2 environments, but other species, e.g., show the opposite response (Bazzaz 1995). There is no way to predict with any confidence the response of reproductive output or allocation to elevated CO2 in any species until we do the appropriate experiments. As K6rner (1993) has pointed out, there is no way that we can now, or will be able in the foreseeable future, to predict ecosystem processes from the physiological properties of organisms. To make the philosophical point that p h e n o m e n a at any level of organization are ultimately reducible to and driven by p h e n o m e n a at lower levels, does not mean that we are anywhere near being able to do this. Numerous ecologists (e.g., Allen and Starr, 1982; O'Neill 1986) have argued that pure reductionism in ecology will usually fail. If such reductionism were possible we should all be molecular biologists, or physical chemists, not ecologists. Levin (1993) suggested there may be laws for scaling up, but even if this is so, we are at present very far from discovering and applying them. The paradigm for scaling up in biology has been the use of biochemistry in medicine: antibiotics are molecules that kill bacteria in a test tube, then scale up to cure disease at whole-body level, and then scale up to control epidemics at the population level. However, this type of successful scaling up has proven to be the exception, not the rule. The success of this example of scaling up may be because it takes place mostly within individuals, and the individual is the product of natural selection. Scaling up to supraorganismal levels, such as the community or ecosystem, operates u n d e r no such constraints. Confidence in our ability to scale up depends on the available data and our theoretical understanding of the relationships between the levels of organization over which we are scaling (O'Neill 1986). The important argument against scaling up is not philosophical, but depends on the

available data and state of the art. If, in the scores of experiments that have been done on the effect of elevated CO2, we did observe simple transparent reductionism, it would be quite reasonable to apply this in predicting CO2 effects. For example, if increased CO2 almost always resulted in increased photosynthesis at the leaf level, and increased biomass accumulation at the whole plant, population, and community levels, we would have a strong basis for applying this prediction generally. But CO2 research has not yielded such general and simple patterns. As Bazzaz (1990) has pointed out, competitive outcomes will be modified by CO2 and by the interaction of CO2 with other environmental factors as different species behave differently in a high COz world, and their response will depend on the identity of the competing species. We cannot predict the behavior of a system from a lower level without either (1) evidence for such simple patterns across several levels, or (2) a well-developed theory that spans the levels in question. The data we have does not support (1), and (2) would require a level of ecological theory far beyond what we have available today or in the foreseeable future. The effects of CO2 on terrestrial ecosystem will ultimately be reducible to physiology and interactions among individuals and their environments. But when, as in ecology, we do not have a very good understanding of the processes in question, scaling up from a lower level of organizations is much less reliable than predictions based on data from the same level as the phenomena to be predicted.

In light of this, we can distinguish two basic types of studies on the effects of elevated CO2 on plants. (1) Reductionist experiments which study the mechanisms of CO2 effects; and (2) Holistic experiments which look at CO2 effects on whole systems that are as similar as possible to those about which we are trying to make predictions. These two classes of experiments represent two legitimate, but in many cases fundamentally different, scientific goals. Scientific understanding is ultimately based on reductionism and mechanism, but the best currently accessible predictions of many p h e n o m e n a often come from nonmechanistic, holistic "calculation tools" Loehle, 1983; see also Peters, 1991). To argue that one of these two scientific goals is better or more important than the other misses the p o i n t - - t h e y represent different goals, although this is not to say that they do not: interact. Both can have integrity and

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scientific validity (and both can be done poorly). I am suggesting that, over the short term, there is often a trade-off between these two goals. As an example of mechanistic research on the effects of CO2 I refer to an e x p e r i m e n t that has been proposed (Bazzaz 1995; K6rner, pers. comm.) on the effect of elevated CO2 on the process of self-thinning (density-dependent mortality) in plant populations. Such an experiment could provide valuable data on the interaction between resource levels and density-dependent mortality. It might even provide insights into the mechanisms of density-dependent mortality beyond questions concerning CO2. Such an experiment, if done reasonably well, would be very worthwhile scientifically. But I believe such an experiment would be practically useless in the near term in helping us to predict the effects of elevated CO2 on terrestrial ecosystems that we will be seeing in the coming decades. Similarly, an e x p e r i m e n t in which we enrich a whole-plant community with CO2 for as long as possible will probably be m u c h more valuable for predicting what will h a p p e n in the coming years, but it will probably not be very useful in showing us the mechanisms by which these changes occur. I call this latter type of e x p e r i m e n t "brute-force empiricism." Much of m o d e r n medicine is based on such brute-force empiricism. We know a treatment works, but we often do not know the mechanism. Would one be willing to take a drug based purely on the data from studies and chemical theories? No, the principles of public health require that clinical trials be performed. If clinical trials are not possible, we want experiments on animals similar to humans. Similarly, if we're going to predict effects of elevated CO2 on terrestrial ecosystems, the best type of data will be from experiments, natural or planned, which are as close to the thing we're trying to predict as is possible. But the clinical trial of a new medicine whose mechanism of action is not known will probably not provide useful information on the mechanism. It will merely tell us if the medicine works in a specific population. The only reliable predictions possible for complex p h e n o m e n a of which we have very limited understanding come from brute-force empiricism and, when necessary, extrapolation. To make a reliable prediction in such a case, one should study the p h e n o m e n o n itself, or a system as similar to it as possible. In young sciences such as ecology and environmental science, data are more trustworthy than theory in making predictions (Peters, 1991; Weiner, 1995). How are we able to predict the effects of specific treatments other than elevated CO2 on terrestrial plant communities? For example, we know from experience that increasing the nutrients in many nutrient-poor plant communities will result in increased biomass and a reduction in species diversity. But we know this from e x p e r i e n c e m t h e e x p e r i m e n t has been conducted many times. The theories that we have at this point to explain

438 why this occurs are still after-the-fact explanations; they are not really the basis for our prediction that when we add phosphorous to an oligotrophic lake, we will get a huge increase in algal growth and a concurrent decrease in algal diversity. Similarly if we are asked to make a prediction of the effects of building a highway on local populations of plant and animals, the most useful type of information would be the effects of other roadbuilding projects on other communities, not deductions from ecological theories. Although such experiments have been done many times, the experiment of elevated CO2 is being done for the first time. The challenges presented by global change are before us. Predicting and analyzing the structure and function of ecological systems on large spatial and long temporal scales are research challenges of rare potential but daunting difficulty. The potential derives from both need and The difficulty reflects the diversity and non linearity of ecological responses. (Ehleringer and Field, 1993; emphasis mine) The dichotomy I have described fits Ehleringer and Field's eloquent diagnosis (Figure 3). Fundamental mechanistic research on effects of elevated CO2 can and should be justified on its own terms, and it will eventually contribute to our understanding and prediction of global change, but it cannot be justified in terms of predicting global change in the near term. But if the goal is obtaining the best prediction of change in terrestrial systems my claim is that an imperfect experiment at the level of organization we want to predict will be better than a perfectly designed experiment at a much lower level. According to this argument, the following studies are most likely to yield reasonable predictions in the near future: (1) The study of naturally occurring communities of high C02, e.g., volcanic vents in Italy (Miglietta and Raschi, 1993; Miglietta 1993; K6rner and Miglietta, 1994),Java (von Faber, 1925), and California (Koch, 1993). According to the arguments advanced above, despite the limitations of such studies (e.g., possible confounding factors such as other contaminating gases, limited replication, etc.), they probably represent the best available information we have for predicting effects of elevated CO2 on communities and ecosystems. This is because such studies are perhaps the only ones that are at the appropriate level temporally. I believe the potential value of comparative studies on naturally-occurring high CO2 communities, in comparison with experimental studies, has been greatly underestimated by researchers. (2) Whole community experiments with elevated CO2, as realistic and long term as possible (e.g., open-top chambers, FACE experiments) (3) Microcosm versions of (2).

27.

Figure 3

Two basic types of research on effects of elevated CO2.

(4) Paleological evidence of community changes correlated with changes in CO2. If it can be established that CO2 levels were much higher in the Cretaceous, paleological data on terrestrial plant communities could be of value. Even information on terrestrial systems during periods of lower CO2 over the past 100,000 years may be useful via extrapolation.

Some of the controversies concerning predictions of global change may result from the two very different uses of the word "prediction" in science. A hypothesis is a prediction: a claim about the behavior of the world based on a theory or model. Hypotheses are one of our most important research tools. Many of the most exciting and important hypotheses in science are controversial. But the word "prediction" is also used to describe consensus expectations from the scientific and engineering communities on which extra-scientific decisions can and should be based. Although the rising levels of CO2 are predictions in this latter sense, even the best of our predictions about the ecological effects of rising CO2 are only hypotheses, part of the research program in global change, but not yet firm bases for policy decisions. It has been said many times that as science progresses we answer questions, but we often raise more questions than we answer. Perhaps one of the most important things we have learned from CO2 research over the past decade is that things are not as simple as we might have hoped, that we do not know very much, that it will not be easy to make predictions about global effects. Ecology as a science is not yet developed enough to produce the predictions we are being asked to make. We must resist the temptation to confuse the importance of an issue with our ability to understand it. Questions concerning the ecological effects of anthropogenic environmental changes such as elevated CO2 are perhaps among the most

important scientific questions facing the world today, but it does not follow that we have or soon will have the means to answer them. Policy makers want predictions, and they give scientists grants to produce such predictions. I do not think ecology will be well served if we claim to understand more than we do. Rather we are obliged to communicate to policy makers the concept of uncertainty with which they seem so uncomfortable. But if we can use the opportunity presented by global changes such as elevated CO2 to do the fundamental ecological research needed to develop a scientific understanding of the processes involved, we can bring scientific opportunity and practical need together in a way that will further both our science and our public responsibility.

I thank S. Bassow, F. A. Bazzaz, M. Jasienski, C. K6rner, C. Loehle, S. C. Thomas, P. Voss, and an anonymous reviewer for comments on an earlier version of this chapter. Special thanks to F. A. Bazzaz for hosting my visit to Harvard. This work was supported by a Bullard Fellowship from Harvard Forest.

Allen, T. F. H., and Starr, T. B. (1982). "Hierarchy: Perspectives for Ecological Complexity." Univ. of Chicago Press, Chicago. Bazzaz, F. A. (1990). The response of natural ecosystems to the rising global CO2 levels. 21, 167-196. Bazzaz, F. A., and Garbutt, K. (1988). The response of annuals in competitive neighborhoods: Effects of elevated CO2. 69, 937-946. Bazzaz, F. A., and McConnaughay, K. D. M. (1992). Plant-plant interactions in elevated COs environments. 40, 547-563. Bazzaz, F. A., Bassow, S. L., Berntson, G. M., and Thomas, S. C. (1996). Elevated COs and terrestrial vegetation: Implications for and beyond the global carbon budget. "Global Change and Terrestrial Ecosystems" (B. Walker, ed.), pp. 43-76. Cambridge Univ. Press, Cambridge, UK. Bloom, A.J., Chapin, F. S., and Mooney, H. A. (1985). Resource limitation in plantsmAn economic analogy. 16, 363-392. Ehleringer, J. R., and Field, C. B. (eds.) (1993). "Scaling Physiological Processes: Leaf to Globe." Academic Press, San Diego. Koch, G. W. (1993). The use of natural situations of COs enrichment in studies of vegetation responses to increasing atmospheric COs. "Design and Execution of Experiments on COs Enrichment" (E.-D. Schulze and H. A. Mooney, eds.), pp. 381-391. Ecosystem Research Report 6, Commission of the European Community, Brussels. K6mer, C. (1988). Does global increase of COs alter stomatal density? 181, 253-257. K6rner, C. (1993). COs fertilization: The great uncertainty in future vegetation development. "Vegetation Dynamics and Global Change" (A. M. Solomon and H. H. Shugart, eds.), pp. 53-70. Chapman & Hall, London.

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K6rner, C., and Miglietta, F. (1994). Long term effects of naturally elevated C O 2 o n mediterranean grassland and forest trees. 99, 343-351. Levin, S. A. (1993). Concepts of scale at the local level. "Scaling Physiological Processes: Leaf to Globe." (J. R. Ehleringer and C. B. Field, eds.), pp. 7-19. Academic Press, San Diego. Loehle, C. (1983). Evaluation of theories and calculation tools in ecology. 19, 230-247. Loehle, C. (1995). Anomalous responses of plants to CO2 enrichment. 73, 181-187. Miglietta, F., and Raschi, A. (1993). Studying the effect of elevated CO2 in the open in a naturally enriched environment in central Italy. 105, 391-400. Miglietta, F., Raschi, A., Bettarini, I., Resti, R., and Selvi, F. (1993). Natural COz springs in Italy: A resource for examining long-term response of vegetation to rising atmospheric CO2 concentrations. 16, 873-878. Mooney, H. A., and Koch, G. W. (1994). The impact of rising COz concentrations on the terrestrial biosphere. 23, 74-76. Mooney, H. A., Drake, B. G., Luxmoore, R. J., Oechel, W. C., and Pitelka, L. F. (1991). Predicting ecosystem responses to elevated CO2 concentrations. 41, 96-104. O'Neill, R. V., DeAngelis, D. L., Wade, J. B., and Allen, T. F. H. (1986). "A Hierarchical Concept of Ecosystems." Princeton Univ. Press, Princeton, NJ. Patten, B. C. (ed.) (1983). "Systems Analysis and Simulation in Ecology." Academic Press, New York. Peters, R. H. (1991). "A Critique for Ecology." Cambridge Univ. Press, Cambridge, UK. Reekie, E. G., and Bazzaz, F. A. (1991). Phenology and growth in four annual species grown in ambient and elevated CO2. 69, 2475-2481. Reynolds, J. F., and Acock, B. (1985). Predicting the response of plants to increasing carbon 29, 107-129. dioxide: A critique of plant growth models. Reynolds, J. F., Hilbert, D. W., and Kemp, P. R. (1993). Scaling ecophysiology from the plant to the ecosystem: A conceptual framework. "Scaling Physiological Processes: Leaf to Globe" (J. R. Ehleringer and C. B. Field, eds.), pp. 127-140. Academic Press, San Diego. Tilman, D. G. (1986). Resources, competition and the dynamics of plant communities. "Plant Ecology" (M. J. Crawley, ed.) pp. 51-75. Blackwell Sci., Oxford. von Faber, F. C. (1925). Untersuchungen fiber die Physiologie der javanischen SolfatarenPflanzen. 18/19, 89. Weiner, J. (1995). On the practice of ecology. 83, 153-158. Woodward, F. I. (1987). Stomatal numbers are sensitive to increases in CO2 from pre-industrial levels. 327, 617-618. Woodward, F. I., Thompson, G. B., and McKee, I. F. (1991). The effects of elevated concentrations of carbon dioxide on individual plants, populations, communities, and ecosystems. 67 (Suppl. 1), 23-38.

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2 The Significance of Biological Variation, Organism Interactions, and Life Histories in CO2 Research

The diversity of structures, functions, and responses to external factors among individuals of a population and between species and assemblages of species provides the raw material for natural selection, including the basis for adaptation to changing environmental conditions. Biological diversity also sustains the richness of ecosystem functions. Because of this intrinsic variability of living systems the responses to any sort of external forcing will also vary. This volume explores the interaction between one aspect of global change, increased atmospheric CO2, and the responses of communities of organisms exposed to it. In contrast to most of the preceding studies with increased CO2, the studies here emphasize ways that the responses of populations and communities can amplify, suppress, or redirect the responses of individual organisms. Increasing atmospheric CO2 is an external driver likely to affect the whole biosphere. CO2, in addition to solar energy and water, is a basic resource for life on earth. Its atmospheric concentration has increased by 27% since the beginning of the industrial revolution and is likely to double within less than 100 years. Although atmospheric CO2 has fluctuated in the past, the recent rapid increase, caused primarily by fossil fuel consumption and anthropogenic deforestation, is unprecedented. Understanding the responses of plants and plant communities to altered carbon supply is a central theme of global change research. This volume focuses on the varia443

Copyright 9 1996 by Academic Press, Inc. All rights of reproduction in any form reserved.

444 tion of responses in populations and communities to the continuing increase of atmospheric COz, and it sets the stage for assessing the implications of these responses for other aspects of biosphere function.

This book appears at an important point in the development of our understanding of plant and ecosystem responses to elevated CO2. Until recently, CO2 enrichment was considered to be almost always beneficial to plants. Based mainly on data from agricultural plants grown with abundant nutrients, water, and light, it was assumed that natural communities will uniformly and strongly increase growth and carbon storage under elevated CO2. Results of a number of recent CO2 enrichment studies in less productive, more natural settings, where competition for space and other resources was allowed, reveal a richer suite of responses. Stimulation of plant growth by increased CO2 is often very modest and less important for community and ecosystem function than a number of other effects, some of which are positive and some of which are negative (Bazzaz 1995; K6rner, 1996; Field 1995). Most past studies of plant responses to increased atmospheric CO2 have been designed to maximize the resolution for detecting CO2 effects by minimizing biological and environmental variability. Although this approach has been invaluable for characterizing the CO2 sensitivity of particular genotypes of a few species and for exploring direct and indirect mechanisms underlying CO2 effects, this approach is not sufficient as a basis for understanding at the community or ecosystem scale. This book brings variance to the center stage. The future of our biosphere under changed atmospheric conditions will largely depend on how selection will act on this variance and how it will translate into new assemblages of genotypes and species. We must understand the variance of plant responses to elevated CO2 in a variable environmental matrix and the mechanisms behind them in order to correctly predict the furore of a CO2-enriched biosphere, both in terms of biomass production and biological diversity. This recognition motivates the focus on population and community studies. In general, the critical information for understanding the implications of CO2 effects on the composition of species and communities is only beginning to accumulate. The chapters in this volume synthesize much of the currently available information, considering both the nature of the responses and their consequences for other processes. Though providing a still incomplete picture, these studies present a compelling case for major roles of COz responses in genotypes within species and species within communities. These roles are clearly important enough that population

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and community processes should receive a high priority in the continuing initiative to understand and predict CO2 responses at the ecosystem and global scales.

This volume deals largely with experiments. Experimentalists are using a number of model systems designed to produce unequivocal results under the conditions of the experiment, but their application to the real world depends to a large measure on scaling in space a n d time beyond the experimental conditions. Mathematical models, including both conceptual and simulation models, provide powerful but dangerous tools for the scaling needs. Model predictions become most suspect when pushed far outside the range of validation experiments, for example when used to project responses to gradually increasing CO2 on the basis of initial responses to a step-change or when response functions from fast-growing agricultural plants are used to predict responses in late successional, natural communities. Kingsolver (Chapter 1) discusses compelling empirical and theoretical reasons to suppose that evolutionary responses to abrupt step-changes in the environment will be qualitatively different from responses to gradual progressive changes. Under natural conditions, selection is likely to involve polygenetic responses rather than the monogenetic ones usually tested in laboratories. Several research groups have now documented substantial intraspecific variation in response to CO2 (cf. Ackerly and Bazzaz, 1995; Bazzaz 1995, Curtis Chapter 2). In most wild plant species, especially woody ones, life cycles are too slow to study selective processes under elevated CO2. Yet, some extremely shortlived species may serve as useful model organisms. Tousignant and Potvin (Chapter 3) used a fast-growing wild mustard (Brassicajuncea) and observed its biomass production over seven generations during which CO2 was increased by 40 ppm and temperature was increased by 0.5 K for each successive generation. Gradual selection for faster vegetative growth occurred and was verified as genotypic with reciprocal transplant experiments. By the end of the reproductive phase, however, this response disappeared and fruit biomass fell from 3.5 g in controls to only 1 g in the final climate (630 ppm CO2). This late response was fully plastic (phenotypic) with no sign of genetic adaptation. CO2 responses of plants can have genetic as well as phenotypic dimensions that manifest themselves throughout the life cyclema challenge for scientists working with trees or slow-growing and late-reproducing perennials.

446 What are the mechanisms that make a genotype a winner under increased CO2? Curtis (Chapter 2) present data for that bear a clear message: Genotypes with a pronounced and positive photosynthetic gain under elevated CO2 are not consistent "winners" in terms of biomass. In fact, 11 of the 19 seed families that showed increased CO2 uptake showed no biomass response, while some of the seed families with little or no photosynthetic response to CO2 had quite large biomass responses. Hence, the marked intraspecific variation in the CO2 response of growth is not tightly linked to CO2 responses of carbon fixation per unit leaf area. With morphological features, such as genetically determined plant size, were much better predictors (Curtis Chapter 2). Habitat breadth in current environments is not necessarily a good predictor of responses to elevated CO2 under natural conditions. Schmid (Chapter 4) present results of a study in which various genotypes of a specialist and a generalist species of were exposed to CO2-enriched atmospheres in their natural field environment. In contrast to the initial hypothesis that niche breadth would confer greater CO2 sensitivity, the specialist profited much more from elevated CO2 and exhibited a wider spectrum of genetic variation in CO2 responsiveness. Surprisingly, genetic variance of biomass increased under elevated CO2, underlining the potential importance of intraspecific differences in response. Thomas and Jasienski (Chapter 5) highlight the role of plant density and plant-plant interactions. They suggest that because rapidly rising CO2 is a relatively novel selective agent, its strength may be difficult to predict. If selection by CO2 enrichment is sufficiently strong, it may not be effectively counterbalanced by selection by other environmental factors such as frost and drought. This biased selection for one or few traits could reduce overall fitness in the long term.

The responses of plant communities, their pollinators, dispersers, symbionts, and pathogens to elements of the global change are critical regulators of biological diversity, ecosystem function, and the provision by ecosystems of goods and services valued by humans. But, relevance to ecosystem and global questions is not the only motivation for focus on community and population processes in a CO2-enriched world. In addition, external forcing from global change provides an invaluable probe for mechanistic studies at the community and population levels. Community responses to increased CO2 may involve several levels of interaction. Increases in the population of one species and losses in others can fundamentally change interspecific interactions at all levels of complexity. For example, an important pollinator of one

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species may become rare as a result of decreases in the abundance of a preferred food plant for larvae, or root competition between two species could allow entry of a third species largely occupying a different soil horizon. Some generalizations are now emerging from work with wild plants under elevated CO2; for example, Grime (Chapter 6) suggests that, on fertile land, slow-growing stress tolerators are likely to become losers, whereas fastgrowing species will increase. On less fertile sites chances will be more equal. Based on observations on the British Isles, Grime noted, with surprise, that regenerative attributes are poor predictors of CO2 sensitivity of species. Screening tests indicate that fast-growing herbaceous species currently expanding in heavily populated countries of Europe are also most responsive to CO2 enrichment (cf. Poorter Chapter 25). This observation is consistent with higher CO2 responsiveness of early versus late successional species (Bazzaz and Miao, 1993; Sch~ippi and K6rner, 1996), which may explain their current success and facilitate increased dominance in the future. Naeem (Chapter 7) use assemblages of annual plants of varying species number to investigate the role of biodiversity in modulating CO2 effects on communities.They conclude that the higher diversity assemblages produce more biomass per unit land area and that this effect is enhanced under elevated CO2. Manipulating both CO2 and community composition will certainly improve our understanding of vegetation responses to global change. A key factor in such experiments will be the availability of resources other than CO2. The literature is replete with evidence suggesting multiway interactions between species, communities, and resources in regulating ecosystem CO2 responses. Most of the research to date has been done with fast-growing, small plants, largely annuals. Arnone (Chapter 8) presents a review of our current understanding of the responses of longer lived tropical plants to elevated CO2. The central theme of this work is that responses of individually grown plants to high CO2 do not scale simply to results of experiments with individuals grown under competitive conditions or complete ecosystems. When mineral nutrients severely constrain plant growth, speciesspecific differences in foraging success for these resources determine the overall successional process and the ultimate community structure. Results like these highlight the need for effective integration of individual, community, and ecosystem-scale processes under realistic climate change scenarios. Of course, actual competitive outcomes may depend on the species present, their life forms, and their relative abundances and arrangements. Given the heterogeneity in the field, carefully designed and coordinated experiments in both natural and model systems will provide critical extensions of field results (K6rner, 1995b; Lawton, 1995). A conclusion supported by both Naeem and Arnone (Chapters 7 and 8, respectively) is that CO2 enrichment eventually will alter patterns

448 of plant succession and vegetation cover. Whether such changes will lead to alterations of ecosystem processes is one of the key questions for the future. Roy (Chapter 9) point to this scaling problem and present results of a study with species-rich microcosms containing Mediterranean grassland species. Of 57 species, half responded negatively and half positively to CO2 enrichment. But, in only 5 of these species were responses significantly positive. There was no significant difference between annuals and perennials or between major plant families such as Asteraceae (60% of all species stimulated), legumes (40% stimulated) and grasses (30% stimulated). One interesting response was that the CO2 responses of grasses and legumes when mixed were negatively correlated (when grasses were stimulated, legumes were suppressed, and vice versa). This observation does not match predictions derived from studies with isolated, well-fertilized plants (see review by Poorter Chapter 25). The changes in community composition did not translate into a significant effect of elevated CO2 on total biomass, though root mass tended to increase. The study clearly documents that competitive interactions can lead to negative responses of some wild plant species to elevated CO2 (Hunt 1993; Ackerly and Bazzaz, 1995). In the long term, changes at community level may be more important than short-term biomass responses (Bolker 1995). This idea is further supported by results from microcosm experiments with Mediterranean grassland in California (Chiariello and Field, Chapter 10). In this experiment, increased CO2 led to decreased water consumption by some species, allowing other species to profit. Under elevated CO2, the Jasper Ridge assemblage of late season annuals profited from savings in soil moisture by species that are active earlier in the season. Higher soil moisture may lead to fundamental changes of community structure including the invasion of shrubby species or even forest trees. Natural grassland community responses to elevated CO2 are presented by Leadley and K6rner (Chapter 11). They report no significant increase in aboveground plant biomass in either natural communities or in communities with manipulated biodiversity. Similar to the observations by Roy (Chapter 9), legumes did not profit from CO2 enrichment nor did species with high potential growth rates, in contrast to the conclusions of Grime and Poorter (Chapters 6 and 25, respectively). Surprisingly, the slow-growing sedge was the only species out of 30 that showed a clear and strong positive response to CO2 enrichment. It seems that the conventional assumptions about functional group responses to elevated CO2 need to be reassessed in a more natural context. Polley (Chapter 12) use documented natural patterns of plant succession, combined with theoretical considerations, to evaluate the possibility that vegetation change due to elevated CO2 may already be underway. They suggest that rising CO2 was most influential in grasslands, in which

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water or nitrogen previously limited woody plant recruitment, and in which rising CO2 is now significantly increasing growth rate and fecundity of woody plants. These authors join others in this volume in emphasizing the importance of life history in predicting long-term responses of vegetation to elevated CO2. Predictions become even more challenging when interactions between elevated CO2 and other elements of global change come into play. GwynnJones (Chapter 13) present data from a field experiment with natural subarctic vegetation under both elevated CO2 and enhanced UV-B radiation. In these experiments, all species behave individualistically. The deciduous dwarf shrub was very sensitive to perturbations, showing both CO2 and UV-B responses in the first season. Responses were, however, less pronounced in the second season. Other dwarf shrub species were rather unresponsive to either environmental perturbation. CO2 fertilization may lead to greater plant biomass, litter production, or both. Under dry conditions, this may lead to increased fire frequency (Crutzen and Goldammer, 1993). CO2 effects may be most important where elevated COz promotes a switch between contrasting fire/fuel cycles. COz effects on fire frequency, mediated through enhancement of fuel load, may be a major controller of species composition (Sage, Chapter 15). Independent of changes in fire frequency, Mediterranean shrublands and forests may be particularly sensitive to COz enrichment through amelioration of drought stress. Scarascia (Chapter 14) report that the Mediterranean arboreal species was favored over typical macchia shrubs, perhaps as a consequence of COz-related improvements in soil moisture status. Thus, CO2 effects may facilitate transitions from shrub to forest communities unless, of course, a drier climate counteracts the positive effect of CO2 on soil moisture (Field 1995).

Population and community responses to elevated C O 2 may depend on a number of factors, including species characteristics, intraspecific variation, plant density, other biotic factors (herbivores, pathogens, pollinators), soil resources, climate, and local history. Carefully designed experiments are required to unravel these multidimensional interactions. Species within a mixed community show a range of responses to elevated CO2 in the majority of studies to date (Reynolds, Chapter 18). One of the best-studied interactions is between C3 and C4 species. Even with C3-C4 interactions, where the contrast in photosynthetic physiologies suggests a consistent outcome of competition, actual interactions can depend strongly on soil fertility, moisture, and species characteristics. Responses of other functional groupings

450

are even more challenging to predict under natural growth conditions. For this reason Reynolds (Chapter 18) concluded that it may be more productive to focus on understanding performance of species grown in relatively complex mixtures, than to extrapolate from experiments on simple, species-poor mixtures, except in agricultural research where such communities predominate. Examples of complex, multidimensional interactions are presented by L~scher (Chapter 19) and Campbell and Hart (Chapter 20). L~scher report large differences in the CO2 responses of seven perennial species, typical of permanent temperate grasslands, grown within a matrix of On these fertile soils, legumes showed a strong positive response to elevated CO2 while three grass species responded negatively. Surprisingly, no intraspecific variability in these responses was detected. In contrast to the pattern observed by L~scher et al. (Chapter 19) in Swiss lowlands, Campbell and Hart (Chapter 20) report no stimulation of legume biomass in swards of grazed turf under the cooler temperatures in New Zealand. At lower temperatures, increased CO2 tended to favor grasses. But competitive suppression of under increased CO2 was significantly reduced when temperature was increased to 28/23~ The competitive outcome between legumes and grasses under elevated CO2 is also sensitive to the grass species used. Under elevated CO2, and restricted most severely, whereas was a weak competitor. The effect of increased CO2 on a given target species depends on the community context. When multiple life forms interact, morphology can become a key determinant of interaction, and predictions of CO2 responses must integrate beyond the CO2 responses of photosynthesis and growth in individual plants and single-species communities. Gloser (Chapter 21) assessed competitive outcome under elevated CO2 in an artificially planted tree-grass mixture. Although the predicted reduction of the light compensation point and increase of shade tolerance of spruce under elevated CO2 did not occur, the competitive success of a was clearly enhanced under CO2 fertilization, reducing early tree-seedling success and tree recruitment. Differences in morphology can influence CO2 responses of plants more than physiological differences (K6rner, 1993a). CO2 enrichment can also influence morphology within a single life form, as illustrated for tropical tree species by Reekie and Bazzaz (1987). Developmental processes represent a second major challenge to our ability to predict plant-plant interactions under elevated CO2 (Reekie, Chapter 22). The fact that CO2 can influence development directly, severely constrains attempts at prediction, particularly in cases where not all phases of the life cycle can be studied, as in trees.

28.

Effects of increased C O 2 o n plants and plant communities are very likely to lead to secondary (and tertiary) effects on microbes, including symbionts, parasites, and decomposers. One of the most important plant-microbe interactions is the symbiosis between nitrogen-fixing bacteria and legumes. Since nitrogen is a limiting resource for growth in many natural ecosystems, any facilitation of nitrogen fixation as a result of CO2 fertilization could have far-reaching effects on community structure and ecosystem function. Hartwig (Chapter 16) found that CO2 fertilization in the field enhances growth and nitrogen fixation by white clover and increases its proportion in a grass sward at the expense of associated grasses. This confirms results of earlier growth chamber observations (Overdieck, 1986; Nijs 1989) but contrasts with the results of Campbell and Hart (Chapter 20). Although nitrogen fixing symbionts are restricted to few plant families, plant-fungal mutualisms exist in the vast majority of species. Increased carbon availability may stimulate nutrient uptake and delivery by mycorrhizas, yet increased mycorrhizal biomass could also lead to increased carbon demands and perhaps diminishing returns on nutrients. Most studies to date indicate no or modest effects of increased CO2 on mycorrhizal abundance (e.g., Whitbeck, 1994). Recent evidence from work with grassland microcosms suggests that mycorrhizal fungi may not necessarily become more mutualistic under elevated CO2, but may even become parasitic (Sanders, Chapter 17). The responses appear to be species-specific, enhancing the possibility that effects of CO2 enrichment on plant-mycorrhiza interactions will modify the structure of plant communities.

Effects of C O 2 enrichment on plant tissue composition suggest secondary effects not only on microbes but also on animal consumers. Feedbacks from differential consumption can affect species composition and abundance (Lindroth, Chapter 23; Lincoln et al., 1993). In general, insects fed material grown under increased CO2 increase consumption, probably as a consequence of the lower protein concentration in CO2-fertilized leaf tissue. Responses may, however, vary among insects. Differential responses may even be found between males and females of the same species (Traw and Bazzaz, unpublished). There are a number of gaping holes in our understanding at the population level. For example, will reduced growth and prolonged development of insects alter mortality and natality rates such that populations decline? From the perspective of tree defoliation, to what degree will decreases in herbivore populations offset increased

452

consumption rates by individual insects? Lindroth concludes that little is known about potential intraspecific variation in insect responses to CO2induced changes in host quality. The same is true for the response of herbivores when provided with a choice of different species (cf. Arnone, Chapter 8). Considering such questions will require long-term studies in ecosystems with realistic levels of complexity. Large ruminants may respond quite differently from insects (Owensby Chapter 24). Unlike insects, where intake typically increases as diet quality decreases, ruminant intake usually declines with decreasing forage quality. With ruminants, the response of consumption amplifies the decrease in growth per unit of consumption, probably resulting in reduced growth and reproduction. According to Owensby a future high CO2 world seems destined to reduce individual animal performance.

Modeling the future of our biosphere requires generalization. Variation within species and populations is currently handled incompletely and in only some of the models designed to predict CO2 responses at the landscape or global scale. One attractive approach to generalization is tosearch for functional types that may serve as substitutes for taxonomic units but respond consistently to increased CO2 under natural conditions. Poorter (Chapter 25) present a review of plant CO2 responses in which they attempt to distill "functional group-specific" CO2 responses. In general, they confirm the greater CO2 sensitivity of C~ plants but provide evidence for substantial responses in C4 and CAM plants. On average, potentially fast-growing wild species and crop species show relatively strong growth responses to CO2 (when grown under optimal conditions and in isolation) whereas inherently slow-growing species show much smaller responses. When nutrient availability is low, plant growth is, on average, unresponsive to high CO2. Poorter conclude that this is one of the reasons we expect growth responses of most natural vegetation in the field to be small. Under competitive conditions the differential responses of species may drastically change, and the overall productivity response may be smaller than for individually grown plants (Bazzaz and McConnaughay, 1992; Baz1995). Aboveground plant parts interact primarily by affecting the light climate of their neighbors. Hirose (Chapter 26) examine interactions between canopy structure and CO2 enrichment. Theoretical considerations (Long, 1991) suggest that elevated CO2 should lead to moderate increases in leaf area index. This is observed in some studies, especially with agricultural species. In other examples, leaf area index is unaffected by increased CO2.

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Experimental stands of and exhibited no effect of C O 2 on leaf area index (Hirose Chapter 26), similar to reports for other plant canopies (Arnone, Chapter 8; H~ittenschwiler and K6rner, 1996a). Some natural plant communities may adjust individual allometry in such a way that leaf area per unit plant mass is reduced rather than increased. In cases where leaf area index does increase in response to elevated CO2, the result could be a loss of suppressed individuals, elimination of less shadetolerant species from the understory, and decreased biological diversity. Alternatively, increased CO2 may enhance survival under lower light, mitigating shading effects (Long, 1991; Bazzaz and Miao, 1993; H~ittenschwiler and K6rner, 1996b).

The diversity and multidimensionality of possible population and community responses to increased CO2 pose major challenges for the extension of these responses to the scale of ecosystem function, the global carbon cycle, or impacts on ecosystem goods and services valued by humans. To date, most of the models, both conceptual and quantitative, designed to explore questions at these scales either completely ignore population and community responses, or they treat only a few aspects. This approach is a reasonable starting point, but the field is now at the portal of an era where further progress in understanding CO2 responses is critically dependent on an effective integration across fields and approaches, including physiology, population and community studies, and ecosystem studies. Early predictions of ecosystem-scale responses to increased CO2 were typically extrapolated from studies on individual plants (e.g., Strain and Bazzaz, 1983). More recent assessments include limited whole-ecosystem data (e.g., Mooney 1991; K6rner, 1996; Koch and Mooney, 1996) and an acknowledgment of the likely importance of population and community processes (e.g., Bazzaz, 1990; K6rner, 1995a). These assessments lack, however, a framework for translating an appreciation that these processes are important into concrete predictions about outcomes. As a consequence of this lack of a framework and a shortage of data, most of the quantitative models used to explore ecosystem and global CO2 responses work as if the vegetation consisted of only a single species, or perhaps a single plant, a single decomposer, and a single herbivore (e.g., Melillo 1993; Ojima 1993). Early models predicting species variation in responses to global change did not include CO2 effects, and simulated responses to only altered temperature and precipitation (e.g., Pastor and Post, 1988).

454 A number of recently developed simulation models predict changes in the equilibrium distribution of potential natural vegetation, in response to altered climate and increased CO2 (e.g., Nielson, 1993; Prentice 1993). These models, which redistribute vegetation types on the basis of moisture and carbon balance, still treat each major biome as if it were a single species. Dynamic versions of these models, now under active development, replace biomes with a number of functional types, intended to compete more or less realistically and to co-occur, where appropriate. Yet, the challenge of defining broadly useful functional groups is substantial, and the information necessary to associate functional groups with CO2 responses is incomplete (K6rner, 1993b). Modeling approaches based on the hypothesis that biomes stay in place or that responses of vegetation types can be characterized as responses of single aggregate species are a reasonable starting point, given the clear need for synthesis and the fact that global changes on the time scale of decades to a century are fast relative to the life span of many trees. Yet, an accumulating body of evidence, including each of the chapters in this volume, highlights issues where population a n d / o r community aspects of ecosystem-scale CO2 responses are critically important, on time scales that are potentially quite rapid. Broadly successful models at the ecosystem and larger scales will require a combination of increased data and improved tools for generalization. The community has, thus far, not converged on a single approach for providing these. Studies on natural ecosystems, microcosms, and synthetic canopies can all provide essential information. The challenge is deciding how to use the information from each level and avoiding the temptation to focus on a subset of well-understood or easily modeled processes (Weiner, Chapter 27). The chapters in this volume highlight a number of mechanisms that will be central to the development of integrated understanding of plant and ecosystem responses to increased atmospheric CO2 in future integrative models, but more important points were made here than we can summarize. Yet, many of the conclusions form a relatively compact suite. (1) Intraspecific variation in CO2 responses is often comparable to or even greater than interspecific differences. Understanding intraspecific variation and its consequences is a critical prerequisite for developing mechanistic predictive tools. (2) CO2 responses of plants grown in communities can rarely be extrapolated directly from responses of individual plants grown alone. (3) Morphological and developmental traits are major determinants of plant CO2 responsiveness. As a consequence, they may exert strong influences on both community structure and ecosystem function. (4) Success under increased CO2 often reflects responses to indirect effects, for example, altered soil moisture, herbivory, or symbiotic associations.

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(5) Ecosystem scale consequences of increased C O 2 c a n be amplified or suppressed by population and community responses. For example, a change in fire frequency or a transition from a grassland to a shrubland can have large effects on production, carbon storage, or watershed yield. (6) Population and community processes are typically the dominant controls on the ability of ecosystems to provide goods and services valued by humans. A narrow focus on production or carbon storage is likely to miss many of the most consequential ecosystem responses to increased CO2. (7) Ecosystem and global scale models designed to provide useful predictions of the consequences of global CO2 enrichment for policy must place a priority on improving the characterization of population and community processes.

Ackerly, D. D., and Bazzaz, F. A. (1995). Plant growth and reproduction along C O 2 gradients: 1, Non-linear responses and implications for community change. 199-207. Bazzaz, F. A. (1990). The response of natural ecosystems to the rising global CO2 levels. 21, 167-196. Bazzaz, F. A., and McConnaughay, K. D. M. (1992). Plant-plant interactions in elevated CO2 environments. 40, 547-563. Bazzaz, F. A., and Miao, S. L. (1993). Successional status, seed size, and responses of tree seedlings to CO2, light, and nutrients. 74, 104-112. Bazzaz, F. A., Jasienski, M., Thomas, S., and Wayne, P. (1995). Microevolutionary responses in experimental populations of plants to CO2-enriched environments: Parallel results from two model systems. 92, 8161-8165. Bolker, B. M., Pacala, S. W., Bazzaz, F. A., Canham, C. D., and Levin, S. A. (1995). Species diversity and ecosystem response to carbon dioxide fertilization: Conclusions from a temperate forest model. 1, 373-381. Crutzen, P.J., and Goldammer, J. G. (eds.) (1993). "Fire in the Environment. The Ecological, Atmospheric, and Climatic Importance of Vegetation Fires." Wiley, Chichester. Field, C. B., Jackson, R. B., and Mooney, H. A. (1995). Stomatal responses to increased COz: Implications from the plant to the global scale. 18, 1214-1226. H~ttenschwiler, S., and K6rner, Ch. (1996a). System-level adjustments to elevated COz in model spruce ecosystems. in press. H~ttenschwiler, S., and K6rner, Ch. (1996b). Effects of elevated CO2 and increased nitrogen deposition on photosynthesis and growth ofunderstorey plants in spruce model ecosystems. in press. Hunt, R., Hand, D. W., Hannah, M. A., and Neal, A. M. (1993). Further responses to CO2 enrichment in British herbaceous species. 7, 661-668. Koch, G. W., and Mooney, H. A. (eds.) (1996). "Carbon Dioxide and Terrestrial Ecosystems," Physiological Ecology Series. Academic Press, San Diego. K6rner, Ch. (1993a). CO2 fertilization: The great uncertainty in future vegetation development. "Vegetation Dynamics and Global Change (A. M. Solomon and H. H. Shugart, eds.), pp. 53-70. Chapman & Hall, New York/London. K6rner, Ch. (1993b). Scaling from species to vegetation: The usefulness of functional groups. "Biodiversity and Ecosystem Function" (E. D. Schulze & H. A. Mooney, eds.), pp. 117-140. Ecological Studies 99. Springer-Verlag, Berlin/Heidelberg/New York.

456 K6rner, Ch. (1995a). Biodiversity and COs: Global change is under way. 4, 234-243. K6rner, Ch. (1995b). Towards a better experimental basis for upscaling plant responses to elevated COs and climate warming. 18, 1101-1110. K6rner, Ch. (1996). The response of complex multispecies systems to elevated COs. "Global Change and Terrestrial Ecosystems" (B. H. Walker and W. L. Steffen, eds.), pp. 20-42. Cambridge Univ. Press, Cambridge, UK. Lawton, J. H. (1995). Ecological experiments with model systems. 269, 328-331. Lincoln, D. E., Fajer, E. D., and Johnson, R. H. (1993). Plant-insect herbivore interactions in elevated COs environments. 8, 64-68. Long, S. P. (1991). Modification of the response of photosynthetic productivity to rising temperature by atmospheric COs concentrations: Has its importance been underestimated? 14, 729-739. Melillo, J. M., Kicklighter, D. W., McGuire, A. D., Moore, B., III, Vorosmarty, C. J., and Grace, A. L. (1993). Global climate change and terrestrial net primary production. 363, 234-240. Mooney, H. A., Drake, B. G., Luxmoore, R. J., Oechel, W. C., and Pitelka, L. F. (1991). Predicting ecosystem responses to elevated COs concentrations. 41, 96-104. Nielson, R. P. (1993). A mapped ecotone response to climatic change: Some conceptual and modelling approaches. 3, 385-395. Nijs, I., Impens, I., and Behaeghe, T. (1989). Effects of long-term elevated atmospheric COs concentration on and canopies in the course of a terminal drought stress period. 67, 2720-2725. Ojima, D. S., Parton, W. J., Schimel, D. S., Scurlack, J. M. O. (1993). Modeling the effects of climatic and COs changes on grassland storage of soil C. 70, 643-657. Overdieck, D. (1986). Long-term effects of an increased COs concentration on terrestrial plants in model ecosystems. Morphology and reproduction of L. and 30, 323-332. Pastor, J., and Post, W. M. (1988). Responses of northern forests to COrinduced climate change. 334, 55-58. Prentice, I. C., Sykes, M. T., and Cramer, W. (1993). A simulation model for the transient effects of climate change on forest landscapes. 65, 51-70. Reekie, E. G., and Bazzaz, F. A. (1987). Reproductive effort in plants. 1. Carbon allocation to reproduction. 129, 876-896. Sch~ippi, B., and K6rner, Ch. (1996). Growth responses of an alpine grassland to elevated COs. 105, 43-52. Strain, B. R., and Bazzaz, F. A. (1983). Terrestrial plant communities. and Plants: The Response of Plants to Rising Levels of Carbon Dioxide" (E. Lemon, ed.), pp. 177-222. American Association for the Advancement of Science, Washington, DC. Whitbeck, J. L. (1994). "Effects of Above- and Below-Ground Resource Distribution on the Ecology of Vesicular-Arbuscular Mycorrhizas." Ph.D. thesis, Stanford University, Stanford, CA.

Index

canopy development model, 418-420 canopy development model, 418-420 Animals biodiversity effects, 451-452 ruminants, forage plant quality, 363-369 carbon dioxide impact, 366-367 cattle production impact, 367-369 future research directions, 369 ruminant digestion, 364-366 Bacteria, nitrogen fixation, 253-261 field studies, 258-259 model mechanics, 259-260 nitrogen availability, 255-258 plant growth effects, 255 symbiotic process, 254-255 Biodiversity community composition changes, 93-99 discussion, 97-98 methods, 94-96 overview, 93-94 results, 96 summary, 98-99 grassland plant species dominance, 159-174 community responses, 164-166 discussion, 166-173 aboveground biomass changes, 173-174 community composition consequences, 166-170 diversity manipulation interpretation, 172-173 functional groups, 170-172

response variation, 174 experimental design, 160-164 Mediterranean old-field microcosms, 124-126 significance, 443-455 community responses, 446-449 ecosystem consequences, 453-455 genotypic population responses, 445-446 global consequences, 453-455 modeling, 452-453 plant-animal interactions, 451-452 plant-microbe interactions, 451 plant-plant interactions, 449-450 theory, 452-453 variance study, 444-445 Biomass allocation patterns calcareous grassland plants, species dominance, 173-174 competitive performance role, 108-111 grasses verses 305-308 Mediterranean old-field microcosms, 126, 129, 131-132 global change responses, 23-30 competition, 319-329 interactions, 327-329 low light acclimation, 321-325, 329 shade tolerance, 320-326 CAM species, interspecific growth response variation, 380-384 Canopy development, herbaceous plant stands, 413-428 418-420

Canopy development, herbaceous plant stands (continued) 418-420 future research directions, 427-428 leaf area index optimization, 420-426 light interception, 414-418 model, 415-416 photon partitioning, 416-418 nitrogen allocation, 420-426 Cattle, Ruminant animals C4 plants, competition C3 versus C4 species, 275-278, 282-283 grasses verses 301-315 dry mass results, 305-308 long term implications, 314-315 methods, 303-305 nutrient status, 308-311,314 phenology, 311-313 shoot morphology results, 308 species competitive abilities, 313 temperature effects, 311-313 theory, 301-303 grassland legumes versus nonlegume responses, 287-297 intraspecific response variability, 293-296 methods, 288-289 nitrogen availability effects, 292-293 response variability, 289-292 Chemistry, Plant chemistry Climate, change responses 23-30 evolutionary responses, 7-11 genetics, 4-7 grasses verses 311-313 overview, 3-4 thermal sensitivity, 7-11 Communities, composition changes calcareous grasslands, 166-170 discussion, 97-98 methods, 94-96 overview, 93-94 results, 96 summary, 98-99 fire disturbances, 231-245 carbon dioxide effects, 235-241 cycle prediction, 241-243 fire role, 232-235 research priorities, 243-244

Competition developmental process implications, 333-344 carbon dioxide responsiveness, 341-343 competitive ability, 334-336 developmental patterns, 334-336 effects prediction, 336-341 plant-plant interactions differential responses, 275-283 C3 versus C~ species, 278-282 C~ versus C4 species, 275-278, 282-283 functional groupings, 284 grasses verses 301-315 dry mass results, 305-308 long term implications, 314-315 methods, 303-305 nutrient status, 308-311,314 phenology, 311-313 shoot morphology results, 308 species competitive abilities, 313 temperature effects, 311-313 theory, 301-303 grassland legumes versus nonlegume responses, 287-297 intraspecific response variability, 293-296 methods, 288-289 nitrogen availability effects, 292-293 response variability, 289-292 overview, 273-275 versus 319,-329 low light acclimation, 321-325, 329 shade tolerance, 320-326 species interactions, 327-329 species dominance, calcareous grassland plants, 159-174 aboveground biomass changes, 173-174 community composition consequences, 166-170 community responses, 164-166 diversity manipulation interpretation, 172-173 experimental design, 160-164 functional groups, 170-172 response variation, 174 tropical ecosystems belowground interactions, 114-115 leaf area index, 111-112

photosynthetic performance role, 113-114 plant morphology effects, 108-111 Cryptogams, ultraviolet-B radiation effects, sub-arctic heathlands, 202-204 Decomposition, ultraviolet-B radiation effects, sub-arctic heathlands, 203 Developmental processes, competitive success implications, 333-344 carbon dioxide responsiveness, 341-343 competitive ability, 334-336 developmental patterns, 334-336 effects prediction, 336-341 Disturbances, Ecology Diversity, Biodiversity Dominance, Species dominance Ecology fire disturbances, 231-245 carbon dioxide effects, 235-241 fuel composition, 237-239 fuel moisture content, 239-241 fire cycle prediction, 241-243 fire role, 232-235 research priorities, 243-244 functional groups, interspecific growth response variation, 390-391 prediction problems, 431-440 extrapolation, 432-434 holistic experiments, 436-439 reductionism experiments, 436-439 theory, 434-436 uncertainty, 439-440 Europe, vegetation changes, 85-91 carbon dioxide response, 88 current changes, 86-88 feedbacks, 89-90 functional plant types, 88 future prospects, 91 Evolution change potential, 13-21 experimental methods, 15-17 future research directions, 21 overview, 13-15 results, 17-20 climate change responses 23-30 genetics, 4-7 overview, 3-4 thermal sensitivity, 7-11

grassland plant population responses, 31-48 experimental design, 38-39 outlook, 47-48 results, 39-47 theory, 31-38 microevolutionary responses, 51-75 conceptual issues, 54-58 ecosystem process effects, 73-74 empirical data, 58-61 genetic correlation structure, 67-68 genetic variability, 54-61 heritability, 64-67 overview, 51-54 phenotypic variability, 62-64 quantitative genetic framework, 61-62 selection characteristics, 68-73 selection process effects, 61-68 Fire ecology, 231-245 carbon dioxide effects, 235-241 fuel composition, 237-239 fuel moisture content, 239-241 fire cycle prediction, 241-243 fire role, 232-235 research priorities, 243-244 Forage plants, quality, 363-369 carbon dioxide impact, 366-367 cattle production impact, 367-369 future research directions, 369 ruminant digestion, 364-366 Functional groups European vegetation changes, 88 interspecific growth response variation, 375-392 C3 species differences, 384-389 ecological aspects, 390-391 low nitrogen level differences, 389-390 methodology, 376-380 limitations, 380 protocol, 377 weight ratio aspects, 377-380 need, 375-376 photosynthetic pathway differences, 380-384 woody species differences, 389 plant-plant competition, 284 research usefulness, 170-172, 375-376 Fungi, community interactions, 265-271 consequences, 268-271 symbiotic responses, 266-268

Genetic variability, Evolution Grassland communities community responses, 139-155 analysis, 144-145 discussion, 151-155 aboveground litter, 153 carbon dioxide response, 153-155 nutrient effects, 151 seed dormancy, 151-152 soils, 152 experimental design, 140-142 methods, 142-144 results, 145-151 carbon dioxide effects, 148-150 community effects, 147-151 invasion, 150-151 nutrient effects, 147, 150 production totals, 145-147 competition grasses verses 301-315 dry mass results, 305-308 long term implications, 314-315 methods, 303-305 nutrient status, 308-311,314 phenology, 311-313 shoot morphology results, 308 species competitive abilities, 313 temperature effects, 311-313 theory, 301-303 legumes versus nonlegume growth responses, 287-297 intraspecific response variability, 293-296 methods, 288-289 nitrogen availability effects, 292-293 response variability, 289-292 versus 319-329 low light acclimation, 321-325, 329 shade tolerance, 320-326 species interactions, 327-329 species dominance, 159-174 aboveground biomass changes, 173-174 community composition consequences, 166-170 community responses, 164-166 diversity manipulation interpretation, 172-173 experimental design, 160-164

functional groups, 170-172 response variation, 174 genetic variation, 31-48 experimental design, 38-39 outlook, 47-48 results, 39-47 theory, 31-38 nitrogen fixation, 253-261 field studies, 258-259 model mechanics, 259-260 nitrogen availability, 255-258 plant growth effects, 255 symbiotic process, 254-255 ultraviolet-B radiation effects, sub-arctic heathlands, 202 woody plant invasion, 177-190 carbon dioxide influence, 181-190 seedling establishment, 185-189 vegetation change effects, 189-190 water availability interactions, 182-185, 188-189 overview, 177-181 Growth response grassland community competition, legume versus nonlegume growth responses, 287-297 intraspecific response variability, 293-296 methods, 288-289 nitrogen availability effects, 292-293 response variability, 289-292 interspecific variation, 375-392 Cs species differences, 384-389 ecological aspects, 390-391 functional types need, 375-376 low nitrogen level differences, 389-390 methodology, 376-380 limitations, 380 protocol, 377 weight ratio aspects, 377-380 photosynthetic pathway differences, 380-384 woody species differences, 389 Heathland, Sub-arctic heathland Herbaceous plants, canopy development, 413-428 418-420 418-420 future research directions, 427-428 leaf area index optimization, 420-426 light interception, 414-418

model, 415-416 photon partitioning, 416-418 nitrogen allocation, 420-426 Herbivory tropical plant communities, insect responses, 115-118 ultraviolet-B radiation effects, sub-arctic heathlands, 203-204 Heritability, Evolution Holistic experiments, ecological prediction problems, 436-439 Insects evolutionary climate change responses, genetics, 4-7 forest communities, 347-359 direct effects, 349-353 accelerated development, 351 altered biochemistry, 351 insect performance, 351-353 plant chemistry, 349-351 indirect effects, 354-355 interactive effects, 353-354 outbreak prediction, 356-357 recommendations, 357-359 resource availability, 353-354 tritropic interactions, 355-356 plant species dominance interactions, 115-118 ultraviolet-B radiation effects, sub-arctic heathlands, 203-204 Invasion, Competition grassland communities community responses, 150-151 woody plants, 177-190 carbon dioxide influence seedling establishment, 185-189 vegetation change effects, 189-190 water availability interactions, 182-185, 188-189 Leaf area index carbon metabolism, 221-222 competitive success role, tropical plants, 111-112 herbaceous plant canopy development, 420-426 Legumes competition grasses verses 301-315 dry mass results, 305-308

long term implications, 314-315 methods, 303-305 nutrient status, 308-311, 314 phenology, 311-313 shoot morphology results, 308 species competitive abilities, 313 temperature effects, 311-313 theory, 301-303 grassland legumes versus nonlegume responses, 287-297 intraspecific response variability, 293-296 methods, 288-289 nitrogen availability effects, 292-293 response variability, 289-292 nitrogen fixation, 253-261 field studies, 258-259 model mechanics, 259-260 nitrogen availability, 255-258 plant growth effects, 255 symbiotic process, 254-255 Light, Photosynthetic pathways; Shade tolerance competitive success role, tropical plants, 111-112 herbaceous plant canopy development, 414-418 model, 415-416 photon partitioning, 416-418 versus competition, low light acclimation, 321-325, 329 L., photochemical efficiency, 218-219 Livestock, Ruminant animals Mediterranean communities old-field microcosms, 123-136 community responses, 124-127 experimental designs, 124-126 species responses, 126-127 ecosystem responses, 127-131 carbon dioxide exchange, 127-129 community type interactions, 131 ecosystem processes, 133-135 nutrient fluxes, 129-131 soil microbiology, 131 standing biomass, 129 water fluxes, 129-131 individual species biomass production, 131-132 intraspecific response variability, 133

Mediterranean communities old-field microcosms (c0ntinued) phenology changes, 126-127, 132-133 reproduction changes, 127, 132-133 time scale considerations, 135-136 woodlands, 209-226 discussion, 223-226 experimental methods, 211-216 anatomical observations, 215 biochemical analyses, 215 fluorescence measurements, 214-215 gas exchange measurements, 213-214 growth measurements, 215-216 setup, 212-213 site selection, 211-212 results, 216-223 carbon dioxide uptake, 217-218 leaf anatomy, 221-222 nitrogen concentration, 220 photochemical efficiency, 218-219 shoot growth, 222-223 total nonstructural carbohydrates, 218-219 water availability, 216-217 Microbes, Bacteria; Fungi Mosses, ultraviolet-B radiation effects, subarctic heathlands, 202-203 Natural selection, Evolution Nitrogen concentration effects, Mediterranean woodlands, 220 fixation, grassland ecosystems field studies, 258-259 interspecific variability, 292-293 model mechanics, 259-260 nitrogen availability, 255-258 overview, 253-254 plant growth effects, 255 summary, 260-261 symbiotic process, 254-255 herbaceous plant canopy development, 420-426 interspecific growth response variation, low level differences, 389-390 Nutrients competitive success role annual grassland microcosms, 147, 150-151 grasses verses 308311,314

Mediterranean old-field microcosms, 129-131 tropical plant communities, 118 forest insect community effects, 349-351 Phenology competitive responses, grasses verses 311-313 Mediterranean old-field microcosms, 126-127, 132-133 Photosynthetic pathways, Light competition C3 versus C3 species, 278-282 C3 versus C4 species, 275-278, 282-283 grasses verses 301-315 dry mass results, 305-308 long term implications, 314-315 methods, 303-305 nutrient status, 308-311,314 phenology, 311-313 shoot morphology results, 308 species competitive abilities, 313 temperature effects, 311-313 theory, 301-303 grassland legumes versus nonlegume responses, 287-297 intraspecific response variability, 293-296 methods, 288-289 nitrogen availability effects, 292-293 response variability, 289-292 tropical ecosystems, community responses, 113-114 interspecific growth response variation, 380-384 competition, 319-329 interactions, 327-329 low light acclimation, 321-325, 329 shade tolerance, 320-326 carbon dioxide elevation response, 13-21 experimental methods, 15-17 future research directions, 21 overview, 13-15 results, 17-20 Plant chemistry, processes forest insects consequences, 349-351 Mediterranean woodlands community analysis, 215, 218-219 carbon dioxide responses experimental design, 38-39

results, 39-47 genotypic responses, 42-45 prediction consequences, 45-47 species responses, 39-42 L., carbon metabolism, 209-226 discussion, 223-226 experimental methods, 211-216 anatomical observations, 215 biochemical analyses, 215 fluorescence measurements, 214-215 gas exchange measurements, 213-214 growth measurements, 215-216 setup, 212-213 site selection, 211-212 results, 216-223 carbon dioxide uptake, 217-218 leaf anatomy, 221-222 nitrogen concentration, 220 photochemical efficiency, 218-219 shoot growth, 222-223 total nonstructural carbohydrates, 218-219 water availability, 216-217 Radiation,

Light; Ultraviolet-B radiation carbon dioxide elevation response, 13-21 experimental methods, 15-17 future research directions, 21 overview, 13-15 results, 17-20 Reductionism, ecological prediction problems experiments, 436-439 theory, 434-436 Root growth, competitive success role, tropical plants, 114-115 Ruminant animals, forage plant quality, 363-369 carbon dioxide impact, 366-367 cattle production impact, 367-369 future research directions, 369 ruminant digestion, 364-366 Seeds dormancy, annual grassland community responses, 151-152 establishment, woody plant invasion, 185-189

Shade tolerance,

Light

versus interactions, 319-329 species interactions, 327-329 tolerance mechanisms, 320-326 low light acclimation, 321-325, 329 tolerance changes, 326 Shoot growth grasses verses 308 L., carbon metabolism, 222-223 Shrubs, Woody plants Soil annual grassland community responses, 152 Mediterranean old-field microcosms, microbiology, 131 Species dominance calcareous grassland plants, 159-174 community responses, 164-166 discussion, 166-173 aboveground biomass changes, 173-174 community composition consequences, 166-170 diversity manipulation interpretation, 172-173 functional groups, 170-172 response variation, 174 experimental design, 160-164 insect effects, 115-118 tropical plant community responses, 103-107 Sub-arctic heathland, ultraviolet-B radiation effects, 197-205 decomposition, 203 herbivory, 203-204 methodology, 198-200 primary producer response cryptogams, 202-204 dwarf shrubs, 200-202 grasses, 202 species-specific responses, 204-205 site description, 198-200 Symbiotic interactions nitrogen fixation, grassland ecosystems, 253-261 field studies, 258-259 model mechanics, 259-260 nitrogen availability, 255-258 plant growth effects, 255 symbiotic process, 254-255

Symbiotic interactions (c0ntinued) plant-fungal interactions, 265-271 consequences, 268-271 symbiotic responses, 266-268 Temperature competitive effects, grasses verses 311-313 evolutionary climate change responses, 7-11 Trees, Woody plants grassland plant competition, 301-315 long term implications, 3 1 4 - 3 1 5 methods, 303-305 phenology, 311-313 results dry mass, 305-308 nutrient status, 308-311,314 shoot morphology, 308 species competitive abilities, 313 temperature effects, 311-313 theory, 301-303 Tritropic interactions, forest insects, 355-356 Tropical ecosystems, plant community responses, 101-119 community responses, 103-111 biomass allocation patterns, 108-111 competitive performance, 108-111 individually grown versus competitively grown plants, 107-108 plant morphology effects, 108-111 species shifts, 103-107 competitive success belowground interactions, 114-115 leaf area index, 111-112 photosynthetic performance role, 113-114 plant morphology effects, 108-111 individual responses, 102-103 insect herbivory responses, 115-118 leaf area index effects, 111-112 light effects, 111 - 112 recommendations, 118-119 Ultraviolet-B radiation, sub-arctic heathland, 197-205 decomposition, 203 herbivory, 203-204 methodology, 198-200 primary producer response

cryptogams, 202-204 dwarf shrubs, 200-202 grasses, 202 species-specific responses, 204-205 site description, 198-200 Water grassland communities, woody plant invasion, 182-185, 188-189 Mediterranean communities old-field microcosms, 129-131 woodlands, 216-217 Woody plants forest insect consequences, 347-359 direct effects, 349-353 accelerated development, 351 altered biochemistry, 351 insect performance, 351-353 plant chemistry, 349-351 indirect effects, 354-355 interactive effects, 353-354 outbreak prediction, 356-357 recommendations, 357-359 resource availability, 353-354 tritropic interactions, 355-356 functional groups, interspecific growth response variation, 389 grassland community invasion, 177-190 carbon dioxide influence, 181-190 seedling establishment, 185-189 vegetation change effects, 189-190 water availability interactions, 182-185, 188-189 overview, 177-181 Mediterranean ecosystems, 209-226 discussion, 223-226 experimental methods, 211-216 anatomical observations, 215 biochemical analyses, 215 fluorescence measurements, 214-215 gas exchange measurements, 213-214 growth measurements, 215-216 setup, 212-213 site selection, 211-212 results, 216-223 carbon dioxide uptake, 217-218 leaf anatomy, 221-222 nitrogen concentration, 220 photochemical efficiency, 218-219 shoot growth, 222-223

total nonstructural carbohydrates, 218-219 water availability, 216-217 versus competition, 319-329

low light acclimation, 321-325, 329 shade tolerance, 320-326 species interactions, 327-329 ultraviolet-B radiation effects, sub-arctic heathlands, 200-202

Physiological Ecology Series Editor Harold A. Mooney

Fakhri A. Bazzaz Robert W. Pearcy

Editorial Board F. Stuart Chapin James R. Ehleringer Martyn M. Caldwell E.-D. Schulze

T. T. KOZLOWSKI. Growth and Development of Trees, Volumes I and II, 1971 D. HILLEL. Soil and Water: Physical Principles and Processes, 1971 V. B. YOUNGER and C. M. McKELL (Eds.). The Biology and Utilization of Grasses, 1972 J. B. MUDD and T. T. KOZLOWSKI (Eds.). Responses of Plants to Air Pollution, 1975 R. DAUBENMIRE. Plant Geography, 1978 J. LEVITT. Responses of Plants to Environmental Stresses, Second Edition Volume I: Chilling, Freezing, and High Temperature Stresses, 1980 Volume II: Water, Radiation, Salt, and Other Stresses, 1980 J. A. LARSEN (Ed.). The Boreal Ecosystem, 1980 S. A. GAUTHREAUX, JR. (Ed.). Animal Migration, Orientation, and Navigation, 1981 F. J. VERNBERG and W. B. VERNBERG (Eds.). Functional Adaptations of Marine Organisms, 1981 R. D. DURBIN (Ed.). Toxins in Plant Disease, 1981 C. P. LYMAN, J. S. WILLIS, A. MALAN, and L. C. H. WANG. Hibernation and Torpor in Mammals and Birds, 1982 T. T. KOZLOWSKI (Ed.). Flooding and Plant Growth, 1984 E. I. RICE. Allelopathy, Second Edition, 1984

M. L. CODY (Ed.). Habitat Selection in Birds, 1985 R.J. HAYNES, I~ C. CAMERON, K. M. GOH, and R. R. SHERLOCK (Eds.). Mineral Nitrogen in the Plant-Soil System, 1986 T. T. KOZLOWSKI, P.J. KRAMER, and S. G. PALI_ARDY. The Physiological Ecology of Woody Plants, 1991 H. A. MOONEY, W. E. WINNER, and E.J. PELL (Eds.). Response of Plants to Multiple Stresses, 1991 F. S. CHAPIN III, R. L. JEFFERIES, J. F. REYNOLDS, G. R. SHAVER, and J. SVOBODA (Eds.). Arctic Ecosystems in a Changing Climate: An Ecophysiological Perspective, 1991 T. D. SHARKEY, E. A. HOLLAND, and H. A. MOONEY (Eds.). Trace Gas Emissions by Plants, 1991 U. SEELIGER (Ed.). Coastal Plant Communities of Latin America, 1992 JAMES R. EHLERINGER and CHRISTOPHER B. FIELD (Eds.). Scaling Physiological Processes: Leaf to Globe, 1993 JAMES R. EHLERINGER, ANTHONY E. HALL, and GRAHAM D. FARQUHAR (Eds.). Stable Isotopes and Plant Carbon-Water Relations, 1993 E.-D. SCHULZE (Ed.). Flux Control in Biological Systems, 1993 MARTYN M. CALDWELL and ROBERT W. PEARCY (Eds.). Exploitation of Environmental Heterogeneity by Plants: Ecophysiological Processes Above- and Belowground, 1994 WILLIAM K. SMITH and THOMAS M. HINCKLEY (Eds.). Resource Physiology of Conifers: Acquisition, Allocation, and Utilization, 1995 WILLIAM K. SMITH and THOMAS M. HINCKLEY (Eds.). Ecophysiology of Coniferous Forests, 1995 MARGARET D. LOWMAN and NALINI M. NADKARNI (Eds.). Forest Canopies, 1995 BARBARA L. GARTNER (Ed.). Plant Stems: Physiology and Functional Morphology, 1995 GEORGE W. KOCH and HAROLD A. MOONEY (Eds.). Carbon Dioxide and Terrestrial Ecosystems, 1996 CHRISTIAN KORNER and FAKHRI A. BAZZAZ (Eds.). Carbon Dioxide, Populations, and Communities, 1996

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