Desert Puma: Evolutionary Ecology And Conservation Of An Enduring Carnivore

About Island Press Island Press is the only nonprofit organization in the United States whose principal purpose is the publication of books on environmental issues and natural resource management. We provide solutions-oriented information to professionals, public officials, business and community leaders, and concerned citizens who are shaping responses to environmental problems. In 2001, Island Press celebrates its seventeenth anniversary as the leading provider of timely and practical books that take a multidisciplinary approach to critical environmental concerns. Our growing list of titles reflects our commitment to bringing the best of an expanding body of literature to the environmental community throughout North America and the world. Support for Island Press is provided by The Bullitt Foundation, The Mary Flagler Cary Charitable Trust, The Nathan Cummings Foundation, Geraldine R. Dodge Foundation, Doris Duke Charitable Foundation, The Charles Engelhard Foundation, The Ford Foundation, The George Gund Foundation, The Vira I. Heinz Endowment, The William and Flora Hewlett Foundation, W. Alton Jones Foundation, The John D. and Catherine T. MacArthur Foundation, The Andrew W. Mellon Foundation, The Charles Stewart Mott Foundation, The Curtis and Edith Munson Foundation, National Fish and Wildlife Foundation, The New-Land Foundation, Oak Foundation, The Overbrook Foundation, The David and Lucile Packard Foundation, The Pew Charitable Trusts, Rockefeller Brothers Fund, The Winslow Foundation, and other generous donors.

About the Hornocker Wildlife Institute The Hornocker Wildlife Institute was founded by Maurice Hornocker in 1985 as an independent, nonprofit organization with the mission to conduct longterm ecological research, support graduate and post-graduate students, and disseminate information to the public and to the agencies responsible for conservation and management of wildlife and wildlands. In the year 2000, the institute became part of the Wildlife Conservation Society, known for its field science and conservation projects around the world for more than one hundred years. The institute now forms the core of the WCS Global Carnivore Program, which directs and advises carnivore research and conservation efforts worldwide from its offices in Bozeman, Montana. Desert Puma is the first in a series of publications on long-term scientific projects under the HWI/WCS banner.

Desert Puma

To our son Oren, and our parents Rita and James Logan, Joan and George Sweanor

Desert Puma E v o l u t i o n a ry E co l o g y a n d Co n s e r v a t i o n o f a n E n d u r i n g Ca r n i v o re

Kenneth A. Logan and Linda L. Sweanor HORNOCKER WILDLIFE INSTITUTE, A Program of the Wildlife Conservation So c i e t y

Washington • Covelo • London

Copyright © 2001 Kenneth A. Logan and Linda L. Sweanor All rights reserved under International and Pan-American Copyright Conventions. No part of this book may be reproduced in any form or by any means without permission in writing from the publisher: Island Press, 1718 Connecticut Avenue, N.W., Suite 300, Washington, DC 20009. ISLAND PRESS is a trademark of The Center for Resource Economics. Library of Congress Cataloging-in-Publication Data Logan, Kenneth A. Desert Puma : evolutionary ecology and conservation of an enduring carnivore / Kenneth A. Logan and Linda L. Sweanor. p. cm. Includes bibliographical references (p. ). ISBN 1-55963-866-4 (cloth : alk. paper) — ISBN 1-55963-867-2 (paper : alk. paper) 1. Puma—New Mexico. 2. Desert animals—New Mexico. I. Sweanor, Linda L. II. Title. QL737.C23 L64 2001 599.75’24’097896—dc21 2001003356 British Cataloguing-in-Publication Data available. Printed on recycled, acid-free paper Manufactured in the United States of America 10 9 8 7 6 5 4 3 2 1

Contents

xv

List of Figures, Tables, and Photos Foreword

xxiii

Acknowledgments

xxvii

Part 1. Setting the Stage Chapter 1. Introduction

3

Rationale and Approach 5 Synopsis of Previous Studies 6

Chapter 2. Pumas Past and Present Puma Phylogeny 9 Puma Distribution and Status Pumas in the Southwest 16 Taxonomy 16 Description 18 Statistic 21

9

15

Chapter 3. Our Outdoor Laboratory

23

Physiography and Geology 26 Climate 27 Flora 29 Fauna 30 History of Human Use 33 History of Puma Exploitation 36 vii

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Chapter 4. Studying Wild Pumas

39

Life Afield 39 To Catch a Puma 42 Monitoring Desert Mule Deer and Desert Bighorn Sheep Radiotelemetry 54 Investigating the Dead 58 Overview of Analytical and Statistical Methods 59

51

Part 2. Puma Life History Strategies and Population Dynamics Chapter 5. A Puma Population in the Desert Research Hypotheses and Predictions Terms for Pumas 64 Counting Pumas 65

63

Chapter 6. Puma Population Structure

69

Sex Structure 69 Cubs 69 • Subadults 73 • Adults 73 Age Structure 75 The Population 75 • Adult Pumas 78 Summary 80 Statistics 81

Chapter 7. Reproduction

83

Natality 83 Timing of Births 88 Mating, Gestation, and Birth Intervals Puberty and First Litters 93 Parental Investment 96 Reproductive Success 96 Females 98 • Males 103 Summary 110 Statistics 111

91

63

Contents

Chapter 8. Mortality and Survival

ix

115

Human-Caused Mortality 115 Natural Mortality 117 Cubs 117 • Subadults 122 • Adults 127 Why Do Pumas Kill Other Pumas? 139 Summary 142 Statistics 143

Chapter 9. Independence of Puma Progeny, and Philopatry, Emigration, and Immigration 145 Independence of Progeny 146 Philopatry and Dispersal 148 Emigration 153 Recruitment of Progeny and Immigrants Summary 154

154

Chapter 10. Puma Population Density, Growth, and Metapopulation Structure 157 Experimentally Removing Pumas 157 Density 160 Rates of Population Increase 169 Metapopulation Dynamics 175 Summary 179

Part 3. Puma Behavior and Social Organization Chapter 11. How Should Desert Pumas Behave?

183

Two-Strategies Hypothesis 183 Self-Limiting Hypothesis 184

Chapter 12. Adult Home Range Characteristics Delineating the Home Range 189 Seasonal and Annual Home Range 191 Birth-Interval Home Range 192

189

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Lifetime Home Range 195 What Factors Influence Adult Home Range Size? 195 Home Range Size, Prey Abundance, and Puma Density 201 Does Prey Abundance Affect Home Range Size? 202 • Does Puma Density Affect Home Range Size? 204 • Does Home Range Size Reflect an Attempt at Population Self-Limitation? 210 Adult Home Range Fidelity 211 Method 1—Fidelity Index 213 • Method 2—Distances between Mean Locations 214 • Home Range Shifts in Pumas 216 • Homing by Translocated Pumas 222 • Benefits of Fidelity and the Two-Strategies Hypothesis 223 • Fidelity in Desert Pumas and the Self-Limiting Hypothesis 225 Summary 225 Statistic 227

Chapter 13. Subadult Ranging Behavior

231

Philopatry in Females 232 Female Dispersal 233 Male Dispersal 236 Frustrated Dispersal 239 Why Do Pumas Disperse? 240 Transient Behavior in Pumas 244 Summary 245 Statistic 246

Chapter 14. Interactions between Pumas Spatial Relationships

247

247

Home Range Overlap Indices

249 • Nearest-Neighbor Analysis

254

Spatiotemporal Relationships Direct Interactions 257

255

Associations between Independent Pumas between Family Members 267

260 • Associations

Communication among Pumas 269 Vocalizations 269 • Chemical Communication 272

Contents

Summary Statistics

xi

276 277

Chapter 15. Adaptive Significance of Puma Social Organization 281 The Social Structure of Desert Pumas 281 Female Structure 282 • Male Structure 283 The Self-Limiting Hypothesis 284 Land Tenure and Territoriality 285 • Do Desert Pumas Exhibit Land Tenure or Territoriality? 286 The Two-Strategies Hypothesis 288 Female Strategy 288 • Male Strategy 290 Pumas and Other Big Cats—Similar Strategies? 294 Summary 297

Part 4. Puma–Prey Relationships Chapter 16. Puma Diet

301

Patterns of Pumas and Prey 301 Puma Diet on the San Andres Mountains Summary 308

Chapter 17. Pumas and Desert Mule Deer

302 311

Hypotheses, Predictions, and Terms 311 Characteristics of Dead Deer 312 Fates of Radio-Collared Deer 314 Mule Deer Population Dynamics 321 Puma Predation and Mule Deer Population Growth 322 Some Behavioral Interactions between Deer and Pumas 331 Did Puma Predation Limit the Deer Population? 332 Did Pumas Limit Their Own Density and Not Harm Their Food Supply? 333 Cases of Pumas and Other Carnivores Limiting Prey Populations 335 What Limits the Puma Population? 336

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How Would a Puma Population Respond to a Prey Crash? Summary 338 Statistics 339

Chapter 18. Pumas and Desert Bighorn Sheep

337

341

Hypothesis and Predictions 341 Pre-history, History, and Threats 342 Sheep Population Characteristics during Our Research 346 Fates of Radio-Collared Sheep 347 Survival Rates and Agent-Specific Mortality 350 Did Puma Predation Limit the Sheep Population? 354 Finale of the Sheep Population 354 Pumas and Other Sheep Populations 356 Summary 357 Statistic 357

Chapter 19. Synthesis: Pumas and Weather Modulate Large-Mammal Population Dynamics on the San Andres Mountains 359

Part 5. Pumas and People Chapter 20. Conservation and Management of Wild Pumas 365 Threats to Pumas Habitat Loss

367 367 • Puma Overkill 371

Alleviating Threats

377 Habitat Conserv a t i on 378 • Preventing Unnecessary Ove rk i ll 383 • Ad a p t i veManagement—Inv o lving People 384

Summary 395 Statistic 395

Chapter 21. Epilogue

397

Appendix 1. Morphological Measurements of Pumas At Least 3.5 Months Old on the San Andres Mountains, New Mexico, 1985–1995 399

Contents

Appendix 2. Reproductive Chronology of Mated Pairs of Pumas on the San Andres Mountains, New Mexico, 1987–1994 413 Appendix 3. Methods and Estimates of Annual Home Range Size for Pumas on the San Andres Mountains, New Mexico 415 Appendix 4. A Deterministic, Discrete Time Model That Simulated Mule Deer Population Dynamics in the Treatment Area, San Andres Mountains, New Mexico, 1987–1995. See Chapter 17 for its application. 419 References Index

423

451

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List of Figures, Tables, and Photos

Figures 3-1 3-2 4-1 6-1 6-2

6-3 7-1 7-2

8-1 8-2 8-3

9-1

The puma study area, San Andres Mountains, New Mexico. 24 Annual and growing season precipitation, San Andres Mountains, New Mexico, 1985–1994. 28 Locations of resident adult pumas on the San Andres Mountains, New Mexico, 1985–1995. 55 Masses of puma cubs, San Andres Mountains, New Mexico, 1986–1994. 71 Age structure of the puma population in the Treatment Area and Reference Area each January, 1989–1995, San Andres Mountains, New Mexico. 76 Adult puma age structure in the Treatment Area and Reference Area in three broad age classes, San Andres Mountains, New Mexico. 80 Distribution of births of seventy-eight puma litters by month, 1986–1994, San Andres Mountains, New Mexico. 88 Scatter plot of the number of litters produced by adult female and male pumas monitored for at least twelve months by radiotelemetry, San Andres Mountains, New Mexico. 100 Puma cub survival rates from birth to thirteen months, San Andres Mountains, New Mexico. 119 Causes of death in puma cubs, San Andres Mountains, New Mexico. 121 Relationship of adult puma density to frequency of independent puma deaths from intraspecies strife in the Treatment Area and Reference Area, San Andres Mountains, New Mexico. 135 Dispersal moves of pumas from the San Andres Mountains to other habitats in New Mexico. 151 xv

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List of Figures, Tables, and Photos

10-1 Observed exponential rates of increase for adult pumas in the Treatment Area and Reference Area using January population estimates, San Andres Mountains, New Mexico. 171 12-1 The means and standard deviations of annual, birth interval, and lifetime home range sizes, based on the 90 percent adaptive kernel home range estimator, for adult pumas on the San Andres Mountains, New Mexico, 1986–1994. 192 12-2 Home range size for female pumas during three consecutive cub-rearing periods on the San Andres Mountains, New Mexico, 1986–1994. 194 12-3 The home range of puma F15 during three consecutive cub-rearing periods, San Andres Mountains, New Mexico. 194 12-4 Adult puma home range size correlated with adult puma density in five study areas (Alberta, British Columbia, Idaho, New Mexico, and Utah) in North America. 204 12-5 Changes in annual home range size and density of adult pumas in the Treatment Area, San Andres Mountains, New Mexico. 207 12-6 Puma M3’s annual home range, 1988–1990 (a), and 1991–1993 (b), in the Treatment Area, San Andres Mountains, New Mexico. 209 12-7 A simplified example of a fidelity index. 212 12-8 Frequency distribution of the fidelity index (FI1) for adult male and female pumas, based on the 90 percent adaptive kernel home range estimator, San Andres Mountains, New Mexico, 1986–1994. 214 12-9 Fidelity index (mean and standard deviation) for adult pumas on the San Andres Mountains, New Mexico. 215 12-10 Examples of strong annual home range fidelity in adult pumas on the San Andres Mountains, New Mexico. 215 12-11 Puma M36’s annual home ranges during six of seven consecutive years, San Andres Mountains, New Mexico. 216 12-12 Examples of home range shifts exhibited by adult pumas over consecutive years, San Andres Mountains, New Mexico. 217 14-1 Mean and standard deviation of the annual spatial overlap and spatiotemporal overlap between pairs of same-sex adult pumas on the San Andres Mountains, New Mexico. 259 14-2 Number of associations between independent pumas that were related to breeding, non-breeding, or unknown activities on the San Andres Mountains, New Mexico, 1985–1995. 263 14-3 Home ranges for adult pumas M19 and M29 in 1991, San Andres Mountains, New Mexico. 264 17-1. Rates of survival, puma predation, and death from other causes for radio-collared mule deer, San Andres Mountains, New Mexico. 318

List of Figures, Tables, and Photos

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17-2 Desert mule deer population trend on the San Andres Mountains, New Mexico. 325 17-3 Relationship of deer population growth rates to puma predation rates on radio-collared deer, San Andres Mountains, New Mexico. 326 17-4 Relationship of deer population growth rates to fawn production, San Andres Mountains, New Mexico. 327 17-5 Relationship of adult puma numbers to predation rates on radiocollared deer, San Andres Mountains, New Mexico. 328 17-6 Mule deer and puma population trends on the San Andres Mountains, New Mexico. 334 18-1 Number of adult and yearling desert bighorn sheep observed in annual surveys and radio-collared during each year, San Andres Mountains, New Mexico. 348 18-2 Rates of survival, puma predation, and deaths from other causes for radio-collared desert bighorn sheep, San Andres Mountains, New Mexico. 354 20-1 Trends in number of puma-hunting permits issued and number of pumas killed by hunters in New Mexico. 373 20-2 A hypothetical zone-management approach for pumas in New Mexico. 385 A3-1 Home range sizes of pumas M5 and F45 plotted against the number of locations used to determine their size. 416

Tables 4-1 5-1

6-1 6-2 6-3

6-4

Summary of puma snare capture efforts on the San Andres Mountains, New Mexico, 1985–1995. 46 Percent accuracy for the estimated number of adult pumas per year, 1986–1994, in the Treatment Area and Reference Area, San Andres Mountains, New Mexico. 67 Sex ratios of adult pumas in the Treatment Area and Reference Area each year, 1988–1994, San Andres Mountains, New Mexico. 74 Sex ratios of adult pumas in the Treatment Area and Reference Area each January, 1989–1995, San Andres Mountains, New Mexico. 75 Proportion of pumas in three broad age classes in the Treatment Area population each January, 1989–1995, San Andres Mountains, New Mexico. 77 Proportion of pumas in three broad age classes in the Reference Area population each January, 1989–1995, San Andres Mountains, New Mexico. 77

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List of Figures, Tables, and Photos

6-5

Mean ages of adult pumas in the Treatment Area and Reference Area each January, 1989–1995, San Andres Mountains, New Mexico. 78 Annual survival rates for adult pumas, 1987–1994, San Andres Mountains, New Mexico. 128 Number, percentage, and ages of adult pumas that died of natural causes on the San Andres Mountains, New Mexico, 1985–1995. 130 Dispersal distances for independent pumas born on the San Andres Mountains, New Mexico, and for pumas with origins outside the San Andres Mountains, 1986–1994. 150 Puma population, number of pumas removed, and post-removal population in the Treatment Area, December 1990–July 1991, San Andres Mountains, New Mexico. 158 Estimated puma population each January in the Treatment Area (1988–1995) and Reference Area (1989–1995), San Andres Mountains, New Mexico. 161 Estimated density of pumas each January in the Treatment Area (1988–1995) and Reference Area (1989–1995), San Andres Mountains, New Mexico. 162 Estimated puma population each January, 1989–1995, San Andres Mountains, New Mexico. 163 Yearly adult puma density estimates for the Treatment Area (1988–1994) and Reference Area (1989–1994), San Andres Mountains, New Mexico. 164 Biological year adult puma density estimates for the Treatment Area (1987–1988 to 1993–1994) and Reference Area (1988–1989 to 1993–1994), San Andres Mountains, New Mexico. 165 Estimates of puma population composition and density in North American studies that employed intensive capture-mark-recapture and radiotelemetry techniques. 167 Observed exponential rates of increase for the adult puma population in the Treatment Area and Reference Area, San Andres Mountains, New Mexico. 170 Female puma home range size during an entire birth interval, San Andres Mountains, New Mexico. 193 Cumulative home ranges for ten adult male and six adult female pumas that were radio-monitored for forty-eight consecutive months on the San Andres Mountains, New Mexico. 196 Home range estimates for adult pumas in North America. 199 Annual home range size for adult pumas during years of relatively low and high deer densities, San Andres Mountains, New Mexico. 203

8-1 8-2 9-1

10-1

10-2

10-3

10-4 10-5

10-6

10-7

10-8

12-1 12-2

12-3 12-4

List of Figures, Tables, and Photos

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12-5 Mean annual home range size and density for adult male and female pumas on the San Andres Mountains, New Mexico, 1988–1994. 205 12-6 Distance between a female puma’s mean locations during consecutive six-month periods as she raised young cubs, older cubs, regained solitary status, and raised her subsequent litter of young cubs, San Andres Mountains, New Mexico. 221 14-1 Spatial relationships between adult same-sex pumas in other North American study areas. 248 14-2 Number of adult pumas of the same and opposite sex with which each puma shared parts of its home range, San Andres Mountains, New Mexico. 251 14-3 Percent home range overlap between pairs of adult pumas in the San Andres Mountains, New Mexico. 252 14-4 Percentage of a puma’s home range shared by all other adult pumas of the same sex, San Andres Mountains, New Mexico. 253 14-5 Percent home range overlap between adult pumas on the San Andres Mountains, New Mexico, during 1992. 254 14-6 Clark-Evans ratios for distances between arithmetic centers of nearest neighbors on the San Andres Mountains, New Mexico. 256 14-7 Spatiotemporal overlap indices for pumas on the San Andres Mountains, New Mexico. 258 14-8 Associations between independent pumas on the San Andres Mountains, New Mexico. 261 14-9 Comparisons of adult M-M, F-F, and M-F dyad associations in the San Andres Mountains puma population, New Mexico. 262 14-10 Scrape sites used by four resident adult male pumas on the San Andres Mountains from September 1985 to September 1988. 274 16-1 Prey killed by pumas on the San Andres Mountains, New Mexico, 1985–1995. 304 16-2 Prey items identified by hair and bone remains in 832 puma fecal samples and four stomachs collected from the San Andres Mountains, New Mexico, during 1985–1995. 306 16-3 Puma prey utilization based on 832 puma fecal samples and four stomachs collected from the San Andres Mountains, New Mexico, during 1985–1995. 307 17-1 Age and sex of desert mule deer that died on the San Andres Mountains, New Mexico, 1985–1995. 313 17-2 Survival rates of radio-collared desert mule deer, San Andres Mountains, New Mexico, 1987–1995. 316 17-3 Rates of puma predation and deaths from other causes in

xx

List of Figures, Tables, and Photos

17-4 17-5 17-6 17-7

18-1 18-2 18-3

A3-1

radio-collared desert mule deer, San Andres Mountains, New Mexico, 1987–1995. 317 Survival rates and agent-specific mortality rates of radio-collared deer, San Andres Mountains, New Mexico, 1987–1994. 320 Mule deer population composition, San Andres Mountains, New Mexico, 1988–1994. 323 Model parameter estimates used to simulate trends in the deer population on the San Andres Mountains, New Mexico, 1987–1995. 324 Finite rates of increase estimated by modeling the desert mule deer population on the San Andres Mountains, New Mexico, 1987–1995. 325 Desert bighorn sheep observed in surveys conducted on the San Andres Mountains, New Mexico, 1986–1994. 346 Survival rates of radio-collared desert bighorn sheep, San Andres Mountains, New Mexico, 1987–1994. 351 Rates of puma predation and other causes of death in radio-collared desert bighorn sheep, 1987–1994, San Andres Mountains, New Mexico. 353 Annual home range size for twenty-four adult male and thirty adult female pumas on the San Andres Mountains, New Mexico, 1986–1994. 416

Photos 1 2 3 4 5 6 7 8 9 10 11 12 13

Adult male puma M3 was resident on the San Andres Mountains until his death at twelve years of age. 18 Puma F47’s four-week-old cubs at the birth nursery. 20 San Andres Peak after sunup. 25 Upper Sulphur Canyon. 25 Puma paw petroglyph near Three Rivers, New Mexico. 33 Hembrillo Basin Camp. 40 San Andrecito Camp. 41 Puma tracks in the sand. 41 Puma M7 caught in a snare by his right forefoot. 43 Linda Sweanor using a pole syringe to inject puma F37 with immobilizing drugs. 44 Ken Logan hauling puma F37 for translocation to northern New Mexico. 45 Puma F27 at her birth nursery. 46 Adult female puma F47 with eartag and radio collar. 48

List of Figures, Tables, and Photos

xxi

14 Six-week-old cub F162 with eartag, tattoo, and radio collar. 49 15 New Mexico Department of Game and Fish biologist Amy Fisher with a radio-collared mule deer. 49 16 Puma F147’s three cubs at five weeks of age. 84 17 Puma F54’s birth nursery, where she had four cubs. 85 18 Orphaned puma F10 at ten months of age and nine days after her mother, F2, died. 122 19 Puma F15’s skull showing fatal bite wounds to the braincase and old damage to the zygomatic arch. 131 20 Puma M22’s skull showing mended canine puncture wounds. 133 21 Three eleven-month-old siblings F107, M108, and F109 with Ken Logan and Frank Smith. 149 22 Aerial telemetry was critical to estimating puma home ranges and determining puma interrelationships. 190 23 Brian Spreadbury with four-month-old puma F54. 234 24 Puma F40 was killed and eaten by territorial puma M19. 266 25 Male pumas were responsible for all of the killing of other pumas on the San Andres Mountains. 291 26 Desert mule deer were the most important prey to pumas on the San Andres Mountains. 303 27 A mule deer buck killed and eaten by a puma. 314 28 A desert bighorn ewe killed and eaten by a puma. 348 29 A yearling desert bighorn ram with ear canals occluded with scabs. 349 30 The puma is a keystone species in wild desert ecosystems, and it can serve as an umbrella species in conservation efforts. 361

Foreword

My involvement in New Mexico began in May 1984. Dr. Wain Evans of the New Mexico Department of Game and Fish asked if I would meet with the New Mexico wildlife governing body, the State Game Commission, to discuss puma research and management. The outcome of the meeting was an invitation to develop a research project that would provide knowledge to guide the state’s puma management program. I welcomed this opportunity for two reasons: First, I was eager to study this adaptable carnivore in an entirely different environment from that of my experience, spanning some twenty years, in the northern Rockies. Would there be similarities and would there be differences in the way pumas live in a relatively simplified desert environment? And what could we learn to help establish unifying principles for this species to aid in its conservation throughout its range? Secondly, this opportunity coincided with my founding of the Hornocker Wildlife Institute and the proposed puma research fit the nonprofit Institute’s mission statement: The Hornocker Wildlife Institute, Inc., was founded to stimulate curiosity about the natural world and its complexity; to provide a direct, straight-forward framework in which to satisfy that curiosity through observation and learning; to create an understanding of man’s place in the world’s fragile ecological structure and his responsibility to it. The Institute is designed to conduct intensive long-term research with special emphasis on threatened and endangered species and their wild environments; to train and develop superior post-graduate and graduate scientists; to make new knowledge available to the scientific community, to the agencies charged with managing wilderness and wild lands, and to the xxiii

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public. Research focuses on scholarly, creative efforts designed to make lasting contributions to our knowledge of the natural world. The project in New Mexico that we envisioned would become a flagship effort of the fledgling Institute. At the urging of Commission Chairman James Koch and members Thomas Arvas and David Salman, I worked with Dr. Wain Evans, Department Director Harold Olson, and others in developing the research. Over a period of several months, we traveled to different potential study sites in New Mexico, settling on White Sands Missile Range as the best area in which successful research could be conducted. Major General Niles Fulwyler, Commander at White Sands, agreed, and a Memorandum of Understanding was drafted. The result of these deliberations was a ten-year contract between the State of New Mexico and the Hornocker Wildlife Institute to conduct a comprehensive study of pumas in a desert environment. I already knew who I would approach to do the work. Ken Logan had invited me to visit his puma project in northern Wyoming in 1982. He was studying an exploited puma population for his master’s degree project at the University of Wyoming. I was impressed with his approach and dedication and had maintained contact with him over the years. He and Linda Sweanor, another dedicated wildlife researcher and student at the University, had worked together on bighorn sheep projects in northwestern Wyoming, and later married. They eagerly accepted the offer to work as a team on the New Mexico puma project. At the same time, I invited Frank Smith to join our team. Frank had thirty years of experience tracking and controlling pumas for the New Mexico Department of Game and Fish and was considered the most knowledgeable person in the region. I met this exceptional individual on my first trip to the field in New Mexico and was convinced he would be a major player in a successful effort. He agreed, and for seven years Frank contributed immeasurably to the project. This book is a result of the ten-year puma project and is testimony to the wisdom of long-term field study and observation. It fulfills, above and beyond, the original mission statement of the Hornocker Wildlife Institute and rightfully takes its place as a signature project. It is a tribute to the commitment and passionate dedication of its authors; it is a tribute to the vision of those New Mexico game commissioners who committed resources to long-term field research in a day and age when this is a rarity. Several years ago I wrote the following in the foreword of Ted Bailey’s book, The African Leopard, about our leopard research in South Africa:

Foreword

xxv

Because they are consummate predators, cats sit at the apex of the food chain. As such, they act as bellwethers of the condition of the environment—healthy populations of cats mean healthy populations of prey and a healthy environment. Yet one-third of the world’s species of cats are currently threatened, if not endangered. As the world’s human population grows and irreversibly alters many environments, we may lose some species of cats before we learn anything about them. Dedicated research like Dr. Bailey’s is essential for gaining the new knowledge that conservation efforts require. His work will become a landmark in guiding the conservation of leopards throughout much of their range. Those comments are appropriate here. Ken’s and Linda’s work, in the finest tradition of scholarly and rigorous scientific inquiry, has advanced our knowledge of pumas far beyond any previous work. The fact that this new knowledge can be utilized throughout this species range goes without saying. Their work truly will become a landmark in puma conservation. MAURICE HORNOCKER Senior Scientist Hornocker Wildlife Institute/ Wildlife Conservation Society

Acknowledgments

A dream came true for field ecologists like us, to study pumas for ten years in one of the most beautiful desert settings in North America. For that, we thank Dr. Maurice Hornocker. He was invited to New Mexico by the state Game and Fish Department and the State Game Commission to design the project and assume responsibility for its conduct. He hired us to do the work. Maurice was unflagging in his support for us, both in the triumphs and in the struggles of the research. We benefited immensely from his sage advice. At critical times when funding was unavailable, Maurice and his Hornocker Wildlife Institute (HWI) came through to continue our financial support. This project simply would not have happened without him. In addition, he served as the major advisor for both of our graduate programs at the University of Idaho. Ecological studies of this magnitude, intensity, and difficulty require a dedicated corps of researchers. We are forever grateful to the ones that worked with us. J. Frank Smith, former Conservation Officer and Depredation Animal Control Officer for the New Mexico Department of Game and Fish and self-made naturalist, was our cohort for seven years. Even with his thirty-plus years’ experience in tracking pumas, he was always yearning to learn more. His extensive experience was especially important in giving the project a jump start in the beginning. Brian Spreadbury hailed from British Columbia, Canada, where he studied pumas for his master’s degree project; he worked with us three years. Brian’s considerable experience in the bush enabled him to accomplish all that we asked of him with ease and to the highest standards. His training in search and rescue made us considerably more comfortable when we went on remote forays to find pumas. If disaster struck, we knew Brian would do everything possible to get us out alive. After his work on our project, he returned to British Columbia, found employment as a wildlife biologist with a coal mining company for a while, then became a park warden for Parks Canada. Toni Ruth was finishing up her master’s degree project on puma–human interactions in Big xxvii

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Bend National Park, Texas, when we hired her to study the pumas we translocated to northern New Mexico. Later, she came to our southern New Mexico study area to assist us. In all, Toni spent three years on our project, then transferred to another HWI study of puma-wolf interactions in and around Glacier National Park, Montana, for her Ph.D. studies. Later, she went on to study puma-wolf relationships in Yellowstone National Park. Jennifer Cashman came from Arizona, where she had studied desert mule deer water requirements and puma diet in the Sonora Desert. She worked with us the last three years of the project and later worked on HWI’s black bear research in New Mexico. Jeff Augustine, a Wisconsinan, had studied beavers and coyotes but endeavored to study the big cats. On our project, Jeff always came through with his enthusiasm and careful field work. At our camps, we could always count on him to strike up enjoyable, probing discussions on evolution, ecology, and conservation. Jeff worked the last two years of our project, then went to Siberia to study Amur leopards for HWI. Patricia Sweanor worked with us only a few months, yet we benefited from the perspectives on large-mammal ecology she developed while studying moose in Sweden. She left for Colorado and assisted the National Park Service in the restoration of bighorn sheep in western U.S. parks. These people never shirked the primitive living conditions in the desert; in fact, they thrived there, performing yeoman’s services to accomplish our research objectives. Many of the observations upon which this book is based are due to their efforts. Experiences we shared with these people will forever be etched in our memories. Back at Hornocker Wildlife Institute headquarters at the University of Idaho, people were toiling away, tending to the fusillade of paperwork that attended the project’s multi-agency agreement. We thank Dr. Howard Quigley, Molly Parrish, and Linda Harris for their attentiveness to our needs. Howard became the Institute’s president during the last two years of the field research and thereafter made sure that we were supported financially so we could write this book. We will always be grateful for his faith in us and his constant patience. We also thank Sandra Martin for securing the funds that sustained us. We thank our pilots Bob Pavelka, Ed Pavelka, and Carl Hendrickson of Ed’s Flying Service (Alamogordo, New Mexico). They were the ultimate professionals, always providing us meticulously maintained aircraft and safe flying as we tracked radio-collared animals. The New Mexico Department of Game and Fish financed the field research, initial data analysis, and development of New Mexico’s puma management plan mostly with funds provided by the Federal Aid in Wildlife Restoration Act and New Mexico’s Share With Wildlife tax checkoff program. Dr. Wain Evans and Wally Haussamen were particularly helpful in coordinating our field work with

Acknowledgments

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Department operations. Amy Fisher, Darrel Weybright, and Doug Humphreys planned and executed the capture operations and aerial surveys of desert mule deer and desert bighorn sheep, making it possible for us to gather detailed information on the relationships of pumas to deer and sheep. Larry Temple facilitated the translocation of pumas from our southern study area to northern New Mexico and helped radio-track those cats. These long-term studies are dependent on leadership and foresight of individuals within agencies who understand the need to keep them going even in the face of political opposition. For that crucial support, we are grateful to Wain and directors Harold Olson, William Montoya, Jerry Maracchini, and state game commissioners James Koch, Dr. Thomas Arvas, and David Salman. We especially appreciate the leadership of Jimmy Gonzalez, who personally saw to it that our research findings were taken to the public of New Mexico, Department employees, and other wildlife professionals. In addition, he had us directly involved in the development of New Mexico’s puma management plan. The U.S. Army, White Sands Missile Range, hosted our project. Major General Niles Fulwyler made it possible for us to conduct the research on the missile range. His support was a natural outgrowth of his personal interests in biology, paleontology, archeology, and geology. Daisan Taylor, Patrick Morrow, and Dave Holderman were missile range wildlife biologists who dutifully assisted us by ushering the obligate reams of paperwork through the daunting army bureaucracy, thus “breaking trail” for us to work in the field. Dave’s keen interest in applying scientific information to wildlife management was especially encouraging; later he was key to the incorporation of our information in wildlife management on the missile range. Military police game wardens—and Sergeant Artemis Hogan in particular—were tireless in keeping poachers off White Sands Missile Range. We are especially grateful to John Collins, Edwin Erickson, and Daniel Ansbach III for scheduling our research activities as missile-range missions, thus eliminating conflicts and keeping us out of harm’s way. We were proud of the mission code “Alpha-Alpha” that they assigned to us for being “out there all of the time.” The U.S. Fish and Wildlife Service aided our project on two fronts. San Andres National Wildlife Refuge personnel Patty Hoban, Mara Weisenberger, Gary Montoya, and Steve Berendzen provided us with critical information on desert bighorn sheep and allowed us to use camps on the refuge. Patty, Mara, and Steve helped us capture some puma cubs. And Mara provided us with some detailed observations of pumas. Federal aid coordinators Dave Parsons and Laurel Wiley administered this project in accordance with the Federal Aid in Wildlife Restoration Act. We rarely got to see some vital people with whom we interacted daily dur-

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ing the field work. They were the two-way radio station operators in Santa Fe, Las Cruces, and Raton who relayed our messages back and forth. Thank you for helping us to keep people and animals safe and to efficiently coordinate field activities. We also thank the Jornada Experimental Range and the National Aeronautics and Space Administration, White Sands Test Facility for access to their areas adjacent to White Sands Missile Range. We are extremely grateful to veterinarians Maury Brown, Frank Coons, Michael Richards, and Brett Snyder for their unselfish professionalism. They operated on puma F147’s fractured leg and rehabilitated her, making it possible for her to return to the wild and successfully raise cubs. We also thank the Rio Grande Zoological Park in Albuquerque for providing the place to rehabilitate F147. A special thanks goes to all those carnivore researchers and conservationists in North America who wrote the commander of White Sands Missile Range in support of our research when it was reviewed at the halfway point to decide on continuation or termination. Your letters were helpful. In addition, several wildlife managers and puma researchers shared their valuable opinions with us about what was needed to further puma conservation. We especially benefited from the feedback of Nick Smith, Jimmy Gonzalez, Charles Hayes, and Bill Dunn of the New Mexico Department of Game and Fish; Tom Beck of the Colorado Division of Wildlife; John Beecham of Idaho Department of Fish and Game; Rich DeSimone of the Montana Department of Fish, Wildlife and Parks; Steve Torres and Vern Bleich of the California Department of Fish and Game; Jimmy Rutledge of the Texas Parks and Wildlife Department; and Kerry Murphy of the National Park Service, Yellowstone National Park. Many people in northern New Mexico were essential to the success of the puma translocation portion of this project. We acknowledge the support from the communities and surrounding areas of Raton, Cimarron, Ute Park, Eagle Nest, Angel Fire, and Folsom. We are particularly thankful for the cooperation from Vermejo Park Ranch, the C.S. Cattle Company, and the National Rifle Association Whittington Center. Appreciation for access to private land is extended to the Hennigan Ranch, Chase Ranch, Philmont Scout Ranch, and Sauble Circle Dot Ranch. We are grateful to the late Rick Poe, our pilot, who flew us all around northern New Mexico to find the wayward radio-collared pumas. Scientific reviewers of draft manuscripts provided invaluable recommendations that improved this book. We are grateful to Doctors Maurice Hornocker, Howard Quigley, Earnest Ables, Edward Garton, James Peek, Arthur Rourke (all from the University of Idaho), Walter Boyce (University of California,

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Davis), Paul Krausman (University of Arizona), Brian Miller (Denver Zoological Foundation), and Wain Evans (New Mexico Department of Game and Fish, retired). Some of the University of Idaho professors were also members of our graduate programs and contributed immensely to our education. Special thanks are extended to Tim and Karen Hixon, Summerlee Foundation, McCune Charitable Trust, Richard King Mellon Foundation, Pond Foundation, Thaw Foundation, Harry Bettis and Laura Moore Cunningham Foundation, and Larry Westbrook for providing funding for the writing of this book. We are very grateful to our editors at Island Press, particularly Barbara Dean, Barbara Youngblood, Cecilia González, and Erin Johnson for improving the manuscript and for guiding the book to completion. For us, this project was an expedition, not only into a region of the Chihuahua Desert that was little known, but also into our own physical, intellectual, and emotional limits. Ten years is a long time to maintain peak intensity in laborious field research. But the place and the life kept us always looking and stepping forward. Without a doubt, our deepest satisfaction was in trying to figure out why life works the way it does on a piece of Earth, the San Andres Mountains. Every canyon, ridge, and mountain peak became familiar to us. It was inevitable. Daily, we searched for or followed pumas wherever they might go, which was everywhere in those desert mountains. A clandestine helicopter crew could have blindfolded us and plunked us down alone in some secluded spot in the middle of night, but by daybreak, or even before, we would have known where we were. The rigors and pleasures of the land, its seasons, and the animals defined our way of life. We will always regard the San Andres Mountains as “our home.” The San Andres Mountain range is unique in that it is the largest single block of ecologically intact Chihuahua Desert mountains remaining in North America. This vibrant ecosystem deserves concerted attention by the agencies responsible for its land and resources, and a caring public, to ensure that its natural values are preserved. It is our hope that scientific information contained in this book will promote that effort. Finally, to the pumas, thank you for the wonder. We hope our work will help people to understand you and to contribute to your endurance. —KENNETH A. LOGAN and LINDA L. SWEANOR

P a rt I

Setting the Stage

Chapter 1

Introduction

C a r n i vo res stir within us a primitive curiosity. We have been honing our senses to these flesh-eaters ever since our human ancestors re a l i zed that they could be killed and eaten by such beasts. This curiosity has gradually developed into a highly sophisticated form we call science. Now, we delve into evolution, biology, and ecology to better understand carnivo res and our relationships to them. C a r n i vo res profoundly impact animals and ecosystems. T h rough predation, they transfer matter and its associated energy into their own trophic level and d i ve rt some of what they do not consume to scavengers, detritivo res, and m i c roorganisms (Ricklefs 1990). W h e re carnivo res are the highest-level consumers and closely linked with the dominant herbivo res, they can alter production in plant communities (Mc L a ren and Peterson 1994). Carnivo res can impact the dynamics of prey populations by limiting (Be r g e rud et al. 1983, Messier 1991, Gasaway et al. 1992) or regulating (Messier 1995) their numbers, and they are a major factor contributing to cyclic pre d a t o r - p rey systems ( K rebs et al. 1995). Carnivo res partially shaped the evolution of prey by the selection for morphological, physiological, and behavioral variations that enhance surv i val. For example, cervids have acute senses for predator detection and slender elongate limbs powe red by large proximal muscle groups for rapid escape (Putman 1988). In addition, prey evo l ved fitness-enhancing antipre d ator strategies, such as social grouping (Berger 1978), vigilance (Hunter and Skinner 1998), crypsis (Caro and Fitzgibbon 1992), specialized locomotion ( C a ro 1986, Geist 1998), avoidance (Mech 1977b), migration (Be r g e rud and Page 1987), and birth synchrony (Rutberg 1987). Interspecific competition 3

4

PART I. SETTING THE STAGE

among carnivo res can affect behavioral patterns, influence re s o u rce part i t i o ning, and may have been an evo l u t i o n a ry force contributing to assemblages of c a r n i vo res in rich environments (Schaller 1972, Mills 1990, Caro 1994, Durant 1998). Carnivores influenced human evolution. Carnivory by humans may have had its humble beginnings when ancestral hominids scavenged the kills of carnivores (Blumenschine 1991). This new, rich food source enabled hominids to stride out from the African tropics into temperate habitats and beyond. Living among big carnivores surely induced strong selective forces for beings that could outwit such dangerous competitors and predators. And the high-quality, easyto-digest carnivorous diet was essential for the development of a much more complex neural system (Aiello and Wheeler 1995). Humans may partly owe the evolution of our large encephalized brain and extreme abilities for reason and cunning to large carnivores (Wilson 1980:133–137). Modern humans are still influenced by carnivores. Carnivores kill and eat our livestock, pets, and wild prey, and they sometimes physically threaten, or even kill and eat, humans. Yet their form, intelligence, and beauty are aweinspiring and are perhaps even the nascence for domestication of their gentler forms. They are our companions, and, in special cases, we depend on them to aid us in disability, search and rescue, and law enforcement. Felids, in particular, may provide us healthier lives. Because felid genome organization is similar to that of humans (Nash and O’Brien 1982, Rettenberger et al. 1995, Wienberg et al. 1997), cats, wild and domestic, are being used in coordination with the Human Genome Project to study genetic links to hereditary defects and diseases that afflict both cats and humans (O’Brien 1997). Scientific knowledge and personal experience have cultivated human appreciation for the beauty and ecological role of carnivores. Hence, we have deemed it necessary to conserve them and even to make them the focus of complex, landscape-scale conservation strategies (Hummel et al. 1991, Noss et al. 1996, Weber and Rabinowitz 1996). For some of the most endangered carnivores, conservation efforts have extended beyond the people that live on the land with the animals to include national and international governments and nature conservation organizations (see Schaller 1993, Seidensticker 1997). As the human population burgeons and uses up more space and resources, we need to know more about carnivores and how we influence their populations and habitats if we want them as members of Earth’s biota. This book on the puma (Puma con color) is our attempt to convey a scientific understanding of this magnificent carnivore and to present ways in which enlightened humans can continue to coexist with the puma.

CHAPTER 1. INTRODUCTION

5

Rationale and Approach This puma research originated from a contract secured by Dr. Maurice Hornocker with the New Mexico Department of Game and Fish in 1985, following several months of consultation and project development between Dr. Hornocker and Department personnel. At that time, the Department and its governing body, the State Game Commission, requested basic biological and ecological information that wildlife managers could use to develop management strategies for pumas and their prey. Hence, our research was mission-oriented, taking the form of applied ecology. This was the first intensive, long-term investigation of pumas living in a desert; therefore, much of our work describes in detail the natural history of pumas in that environment. Moreover, we tested hypotheses on pumas and other mammals previously posed in the scientific literature. And as patterns emerged from our data, we developed other hypotheses. In some instances, we offer measured speculation for natural phenomena we observed but for which we could not gather quantitative data; our hope is that scientists may be able to build on these ideas. The goal of New Mexico wildlife managers was to use scientific information to develop management and conservation strategies on pumas to address concerns of their most politically influential constituents. Their operational purpose was to manage for a self-perpetuating puma population while dealing with interrelated issues, including maximizing opportunities for recreational puma hunting; minimizing competition between hunters and pumas for big game animals, especially mule deer; minimizing puma predation on desert bighorn sheep, a state-listed endangered species; and minimizing puma predation on livestock. In consideration of the wildlife managers’ needs, we developed three main research objectives: (1) to describe and quantify puma population dynamics, (2) to describe and quantify puma social organization, and (3) to describe and quantify the relationships of pumas to their prey, specifically desert mule deer (Odocoileus hemionus crooki) and desert bighorn sheep (Ovis canadensis mexi cana). Understanding puma population dynamics and life history strategies is essential to developing scientific approaches to puma management and conservation. It is also the first step in testing hypotheses about puma social organization and effects of puma predation on prey. Social organization is important to investigate because it may limit the population (Seidensticker et al. 1973), and it influences sex ratios, reproduction, mortality, dispersal, recruitment, genetic makeup, and gene flow. Studying relationships of pumas to their prey is critical to understanding how puma predation affects prey populations and how prey affect puma populations.

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PART I. SETTING THE STAGE

When we started this project, we made a significant long-term commitment. Our experience with pumas taught us that their low population densities, cryptic lifestyle, and use of complex habitats would make them extremely difficult and challenging to study. We anticipated that it would take at least two years of the project simply to develop an intensive population-monitoring routine to reliably quantify puma population characteristics and behavior in our large desert study area. In addition, evaluating effects of puma predation and other limiting factors on mule deer and bighorn sheep population fluctuations would require several years. Also, we wanted to experimentally reduce puma density on the study area to test hypotheses relevant to puma population dynamics, social organization, and puma-prey interactions. This required an intensive study of puma and prey population dynamics before puma removal, a subsequent removal of pumas at a rate high enough to cause a substantial population reduction (i.e., more than 50 percent of adult pumas), and, finally, a comprehensive study of the dynamics after the removal. In our estimation, we could accomplish the research goal and objectives in a minimum of ten years. Our work became the first long-term research of pumas in a desert environment. In the process, we studied the largest number of individual pumas ever in an ecological project. As we studied the pumas, we constantly asked ourselves, “Why do pumas live and behave the way they do?” This simple question characterized our second and not-so-simple goal, which was to explain the evolutionary ecology of pumas. Evolutionary ecology integrates all that we understand about puma paleontology, evolution, genetics, biology, and ecology. It is a synthesis that helps us to comprehend where pumas came from, how they adapted to environments, how they affect the environment, and what impacts humans may have on them. Evolution—with natural selection its key mechanism for change—is so far the best scientific explanation for life on Earth (Trivers 1985, Stearns 1992, Mayr 1996, Freeman and Herron 1998). Thus, we made it the central theme of this book. We hope to render a more complete concept of this beast, something akin to a photographer metering the light, composing the scene, and turning the camera lens to snap into sharper focus an image that grasps the essence of the subject.

Synopsis of Previous Studies Although pumas have been subjects of numerous short-term studies, there have been few intensive, continuous investigations of eight or more years, which would approach the natural life span of this carnivore in the wild. The first of these was the classic puma research by Maurice Hornocker and colleagues in the River of No Return Wilderness in central Idaho from 1964 to 1972 (Hornocker

CHAPTER 1. INTRODUCTION

7

1969, Hornocker 1970, Seidensticker et al. 1973). The first five years of research involved intensive capture, marking, and recapture techniques to quantify the puma population, and ground and aerial surveys of deer and elk to assess the impact of puma predation on those species. Not until the subsequent three-year companion study by Seidensticker et al. (1973) were the biologists able to employ the new technology of radiotelemetry to describe puma social organization. They also developed the basic techniques that would thereafter be used in all subsequent field studies of puma population dynamics, behavior, and habitat use. More importantly, they developed original biological concepts about pumas. Hornocker (1969:462, 464) described a type of nonaggressive territoriality in pumas maintained through a “mutual avoidance reaction” and concluded that the primary function of such behavior was to “limit population size.” The biologists developed that idea further into the only published hypothesis on the evolution of puma social organization. They postulated that the social organization evolved to limit the density of breeding pumas to a level below that set by their prey (Seidensticker et al. 1973). This was one of the hypotheses we tested relative to the way pumas lived in our desert study area. In Nevada, Dave Ashman and colleagues with the Nevada Department of Wildlife studied pumas from 1972 to 1982 in eleven mountain ranges in the northeast and central parts of the state. The bulk of their work was done in the Ruby Mountains and the Monitor Range. They focused on puma population dynamics, movements, and predation (Ashman et al. 1983). From 1978 to 1989, a group of graduate students assembled by Fred Lindzey studied a puma population in the Boulder-Escalante area of south-central Utah. They investigated a diverse range of topics, including puma population dynamics, energetics, predation, habitat selection, effects of sport-hunting, and survey methods (Lindzey et al. 1989). Allen Anderson studied pumas on the Uncompahgre Plateau in southwestern Colorado from 1981 to 1988. Although his main focus was puma population biology, he also provided information on puma movement patterns, intraspecific interactions, morphological and physiological characteristics, and predation (Anderson et al. 1992). Martin Jalkotzy and Ian Ross studied puma population dynamics from 1981 to 1989 along the eastern slope of the Rocky Mountains in southwestern Alberta (Ross and Jalkotzy 1992). They later provided information on puma predation (Ross and Jalkotzy 1996, Ross et al. 1997). Kerry Murphy studied the ecology of pumas in the Northern Yellowstone Ecosystem from 1987 to 1996. He collaborated with a host of other biologists and geneticists to investigate puma-prey relationships, competition between pumas and bears, and puma reproductive success (Murphy 1998). The longest study is that of the endangered Florida panther, which has been investigated since 1981. Interagency and interdisciplinary teams of researchers have

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PART I. SETTING THE STAGE

looked into practically every aspect of the remnant population of this feline, including population and social biology, predation, habitat selection, diseases, and genetics (Belden 1982, Belden et al. 1988, Maehr et al. 1989, O’Brien et al. 1990, Roelke et al. 1993a, Roelke et al. 1993b, Maehr and Cox 1995). The number of individual pumas studied in these investigations ranged from fortyseven in Colorado (Anderson et al. 1992) to about a hundred in Nevada (Ashman et al. 1983) and Utah (Lindzey et al. 1989). By comparison, we studied 294–295 individual pumas in ten years. Along with our own work, we treated all these studies, and many of the short-term studies, as independent sources of data on pumas because they were done in different conditions, including climate (e.g., temperate, desert, tropical), habitat (e.g., continuous, fragmented, isolated), prey diversity and density (e.g., high, low), and selective pressures (e.g., hunted, nonhunted, other carnivorous competitors, lack of competitors). This allowed us to contrast our findings—on puma population characteristics, life history strategies, behavior, social organization, and relationships of pumas to their prey—with pumas in other environments. This book tells our story of puma research in twenty-one chapters apportioned among five parts. Part 1 sets the stage for the research and includes background information on development of the project, puma phylogeny, taxonomy, and description. We also describe our study area and how we studied pumas. Part 2 covers puma life history strategies and population dynamics. Part 3 describes puma behavior and social organization. Part 4 analyzes relationships of pumas to their prey, particularly desert mule deer and desert bighorn sheep. Part 5 presents our ideas for conserving and managing pumas in the wild. Four appendices cover puma morphometrics, reproductive chronology, home range estimation, and mule deer population dynamics.

Chapter 2

Pumas Past and Present

Puma Phylogeny Paleontologists use fossils to construct a phylogeny (i.e., evolutionary history) of carnivores, albeit, an incomplete one. The present record is that the Carnivora evolved from the basal family Miacidae (small, mostly arboreal carnivores) during the Eocene epoch (Vaughan 1997), about fifty million years ago. The most specialized carnivores of all, the true cats (family Felidae) apparently evolved in the Miocene about twenty million years ago. Their ancestors probably were of the genus Pseudaelurus, the most common felid in the early and middle Miocene, and were lynx-sized predators with arboreal and terrestrial stalk-andambush hunting modes (Werdelin 1996). In the middle Miocene, felids began their radiation into the great sabertooths (Machairodus, Homotherium, Megan tereon, Smilodon) and other cats with conical canines (Felis, Puma, Panthera, Metailurus, Miracinonyx, Acinonyx) that came to occupy the Pliocene and Pleistocene epochs about 5.3 million to twelve thousand years ago (Hunt 1996). Phylogenetic relationships for thirty-four of the thirty-seven species of extant felids, based on maternally inherited mitochondrial genes, have been arranged into eight major clades and four unaligned species (Johnson and O’Brien 1997, Pecon-Slattery and O’Brien 1998). Puma is the namesake for the clade that also includes the cheetah (Acinonyx jubatus) and jaguarundi (He r p a i l u rus yaguarondi); all members were thought to have originated in North America. Other groups are ocelot lineage (ocelot Leopardus pardalis, tigrina L. tigrinus, margay L. wiedii, pampas cat Oncifelis colocolo, Geoffroy’s cat O. geoffroyi), 9

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PART I. SETTING THE STAGE

domestic cat lineage (domestic cat Felis catus, jungle cat F. chaus, African wild cat F. libyca, sand cat F. margarita, black-footed cat F. nigripes, Chinese desert cat F. bieti, European wild cat F. silvestris), panthera group (lion Panthera leo, leopard P. pardus, tiger P. tigris, snow leopard P. uncia, jaguar P. onca, clouded leopard Neofelis nebulosa), lynx genus (bobcat Lynx rufus, Canadian lynx L. canaden sis, Siberian lynx L. lynx), Asian leopard cat group (Asian leopard cat Prionailurus bengalensis, flat-headed cat P. planiceps, fishing cat P. viverrinus), caracal group (caracal Caracal caracal, African golden cat Catopuma aurata), and bay cat group (Asian golden cat C. temminckii). Unaligned species include the serval (Leptailurus serval), rusty-spotted cat (Prionailurus rubiginosus), Pallas’ cat (Otocolobus manul), and marbled cat (Pardofelis marmorata). The puma group is considered to be the most ancestral, having diverged about 8.5 million years ago. By comparison, the other large cats in panthera group last shared a common ancestor about six million years ago (Johnson and O’Brien 1997, Pecon-Slattery and O’Brien 1998). Within the puma group, the cheetah diverged first from a common ancestor about five to eight million years ago; puma diverged from a common ancestor with the jaguarundi about four to five million years ago (Johnson and O’Brien 1997, Culver 1999). Extant puma lineages last shared a common ancestor about 0.39 million years ago (Culver et al. 2000). About the same time, Homo sapiens was emerging in Africa (Freeman and Herron 1998). An obscure puma fossil record has lead to a paleontology that is oblique to the phylogenetics of Puma concolor. Puma-like felids have been relatively common in North America since about the late Blancan land mammal age about 2.5 million years ago. Miracinonyx inexpectatus was a form intermediate to modern pumas and cheetahs, but larger, and may have been ancestral to Puma concolor (Kurtén 1976). A transition from one form to the other may have occurred during the Rancholabrean land mammal age when P. concolor became widespread in North America; the earliest fossil finds are from the Sangamonian interglacial about 0.2–0.3 million years ago (Kurtén and Anderson 1980). The puma was thought to be indigenous to North America (Adams 1979). In South America, P. concolor lacked probable ancestors and was thought to have immigrated from the north during the Ensenadan land mammal age about 0.5–0.8 million years ago (Webb 1976, Savage and Russell 1983). According to this scenario, the presumed Ensenadan appearance of P. concolor in South America predates the earliest fossils of the species found in North America. Van Valkenburgh et al. (1990) suggested that P. concolor may have evolved from an unknown species in the Neotropics because Puma has shorter limbs and larger head and teeth than M. inexpectatus, which are characteristics of a more primitive condition. Phylogeographic research (i.e., study of the phylogenetic relationships and

CHAPTER 2. PUMAS PAST AND PRESENT

11

geographic distributions of individuals in a species) on pumas across the Western Hemisphere by Culver and her colleagues (Culver 1999, Culver et al. 2000) suggest that pumas emerged in eastern South America and then dispersed to other parts of South America and eventually to North America. Culver (1999) found ancestral mitochondrial DNA haplotypes (mtDNA is maternally inherited; a haplotype is a set of alleles from closely linked loci carried by an individual and usually inherited as a unit) exclusively in extant pumas from Brazil and Paraguay south of the Amazon River. Patterns of genetic variation in mitochondrial and microsatellite markers (microsatellites are nuclear DNA sequences inherited from both parents and comprising variable numbers of tandemly repeated bases, usually five to forty, for example, CACACACACA) supported their contention that eastern South America was the site of origin. Pumas in eastern South America (i.e., the central population) had the highest genetic variation, while pumas in North America and southern South America (i.e., peripheral populations) had the lowest variation. This sequence of evolution and migration and Culver’s estimated coalescence time of 0.39 million years for puma mitochondrial DNA haplotypes resolves the estimated dates for the appearance of P. concolor in South America and the earliest puma fossils in North America. Culver (1999) points out that a puma ancestor still may have descended from the North American M. inexpectatus, dispersed to South America, and then speciated into the modern puma, or that the puma descended from a yet-unknown South American ancestor (also see Van Valkenburgh et al. 1990). Puma ancestors might have entered South America from North America in the midst of the “Great American Interchange” during the Uquian land mammal age about 1.5–3 million years ago (Marshall et al. 1982). A small founder population crossing an isthmus of variable integrity, the presence of other geographic barriers in South America (e.g., broad river systems, high rugged mountain ranges), behavioral shifts in response to novel environments and competitors, and concomitant extinctions of indigenous species would have provided a constellation of conditions ripe for evolution. For the North American puma, Culver’s research tells a story of mass extinction, then recolonization. Based on the low variance in the number of microsatellite repeats, the presence of only one mitochondrial haplotype (relative to other phylogeographic puma groups), and a molecular clock based on microsatellite allele variance, the North American puma population probably experienced a founder event about ten thousand to twelve thousand years ago. Culver and colleagues (2000) believe that the puma that inhabited North America (up to about 0.3 million years ago) went extinct along with the many other large mammals during the late Pleistocene (see below). The geneticists conclude, “Most likely modern North American pumas descended from a founder event

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PART I. SETTING THE STAGE

involving a small number of individuals who migrated ‘out of South America’ approximately 10,000–12,000 years before the present and subsequent to the abrupt Pleistocene extinction of large North American mammal species” (Culver et al. 2000:196). While pumas were living in Pleistocene North America, the large mammal fauna was far richer than in the Holocene epoch. Mammals were huge compared to their modern relatives. This was likely because the environments they lived in were highly productive, and large-bodied animals had survival, and hence selective, advantages in a perilous world of large carnivores. Diversity of the herbivore fauna was similar to that of Africa’s Pleistocene and modern fauna (Stuart 1991, Burney 1993, Van Valkenburgh and Hertel 1993). Four glaciations, three intervening interglacials (Kurtén and Anderson 1980), and attendant habitat and animal dynamics provided selective forces for evolution of this assemblage. In addition, Eurasian mammals immigrated across the Bering Bridge (Kurtén and Anderson 1980). In late Pleistocene North America, there were fifty-six herbivore species larger than 30 kg, including twenty-nine that exceeded 300 kg. Moreover, a rich carnivore assemblage, including fifteen species coyote-sized or larger, preyed or scavenged on the herbivores. Today by comparison, there are only eleven herbivores larger than 30 kg, three herbivores larger than 300 kg, and seven carnivore species equal to or larger than the coyote (Van Valkenburg and Hertel 1993). Stratigraphic ranges for Pleistocene mammals in North America constructed by Kurtén and Anderson (1980) display the array of large herbivores that pumas may have preyed upon and carnivores with which they may have competed. There were two species of capybaras (Hydrochoerus, Neochoerus), perhaps as many as thirteen species of horses, onagers, and asses (Equus), three species of tapirs (Tapirus), two species of peccaries (Mylohyus, Platygonus), seven species of camels (Camelops, Hemiauchenia), seven species of deer (Odocoileus, Navaho c e ros, Sangamona, Alces, Cervalces, Cerv u s), nine species of pronghorns (Capromeryx, Tetrameryx, Stockoceros, Antilocapra), and three species of mountain goats and mountain sheep (Oreamnos, Ovis). There were other mammals that were simply too enormous for pumas to kill, including giant ground sloths (Eremotherium, Nothrotheriops, Glossotherium), two species of bison (Bison), a mastodont (Mammut), and mammoths (Mammuthus). A diverse carnivore fauna, acting as predator and scavenger, was supported by the herbivores. There were five species of bears, including the cave bear (Tremarctos floridanus), lesser short-faced bear (Arctodus pristinus), giant shortfaced bear (A. simus), grizzly (Ursus arctos), and black bear (U. americanus). Besides the puma there were five other species of large cats, including the sabertooth (Smilodon fatalis), scimitar cat (Homotherium serum), lion (Panthera leo

CHAPTER 2. PUMAS PAST AND PRESENT

13

atrox), jaguar (P. onca), and cheetah (M. trumani). Among the canids, there were the timber wolf (Canis lupus), red wolf (C. rufus), dire wolf (C. dirus), coyote (C. latrans), and dhole (Cuon alpinus). The selective pressures imposed by this wide range of prey and competitors no doubt helped to shape the evolution of the puma. Excavations at four sites in southern New Mexico (i.e., Burnet Cave and Dry Cave in Eddy County, Blackwater Draw in Lea County, U-Bar Cave in Hidalgo County) indicate that the region supported some of these beasts in the late Pleistocene (Harris 1987). Large herbivores and carnivores identified in those deposits included Shasta ground sloth (Nothrotheriops shastensis), tapir, five species of horses, peccary (Platygonus), three species of camels (Camelops, Hemi auchenia), two species of deer (Odocoileus, Navahoceros), three species of pronghorns (Antilocapra, Stockoceros, Tetrameryx), bison, and possibly Harrington’s mountain goat (Oreamnos harringtoni). Carnivores found at the caves were the coyote, gray wolf, dire wolf, giant short-faced bear, sabertooth, jaguar, and puma. This diversity of large mammals in North America came to a relatively abrupt end in a wave of extinctions during the late Pleistocene about 11,500–10,500 years ago (Stuart 1991). Mass extinctions were concurrently occurring in South America; in fact, no other continent lost as many animals (Burney 1993). Although the exact causes of the extinctions are not clear, some hypotheses have been forwarded to explain them. Severe environmental changes brought by a shifting climate at the end of the last ice age with attendant transformations of vegetation, redistribution of fauna, and new competitive relationships may have triggered extinctions among nonadaptive species. Another hypothesis suggests paleolithic hunters who came to North America from Eurasia about twelve thousand years ago via the Bering Bridge and were south of the ice sheets by about 11,500 years ago overkilled the large and conspicuous slowbreeding mammals not adapted to this novel predator. These technologically advanced humans effectively used sharp, stone-tipped spears to kill large mammals, even mammoths. It may be more likely that combined effects of environmental shifts and overkill by humans caused extinctions. Large herbivore distributions and population numbers may have been reduced initially by disruptive environmental transition and habitat loss, making the herbivores vulnerable to overkill by an increasing population of paleolithic hunters. As the large herbivores disappeared, so did many of their specialist predators (Kurtén and Anderson 1980, Stuart 1991). Still another, the “keystone herbivore hypothesis” (Owen-Smith 1987, 1989), suggests that paleolithic hunters eliminated the megaherbivores (species with adult mass greater than 1,000 kg) that were essential to maintaining a diverse habitat mosaic, thus promoting a diverse, large-her-

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PART I. SETTING THE STAGE

bivore fauna. In the absence of megaherbivores, grasslands turned to woodlands, triggering a decline in open-country herbivores, and, we would suggest, making others more vulnerable to predation. Time lags between the decline of herbivores and the decline of their predators may have triggered inversely densitydependent predation and further hastened the decline of herbivores. As large herbivores disappeared, so did their predators. All of the sabertooth cats went extinct, and most conical-toothed cats suffered restrictions in their ranges (Martin 1980). Pumas, it seems, were victims too. Regardless of their point of origin, pumas thrived after catastrophic late Pleistocene extinctions, an expected result for such a eurytopic species (Erwin 1998). Because of their moderate size and ability to sustain themselves on a wide range of prey in various habitats, they had advantages over specialist carnivores. As other large carnivores went extinct, interspecific competition would have declined. Moreover, pumas were adapted to dense woodlands and rugged terrain where other post-Pleistocene herbivores also thrived, perhaps because they were less conspicuous to human hunters. In addition, because of their smaller size, they would be expected to mature faster, have greater fecundity, and, hence, have greater intrinsic rates of increase than the doomed megaherbivores (Eisenberg 1981, Read and Harvey 1989). Post-Pleistocene North America that lay before the puma had a relatively impoverished large-mammal fauna. Ecosystems in the Southwest, in particular, would become much simpler. In the Chihuahua Desert, the puma’s large-mammal prey would be composed only of desert mule deer, white-tailed deer (Odocoileus virginianus), collared peccaries (Pecari tajacu), and desert bighorn sheep. Competitors with which pumas would have to contend were still formidable but reduced in diversity to gray wolves, coyotes, jaguars, and on occasion grizzly bears and black bears. Mule deer and desert bighorn sheep benefited from the low diversity in the mammal fauna following the extinctions. Mule deer emerged as a new form about nine thousand to eleven thousand years ago, presumably the result of i n t e r b reeding of white-tailed does and black-tailed bucks (Geist 1998). Bighorn sheep dispersing from the north became established in what is now the northern Chihuahua De s e rt about thirteen thousand to fifteen thousand ye a r s ago; they began showing characteristics of the modern desert bighorn sheep b e t ween eight thousand and eleven thousand years ago (Geist 1985). Comp a red to the relationships that must have evo l ved between the Pleistocene puma and its prey during hundreds of thousands, if not millions, of years of c o e volution, the Holocene relationships of pumas with their prey in the So u t hwest are re l a t i vely young. Neve rtheless, for the past eight thousand to eleve n thousand years, the finely tuned mountain pre d a t o r, the puma, would provide

CHAPTER 2. PUMAS PAST AND PRESENT

15

a strong selective force to which mule deer and desert bighorn sheep would need to adapt to surv i ve .

Puma Distribution and Status Historically, pumas have had the broadest geographic distribution of any terrestrial mammal in the Western Hemisphere, except for humans. Pumas ranged from northern British Columbia to Patagonia and from the Atlantic to the Pacific coasts (Young 1946). The huge geographic range of the puma is testimony to its extraordinary adaptability. Pumas have occupied practically every type of biogeographic zone, including boreal foothills, temperate mountains and forests, tropical rainforests, grasslands, and deserts (Young 1946; Ian Ross, personal communication) along an elevation gradient ranging from sea level to 3,350 m in North America, and to 4,500 m in South America (Nowak 1991). However, European immigrants to the Americas since the 1500s brought predator control and habitat loss. Settlements, agriculture, and industry transformed habitats, making them unsuitable for pumas. Many prey species were extirpated. Pumas were killed outright mainly to protect livestock and game animals and to allay human fears. Basically, pumas were considered to be “bad animals.” By the late 1800s in North America, eastern puma populations were extinct or severely reduced, and by the early 1900s, western populations were diminished (Nowak 1976). For pumas in North America, this meant a contraction to about one-half of their modern geographic range (Logan and Sweanor 2000). Legal protection for pumas in North America has been quite recent. Since 1965, regulations on killing pumas by all of the western United States (except for Texas) and provinces of Canada have enabled populations to recover from historical low levels. In a survey we conducted in 1997 on puma population status in fourteen western states and two western Canadian provinces (Logan and Sweanor 2000), 62 percent reported increasing or stable trends, 25 percent reported declining or stable trends, and 13 percent did not know the trend in their puma populations. Passage of the Endangered Species Act in 1973 gave pumas in eastern United States full protection and may have prevented the extinction of the Florida panther subspecies (P. concolor coryi). Even in recent years, pumas have been sighted in several other eastern states and provinces, but very rarely have those reports been authenticated. In addition, it is not known whether those individuals were escaped captive animals or wild. Status of the puma across its range in Central and South America is sketchy. It appears that pumas still occupy almost all of their historical range except for the densely human-inhabited areas and landscapes altered for agriculture and

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PART I. SETTING THE STAGE

livestock. Puma abundance has been reduced in eastern Brazil and northeastern Argentina (Nowell and Jackson 1996). Lopez-Gonzalez (1999) reported that puma hunting was prohibited throughout South America, except in Peru, and that the species had legal protection in Central America, except in El Salvador, where the puma was nearly extinct.

Pumas in the Southwest As European humans immigrated to the Southwest beginning in the late 1500s, and with an accelerating rate of immigration during the late 1800s and early 1900s, the large carnivore fauna in the desert was depleted. Humans organized extermination campaigns sanctioned by state and federal governments with the intent to protect livestock and big-game animals. Carnivores were killed by any means possible, including shooting, trapping, and poisoning (Brown 1984, 1985). Wolves were extirpated from the Southwest by about 1925 (Brown 1984), followed by jaguars in about 1930 (Findley et al. 1975, Hoffmeister 1986), and grizzly bears in about 1935 (Brown 1985). Pumas survived this onslaught probably because of their solitary, highly cryptic nature and their propensity to inhabit the most rugged terrain, but even so, puma populations declined. In New Mexico, puma numbers were severely reduced. Puma killing was encouraged statewide with a bounty that lasted from 1867 until 1923 (New Mexico Department of Game and Fish Operational Plan, 1987–1995, Nowak 1976). Young (1946:28) reported that the puma in New Mexico “of late years, due to intensified hunting, is not as common as it was at the beginning of the present century. The animal may now be said to be confined mainly to the rougher mountainous sections west of the Rio Grande.” Not until 1971, when the legal status of the puma was changed to effectively curb human-caused mortality, did the species have the opportunity to increase and recolonize historical habitat. Today, there are pumas inhabiting most habitats in New Mexico.

Taxonomy The puma belongs to the order Carnivora, suborder Feliformia (i.e., the felids, herpestids, hyaenids, viverrids), family Felidae, subfamily Felinae (which also includes small cats of the genera Caracal, Catopuma, Felis, Herpailurus, Leopar dus, Leptailurus, Lynx, Oncifelis, Oreailurus, Otocolobus, Prionailurus, Profelis) (Wozencraft 1993). Linneaus originally named the puma Felis concolor in 1771, but Jardine renamed the genus Puma in 1834 (Wozencraft 1993). Nowak (1991) presented three taxonomic arrangements for the thirty-seven species in

CHAPTER 2. PUMAS PAST AND PRESENT

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the Felidae family from three authors (Ewer 1973, Hemmer 1978, Leyhausen 1979) and also from one of his own, which was a composite from a variety of sources. Each arrangement had a varying number of genera. The puma was placed in the genera Profelis and Felis once each, and in Puma twice. Nowak’s arrangement included twenty-nine species in the genus Felis of which the puma was the largest cat. More recently, Wozencraft (1993) upgraded many of the subgenera within Felis to full generic status and placed the puma back in the monotypic genus Puma in support of Jardine’s 1834 recognition of the unique evolution of the species (Nowell and Jackson 1996). Goldman, in 1946, compiled the first intensive study of the phylogeography of the puma. He re c o g n i zed thirty puma subspecies in the Western Hemisphere based on morphological and pelage characteristics from a total of 764 specimens composed of skulls and skins collected from throughout the puma’s range. Howe ve r, the validity of some of these subspecies was questionable due to small sample sizes and an unknown age distribution of the specimens. Some of the skulls examined we re without skins, and some of the skins we re without skulls. Ni n eteen of the subspecies were described from fewer than nine specimens each, including six subspecies that we re described from only one specimen each. Go l dman (1946) described thirteen subspecies in No rth America (including Canada, the United States, and Mexico). The subspecies Felis [Pu m a] concolor azteca, which he described from 228 specimens (the largest number in the collection), had a geographic range that included almost all of New Mexico, most of Arizo n a , and the western half of Mexico. This would be the subspecies that we studied. Modern molecular genetic techniques tell a different story about puma phylogeography. Culver (1999) examined subspecies of puma by using three mitochondrial genes and ten microsatellite loci in biological samples collected from a total of 315 pumas from throughout the historical range. Twelve of her specimens were from pumas that we studied on the San Andres Mountains in New Mexico. Culver (1999) identified six phylogeographic groups: (1) North America (Canada south to Guatemala and Belize), (2) Central America (Nicaragua, Costa Rica, and Panama), (3) eastern South America (Brazil south of the Amazon River and Paraguay), (4) northern South America (Columbia, Venezuela, Guyana, French Guyana, Ecuador, Peru, and Bolivia), (5) central South America (northeastern Argentina and Uruguay), and (6) southern South America (Chile, southwestern Argentina). Hence, Culver (1999, 2000) recommended six subspecies for puma and named them based on the oldest Latin name among the previous subspecies that were combined. They included P. c. couguar for North America, P. c. costaricensis for Central America, P. c. concolor for northern South America, P. c. capricornensis for eastern South America, P. c. cabrerae for central South America, and P. c. puma for southern South America.

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PART I. SETTING THE STAGE

Description The puma is the fourth-largest cat in world. It is comparable in mass to the African leopard and snow leopard. The jaguar is the largest cat in the Western Hemisphere, but its body size overlaps with that of the puma. At the extremes, jaguars can be 80 percent larger than pumas. The African lion and tiger are two to three times larger. In the Western Hemisphere, the puma and the jaguar are the only extant large wild felids. Puma body size, in general, increases with latitude (Kurtén 1973). Puma masses compiled by Anderson (1983) clearly indicate sexual dimorphism. Males weighed significantly more than females (averaging 40 percent heavier) in five out of six North American subspecies for which data were available; insufficient sample size may have precluded the sixth. Mean masses for adult specimens (twenty-four months or older) ranged from 52.8 to 68.0 kg for males and from 34.4 to 48.0 kg for females. The heaviest puma on record was a 125.2 kg eviscerated male killed in Arizona (Musgrave 1926). Adult male pumas reached total lengths (body plus tail) of 202.2–230.8 cm and adult females measured 183.6–201.7 cm. Shoulder height measurements for adults ranged from 56.0 to 78.7 cm for males and from 53.4 to 76.2 cm for females. Adult desert pumas (twenty-four months or older) that we studied on the San Andres Mountains exhibited similar morphometric characteristics (see

PHOTO 1. Adult male puma M3 was resident on the San Andres Mountains until his death at twelve years of age.

CHAPTER 2. PUMAS PAST AND PRESENT

19

Appendix 1). On average, males weighed 70 percent more than females. Male masses ranged from 45.4 to 71.7 kg and female masses ranged from 24.5 to 40.4 kg [1]. Total lengths for males ranged from 200 to 227 cm, and females ranged from 172 to 205 cm. The body and tail comprised about 63 percent and 37 percent of the total body length, respectively. Height at shoulder for males ranged from 54 to 67.5 cm, and for females ranged from 43 to 61 cm. Pumas have a relatively compact head and a slender, elongate, muscular, lithe body on powerful limbs. Forelimbs are somewhat shorter and heavier than the aft and have larger paws on supine wrists, adaptations for handling prey and for climbing. The hind limbs, proportionately the longest in large felids (Gonyea 1976), propel the puma during quick bursts and help it to catapult cliffs, rock outcrops, and trees. The long, muscular tail is cranked to and fro apparently for maintaining balance while attacking prey, hustling over broken terrain, and climbing trees. Retractile claws on the feet are used for self-defense, and for seizing prey, gaining traction on slippery media, and climbing trees. Forefeet have five toes, four of which support the puma on the ground. Although the pollex is nonsupporting, it has the largest claw and is used for combat, climbing, and grasping prey. Hind feet have four supporting toes. Claws on the hind feet are not as robust, recurved, or sharp as the foreclaws, but they are used for traction and climbing. Toe pads are oval and the plantar pad has three distinct rear lobes, a common feature in cats. Width measurements of plantar pads can be used to help distinguish tracks of adult male and female pumas within the same population. We used this as a guide in our study to quickly classify tracks that we encountered. Tracks with forefoot plantar pads measuring 55 mm wide or more were usually of adult males, and those measuring 50 mm wide or less were usually of females (see Appendix 1). However, sometimes there was confusion when subadult males had foot sizes similar to those of females. The outward appearance of an adult puma’s pelage is principally of one color (hence the epithet concolor), with varying hues of tawny, reddish brown, and grayish-brown. We observed all these variations within our study population. A black “mustache” accents the sides of the muzzle at the base of the vibrissae and contrasts sharply against the white hair around the mouth. Long, stout, white, black, or brown vibrissae are highly innervated and are probably important for directing a puma’s killing bite or a mother’s affections to her cubs. The nose pad can be bright pink, neutral, or brown, and is sometimes flecked with black. Black patches of hair are on the backs of the pinnas and may have a sparse median gray patch. The front of the pinnas have white hair, thicker at the margins. Whitish hair covers the underparts of the neck, chest, abdomen, legs, and tail. The dorsal side of the tail resembles the color of the puma’s back. The tip

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PART I. SETTING THE STAGE

of the tail is black. Dark bars transverse the inner sides of the forelimbs at and below the angle of the elbows; they are black in younger animals and fade to brown with age. Sometimes white flecks of hair are scattered on the top of the head, nape, back, and shoulders. We believe the white hairs grow from skin cells traumatized from claw and teeth punctures during fights between pumas, or from tick bites. Although the adult puma lacks the stripes or spots present on many of the other felids, its pelage camouflages it among like-colored objects and light patterns in the rocks, grass, and shrub cover of its habitats. We can attest to this during literally hundreds of approaches to observe pumas up close. Their pelage colors and textures appear to meld with their surroundings. Cubs are born fully furred and with black spots on reddish-brown to graybrown coats and with black rings on their tails. These coat patterns effectively hide cubs among the rocks, holes, and low vegetation at nurseries. Birth weights average 508.3 grams (Anderson 1983). Within two weeks of birth, a cub’s eyes are fully open (Young 1946) and are blue. We noted that the eyes of cubs as young as five months had turned to the brown or amber color of adult pumas. Pelage spots and rings fade into light brown dapples by the time cubs reach nine months old. Dapples disappear usually before twenty-four months of age, about the time of sexual maturity. But we saw faint dapples persist on forelimbs and hind limbs of known-age pumas that were thirty months old.

PHOTO 2. Puma F47’s four-week-old cubs at the birth nursery.

CHAPTER 2. PUMAS PAST AND PRESENT

21

Genders of adult pumas can be distinguished by their external sex organs. Males have a spot of black hair about 2.5 cm in diameter that encircles the opening of the penis sheath and is about 12 cm anterior-ventral to the anus. The scrotum, situated between the anus and the black spot, is mostly covered with whitish hair but with flecks of silver and brown. The female’s vulva is directly below the anus, and it may be encircled by a line of black hairs that is sometimes faint and broken. We used these characteristics to accurately determine the sex of pumas that we treed in Wyoming during a previous study (Logan et al. 1986) either with the naked eye or with binoculars. The male’s sex organs are visually evident, but those of the female are usually hidden beneath the base of the tail. The puma has thirty teeth, with an upper/lower dental formula of incisors, 3/3; canines, 1/1; premolars, 3/2; molars, 1/1. The relatively small number of teeth and vestigial teeth (P2, M1) may be the result of selection for shorter jaws that deliver more effective biting action—a functional adaptation for solitary hunters of large, potentially dangerous prey. Predatory behavior and a strict carnivorous diet are reflected in the teeth morphology. Large conical canines grab prey; puncture skin, muscle, ligaments, and sinew; and separate skeletal joints. Robust carnassials shear apart tissues and break bones. Small, closely spaced incisors pluck hair or feathers from the skin of prey, strip tissues from bone, and are used for self-grooming. The form and function of the puma is that of a highly adaptive asocial predator suited for environments with rugged terrain and closed vegetative cover where prey is dispersed and clumped. The puma preys on mammals ranging in size from hares (Iriarte et al. 1990) to adult elk (Cervus elaphus) (Hornocker 1970). Of the large felids, from leopards to tigers, pumas routinely kill the largest prey relative to their own mass (Packer 1986). Selective pressures designed the puma as an ambush and stalking predator that attacks its prey with a quick powerful rush, overwhelms the victim with staggering strength, and delivers a killing bite in seconds.

LN N5LN5) 1. Summary morphometric statistics on adult pumas (twenty-four months and older) captured on the San Andres Mountains, New Mexico (refer to Appendix 1): Male masses (kg): n = 27, x– = 56.3 ± 6.1, median = 55.3. Female masses: n = 33, x– = 33.1 ± 3.9, median = 33.1. Test for difference in mass between males and females: two-sample t-test: t = 17.497, 58 d.f., P < 0.0001.

Chapter 3

Our Outdoor Laboratory

The San Andres Mountains comprised our 2,059 km2 study area in south-central New Mexico (Fig. 3-1). The range extends north from San Augustin Pass on U.S. Highway 70 in Doña Ana County to Mockingbird Gap in Socorro County. The area was almost completely within White Sands Missile Range, which was under the jurisdiction of the U.S. Army. About 93 km2 of the study area was outside the western boundary of White Sands Missile Range and was primarily public domain administered by the U.S. Department of Interior’s Bureau of Land Management, with small private inholdings owned by cattle ranchers who leased Bureau and state trust lands for grazing. Only about thirteen people, including an average of four puma research team members, inhabited the San Andres Mountains year-round, for a human density of about 0.65 per 100 km2. We chose the San Andres Mountains as our study area for a number of reasons: (1) We preferred a desert area because intensive, long-term research on pumas in a desert environment had not been done. This gave us the greatest opportunity to contribute new knowledge about the species. (2) The mountains comprised a large area of puma habitat not contiguous with other large blocks of puma-inhabited areas; thus, we could isolate a puma population for intensive study. (3) The San Andres Mountains constitute a self-contained ecosystem, where none of the large mammals migrate. (4) The area was relatively undisturbed by humans because access and activities were highly restricted by the U.S. Army. (5) Through agreements with cooperating land and natural resources management agencies, we could minimize human-caused confounding variables by prohibiting puma hunting and furbearer trapping and restrict23

FIGURE 3-1. The puma study area (2,059 km2), San Andres Mountains, New Mexico. The sixteen camps are depicted as triangles and include San Nicholas (SN), East San Andres (ES), San Andrecito (SA), Dead Man (DM), Lost Man (LM), Hembrillo Basin (HB), Hembrillo Narrows (HN), Sulphur (S), Buckhorn (BH), Rhode’s Pass (RP), Hardin (H), Rosebud (RB), Good Fortune (GF), Puma Basin (PB), Edifice (E), and Mockingbird Gap (MG).

PHOTO 3. San Andres Peak after sunup.

Slide @318%

PHOTO 4. Upper Sulphur Canyon.

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PART I. SETTING THE STAGE

ing mule deer hunting. In addition, because livestock was prohibited on all but 5 percent of the area, livestock were not an alternate source of food for pumas, nor could they compete with native ungulates. The only human manipulations of the study population would be our own experimental removal of pumas. (6) A network of dirt roads and primitive trails accessible by four-wheel-drive vehicle enabled us to thoroughly explore the mountains for pumas. We partitioned the study area into two subunits to provide us with a Treatment Area (TA) and a Reference Area (RA). The 703 km2 Treatment Area in the southern one-third of the study area was delineated because it held all of the radio-collared mule deer and almost all of the radio-collared desert bighorn sheep in our study. We removed pumas from that area to experimentally study puma population dynamics and how puma predation influenced survival rates and agent-specific mortality in radio-collared deer and sheep. The Reference Area was 1,356 km2 in size; no manipulations of the puma population occurred there, allowing us to observe puma population dynamics under natural conditions (i.e., in the absence of human exploitation).

Physiography and Geology The San Andres Mountains are within the easternmost part of the Mexican Highland section of the Basin and Range physiographic province (Hawley et al. 1976). The mountain range is long and narrow, measuring over 127 km long and 9–30 km wide. It is part of a broken chain of mountains extending to the Oscura Mountains to the north and terminating in the Organ and Franklin Mountains to the south (Fig. 3-1). Two large desert basins flank the range: the Jornada del Muerto to the west and the Tularosa to the east. The Tularosa Basin spans some 97 km east to west at its widest point; the Jornada del Muerto, about 55 km. The San Andres Mountains are composed of a westward-tilted fault block of Precambrian granite and Paleozoic-age limestone, dolomite, sandstone, and shale (Eidenback 1983, Kottlowski et al. 1956). A major fault zone borders the range to the east and separates the great collapsed crest of the Tularosa Basin from the steep east face of the mountains. The precipitous east escarpment rises up to 1,500 m above the basin floor and is characterized by cliff-forming limestones (Van Devender and Toolin 1983). The east face has been eroded back from the original fault boundary. Alluvial fans formed from the weathering granite and limestone bedrock are broken by a network of arroyos and outcrops of Precambrian granite and schist. Fault activity during the last ten million years has disturbed some of the alluvial deposits and underlying bedrock, and fault scarps formed during the past two million years are present along most of the

CHAPTER 3. OUR OUTDOOR LABORATORY

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basin-range margin (Hawley 1983). The western slope is relatively gentle. There, tilted sedimentary rocks dip 10–20 degrees westward into the younger rocks and valley fill of the Jornada del Muerto syncline (Kottlowski et al. 1956). Within the central portion of the mountain range there are fourteen major east-west, convoluted canyons that drain numerous other north-south branches. Internal basins are interrupted by subsidiary tilted blocks, and folds. The southern end of the San Andres Mountains is more geologically similar to the adjacent Organ Mountains to the south and consists of a course-grained phase of the Organ Mountains monzonite batholith. Mockingbird Gap, at the north end of the range, is a broad pass in a down-faulted anticlinal axis. The general north-south trend of the range continues northward in a series of low hills called the Little Burros and is separated by another broad gap from the Oscura Mountains. But the Oscura fault blocks dip eastward and are bounded on the west by a fault-line scarp (Kottlowski et al. 1956). Elevations within the our study area range from about 1,280 m along the east piedmont to 2,730 m at Salinas Peak. The San Andres Mountains are relatively well watered. There are approximately one hundred natural springs distributed throughout the study area that produce perennial surface water. Another thirty springs are intermittent. Perhaps as many as one hundred other sites supply ephemeral water, charged only during the monsoon season. Flows at springs are variable, ranging from a few centimeters deep in a reach of up to 1 m, to shallow, narrow streams that reach about 0.5–1 km. However, the latter only occur at three springs. The average distance between springs is about 1 km, with a range of about 0.06 to 6.8 km (Boykin et al. 1996).

Climate The San Andres Mountains have a semi-arid climate classified as w a rm temperate in Brown et al. (1998), A Classification of No rth American Biotic Communities. Precipitation falls mostly as rain during the monsoon season of July through Se ptember. This results from large-scale systems that push tropical and subtropical moist air from the Gulf of California and the Gulf of Mexico nort h w a rd into New Mexico, bringing intense, but brief, scattered rain showers. Winter moisture fluctuates depending on the re l a t i velatitude of the jet stream, and storms that do occur generally produce slow, drizzling rain or light snow. Weather is seasonal, with hot summers, warm springs and falls, and cold winters. We summarized precipitation data for the Ash Canyon gauge because it occurred at mid-elevation (1,731 m) in the central portion of the Treatment Area and complete data have been collected there since 1937 by the U.S.

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PART I. SETTING THE STAGE

FIGURE 3-2. Annual and growing season (July to September) precipitation, San Andres Mountains, New Mexico, 1985–1994.

Department of Agriculture’s Jornada Experimental Range (Fig. 3-2). During our research period, 1985–1994, mean annual precipitation was 43.6 ± 11.4 cm (± 1 SD), which was 10.8 cm greater than the mean annual precipitation during the previous forty-eight years (1937–1984; ( x– = 32.8 ± 10.2 cm). Moreover, the first, third, and fifth highest annual precipitation occurred during our study (1991, 1992, 1986, respectively). The monsoons bring almost half of the annual precipitation. Thus, the growing season in the San Andres Mountains is marked from July to September. During our research period, an average of 19.8 ± 5.9 cm of precipitation fell during those months. Below-average precipitation during the growing seasons of 1992–1994 contributed to severe drought that resulted in the complete drying of some of the perennial springs. These drought conditions would prove to be pivotal in the way pumas affected the desert mule deer and desert bighorn sheep populations on the San Andres Mountains. Snow fell infrequently during December through February. Continuous snow cover did not persist for more than a few days except along the north-facing slopes at higher elevations. Individual storms generally brought less than 2.5 cm of snow to the lower elevations, whereas higher elevations occasionally received 12 cm or more. The most severe storm occurred in December 1987 and brought 46 cm of snow to elevations above 1,372 m. Temperature records from the Jornada Experimental Station (elevation 1,349 m, 15 km west of our study area) for 1985–1994 gave a mean annual temperature of 14.5 degrees Celsius. July was the hottest month, with temperatures averaging 25.5 degrees Celsius. January was the coldest month; tempera-

CHAPTER 3. OUR OUTDOOR LABORATORY

29

tures averaged 3.4 degrees Celsius. Extreme temperatures in summer reached 42.8 degrees Celsius and in winter dipped to –24 degrees Celsius. The “windy season” typically occurred in March and April. Winds often exceeding 50 km per hour blew across the desert from the west and southwest, parching the herbaceous vegetation and whatever winter moisture was stored in the thin topsoil. Wind velocities as high as 187 km per hour were clocked at the summit of Salinas Peak (White Sands Missile Range climate records).

Flora Woodrat (Neotoma spp.) middens examined by botanists on the San Andres Mountains indicate when the extant regional biota emerged. A mixed-conifer forest dominated by Douglas-fir (Pseudotsuga menziesii), blue spruce (Picea pun gens), and ponderosa pine (Pinus ponderosa) was present at the higher elevations during the late Wisconsin glacial age, about fifteen thousand years ago. Lower elevations supported an open juniper (Juniperus spp.) –oak (Quercus spp.) woodland (Van Devender and Toolin 1983). During the early Holocene (about nine thousand years ago) the climate became warmer and dryer and desert communities began to develop. The vegetation and climate have been virtually modern for about the last 4,400 years. Today, the San Andres Mountains lie at the northern edge of the Chihuahua Desert, which extends mostly southward into northern Mexico and westward into southwestern New Mexico and southeastern Arizona. Flora on the San Andres Mountains mostly represents the Chihuahuan Interior Chaparral, Chihuahuan Desert Scrub, and the Chihuahuan (Semidesert) Grassland biotic communities described in Brown et al. (1998). Localized cooler and moister conditions support small communities of Ponderosa pine and Gambel oak (Quercus gambelli) on Salinas Peak, and Gambel oak with an understory of snowberry (Symphoricarpos rotundifolius) on San Andres Peak. Because plant communities on the San Andres Mountains had not been previously described and mapped, we developed our own scheme to describe the vegetative settings for our observations. We recognized seven vegetative cover types, including tall mixed desert shrub, low mixed desert shrub, grass, mixed mountain shrub, dry channel, moist riparian, and piñon (Pinus edulis) –juniper (Juniperus spp.). Vegetation was highly influenced by elevation, aspect, parent material, and soil type. Sometimes two or more vegetation types occurred as codominants, and shrubs and grass were frequent sub-dominants in the piñonjuniper type. Dominant plants in the tall mixed desert shrub type were generally taller than 1 m. Creosote (Larrea divaricata), mesquite (Prosopis glandulosa), mimosa

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(Mimosa biuncifera), and southwestern condalia (Condalia lycioides) typify this community and were usually found in the desert basins, on alluvial fans, and on south- and west-facing slopes. Stony uplands supported ocotillo (Fouquieria splendens) and sotol (Dasylirion wheeleri). Drier slopes supported low mixed desert shrub vegetation such as mariola (Parthenium incanum), feathered dalea (Dalea formosa), prickly pear (Opuntia spp.), yucca (Yucca baccata), and agave (Agave parryi). Grass communities were composed of black, blue, and sideoats grama (Bouteloua eriopoda, B. gracilis, B. curtipendula), three-awn (Aristida spp.), and muhly (Muhlenbergia spp.). Black grama grew in the limestone hills in association with ocotillo and hairy mountain mahogany (Cercocarpus breviflorus). Muhly typically occurred on alluvial slopes. Localized stands of invader species such as burro grass (Schleropogon brevifolius) and snakeweed (Gutierrezia spp.) were indicative of past overgrazing; however, native grasses have recovered dramatically in most areas (Van Devender and Toolin 1983). Protected slopes and higher elevations supported mixed mountain shrubs generally taller than 1 m, including mountain mahogany, skunkbush sumac (Rhus trilobata), Wright’s silktassel (Garryea wrightii), oak, and pale hop tree (Ptelea trifoliata). Mountain shrubs usually integrated with desert shrubs where the soil became shallow and stony. Piñon and juniper grew in the coolest areas—generally north slopes and the highest elevations. Coverage varied from a few scattered trees to 100 percent. Trees were typically short and usually did not exceed heights of 6 m. Of the junipers, one-seed (J. monosperma) was the most represented. Alligator-bark junipers (J. depeana) were only found in the most protected areas. Dry channel vegetation grew in the major drainage channels. Wide canyon bottoms were gravelly, sandy, and well drained, and they supported vegetation such as Apache plume (Fallugia paradoxa), brickellbush (Brickellia laciniata), algerita (Berberis trifoliata), and desert willow (Chilopsis linearis). Moist riparian vegetation grew where springs, seeps, and a high water table occurred. Cattails (Typha angustifolia) grew in the water, and on the banks were hackberry (Celtis reticulata), Velvet ash (Fraxinus velutina), and cottonwood (Populus deltoides weslizeni) trees, the latter two species reaching heights of up to 9 m. At some perennial springs, and where the water table was high, the exotic salt cedar (Tamarix ramosissima) had invaded.

Fauna Four native ungulate species occurred on the study area: desert mule deer, desert bighorn sheep, pronghorn (Antilocapra americana), and javelina (Pecari tajacu).

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None of these animals made seasonal or elevational migrations. Mule deer were the most abundant ungulate throughout the mountain range, numbering in the thousands. They even inhabited the most rugged terrain preferred by the desert bighorn sheep. They were sparse or nonexistent in the broad desert basins flanking the mountains. Sport-hunting of the deer was prohibited on the San Andres Mountains between 1985 and 1989. However, as a result of pressure from sporthunters in southern New Mexico, limited hunting for buck deer was allowed by the New Mexico Department of Game and Fish in the northern one-quarter of our study area (i.e., north end of the Reference Area) in alternate years including 1990, 1992, and 1994. In those years, forty-four, eighty-two, and sixtyseven bucks, respectively, were killed. The San Andres Mountains supported the only extant, naturally occurring population of desert bighorn sheep in New Mexico. This herd was a peripheral, isolated population at the eastern edge of the geographic range for the species. During this study, only a remnant population of thirty to forty desert bighorns remained. They ranged primarily in the steep, rugged terrain of the east escarpment, and almost all of them lived in the Treatment Area. The desert bighorn sheep is a New Mexico state-listed endangered species, with fewer than 280 sheep statewide (Pederson 1996). Pronghorns infrequently ranged into the foothills in the northern portion of the San Andres Mountains. Typically they traveled in small herds of fewer than twenty animals. The open desert flats were the areas they usually inhabited. Sport-hunting of pronghorns was limited; about thirty to forty buck permits were issued to hunters each year (White Sands Missile Range 1994). Javelina probably numbered fewer than fifty animals on the San Andres Mountains. Small, scattered bands of fewer than ten animals each occurred in the denser piñon-juniper communities in the northern and southern portions of our study area. Oryx (Or yx gazella) were introduced onto the San Andres Mountains in 1969 (Saiz 1975). The fifty-one animals in the original herd were from transplanted stock from Africa’s Kalahari Desert. Oryx preferred the broad desert basins east and west of the mountains, and the population increased and expanded its range during the ten years of our study. Consequently, oryx began to use the large canyons that dissected our study area on a more frequent basis. By the close of the study in 1995, the oryx population numbered approximately one to two thousand animals (White Sands Missile Range 1994). At the beginning of our study, there were probably no more than twenty-five oryx in the mountains at any time, but by 1995 there may have been fifty to one hundred. Because oryx were at relatively low numbers, ate a diet consisting of more than 80 percent grasses (Smith et al. 1998), and had no need for surface water (Saiz

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1975), they probably competed little, if at all, with mule deer and desert bighorn sheep. The New Mexico Department of Game and Fish attempted to limit the oryx population on White Sands Missile Range through sport-hunting. Feral horses, remnants of the recently past ranching culture, ranged in the Tularosa Basin on White Sands Missile Range. However, we never observed horses on our study area. Cattle grazed in valley bottoms and foothills along the western boundary of the study area. Their numbers were small, probably never exceeding more than one hundred head at any one time. Herds were composed of cow-calf groups with few bulls. A variety of small mammals inhabiting the San Andres Mountains were potential puma prey. The most abundant were the black-tailed jackrabbit (Lepus californicus), desert cottontail (Sylvilagus audubonii), New Mexico ground squirrel (Spermophilus mexicanus), rock squirrel (S. variegatus), white-tailed antelope squirrel (Ammospermophilus leucurus), and woodrat (Neotoma mexicana). We rarely observed porcupines (Erethizon dorsatum). About 183 species of birds and thirty-five species of reptiles and amphibians have been documented on the San Andres Mountains (White Sands Missile Range 1994). Ground-dwelling birds included three species of quail. Gambel’s (Callipepla gambelii) and scaled (C. squamata) quail were found in the dry channel and riparian communities, and were most abundant during years of high precipitation. Montezuma quail (Cytonx montezumae) apparently occurred in small numbers with a patchy distribution. Wild turkeys (Meleagris gallopavo) were represented by probably fewer than ten animals. Avian scavengers included turkey vultures (Cathartes aura), golden eagles (Aquila chrysaetos), red-tailed hawks (Buteo jamaicensis), and ravens (Corvus spp.), but these occurred in such low numbers that they rarely clued us to locations of dead animals. Other carnivores on the study area included the coyote (Canis latrans), gray fox (Urocyon cinereoargenteus), badger (Taxidea taxus), bobcat (Lynx rufus), ringtail (Bassariscus astutus), and the striped (Mephitis mephitis) and hog-nosed skunks (Conepatus mesoleucus). Coyotes usually inhabited the upper basins of drainages. We frequently saw gray foxes and their tracks throughout the mountains, but we rarely saw bobcats or their tracks. Historical accounts of jaguars, wolves (Canis lupus baileyi), and bears (Ursus americanus, U. arctos) on the San Andres Mountains are either extremely rare or nonexistent. We found one anecdotal account of a Biological Survey hunter whose dogs “jumped,” but did not catch, a jaguar in the San Andres Mountains in 1937 (Halloran 1946). Black bears apparently occurred in low numbers as

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late as the 1890s (Halloran 1946) but were extirpated about 1908 (J. P. Wood, Jr. personal communication). No records indicated the presence of grizzly bears or wolves on the mountains. However, because wolves once occupied other ranges in southern New Mexico—including the Black Range and Mogollon Mountains to the west and the Sacramento Mountains to the east—all of which were within dispersal range for wolves, it is likely that the San Andres Mountains supported at least a small population of wolves from time to time. Such a population could have been easily extirpated by the earliest non-native human settlers.

History of Human Use Human presence on the San Andres Mountains has waxed and waned since prehistoric times. Nomadic bands of paleolithic hunters pursued now-extinct large herbivores in the northern San Andres Mountains and adjacent basins about eleven thousand years ago. Those people also used the area to quarry finegrained chert from which they manufactured their hunting and processing tools. They left some of their fluted projectile points and scrapers at campsites in Mockingbird Gap and at the mouth of Rhodes Canyon (Beckett 1983, Breternitz and Doyel 1983). By the time modern climatic conditions prevailed some

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PHOTO 5. Puma paw petroglyph near Three Rivers, New Mexico.

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PART I. SETTING THE STAGE

four to five thousand years ago, paleolithic adaptations had been replaced by subsistence hunting-and-gathering traditions known as Archaic or Desert Culture. People hunted modern animal species and relied heavily on wild plant foods such as juniper berries, piñon nuts, mesquite beans, agave, yucca, and prickly pear. They left behind baskets, grinding tools, and projectile points in the San Andres Mountains (Beckett 1983, Eidenbach 1983). During about 1,700–1,200 years ago people in the mountains had a more sedentary lifestyle. Some of their pithouses and shards of their pottery are still there. They also practiced horticulture, growing corn and beans. We found some of their discarded corncobs in dry undercut ledges and shallow caves. These were probably the people that created a red ochre pictograph of a puma that we found on a limestone cliff face only 30 m from our Hembrillo Narrows Camp, near the center of our study area. About the same time, relatives of those people, living about 70 km to the northeast at the western foot of the Sacramento Mountains, etched an oversized likeness of a puma’s paw into basalt. These are the first known observations of pumas to be recorded by humans in the region. For some unknown reason, perhaps due to an extended drought in combination with social and economic conflicts, people essentially abandoned the San Andres Mountains about six hundred years ago. Thereafter, aboriginal activity was sporadic (Breternitz and Doyel 1983). When the Spanish arrived in southern New Mexico in 1540, most of the native peoples they encountered were settled in pueblos along the Rio Grande. Nomadic Apache, who had arrived about 1500, raided the pueblos and villages of settlers (Sale and Laumbach 1989). Apache groups used the San Andres Mountains for seasonal hunting and gathering and as a base from which to conduct raids. They also used the mountains as a refuge from punitive pursuits of the Spanish, Mexican, and United States military. Raids continued into the 1880s when the last Apache bands were confined to reservations. In 1880, one of the last battles of the Apache-American war took place in Hembrillo Canyon, where the famous Apache Chief Victorio fought the U.S. 9th Cavalry (Thrapp 1980, Breternitz and Doyel 1983, Sale and Laumbach 1989). In the canyon, breastworks and pictographs of horse-mounted men testify to those parlous times. Our Hembrillo Basin Camp lay in the middle of the battlefield. Cavalryissue brass littered the ground; here and there on the limestone were splashes of lead from bullets. The battle marked the end of aboriginal peoples’ use of the San Andres Mountains. Anglo and Mexican homesteaders established the first permanent ranches on the San Andres Mountains in the late 1860s. The 1880s brought an influx of Texas cattlemen to the area. Drought and overgrazing in the 1890s forced many ranchers to shift to raising goats and sheep. Settlement in the mountains

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continued through the late 1930s. Ranches we re generally small family outfits that raised angora goats and sheep for the mohair and wool industries. They also kept cattle, horses, and mules for their own uses. Family goat herds numb e red from a few hundred up to two thousand head (Eidenbach 1989). Go a t operations we re active throughout the San Andres Mountains. We counted at least nineteen ruins with corrals and chutes designed for handling goats and s h e e p. It is likely that during the period when goats and sheep we re raised, mule deer and desert bighorn sheep we re subjected to the greatest competition for food and water. Overgrazing may have helped to transform mountain grasslands to communities dominated by shrubs and trees. Na t i ve sheep, in part i cular, we re also at the greatest risk of contracting diseases and parasites fro m their domestic kin. Old-time ranchers who lived in Bear Den Canyon, upper Cottonwood Canyon, and Deadman Canyon, all within the heart of the San Andres Mountains, recollected to us that pumas were fairly common in the mountains, always presenting a threat especially to goats, sheep, and horse and mule foals. They consistently described mule deer as abundant or common, except during droughts. Mule deer meat was a staple food. Desert bighorn sheep, they said, were always in low numbers. Hard-rock mining activity was widespread in the mountains during the period of settlement. Miners were principally searching for galena, copper, barite, and quartz (Sandoval 1979b, Breternitz and Doyel 1983). The U.S. Government began acquiring land in the area in 1912. That year the Jornada Experimental Range, under the jurisdiction of the U.S. Forest Service, was formed along the west flank of the San Andres Mountains and extended westward onto the Jornada del Muerto. In 1933, White Sands National Monument was established in the center of the Tularosa Basin. Eight years later, the San Andres National Wildlife Refuge, encompassing 230 km2, was created near the southern end of the San Andres Mountains, primarily for the protection of desert bighorn sheep and other desert wildlife (Hoban 1986). White Sands Proving Ground (later named White Sands Missile Range) was established in 1945, principally to aid efforts to win World War II. This had a great impact not only on the land in the region but also on the world. On July 16, 1945, the first atomic bomb was exploded in the desert basin at Trinity Site, 12 km north of the northern tip of the San Andres Mountains. Inhabitants of the region had to evacuate to make room for the missile range; hence, the historic era of ranching and mining came to an end, and tight restrictions were placed on other public uses. The San Andres Mountains functioned as a tremendous natural buffer zone for military research and development that took place mainly in the desert basins. Once again, the mountains were left practically

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PART I. SETTING THE STAGE

undisturbed by humans. During the forty years leading up to our study, the mountains recovered from some effects of previous human use.

History of Puma Exploitation Pumas were killed by ranchers and government hunters on the San Andres Mountains during the late 1800s and early 1900s mainly to protect livestock (Eidenbach and Morgan 1994). J. P. Wood Jr. (personal communication), who lived in Bear Den Canyon, perceived that local ranchers kept pumas from becoming a significant problem by keeping them in “check” through trapping and hunting with hounds. U.S. Fish and Wildlife personnel, while carrying out predator control to protect wildlife during 1940 to 1979, killed fourteen pumas on or near the San Andres National Wildlife Refuge (Muñoz 1983). Another five pumas were killed by hunters on other parts of the San Andres Mountains from 1966 to 1971 for the same reason (Anderson and Taylor 1983). The toxicant compound 1,080 (sodium monofluoroacetate) was used to control carnivores on the refuge during 1949 and 1951 (Muñoz 1983). We found three of the former 1080 bait stations; they were marked by weathered juniper posts, the top one-quarter painted red. One still had rusting wire wrapped around the base that once held deadly bait. There were no records of how many animals were poisoned in this way. Sport-hunters with hounds killed eight pumas in the mountains from December 1979 to February 1985, including one male (age not recorded), four females (ages not recorded), and one adult female and her two male cubs. Yet another predator-control action during September 1980 to May 1984 was carried out to protect the remnant population of desert bighorn sheep on the San Andres Mountains (Sandoval 1979a, Evans 1983). Trappers for the New Mexico Department of Game and Fish, U.S. Fish and Wildlife Service Animal Damage Control, and the San Andres National Wildlife Refuge killed forty-two pumas, including thirty-four adults. This last control action was terminated after New Mexico Department of Game and Fish biologists evaluated its effectiveness and concluded that the removal of the pumas did not cause an increase in desert bighorn sheep survival (Evans 1983). Assuming that a total of forty adult pumas were killed on the San Andres Mountains during the forty-three months of exploitation (December 1979–February 1985), then the kill rate averaged eleven adult pumas per year on the San Andres Mountains. The kill rate for all fifty pumas (i.e., adults, subadults, and cubs) averaged fourteen pumas per year. The Oscura Mountains constitute a 673 km2 patch of puma habitat 9 km northeast of the north end of the study area. Puma control was implemented

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there too from October 1980 to October 1981 for the purpose of protecting the desert bighorn sheep. The rationale was that if the puma population was decimated there, then movement of pumas onto the San Andres Mountains would be minimized, further reducing puma predation risk to the sheep. An Animal Damage Control agent killed thirteen pumas during the one-year period. During our ten-year study, however, no pumas were killed for sport-hunting or control on the Oscura Mountains. On the 272 km2 Organ Mountains, connected to the south end of our study area, puma-hunting pressure was relatively light. A total of five pumas (three males, two females) were killed from 1986 to early 1995 (New Mexico Department of Game and Fish kill records). Original—and rather crude—records kept for the forty-two pumas killed on the San Andres Mountains for predator control during the period 1980 to 1984 indicated thirty-four were adults (twenty males, fourteen females), two were yearlings (one male, one female), and six were cubs (i.e., dependent offspring; one male, five females). Similar records kept for pumas killed in the Oscura Mountains indicated eleven were adults (six males, five females) and two were yearling females. We inspected the preserved skulls of twenty-nine of the pumas (sixteen from the San Andres Mountains, thirteen from the Oscura Mountains) that were deposited at the Museum of Southwestern Biology (University of New Mexico, Albuquerque) to compare dental and suture characteristics with skulls of known-age and approximately known-age pumas we studied on the San Andres Mountains. The estimated mean age of nine adult males was 61.2 ± 32.3 months (± 1 SD), and the mean age of eleven adult females was 80.4 ± 36 months. One male and two females were thirteen to eighteen months old. One male, three females, and two pumas of unknown sex were less than twelve months old. Beginning in March 1985, and throughout the time of our study, the San Andres Mountains were closed to puma hunting, except for about 5 percent of the study area that lay outside of the west White Sands Missile Range boundary. The New Mexico Department of Game and Fish did not want to offend ranchers operating in that area by completely eliminating puma hunting. However, even there, all pumas tagged by us were protected by state hunting regulations. Fur-bearer trapping was also eliminated on the White Sands Missile Range portion of our study area in order to minimize risks to pumas. This regulation was particularly important to protect cubs.

Chapter 4

Studying Wild Pumas

Pumas are cryptic, crepuscular, and nocturnal, and normally shun humans. They are scarce in their complex habitats. These traits make pumas one of the most difficult large-terrestrial mammals to study in the world. Field ecologists normally “observe” pumas by their tracks, beds, nurseries, playgrounds, droppings, and scraps of prey. Because chances to observe wild pumas directly are extremely rare, direct, quantitative data must come from pumas wearing collars containing radio transmitters. To attain our research objectives, we employed those means of data gathering and diligent field ecology. To do that, we lived among the pumas.

Life Afield We used sixteen base camps located at strategic locations to efficiently cover large parts of the San Andres Mountains (Fig. 3-1). The camps, along with a network of primitive roads accessible to four-wheel-drive vehicles, facilitated a thorough exploration of the entire study area. We trucked in all our staples and brought some basic comforts to the camps by outfitting them with stoves, lanterns, and cots. Most of our camps were sheltered by large tents. Four of the camps were in abandoned or rarely used structures, including a 1940s-vintage trailer, a hunter checkstation, and a former military police station. Our favorite was San Andrecito Camp, which consisted of a 3 m ¥ 3 m shack built out of missile-engine crates. We retrofitted bunk beds, shelves, and windows with material salvaged from a dilapidated abandoned barn about 10 km away. We covered the shack with tar paper to keep out blowing sand. The camp, perched 39

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on a promontory, overlooked extraordinary puma habitat at the confluence of two north and south drainages that fed into a rugged, winding, east-draining canyon. Two springs within 100 m of camp provided vital water for a variety of wildlife. Pumas that came there to drink, hunt, and socialize passed us in the night, leaving their footprints in the sand. On a few occasions we listened and even watched pumas caterwauling. Our team normally consisted of four persons. During our research from 6 August 1985 to 31 March 1995, our team spent on average 254 days a year in the field (range = 230–289). We accumulated a total of 2,445 field days and about 9,780 total person-days of field research. We were on the San Andres Mountains year-round, normally in ten-day stints, then back in civilization for four days for rest, baths, supplies for the next stint, and to tend to necessary paperwork and needs of agency administrators. However, puma activities sometimes dictated extended stays in the field. Before each ten-day stint, our research team met to discuss observations and progress in the previous stint and the short-term objectives we aimed to accomplish in the field. Each biologist was usually stationed at a different camp. We kept in contact with each other with two-way radios. This allowed us to cover different portions of the study area. From the camps and roads, we ranged out on foot in systematic searches for evidence of pumas. The usual dry desert conditions and sandy

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PHOTO 6. Hembrillo Basin Camp.

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PHOTO 7. San Andrecito Camp.

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PHOTO 8. Puma tracks in the sand.

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or dusty soil surfaces often preserved puma tracks for several days; puma scrapes would persist for weeks at a time. Observations of puma sign gave us a rudimentary understanding of how the cats were using the landscape. All observations were recorded in field journals and plotted on 7.5-minute (1:24,000-scale) U.S. Geological Survey topographic maps. Using that information, we set out to capture the pumas. Once satisfied that we had captured and identified all of the pumas in an area served by a camp, we moved to the next camp in another part of the study area and repeated the process. We continued this process yearround and year after year for the duration of the study.

To Catch a Puma The only reliable way to study puma population dynamics and social organization is to capture as many pumas in the population as is possible, individually tag them, release them, and radio-track their movements. To capture pumas, most other studies used packs of trained dogs to trail pumas by scent, then bay them in trees or on rock ledges. Once bayed, pumas were chemically immobilized, then lowered to the ground for examination (Hornocker 1970, Logan et al. 1986). Success and safety of this method are largely dependent upon the presence of trees, which pumas use to escape the pursuing dogs. This mode of escape is probably the result of a long evolutionary history with other competitors and predators such as wolves and bears. Still, even in treed areas, pumas are sometimes bayed on the ground and mauled by dogs, resulting in severe injuries or death to the pumas or dogs (Shaw 1977, Barnhurst 1986, Anderson et al. 1992). The San Andres Mountains presented us serious problems because trees that could be used by pumas for escape were sparse. Initially, we tried using Frank Smith’s dogs to capture pumas, but without success. Either the dogs could not catch up to the pumas in the dry, rugged terrain or they bayed pumas momentarily on ledges from which the cats later escaped using routes the dogs could not follow. In one instance, the puma fought the dogs, knocking one of them off a cliff, breaking its back. We realized early in the project that dogs simply were not going to yield consistent, safe captures of pumas. We estimated that 80–90 percent of catches would probably be on the ground or on rimrocks and ledges—dangerous places for dogs to hold pumas at bay and for biologists to handle the animals. Cubs would especially be vulnerable to mauling by dogs. Knowing these high stakes, we decided to try a different method for capturing pumas. We built on Frank’s extensive knowledge of catching nuisance and depre d a ting pumas and black bears with foothold traps and snares. We tried the No. 41/2

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PHOTO 9. Puma M7 caught in a snare by his right forefoot.

steel traps (Woodstream Corp., Animal Trap Div., Lititz, Pennsylvania 17543) sparingly early in the study (6 August 1985–11 January 1986) and had limited success. In fact, we only caught one adult female puma with rubber-padded traps after 114 trap-days (one trap-day is defined as one trap set for one day). Be c a u s e of the great risk of injury that those heavy, powe rfully jawed traps brought to small pumas and especially nontarget animals (e.g., deer, sheep, javelina, coyotes, foxes, bobcats, rabbits, hares), we abandoned the technique. Instead, we focused on foothold snares to capture pumas that weighed 10 kg or more. Snare assemblies (Schimetz/Aldrich Spring Activated Animal Snare, Sekiu, Washington 93831) were modified to minimize injuries to pumas and to avoid capturing nontarget animals. We attached two to four rubber bungee cords into the snare assembly to absorb shock as the captured animal struggled. In addition, we attached a slide stop to the foot loop, which minimized its closure to 18–19 cm circumference. This assisted blood circulation to the puma’s foot and allowed smaller-footed, nontarget animals to pull free from the loop (Logan et al. 1999). Moreover, we carefully chose snare sites to minimize injury to captured pumas and risk to nontarget animals. Preferred sites had limber bushes with multiple basal stems to securely anchor the snare drag, and a safety area with a

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PHOTO 10. Linda Sweanor using a pole syringe to inject puma F37 with immobilizing drugs.

circumference 5 m or more around the anchor point. The safety area was cleared of trees, old fence wire, and potentially injurious vegetation (e.g., cacti, yuccas, agaves) to minimize the probability that a struggling puma might be injured. Snares were not set near cliffs or water. We avoided setting snares on trails intensively used by deer and oryx. But when paths indicated infrequent ungulate use, we positioned stick hurdles horizontally about 60–70 cm above the snare. Ungulates generally went around or jumped over the sticks; naive pumas walked under (Logan et al. 1999). We set one to six snares on paths used by pumas and at puma kill caches and scrape sites. We set them at carcasses of ungulates that died from other causes in case pumas came to scavenge. In addition, we set snares along likely travel routes even if we were not certain that pumas used them. Where a travel way was too wide to constrict a puma’s movements through a snare set, we augmented the set with a sight lure consisting of a shiny piece of tin, and occasionally feathers, dangled from a string or wire over the snare. In total, we established 1,211 snare sites throughout the San Andres Mountains. Our intent was to capture and tag all of the adult and independent subadult

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PHOTO 11. Ken Logan hauling puma F37 for translocation to northern New Mexico.

pumas on the study area. We targeted all of them initially; then as the marked population of pumas grew, we targeted the unmarked or unidentified pumas in the population. Later, we recaptured pumas that had radio collars that were nonfunctional or had waning battery power. Pumas with well-functioning radio collars were reliably identified in the field by radiotelemetry; therefore, we persistently tried to avoid recapturing those cats. To prevent excessive stress and trauma to captured animals, we checked all snares each day by 10 a.m. during spring and summer and by 12 p.m. during fall and winter. In the hottest part of summer we sometimes checked snares twice per day (again at about 4 p.m.). But during short periods of exceptionally hot, cold, or snowy weather, we deactivated all snares to eliminate risk altogether. From 6 August 1985 to 23 February 1995, we accumulated a total of 40,419 snare-days (Table 4-1), and captured 107 individual pumas (forty-eight males, fifty-nine females) a total of 209 times. Snare captures of marked pumas (n = 132) outnumbered pumas captured for the first time (n = 78) by snares or trap. Our average capture success with snares was one puma per 193 snare-days. Although we tried to avoid unnecessary recaptures, we still made thirty-one

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PHOTO 12. Puma F27 at her birth nursery.

Table 4-1. Summary of puma snare capture efforts on the San Andres Mountains, New Mexico, 1985–1995.

Year 1985d 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995d aPumas

No. pumas first captured Total pumas and markeda recapturedb 3 7 6 14 7 7 5 15 6 7 1

1 0 9 13 15 18 34 16 16 10 0

No. snare No. snare No. snare- Snare-days captures sites daysc per capture 4 7 15 27 22 25 39 31 22 17 1

16 129 211 227 215 244 287 258 282 268 69

426 1,446 2,149 5,072 3,987 4,675 7,689 4,066 5,793 4,778 452

107 207 143 188 181 187 197 131 263 281 452

first captured with snares and one trap included thirty-six males and forty-two females. pumas recaptured included thirty-five males recaptured seventy-seven times and thirty-four females recaptured fifty-five times. cSteel leg-hold traps were used in 114 trap-days. Only one female was caught. We ceased using traps 22 January 1986. dCapture efforts were abbreviated in 1985 and 1995, extending from August to December in 1985 and from January to February in 1995. bMarked

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recaptures of nontarget pumas (radio-collared pumas that did not need collar replacement). Each male and female was captured an average of 2.4 (range = 1–6) and 1.6 times (range = 1–5), respectively (Logan et al. 1999). We immobilized pumas captured in foothold devices with ketamine hydrochloride (100 mg/ml, Vetalar®, Parke-Davis, Div. of Warner-Lambert Co., Morris Plains, New Jersey 07959) dosed at about 12 mg per kg body mass. The drug was injected remotely, usually into the caudal thigh muscles, by pole syringe (length 3.05 m) or by 3–5 ml aluminum darts fired from a CO2-powered pistol. After induction, we quickly removed pumas from snares, covered their heads, and tethered their legs. If pumas required further calming, we injected xylazine hydrochloride (20 mg/ml, Rompun®, Haver-Lockhart, Bay Vet Div. Cutter Laboratories, Inc., Shawnee, Kansas 66201) intramuscularly with a hand syringe; the dose was about 0.5 mg per kg body mass. We protected immobilized pumas from hyperthermia in hot ambient temperatures by placing them in shade and by cooling them with water that we doused over their bodies, especially the head, chest, abdominal, and inguinal regions. We protected them from hypothermia in cold temperatures by wrapping them in a thermal blanket and placing them in sunlight. We monitored heart rate, respiration rate, and circulation (via capillary refill time) during the period of immobilization. When we removed pumas from the Treatment Area, we used the same techniques for their capture and immobilization. Pumas were removed for two reasons. First, we honored a request from the cooperating agencies to remove individual pumas that killed two or more of the state-endangered desert bighorn sheep in a relatively short time span. Secondly, we removed pumas to experimentally reduce population density. In all, we removed fourteen pumas, including six adults of each sex and two subadult females. One adult male was removed 6 April 1989 because he killed three sheep in a three-month period (January–March 1989). The other thirteen pumas were removed for the experimental reduction in the Treatment Area puma population from 7 December 1990 to 21 June 1991. The pumas were captured and translocated, without injury, to northern New Mexico. We hauled them by truck in individual wooden crates (dimensions: 122 cm long, 24 cm high, 24 cm wide) less than forty-eight hours after capture. They were given food and water during transport but were released without supplemental food at predetermined release sites. All fourteen pumas became subjects of our evaluation of the survival and behavior of translocated pumas (Ruth et al. 1998). Ours was the first study to routinely capture nursling cubs so we could accurately quantify neonatal sex ratio and litter size and individually tag newborns in the population. These data would furnish us information on sex ratio shifts, cub survival rates, and recruitment rates for progeny born in the San Andres

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Slide @318%

PHOTO 13. Adult female puma F47 with eartag and radio collar.

Mountains population and immigrant recruits from other puma populations. Nursling cubs were small (less than 10 kg) and vulnerable, and, hence, required greater care. We usually caught them by hand and sometimes with the aid of a catchpole. In a few instances we had our small non-contentious hound “Spotty” assist us by baying fleet cubs in trees, on the ground, or in rock piles. During the study, we hand captured 163 cubs a total of 186 times. We restrained them without immobilizing drugs; instead, we used a catchpole and our gloved hands. We placed littermates in new burlap sacks to await our examination and tagging procedures and removed them some distance from the nursery to minimize our scent there. The sacks had open mesh for ventilation. Littermates on standby received minimal direct human contact and were relatively calm. After we examined and tagged all the cubs, we returned them to their nursery, then vacated the area posthaste. We sexed and thoroughly examined all the pumas we captured. Drugsedated pumas were weighed with a spring scale and measured with a steel metric tape. But because small cubs we handled were usually very active, accurate morphological measurements, other than mass, were impossible. Early in the study, we estimated ages of pumas based on dental characteristics described in Ashman et al. (1983:23–26). We kept photographs, measurements, and written

Slide @171%

PHOTO 14. Six-week-old cub F162 with eartag, tattoo, and radio collar.

Slide @318%

PHOTO 15. New Mexico Department of Game and Fish biologist Amy Fisher with a radiocollared mule deer.

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descriptions of dental characteristics. As the study progressed, we noted dental characteristics of the known-age pumas in the population, beginning with cubs for which we knew practically the dates of their birth. In addition, we also noted other changes in pelage and eye color. We used those characteristics to age pumas with previously unknown histories, and, when necessary, to adjust estimated ages of pumas that we captured earlier in the study. All captured pumas were marked for life by tattooing an identification number on the inner surface of one pinna. In the other pinna, we inserted a 25 mm–diameter, colored, numbered plastic tag (Duflex TagsTM, Fearing Manufacturing Co., South St. Paul, Minnesota 55075). The eartags gave us a marker that we could see from a distance and were particularly important for identifying tagged progeny that were not radio-collared. Each adult and subadult puma was fitted with a collar containing a 150 or 151 MHz transmitter with a mortality mode set to turn on after six to thirteen hours of immobility (configuration MOD-500 transmitter with X-1 shock crystal and S6A mortality sensor, CLM collar, transmitter cast in polymer. Telonics Inc., Mesa, Arizona 85204). Radio collars weighed at most about 450 grams. Some of the cubs that were more than thirty-one days old also were radio-collared (configuration MOD225 transmitter with S6A mortality sensor, also by Telonics Inc.). We built their collars out of expandable material that would break away within twelve months. Cub collars weighed about 113 grams. The tattoos, eartags, and radio collars made it possible for us to accurately estimate the number of pumas in the population and to determine relationships between them, such as relatedness and breeding pairs. There were occasions when we could not tag all progeny in a litter; consequently, we later had questions regarding the relatedness of untagged independent individuals that we captured. Were these new immigrants? Or were they unmarked progeny? To answer the questions, we collected tissues from most of the pumas whenever we had them in hand. Usually, the plugs of pinna skin and cartilage that we displaced with the eartags were collected because these were the easiest to preserve in the desert field conditions. We also collected muscle tissues from deceased individuals. We sent tissue samples to the Laboratory of Genetic Diversity at the National Cancer Institute in Frederick, Maryland, where Dr. Melanie Culver analyzed alleles at highly polymorphic loci (i.e., microsatellites) and compared them with those of candidate mothers, siblings, and fathers to estimate the likelihood of relatedness. Our snaring technique proved to be relatively safe for capturing pumas weighing 10 kg or more (Logan et al. 1999); life-threatening injuries occurred in only 2.4 percent of total puma snare captures. Four pumas died from capture injuries. One adult female suffered a fatal spinal injury; the other three cats (two

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adult females and one adult male) suffered severe fractures to the ulna and radius of the leg caught in the snare. A fourteen-month-old female cub also suffered a broken ulna and radius. Fortunately, puma F147, otherwise known as “Lefty” (named for her undamaged foreleg), was treated, rehabilitated, and released onto her natal area where she established a home range and raised cubs. Deaths of nine cubs in three litters also resulted from our research activities. One of the adult females that we euthanized because of capture injuries was apparently raising four newborn cubs. We determined this from her placental scars and her milk-producing mammary glands. In another incident, a first-time mother apparently abandoned all four of her forty-two-day-old cubs after we marked two of them. In the final case, we discovered too late that a six-month-old female cub had slipped her expandable radio collar over her front leg; the collar rubbed her skin, causing an open wound. Although we captured the cub and placed her in veterinary hospital, she succumbed to septicemia. This was the only incidence of a radio-collar injury to pumas we studied. During our research we captured, tagged, and released 241 individual pumas; live pumas were handled a total of 396 times. Seventy-eight pumas (thirty-six males, forty-two females) were initially captured with foothold snares. Another 163 pumas (eighty-one males, eighty-two females) were cubs when we initially captured them by hand. We radio-collared 126 pumas (forty-nine males, seventy-seven females). Of pumas radio-collared for the first time, sixtytwo were adults, twenty-six were subadults, and thirty-eight were cubs. We also accounted for another fifty-three to fifty-four pumas in the population that we could not tag. Forty-six were cubs; of these, we knew thirteen died while still dependent on their mothers and nine were still dependent on mothers at the close of the study. Of the remaining eight unmarked pumas, four were found dead at ages ranging from twelve to thirty months, two were detected as new immigrants at the close of the study, and one to two females (one of which may have been tagged and wearing a nonfunctional radio collar) successfully produced cubs (we visually observed one litter and found tracks of another toward the end of the study). In total, we observed 294–295 pumas on the San Andres Mountains; this constituted the largest number of pumas ever studied in a single population.

Monitoring Desert Mule Deer and Desert Bighorn Sheep To study effects of puma predation on the deer and sheep populations we had to accomplish two basic tasks: (1) monitor the dynamics of the deer and sheep populations, and (2) determine the extent of puma predation on those animals. Because our team’s efforts were mainly focused on puma population dynamics

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and predation, we relied largely on biologists of the New Mexico Department of Game and Fish and the U.S. Fish and Wildlife Service to furnish us information via annual surveys on the ungulate populations. Mule deer population composition counts gave us an estimate of the sexes and broad age classes available as puma prey, as well as an index to fawn production. Population composition was estimated by helicopter surveys carried out by Game and Fish biologists during six years and by ground-based surveys by our team during four years. Aerial and ground survey sampling techniques met or exceeded recommendations established by Humphreys and Elenowitz (1988:Appendix A) to stabilize herd composition ratios and to achieve similar (i.e., no difference in) precision in ground and aerial surveys. A minimum of twenty-five groups and one hundred does were counted in all surveys, regardless of the method. Counts were made in winter in nine years and fall in one year. Deer were classified as bucks and does older than one year and fawns of the year (born July–October). When possible, we distinguished between yearling (i.e., one year old) and adult (two years or older) deer. Helicopter-based observations were made by two experienced Game and Fish personnel in a Bell 206 Ranger or Hughes 500D. Counts were made during low-level flights between 7 a.m. and 10:45 a.m. in a one-day period. Ground-based observations were made with 7–10-power binoculars and 15–45-power spotting scopes. Ground surveys were conducted during successive days until minimal requirements were exceeded. Recounts of deer were eliminated by not counting deer whenever there was a possibility of re-observation. We estimated deer survival rates and assayed causes of mortality for a sample of 175 radio-collared deer (ninety-one bucks, eighty-four does) that were one year or older and lived in the Treatment Area during 1987–1995. We tried to maintain a pool of at least thirty radio-collared deer of each sex in the Treatment Area per year. Deer were captured throughout the Treatment Area during nine capture operations from October 1986 to October 1993. In two operations, deer were caught by using the drive net technique (Beasom et al. 1980). In the remaining seven operations, deer were caught in a net fired from a helicopter (Bell 206 Ranger or Hughes 500D). Even though radio-collared deer were dispersed throughout the Treatment Area, captured individuals and their capture locations were not intended to be random representations. Instead, capture operations were more practical—meant to capture as many deer as were needed to meet sample-size objectives with the most efficient use of personnel and equipment (i.e., money). Hence, capture efforts normally concentrated on deer that were the most conspicuous to observers in the helicopter. Deer were sometimes physically restrained. But if they required immobilization, they were injected intravenously with xylazine hydrochloride (20 mg/ml) dosed at about 1

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mg per kg estimated body mass. The drug was reversed with an intravenous injection of yohimbine hydrochloride (AntagonilTM, 5 mg/ml, Wildlife Laboratories, Fort Collins, Colorado 80524) dosed at 0.2 mg per kg body mass. Deer were examined to record sex and physical condition; a rough estimate of age was derived from dental characteristics (Robinette et al. 1957). Deer one year or older were each fitted with a collar containing a 148 or 149 MHz transmitter with a mortality mode set to turn on after two hours of constant immobility (configuration MOD-500 transmitter with S6A mortality sensor by Telonics Inc.). We included in our research only radio-collared deer that survived more than fourteen days after capture to minimize the effect that capture trauma might have on deer survival. We relied on a deterministic, discrete time model to simulate the dynamics of the deer population (see Chapter 17 and Appendix 4). Parameters of the model used the estimates of deer population composition and survival along with estimates of other characteristics gathered on the San Andres Mountains deer population and existing information from other desert mule deer populations in southern New Mexico. Desert bighorn sheep population characteristics were monitored annually by ground- and helicopter-based surveys conducted by U.S. Fish and Wildlife and New Mexico Game and Fish biologists. Observed sheep were classified as adult rams and ewes, yearling rams and ewes, and lambs (distinguished by sex when possible). However, due to funding and personnel constraints, the surveys were not conducted in a standardized fashion. Biologists made ground-based surveys in nine years using binoculars and spotting scopes to search habitats used by radio-collared sheep. During 1986 through 1989 and in 1994, ground-based counts were made by a biologist who searched for the sheep throughout each year. In 1990, 1991, and 1992, the ground-based counts were done during the month of December, 31 August to 10 September, and from May through December, respectively. A helicopter survey was conducted in 1993 by two observers in a Hughes 500D. Biologists in all surveys primarily homed on radiocollared sheep and counted and classified all sheep they observed. We monitored a total of forty-three radio-collared sheep (sixteen rams, twenty-seven ewes) from August 1985 through March 1995. The sheep were captured by Game and Fish biologists using a net-gun fired from a helicopter (Hughes 500D or Bell 206 Ranger) in ten capture operations conducted from October 1980 to October 1993. All sheep were physically restrained, then examined to record sex, age, and general physical condition. Ages of lambs and yearlings were determined from their estimated birth dates. As those individuals advanced in years, their ages were known. Otherwise, ages of adults were estimated by counting horn growth annuli (Geist 1966, Hemming 1969). Radio

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collars placed on sheep were similar to those on the collared deer. Radio-collared sheep were used to find other sheep in the population; therefore, early in the study, Fish and Wildlife and Game and Fish biologists attempted to maintain a relatively high percentage of radio-collared individuals in the population (more than 50 percent of the observed) by capturing sheep annually from 1980 through 1985, and again in 1988. However, from November 1989 to October 1993 the percentage of radio-collared sheep waned to less than 50 percent because of a temporary hands-off policy adopted by the cooperating agencies (i.e., U.S. Fish and Wildlife Service, New Mexico Department of Game and Fish, White Sands Missile Range). As with the radio-collared deer, we only used radio-collared sheep that survived more than fourteen days after capture for analysis of annual survival rates and agent-specific mortality rates.

Radiotelemetry Radiotelemetry was the channel that linked our observations of sign on the ground to real-time observations of pumas. Without it, our task of quantifying puma population dynamics would have been far more difficult. It enabled us to identify tagged individuals that made sign we found and to deduce if untagged pumas might be present. We were also able to forecast births of litters from previously recorded associations of potentially breeding pairs. Radiotelemetry made possible our detailed study of puma social organization. In addition, the technology facilitated our study of interactions between pumas and prey by helping us to find puma kills and enabling us to quantify survival rates and puma predation rates on deer and sheep. We located radio-collared pumas 13,947 times by fixing their positions from the ground (31 percent of locations) and from airplanes (69 percent of locations). Of the total, 8,490 locations were of adult pumas that lived on the San Andres Mountains study area (Fig. 4-1). The remainder were of subadults and cubs on the study area and of adults and subadults that ranged partially or exclusively on the Organ and Oscura Mountains. Ground locations were acquired opportunistically by using portable radio receivers attached to handheld directional antennas (TR-2 receiver with TS-1 scanner/programmer, RA-2A antenna by Telonics Inc.) to take line-of-sight bearings on the strongest aural signal from the transmitter. Three or more bearings taken from different locations were mapped on 7.5-minute-series topographic maps. Plotted bearings produced a triangle or polygon. The approximate geometric center of the triangle or polygon was plotted to represent the location of the radio-collared puma and was recorded as Universal Transverse Mercator (UTM) grid coordinates to the nearest 0.01 km. Error around each location was estimated by using the distance (m)

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FIGURE 4-1. Locations of resident adult pumas on the San Andres Mountains, New Mexico, 1985–1995. We obtained 8,490 locations between the north and south study area boundaries; of those, 99 percent were also within the east and west boundaries. Another 304 locations were obtained in the Organ and Oscura Mountains.

from the center of the triangle or polygon to the most distant vertex. This distance was used as the radius of a circle that contained the location of the puma (Saltz and Alkon 1985). We flew in light fixed-wing aircraft (Cessna 182, 172 XP, or T337) 370 times and logged 1,852 hours to locate radio-collared pumas. Normally we flew once each weekend, but sometimes flights were canceled because of poor weather or

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White Sands Missile Range missions. In each flight, we attempted to locate all of the radio-collared pumas on the study area, as well as dispersing individuals; their numbers varied from ten to forty pumas. Aircraft were rigged with directional antenna mounted on each wing strut, which were connected via coaxial cables to an antenna switch box, a receiver with scanner, and the intercom system. Aerial locations of radio-collared pumas were fixed at sites where we made at least three passes over peak aural signals. The puma’s location was recorded as a UTM coordinate to the nearest 0.01 km. Variations in terrain at puma locations and differences in our flight altitude as influenced by terrain and air turbulence created error in our fixes, which we estimated by flying concentric circles around the locations to mark where the signal waned. We expressed this error as a radius (m) of a circle around the fixed location. Accuracy of radiotelemetry locations was tested during the first three years at 173 of 2,170 locations by finding test collars, puma sign at the locations, dropped collars, dead pumas, and by subsequently walking in on pumas to see them. In all instances the radio collars were within the error radii of the locations (Sweanor 1990). Thereafter, we confirmed radiotelemetry locations on an opportunistic basis by using the same techniques. All of our recorded radiotelemetry locations had estimated error radii of 500 m or less, and 91.5 percent of the locations had error radii of 300 m or less. At all actual puma locations and radiotelemetry locations with error that included single or co-dominant vegetation cover types, we recorded the vegetation and terrain features. Elevation was recorded as indicated on the 7.5-minute-series topographic maps (converted to meters); we also noted the aspect and percent slope (measured with a USGS Topo Map Land Area and Slope Indicator, Reproduction Specialties, Inc., Denver, Colorado 80222). By walking in on free-ranging radio-collared pumas (i.e., they we re not caught in snares), we we re able to visually observe 579 individuals in 287 observations, the most that wild pumas have been viewed during a study. The desert mountains, with their re l a t i vely low, sparse vegetative cove r, made it easier for us to safely approach and visually observe pumas. Normally, we attempted observations of mothers to locate their nurseries and to get initial counts of n ewborns. Subsequently, we approached families to count cubs for surv i va l estimates. In addition, we would sneak in on pumas to see if they made a kill, to check on their physical state after being captured, or to see if consort pairs we re actually together. We also checked the well-being of some newly independent subadults. We usually approached pumas from upslope and when possible from a promontory, such as a cliff, rock outcrop, or boulder pile. Our aim was to gain a visual advantage from a safe distance to observe the cats without causing them

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to move from their chosen locations. We hoped our upslope position also would enable us to appear ominous to pumas that detected us and leave them an easy escape route downslope if they chose to flee. We usually approached in groups of two or more people, but sometimes we were alone. We looked for the slightest movements and kept our hearing trained on two dimensions—listening for the minutest variation in the signal from the radio receiver and listening for any sound from the pumas. Our closest approaches unintentionally brought us to within 5–10 m of pumas. Sometimes, because boulders or rock outcrops shielded transmitter signals at close range, we accidentally got too close before we saw the cats. Sometimes pumas would slink silently away, using any terrain, vegetation, or large rocks for cover. Other times they simply froze except for moving their eyes, ears, or heads to track our every move. Some, in ultra-slow-motion, shifted their bodies into position to watch us. Others slowly positioned their bodies and gathered their feet beneath them, then bolted away. Steadfast ones seemed secure in cover, but watched us intently; a few individuals seemed totally aloof and fell asleep. Only during six close encounters were we threatened by pumas. In every case, females were probably trying to protect their three- to twelve-week-old cubs. Three mothers charged us but aborted their rushes as we stood our ground, yelled at them, and, twice, defended ourselves with a wooden stick or a metal catchpole. One mother stalked Frank head on, approached to within 5 m, and seemed unfazed even when Frank discharged his .22 magnum pistol twice in the air. The puma turned away only after Frank stepped onto a ledge that elevated him about 0.5 m higher than the level of the puma. Two females growled at us as they lay prone at their nursery, feet set beneath them, head and ears perked toward us, eyes locked onto ours. In the latter two instances, we sensed attacks were probably imminent, so we retreated by slowly backing away. Usually we observed families that were unaware of our presence or were apparently indifferent to it. This allowed us unique opportunities to watch cubs interact with their mothers and siblings. We employed similar radiotelemetry techniques on radio-collared deer and sheep. This enabled us to find puma kills and to directly estimate annual survival rates and rates of death attributed to puma predation or other causes. We monitored the status (alive or dead) of radio-collared deer and sheep from the ground on a weekly basis. In addition, we flew in airplanes monthly to check the status of all the radio-collared animals and to specifically search for any animals we may have missed from the ground. When transmitters indicated death by emitting a twofold increase in beat frequency, we investigated. If animals were dead (sometimes the transmitters temporarily failed), we performed necropsies to determine probable proximate causes of death.

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Investigating the Dead To determine the most influential mortality factors to the puma, deer, and sheep populations in our study, we tried to ascertain why animals died. We also recorded other pertinent information, including sex, age, and, when possible, the physical state of the animal prior to death. Extremely high ambient temperatures, especially during May through September, caused such rapid decomposition of carcasses that trying to ascertain condition prior to death was practically impossible unless we found the animals within hours of death. For pumas that were dead less than twenty-four hours and died for reasons that were obscure to us, we collected organ tissues and sent them to the New Mexico Department of Agriculture Veterinary Diagnostic Services in Albuquerque to assay cause of death. Specific criteria were used to categorize dead prey animals as puma prey, probable puma prey, and animals that died of other causes. In our analysis of the effects of puma predation on deer and sheep, we combined the categories of puma prey and probable puma prey. Animals that died of other causes were not associated with any evidence that implicated pumas as the proximate cause of death. By using these categories, we could assess the strength of puma predation as a limiting factor of deer and sheep relative to other nonpredator causes of mortality. We classified animals that were undoubtedly killed by a puma as puma prey. Evidence for puma attack and consumption included puma canine punctures to the back of the neck, the throat, or the head; puma feeding patterns (i.e., plucking or cropping of hair with the incisors, opening of the carcass first at the abdomen or thorax and consumption of vital organs, expulsion of the stomach, consumption of bones, breakage of large bones); puma tracks in an attack sequence or at the cache; puma feces, scrapes, or prey carcass drag line; and coverage of the prey with ground debris (e.g., soil, leaves, sticks). Some animals we found dead were in such advanced states of decomposition or consumption that we could not find puma canine punctures. But because other evidence pointed to puma predation, we called them probable puma prey. Evidence included puma feeding patterns; puma tracks, feces, or scrapes; prey drag lines; and coverage of the prey with ground debris. We also collected puma feces and contents of puma stomachs opportunistically, noted the exact circumstances of their deposition (e.g., random find, association with a specific kill or puma, location and habitat features), and air dried them. They were analyzed by Mike Elmer at the University of Idaho. He provided us a detailed analysis of the diet of pumas on the San Andres Mountains (Elmer 1997).

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In the course of our field research, we kept detailed journals of our day-today activities as well as data forms on each of our observations. We had specific data forms for captured animals, puma locations, and status of radio-collared deer and sheep, and for pumas and prey animals that died. We transferred data on forms to electronic databases that we used to facilitate our analyses by computer.

Overview of Analytical and Statistical Methods Exact analytical and statistical techniques that we used are included in each of the following chapters addressing the findings of our field research. We used parametric statistical methods (Zar 1984) where samples were large (i.e., sample sizes were twenty-five or more, or approached the absolute population) and data appeared to be normally distributed when checked by eye against a normal distribution plot generated by SYSTAT 7.0 (SPSS Inc., Chicago, Illinois). When we could not meet assumptions of normality or equal variances for parametric tests, or if sample sizes were small, we used non-parametric tests (Daniel 1978). Most statistical tests were performed using SYSTAT 7.0 or SAS 6.11 (SAS Institute Inc., Cary, North Carolina). Tests for differences between means or distributions are typically 2-tailed unless specified. Experimental errors were controlled at the 0.10 level of significance because we usually had small sample or population sizes, which are characteristic of large-carnivore studies. The higher alpha level reduces the probability of a Type II error (i.e., failing to reject a null hypothesis that is false) and increases the probability of detecting a change. We note statistical tests in the text by bracketed numbers (e.g., [1]) and report the corresponding results in a special section at the end of each chapter. We typically report mean statistics with ± 1 standard deviation (SD) to express variability of the measurement. Sample size (n) is reported for readers wishing to calculate the standard error. In addition, we provide a summary at the end of chapters in Parts 2–5.

P a rt I I

Puma Life History Strategies and Population Dynamics

Chapter 5

A Puma Population in the Desert

Reliable information on puma life-history traits and population dynamics has been described for pumas in more-northern temperate and contiguous habitats in North America (Hornocker 1970, Seidensticker et al. 1973, Lindzey et al. 1989, Lindzey et al. 1994, Ross and Jalkotzy 1992). But before our study, very little was known of puma populations in the Southwest deserts of North America. Naturally, much of our information on puma population dynamics in the desert is descriptive. In addition, we contrast puma population dynamics and life-history traits in a Treatment Area, where we experimentally reduced the number of pumas, with those on a Reference Area. The basin and range physiography of much of the Southwest naturally fragments puma habitat and may contribute to dynamics that are different than those observed in more contiguous puma habitats. We discuss similarities and differences of pumas on our desert study area with pumas in other populations in North American habitats, and we try to explain them in the context of evolutionary ecology.

Research Hypotheses and Predictions Meager quantitative information on life-history traits and population dynamics of pumas and other solitary-living large felids, such as tigers, leopards, and jaguars, constrained our hypotheses to a few published postulates and to natural phenomena that emerged during our study. We address these specific research hypotheses in the appropriate sections in this chapter. 1. Puma mothers tend to have more litters during the period of maximum 63

64

2.

3.

4.

5.

6.

7.

PART II. PUMA LIFE HISTORY STRATEGIES AND POPULATION DYNAMICS

food abundance. A birth peak should coincide with the fawning period for mule deer, the primary prey of pumas. Pumas kill other pumas to benefit individual survival and reproductive success. Thus, male pumas, who do not take part in raising young, should kill other pumas for food, territory, and mates. But puma mothers, who solely raise young and cannot afford debilitating injury from aggressive encounters, should avoid killing other pumas. Intraspecies strife is density dependent. Frequency of intraspecies killing of independent pumas should increase with density. We examined three hypotheses (hypotheses 4–6 below) on the evolution of the timing of progeny independence from mothers: Timing of independence reduces competition for the mother’s time and energy budgets required for mating, pregnancy, and rearing more progeny. Thus, cubs should become independent when they are physically able to survive on their own and about the time that their mother is ready to breed again (i.e., when she comes into estrus). Timing of independence reduces physical harm to cubs from aggressive males seeking to mate with the cub’s mother. Cubs should become independent before their mother comes into estrus and attracts dangerous males. Timing of independence reduces inbreeding between male offspring and their mothers. Male progeny should reach puberty about the time they became independent from their mothers. Dispersal of puma progeny is independent of adult density (Seidensticker et al. 1973). Thus, all progeny should disperse from their natal areas.

In addition, we investigated puma dispersal patterns so that we could test three hypotheses pertaining to how dispersal affects fitness, discussed in the Chapter 13 section “Why Do Pumas Disperse?”

Terms for Pumas Terms we used for pumas in our study population depended upon their sexual maturity, maternal dependence, site attachments, and place of origin. Adults were pumas that bred or reached the average age of known breeders in the population. Subadults were independent of their mothers’ care but were apparently not yet capable of successful breeding. Cubs were offspring that were dependent on mothers for food and protection. Residents showed site attachment (i.e., continuous use of an area over time). The area where a puma restricted the majority of its movements was considered its home range. Cubs that became subadults and left the boundaries of their natal home range were considered dispersers.

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65

Cubs that established home ranges post-independence that overlapped more than 5 percent of their natal home ranges (based on the 90 percent Minimum Convex Polygon) were considered philopatric (see Chapter 13). Immigrants were pumas that dispersed from some other locality in New Mexico and moved onto the San Andres Mountains; they subsequently established residency. Recruits were either progeny born in the San Andres Mountains puma population or immigrants that entered the resident adult portion of the population. An emi grant was an individual that dispersed completely outside of the San Andres Mountains study area.

Counting Pumas Through our intensive field efforts, we strove to make accurate estimates of the puma populations in both the Treatment Area and the Reference Area for each year. In essence, we tried to census the population. This enabled us to quantify puma population dynamics and vital rates and to relate puma population characteristics to traits of puma social organization and deer and sheep population characteristics. But quantifying puma numbers is a formidable task. Their low densities distributed over complex habitats requires extensive time in the field to quantify numbers by capturing and marking individuals. Furthermore, puma births, deaths, emigration, and immigration can occur year round. Consequently, it was impossible to meet most of the assumptions for capture-markrecapture methods to estimate abundance. Consider the simplest method of all, the Peterson Method, which assumes (1) the population is closed so that the population number is constant during a sampling period, (2) all animals have the same chance of getting caught in the first sample, (3) marking individuals does not affect their probability of recapture, (4) animals do not lose marks between the two sampling periods, and (5) all marks are reported upon discovery in the second sample (Krebs 1999). First, we could not trap for pumas in the Treatment and Reference Areas in a shortenough sampling period to exclude population change; thus, we would violate assumptions 1 and 2. Moreover, differences in survival, behavior, and area of use of territorial males and maternal and non-maternal females would likely affect probability of capture, again violating assumption 2. Second, we learned that pumas became trap-shy after their first capture (Logan et al. 1999), thus violating assumption 3. We could only meet assumptions 4 and 5. For many of these same reasons, we also could not meet assumptions for somewhat more complex techniques for open populations (see Krebs 1999:49). Thus, we had to rely upon more direct methods of quantifying the population and for gauging the accuracy of our estimates. We developed a puma population chart that tracked the lives of all individ-

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PART II. PUMA LIFE HISTORY STRATEGIES AND POPULATION DYNAMICS

uals observed. We examined data on captured pumas, radiotelemetry, puma tracks, and visual observations of untagged pumas. Initially, all adult and subadult pumas captured for the first time were entered on the chart beginning with their date of capture. Cubs were entered on the chart at their estimated birth date. We extended the lifelines on each individual to their known or estimated dates of death, emigration from the population, or disappearance. We also refined the lifelines on adult pumas on the chart as we learned more about when they might have entered the adult population. We estimated absolute densities of adult pumas (i.e., breeders) based on these assumptions and empirical ontogenetic data that we accumulated during the research. First, we assumed that all independent pumas captured for the first time and less than thirty-six months old had just entered the population. However, pumas captured for the first time that were thirty-six months or older were assumed to have entered the population as adults at an earlier date. Thus, we adjusted the estimates of the adult puma population to include those individuals that we had probably missed during previous years. We defined entry dates for the latter group by (1) ages of known-age and approximately known-age males and known-age females when they reached adulthood, and (2) the mean ages of independent male and female pumas less than thirty-six months old captured for the first time and considered to be new recruits to the population. Four female pumas that were not captured were charted into the population because we were able to monitor their movements through a combination of tracks (all four females), associations with radio-collared offspring (two females), associations with radio-collared males (one female), and visual observations of a female and her cubs (one female). Two other adult female pumas, twenty-four and thirty months old, were never radio-collared because they were dead when we observed them. It is possible that the older female was marked, but because she was severely decomposed, we did not find a tattoo. A woodrat, fox, or raven could have easily hauled away her eartag. We charted these two females into the population at their estimated date of death. For female pumas thirty-six months or older, we used twenty-one months of age to define when they entered adulthood in the population. Our criteria were based on (1) the mean age of 21.4 ± 3.1 months for seven known-age females when they first associated with adult males (see “Puberty and First Litters” in Chapter 7), and (2) the mean age of 21.4 ± 2.6 months for eighteen approximately known-age female immigrants that were less than thirty-six months old when first captured. For male pumas thirty-six months or older, we used twenty-four months of age to define when they entered adulthood in the population. Our criteria were based on (1) the mean age of 24.3 ± 2.5 months for one known-age and four

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67

approximately known-age male pumas when they first associated with adult females, and (2) the mean age of 23.9 ± 6.3 months for seven known-age males when they arrived in the area where they established their first territory. In addition, we developed a percent accuracy (PA) from the data on the chart to estimate the accuracy of our annual (January–December) counts of adult pumas in the population. Our equation was: PA = [1 – BLyear i / (BLyear i + Cyear i)] x 100 where BLyear i = the number of adult pumas backlogged into year i, and C year i = the number of adult pumas actually counted (i.e., radio-collared or observed) during year i. The proportion BLyear i / (BLyear i + Cyear i) x 100 estimated the percentage of adult pumas we missed in annual counts. The PA helped us to gauge how well we were meeting our operational objective of counting all of the adult pumas on the study area. The number of adult pumas thirty-six months or older when first captured, and which we backlogged into the population to probable entry dates (i.e., dates of sexual maturity), ranged from zero to three per year in the Treatment Area and from zero to eight per year in the Reference Area (Table 5-1). Understandably, the highest numbers of backlogged adults came during the first full years of the study (1986, 1987) when we were developing our capture and search techniques on the study area. By January 1988 we were thoroughly canvassing the Treatment Area, but that stage did not come for the Reference Area until the latter half of 1988. During the span 1988–1994, the numbers of backlogged

Table 5-1. Percent accuracy (PA) for the estimated number of adult pumas per year, 1986–1994, in the Treatment Area (TA) and Reference Area (RA), San Andres Mountains, New Mexico. Area TA RA

M:Fa PAb M:F PA

1986

1987

1988

1989

1990

1991

1992

0:3 70 5:3 33

1:2 77 2:2 66

0:1 93 0:0 100

0:0 100 1:2 87

0:0 100 1:2 88

0:0 100 2:2 86

0:1 93 1:1 93

1993 1994 0:1 94 1:1 94

0:0 100 0:0 100

aThe number of males (M) and females (F) signifies the number of adults in each sex that we apparently missed in our capture efforts each year. We assumed that all pumas that were thirty-six months or older when first captured had entered the adult population at an earlier date. Those pumas were backlogged into the population chart to the month that females were twenty-one months old and males were twenty-four months old (see text for explanation and empirical criteria). bPercent accuracy = 1 – number of pumas backlogged / number of adult pumas counted plus adult pumas backlogged per year ¥ 100. PA estimates the minimum proportion of the adult population counted each year.

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PART II. PUMA LIFE HISTORY STRATEGIES AND POPULATION DYNAMICS

adults dwindled to 0–1 in the Treatment Area and 0–4 in the Reference Area. We missed four adults in 1991, probably because we spent all of our efforts removing pumas from the Treatment Area until June 1991. The average annual PAs during the 1988–1994 span for the Treatment and Reference Areas were 97 percent and 93 percent, respectively. The population estimates that we report for the Treatment Area begin in 1988, but our estimates for the Reference Area begin in 1989. All our population tables and figures will show the adjusted estimates for the adult puma population for each area. Consequently, our annual estimates of adult pumas probably approached 100 percent of the adult pumas actually present. By charting the population, we were able to make three puma density estimates: (1) We estimated adult and total puma density in January each year (1988–1995 in Treatment Area, 1989–1995 in Reference Area); this was our point estimate that coincided with New Mexico’s puma hunting season (December–March). (2) We estimated adult puma density for each annual period (January–December, 1988–1994 in Treatment Area, 1989–1994 in Reference Area); this represented the number of pumas present throughout an entire year. (3) We estimated annual adult puma density during August–July from 1987 to 1994 in the Treatment Area and from 1988 to 1994 in the Reference Area to coincide with the biological years for pumas and mule deer, which we began in August to coincide with birth pulses for the two species. Radio-collared pumas that lived along the boundary of the Treatment and Reference Areas or that moved out of the San Andres Mountains at the north and south ends of the study area were included in the Treatment Area or Reference Area based on the proportion of their aerial locations recorded in each area during each twelve-month period. For example, a puma located fifteen times in the Treatment Area and twenty-eight times in the Reference Area during one year would be assigned values of 0.39 and 0.61 for each area, respectively. Cubs were included in areas in identical proportions to their mothers. For the annual adult density estimates, we also determined the proportion of time per year that pumas were present on the areas. For example, a puma that apportioned its annual activities by 75 percent in the Treatment Area and 25 percent in the Organ Mountains (south of the study area) but was alive for 60 percent of the year was assigned a value of 0.45 in the Treatment Area for that year. To get the total annual adult density, we summed the proportions for all the adults in the respective areas. We quantified these densities for each area per year and for each area per year per 100 km2. All these methods of quantifying pumas were essential to describing puma population dynamics and how puma numbers related to puma behavior and social organization and to prey population dynamics.

Chapter 6

Puma Population Structure

Sex Structure The most distinguishing attribute of an individual within a population is its sex. As we will explain later, a puma’s sex defines its behavior and how it interacts with other pumas in the population. Examining the sex structure of the population from birth to older life-stages helped us to understand consequences of other population characteristics, including reproduction, survival, population growth, and social organization.

Cubs The sex ratio of puma offspring at birth represents the secondary sex ratio (primary sex ratio is at zygote formation, tertiary sex ratio is at puberty). Overall, male and female cubs were born into the population in equal proportions, a characteristic found in most sexually reproducing vertebrates (Ricklefs 1990). We observed 210 cubs in seventy-six litters. Three other litters with about ten cubs died shortly after birth, before we were able to examine the cubs. We handled 148 nursing cubs in fifty different litters in which we examined all the cubs when they were nine to forty-nine days old (x– = 31.6 ± 8.6); there were seventyfive males and seventy-three females, the equivalent of a hypothetical 1:1 primary sex ratio. In another fifteen weaned litters with cubs 52 to 427 days old (x– = 198.9 ± 121.6) there were fourteen males and twenty females, but the male:female ratio did not differ from 1:1 [1]. In weaned litters, we suspected

69

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PART II. PUMA LIFE HISTORY STRATEGIES AND POPULATION DYNAMICS

that some postnatal mortality had occurred. Theoretically, equal sex ratios of offspring suggests there is a tendency for equal parental investment in each sex (Trivers 1985). The sex ratio of puma offspring on the San Andres Mountains was similar to the sex ratio of 1.1 males to 1.0 females that Lopez-Gonzalez (1999) reported for twenty puma litters in southern Idaho. It was also similar to more limited information on cubs from other captive and wild populations. Robinette et al. (1961) reported twelve male and twelve female cubs born at the National Zoological Park. Likewise, in the central Idaho wilderness, Seidensticker et al. (1973) found twelve male and twelve female cubs that were various ages when they were first observed. Information from other wild populations were also of cubs representing a wide range of ages where postnatal mortality may have affected observed sex ratios. Even though there were more males than females in two studies (Ashman et al. 1983, Spreadbury 1989) and fewer males than females in two other studies (Logan et al. 1986, Ross and Jalkotzy 1992), none of the ratios was significantly different from 1:1. A closer look at our data indicated sex ratio was female biased in first litters, but more males were born in subsequent litters. In fifteen first litters of knownage (n = 8) and approximately known-age (n = 7) mothers in which we sexed all the cubs, there were seventeen males and twenty-eight females. In contrast, there were forty-five males and thirty-five females in twenty-seven subsequent litters produced by nineteen mothers. In the latter group, we did not have a complete record of the reproductive history of the females; some of them might have produced litters prior to our research. Therefore, we discounted each female’s first observed litter, in case it was actually her first, and used only her subsequent litters; these probably represented second to fourth litters. All cubs in both groups were nurslings ranging in age from eighteen to forty-nine days old. Sex ratios in first litters differed from sex ratios in subsequent litters [2]. We looked even more carefully at the sample of mothers for which we had complete reproductive histories to compare sex ratios of their first and subsequent litters. In eight first litters, there were eight male and nineteen female cubs; but in twelve subsequent litters (i.e., second to fourth litters) there were twenty male and eighteen female cubs. Not only was the sex ratio in the first litters different than that in the subsequent litters [3], but also it was different from 1:1 [4]. The number of cubs in first litters (x– = 3.4 ± 0.7) and subsequent litters (x– = 3.2 ± 0.6) were similar. The secondary sex ratio may be influenced by the physical state of female pumas on the San Andres Mountains. We examined masses of nine females (for which we had data) when they were eighteen to twenty-four months old (x– = 20.8 ± 2.2), near the approximate age of puberty (see Chapter 7, “Puberty and

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71

First Litters”) and when they were twenty-eight to sixty months old (x– = 42.2 ± 10.7), and found that they gained mass (mean difference = 3.0 ± 2.5 kg) [5]. This suggests that puma mothers were still growing when they produced their first litters. Hence, there may be a physiological trade-off involving allocation of energy and nutrients for continued somatic growth of the mother, and investing in less-costly female offspring while optimizing litter size (Sibly and Calow 1986, Stearns 1992). Not only are first-time mothers probably growing, but also they likely are inexperienced in raising offspring, and relative to older established females are not as familiar with resources (i.e., food, nurseries) in their home ranges that are vital to the provisioning and safety of young. Without these physiological and behavioral constraints, full-grown, older mothers can invest more in male offspring. Hence, over their reproductive life span, mothers may invest approximately equally in the sexes. In fact, male puma cubs are generally larger than female cubs. When we examined masses (kg) of 108 nursling cubs (eighteen to forty-nine days old) in thirty-five mixed-sex litters and made eighty paired comparisons of masses between male and female siblings within each litter, we found that males outweighed sibling females in forty-nine comparisons (61 percent); male and female sibling masses were equivalent in twelve comparisons (15 percent); and males weighed less than female siblings in nineteen comparisons (24 percent). Masses of male and female cubs within litters diverged in favor of males at about

FIGURE 6-1. Masses of puma cubs, San Andres Mountains, New Mexico, 1986–1994.

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PART II. PUMA LIFE HISTORY STRATEGIES AND POPULATION DYNAMICS

twenty days of age (Fig. 6-1). Other puma biologists have also quantified that male cubs grow larger than female cubs throughout the period of parental investment (Robinette et al. 1961, Maehr and Moore 1992). Hence, male cubs should be more costly for mothers to produce and rear successfully than females. The actual proximate mechanism at work to adjust sex ratio in mammals is not known (Clutton-Brock and Iason 1986, Hiraiwa-Hasegawa 1993, Krackow 1995, James 1996). But two physiological mechanisms have been suggested that may work throughout pregnancy and even before zygote formation to skew sex ratios (Krackow 1995). First, sex-specific embryonic mortality may occur, thus favoring the survival of one sex at birth. This has been linked to steroid hormone levels during pregnancy in laboratory rodents. We would expect that if this mechanism were operating in pumas, then litter sizes for mothers producing their first litters would be smaller than for older mothers. But we found that litter sizes for first litters and subsequent litters were about the same. The second mechanism involves the relative time of insemination within the estrus cycle. This has affected the sex ratio at birth in a variety of mammals (e.g., rabbits, white-tailed deer, humans), and no evidence of fetal loss has been found to account for sex ratio variation. Levels of maternal gonadotropin and steroid hormones at the time of conception and attendant uterine activity may mediate sex-specific sperm selection (Clutton-Brock and Iason 1986, Krackow 1995). Maternal gonadotropin includes two types of hormones, follicle stimulating hormone (FSH) and luteinizing hormone (LH), which are secreted by the pituitary gland located at the floor of the brain and act on the ovary. FSH induces follicular development and secretion of estrogen. LH induces ovulation and stimulates formation of the corpus luteum in the ovary, which manufactures estrogen and progesterone. Steroid hormones include progesterone, estrogen, and testosterone. James (1996, 2000) reviewed data on mammals (including humans) showing that a high proportion of female offspring is associated with high maternal levels of gonadotropin and progesterone at the time of conception. Based on our observations on relative litter sizes, lengths of estrus periods, lengths of associations between breeding pairs, and the numerous copulations exhibited by breeding puma pairs (Eaton 1976), the second mechanism seems more plausible for pumas. Our observations of differential sex ratios in first litters and subsequent litters might be an intra-population phenomenon. Future intensive puma research that quantifies sex ratios of offspring in females with known histories in other populations could test this hypothesis. Certainly, as other researchers ponder explanations for adjustment in sex ratios, other hypotheses may emerge (see Trivers and Willard 1973, Clutton-Brock and Iason 1986, Kruuk et al. 1999, Nunn and Pereira 2000).

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73

Subadults Subadults comprised a smaller proportion of the total population probably because of mortality and emigration, which also made it more difficult to quantify this population segment. Consequently, we quantified subadult sex ratios from the total number of subadults observed during January population estimates from 1988 to 1995 in the Treatment Area and from 1989 to 1995 in the Reference Area. Subadult sex ratios for the Treatment Area (n = 5–6 males, 10–11 females) and the Reference Area (n = 8 males, 10 females) were 1:1.17–1:2.2 and 1:1.2, respectively. None of the ratios was significantly different from 1:1 [6], probably because of small sample sizes. But like those of the weaned cubs, the sex ratio of subadults tended to have fewer males than females. In this age class the divergence was probably linked to greater mortality and emigration rates among males (see Chapters 8 and 9). Very rarely has published literature on pumas clearly quantified the sexes of independent subadults in a manner that allows comparisons with the pumas on the San Andres Mountains, again reflecting the difficulty in quantifying these data. A notable exception was Ross and Jalkotzy’s (1992) study of an increasing and moderately hunted puma population in Alberta, Canada, where they observed nine male and nineteen female subadults. Their findings generally agree with our observations in the Treatment Area.

Adults Adult males were outnumbered by adult females as well (Table 6-1). The maleto-female ratio for adults observed each year (1988–1994) averaged 1:1.4 for the Treatment Area, which was very near the average of 1:1.6 for the Reference Area (1989–1994). Sex ratios of adults were not significantly different from a hypothetical 1:1 ratio in all annual comparisons within the Treatment Area and the Reference Area [7]. Adult sex ratios computed from January population estimates from 1989 to 1995 produced almost identical results (Table 6-2). Mean sex ratios for the Treatment and Reference Areas were 1:1.5 and 1:1.4, respectively. Again, none of the annual comparisons of adult sex ratios in either area were significantly different from 1:1 [8]. The sex ratio of the population of adult pumas that we observed each year was representative of the sex ratio in the entire population because we were observing 86 percent or more of the adult population in each area each year. Before and after the removal of adult pumas from the Treatment Area, adult females were favored numerically, regardless of whether the sex ratio was quantified annually or each January. In addition, by the time the Treatment Area recovered from the experimental removal thirty-one months later, the exact adult sex ratio was restored (see Chapter 10). This suggested that adult pumas that were removed were replaced in kind.

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Table 6-1. Sex ratios of adult pumas in the Treatment Area and Reference Area each year, 1988–1994, San Andres Mountains, New Mexico. Year 1988 1989 1990 1991 1992 1993 1994

Treatment Area a Reference Area a Observed M:F b Operational M:F c Observed M:F b Operational M:F c 1:1.4 1:1.3 1:1.4 1:1.4 1:1.8 1:1.4 1:1.1

1:0.9 1:0.9 1:1.3 1:1.1 1:1.2 1:0.9 1:0.8

1:1 1:1.6 1:1.7 1:1.6 1:1.6 1:1.5 1:1.3

1:0.9 1:0.9 1:1.1 1:1.2 1:1.2 1:1 1:0.7

aIndividuals that overlapped the Treatment Area-Reference Area boundary were counted in both areas. bSex ratios were determined for the number in each sex counted during an entire 12-month period. cOperational sex ratio represents the number of females available for breeding per male in a 12-month-period.

Ob s e rved adult puma sex ratio in our study population, as well as others in North America, indicate a pattern of fewer males than females (Se i d e nsticker et al. 1973, Shaw 1977, Logan et al. 1986, Hopkins 1989, Maehr et al. 1989, Sp re a d b u ry et al. 1996, Ross and Jalkotzy 1992, Beier and Barrett 1993, Lindzey et al. 1994). There are at least three biological reasons for the pattern in adult pumas: (1) Males and females are born into the puma population in equal pro p o rtions on average. But as subadults, male pumas have higher mortality rates than females, hence, fewer males are available as potential re c ruits (see Chapter 8). (2) Females are recruited into the adult population at higher rates than are males (see Chapter 10). (3) Pumas have a polygynous and promiscuous mating system where the dominant males breed with s e veral females (see Chapter 7). Males engage in intense, agonistic competition for access to mates and territory, and males attempt to cover large areas of terrain to pursue mates, both of which affect the spatial distribution of males. This tends to space adult males out over larger areas in relation to females (see Chapter 12). Mate competition may be enhanced by the operational sex ratio—the ratio of adult males to adult females available for breeding each year (Tables 6-1, 62). We excluded females unavailable for breeding because they were rearing cubs that were born in the previous year, unless those cubs reached independence or

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75

Table 6-2. Sex ratios of adult pumas in the Treatment Area and Reference Area each January, 1989–1995, San Andres Mountains, New Mexico. Treatment Areaa Reference Areaa Year Observed M:F b Operational M:Fc Observed M:F b Operational M:Fc 1989 1990 1991 1992 1993 1994 1995

1:1 1:2 1:1.4 1:1.3 1:1.8 1:1.4 1:1.3

1:0.7 1:1.2 1:0.3 1:0.7 1:0.6 1:0.9 1:0.4

1:0.9 1:1.6 1:1.6 1:1.7 1:1.4 1:1.4 1:1.4

1:0.1 1:0.9 1:0.6 1:1.1 1:0.6 1:0.7 1:1.1

aIndividuals

that overlapped the Treatment Area–Reference Area boundary were counted in both areas. bSex ratios were determined for the number of adult pumas in each sex counted in January each year. cOperational sex ratio represents the number of females available for breeding per male in January each year.

died and the female rebred and bore cubs in the tally year. Average operational sex ratios in the Treatment Area and Reference Area were identical, 1:1. In general there were as many years when there were slightly more adult males available per breeding female as there were years when there were slightly more breeding females available per male. In reality, at any one point in time, the operational sex ratio is even higher because the proportion of pregnant or cubrearing females is higher. For example, in January of each year, the average operational sex ratio in the Treatment and Reference Areas was identical, 1:0.7, and highly variable (Table 6-2). Normally, there were more adult males available than there were potential female mates. With these ratios, intense male-to-male competition for mates should be expected in the polygynous, promiscuous mating system of pumas (see Chapters 7 and 8).

Age Structure Another important distinguishing attribute of an individual is its age. Generally speaking, the age of an individual puma influences its survival, reproductive capacity, and social status. Thus, the age structure of the puma population influences the capacity for population growth.

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FIGURE 6-2. Age structure of the puma population in the Treatment Area and Reference Area each January, 1989–1995, San Andres Mountains, New Mexico.

The Population We quantified the proportions of adults, subadults, and cubs in the Treatment Area and Reference Area for each January from 1989 to 1995 (Fig. 6-2). The greatest proportion of the puma population was composed of adults, followed by cubs, and then subadults. In the Treatment Area (Table 6-3), adult males and females comprised a mean proportion of 0.23 ± 0.07 and 0.33 ± 0.08 of the population, respectively. Total adults (males plus females) comprised a mean proportion of 0.56 ± 0.13, subadults a mean of 0.10 ± 0.09, and cubs a mean of 0.34 ± 0.10 of the population. After discounting the first January population estimate following the experimental removal of pumas in the Treatment Area (1992), the mean proportions of the three major age classes in the population were as follows: adult males = 0.25 ± 0.06, adult females = 0.36 ± 0.05, total adults = 0.61 ± 0.08, subadults = 0.07 ± 0.07, and cubs = 0.32 ± 0.10. In the Reference Area (Table 6-4), adult males and females comprised a mean proportion of 0.26 ± 0.03 and 0.35 ± 0.07 of the population, respectively. On average, adults together comprised 0.61 ± 0.09, subadults 0.06 ± 0.02, and cubs 0.33 ± 0.08 of the population. Based on the three broad age classes, the average annual age structure in the Treatment Area and Reference Area were similar.

Table 6-3. Proportion of pumas in three broad age classes in the Treatment Area population each January, 1989–1995, San Andres Mountains, New Mexico. Year 1989 1990 1991 1992 1993 1994 1995 Mean ± SD

Males

Adults Females

Total

Subadults

Cubsa

.32 .20 .25 .14 .17 .30 .25 .23 ± .07

.32 .41 .36 .18 .31 .42 .32 .33 ± .08

.64 .61 .61 .32 .48 .72 .57 .56 ± .13

.18 .12 .04 .23 .10 0 0 .10 ± .09

.18 .27 .36 .45 .41 .28 .43 .34 ± .10

aProportion

of cubs was calculated using the mean of the range of the estimated number of cubs present.

Table 6-4. Proportion of pumas in three broad age classes in the Reference Area population each January, 1989–1995, San Andres Mountains, New Mexico. Year 1989 1990 1991 1992 1993 1994 1995 Mean ± SD aProportion

Males

Adults Females

Total

Subadults

Cubsa

.27 .24 .25 .23 .22 .26 .32 .26 ± .03

.24 .38 .34 .38 .30 .35 .46 .35 ± .07

.51 .62 .59 .61 .52 .61 .78 .61 ± .09

.07 .06 .03 .05 .10 .09 .05 .06 ± .02

.42 .32 .38 .33 .38 .30 .16 .33 ± .08

of cubs was calculated using the mean of the range of the estimated number of cubs present.

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PART II. PUMA LIFE HISTORY STRATEGIES AND POPULATION DYNAMICS

Unfortunately, almost all other literature that reports puma age structure does not use similar age classes to ours; hence, comparisons with our study population were impractical. Only the study of a moderately hunted, increasing Alberta puma population yielded similar data (Ross and Jalkotzy 1992). During five years, the population age structure averaged about 48 percent adults, 19 percent subadults, and 34 percent cubs.

Adult Pumas We estimated the ages (in months) of adult pumas in the Treatment Area and Reference Area in January each year for the seven-year period 1989–1995 (Table 6-5). In the Treatment Area, adult males were generally older than adult females in the first five years but not in the last two years. The distributions of the ages of males and females were identical in all years except 1990 [9]. In the Reference

Table 6-5. Mean ages (in months) of adult pumas in the Treatment Area and Reference Area each January, 1989–1995, San Andres Mountains, New Mexico. Males – x ± SD

All adults x– ± SD

Year

n

1989 1990 1991 1992 1993 1994 1995

7 5 7 3 5 7 7

Treatment Area 76.3 ± 31.0 7 50.4 ± 22.3 83.0 ± 19.6a 10 52.2 ± 24.4a 76.4 ± 33.7 10 58.9 ± 29.5 97.7 ± 40.1 4 80.5 ± 23.1 78.0 ± 49.7 8 60.1 ± 36.3 55.3 ± 36.4 9 66.9 ± 37.3 46.7 ± 16.4 8 72.5 ± 34.0

63.4 ± 30.0 62.5 ± 27.1b 66.1 ± 32.5 87.9 ± 32.7b 67.0 ± 42.9 61.8 ± 37.4 60.5 ± 30.1

1989 1990 1991 1992 1993 1994 1995

8 8 9 9 11 11 12

Reference Area 50.9 ± 24.2 7 50.1 ± 19.7 56.6 ± 26.1 13 43.9 ± 24.1 64.3 ± 27.5 12 53.6 ± 24.8 64.9 ± 32.2 15 47.1 ± 21.5 68.2 ± 34.5 15 47.5 ± 18.1 62.8 ± 30.0 15 52.4 ± 20.5 64.8 ± 35.2 14 65.9 ± 20.5

50.5 ± 22.2 48.8 ± 25.6b 58.2 ± 26.5 53.8 ± 27.4b 56.3 ± 28.2 56.8 ± 25.5 65.3 ± 28.3

aDistribution

n

Females x– ± SD

of ages of males and females in the Treatment Area differed in 1990 (P = 0.05). bDistribution of ages of all adults in the Treatment Area and Reference Area differed in 1990 and 1992 (P < 0.10).

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Area, the distributions of the male and female ages were identical in all years [10]. Still, ages of adults in the Reference Area had a similar profile to the Treatment Area, with males being generally older than females in the first six years but not in the last year (Table 6-5). This tendency for adult males to be older than adult females reflects greater survival rates for males (see Chapter 8). Ages of adult pumas (males and females combined) in the Treatment Area and the Re f e rence Area we re identically distributed in all years except 1990 and 1992 [11] (Table 6-5). Still there was a trend in which adults in the Treatment Area we re generally older than adults in the Re f e rence Area. This characteristic was coincident with a lower density of adult pumas in the Re f e rence Are a , which we believe was a result of greater population reduction in that portion of the San Andres Mountains during the puma control actions that preceded our study. We would expect older-age adults where off-take was less seve re because animals had a greater probability of living longer. Hence, it may be characteristic of populations that are heavily exploited to be composed of relatively young pumas as young-aged recruits composed of progeny and immigrants replace killed adults. We quantified the proportion of adult male and female pumas in three broad age classes (Fig. 6-3). Young adults were pumas twenty-one to thirty-six months old that had recently been recruited into the breeding population. Prime adults were pumas thirty-seven to ninety-six months old that were well established in the population and did most of the breeding. Old adults were pumas 97 to 156 months old that were rapidly declining in the population chiefly because of deaths. Pumas lived to old ages on the San Andres Mountains mainly because they were protected from human exploitation during our study. Moreover, adult males generally lived longer lives than adult females, reflecting their higher natural survival rates (see Chapter 8). The oldest male and female pumas we found were estimated at 152 months and 146 months, respectively. The extreme longevity for wild pumas is probably represented by two Florida panthers. A male was about 180 months old when he was killed by another male panther. And a female was about 158 months old when she was killed by a car (Maehr 1997a). Other old-age pumas were in a wild population in Alberta; there, a 132month-old male died while trying to kill a bighorn sheep, and a 108-month-old female died while she was trying to bring down an elk (Ross et al. 1995). In a puma population in California that had been protected from hunting for twelve years, a 101-month-old male was killed by another puma and a 128-month-old female died of undetermined causes (Hopkins 1989). In contrast, pumas subjected to moderate to heavy hunting pressure in Wyoming very rarely reached eighty-four months of age (Logan et al. 1986). Extreme ages for captive pumas range from about 120 to 216 months (Anderson 1983).

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FPO @ 75%

FIGURE 6-3. Adult puma age structure in the Treatment Area (TA) and Reference Area (RA) in three broad age classes, San Andres Mountains, New Mexico.

LP > >

KX

1. Through capture-mark-recapture and radiotelemetry techniques, we accurately censused the puma population annually, accounting for 93–100 percent of adults in the Treatment Area during 1988–1994 and 86–100 percent of adults in the Reference Area during 1989–1994. By adding in the individual adult pumas we apparently missed, we accounted for about 100 percent of the population each year. Adult pumas were animals that bred or males that were twenty-four months or older and females that were twentyone months or older. Subadults were independent but did not breed. Cubs were dependent on their mothers.

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2. The secondary sex ratio averaged 1:1 for nursling cubs. But it apparently shifted from favoring females in a mother’s first litter to favoring males in her subsequent litters. We speculated that young first-time mothers may produce more of the smaller female cubs and still have optimal litter sizes as a physiological trade-off with somatic growth. 3. Sex ratios for subadults and adults favored females, owing to differential survival rates in subadults and the influence of the social and mating behavior in adults. 4. The operational sex ratio of adults was 1:1 and probably heightened malemale competition for mates. 5. On average, the puma population on the San Andres Mountains comprised 61 percent adults, 6 percent subadults, and 33 percent cubs. The composition was similar in the Treatment and Reference Areas. The age (in months) distribution of adult pumas was similar in the Treatment and Reference Areas. But in general, adults in the Treatment Area were somewhat older than adults in the Reference Area, probably because of past differential exploitation pressure. Adults lived relatively long lives in this protected population. Generally, males lived longer than females. The oldest pumas we found were a 152-month-old male and a 146-month-old female.

LN N5LN5)L 1. Male:female sex ratio for fourteen male and twenty female cubs 52 to 427 days old did not differ from 1:1. Chi-square test, c2 = 1.06, 1 d.f., P > 0.10. 2. Sex ratios in first litters (n = 15) and subsequent litters (n = 27) from nineteen mothers were different. Chi-square test, c2 = 4.675, 1 d.f., P = 0.03. 3. Sex ratios in first litters (n = 8) and subsequent litters (n = 12) of the same females were different. Chi-square test, c2 = 5.901, 1 d.f., P = 0.02. 4. Sex ratios in first litters (n = 8) were different from 1:1. Chi-square test, c2 = 4.482, 1 d.f., P = 0.04. 5. Masses of nine females were different when they were eighteen to twentyfour months old (x– = 31.6 ± 2.6, median = 31.3) compared to when they were twenty-eight to sixty months old (x– = 34.7 ± 2.3, median = 35.4). Sign test, P = 0.07. 6. Sex ratios of subadult pumas in the Treatment Area and Reference Area were not different from 1:1. Treatment Area: Chi-square test, c2 = 1.0 or 2.25, 1 d.f., P > 0.10. Reference Area: Chi-square test, c2 = 0.22, 1 d.f., P > 0.10. 7. Sex ratios of adult pumas observed per year in the Treatment Area and Reference Area did not differ from 1:1. Chi-square test, c2 < 2.71, 1 d.f., P > 0.10, all tests.

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8. Adult sex ratios for January population estimates 1989–1995 for the Treatment Area and Reference Area did not differ from 1:1. Chi-square test, c2 < 2.71, 1 d.f., P > 0.10 all tests. 9. Ages (months) of adult male (n = 3–7) and adult female (n = 4–10) pumas in the Treatment Area, 1989–1995. Distributions of ages were identical for all years (P > 0.10) except 1990 (Mann-Whitney U test, U = 9.0, P = 0.05). 10. Ages of adult male (n = 8–12) and adult female (n = 7–15) pumas in the Reference Area, 1989–1995. Distribution of ages was identical for all years (Mann-Whitney U test, P > 0.10). 11. Ages of adult male and female pumas combined in the Treatment Area (n = 7–17) and Reference Area (n = 15–26) were similar in all years (P > 0.10), except 1990 (Mann-Whitney U test, U = 209.5, P = 0.095) and 1992 (Mann-Whitney U test, U = 131.0, P = 0.026).

Chapter 7

Reproduction

Natality We documented the birth of 220 cubs from seventy-nine litters produced by t h i rty-nine female pumas. Of those cubs, we captured and marked 174 (79 p e rcent). Of the forty-six cubs that we re not marked, we knew of ten cubs from three litters that died shortly after birth, three others disappeared fro m families before we could re c a p t u re them, and nine other cubs we re dependent on their mothers at the close of our study. Hence, we did not have the opportunity to closely examine these cubs. Five nonviable cubs in two litters we re born to the same female: one litter was apparently stillborn and the other was a b o rted. By examining cubs at various known ages during their development, we learned that they suckled until they were six to eight weeks of age. During the nursing stage, cubs were altricial, and mothers kept them at a single nursery or moved them short distances, usually less than 200 m, to alternate nurseries. Moreover, mothers usually tended to their cubs on a daily basis. It was during this period of intensive maternal care that we estimated litter sizes at birth. Once cubs were weaned, they were carnivorous and precocious. They moved to kills their mother made and in the process were subjected to greater perils of their environment. Mortality was expected to increase and thus reduce observed litter sizes. Theoretically, in long-lived itero p a rous animals (i.e., animals that pro d u c e more than one litter in their lifetime), natural selection favors individuals 83

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that produce optimal litter sizes that maximize offspring survival and future b reeding success (Lack 1947, Boyce and Perrins 1987, Freeman and He r ro n 1998). In fifty-three nursling litters in which we counted all the cubs nine to f o rty-nine days postpartum (x– = 32.3 ± 8.9); there was an average of 3.0 ± 0.7 cubs. The distribution of litter sizes for the fifty-three litters was composed of litters with two cubs (n = 13), three cubs (n = 26), and four cubs (n = 14). Twenty-six of the fifty-three litters we re observed at birth nurseries (i.e., where the cubs we re born); the other twe n t y - s e ven litters we re observe d at secondary nurseries (i.e., nurseries used after mothers moved cubs away f rom birth nurseries). For twenty-one other litters that we observed with weaned cubs that we re 52–427 days old (x– = 175.7 ± 112.0), litter sizes ave raged 2.2 ± 0.8 cubs. The smaller litter sizes probably reflects mortality that o c c u r red after we a n i n g . We estimated an overall natality rate of 0.17 by dividing the mean litter s i ze of the fifty-three nursling litters (i.e., 3.0) by the birth interval that we observed for sixteen intervals where at least one cub in the first litter surv i ved to independence or to twe l ve months of age (i.e., 17.4 months; see “ Mating, Gestation, and Birth In t e rvals”). Natality rate in the Tre a t m e n t A rea was 0.16 in the pre - t reatment years (1988–1990) compared to 0.18 in the post-treatment years (1992–1994). This was due to a slightly smaller

Slide @318%

PHOTO 16. Puma F147’s three cubs at five weeks of age.

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Slide @318%

PHOTO 17. Puma F54’s birth nursery, where she had four cubs.

average litter size (x– = 2.7 ± 0.5, n = 6) in pre - t reatment years than in postt reatment years (x– = 3.2 ± 0.6, n = 11) [1]. This difference may have been an artifact of the re l a t i vely small sample sizes of nursling litters in which we observed all the cubs. In addition, we quantified fecundity rates for the Treatment and Reference Areas for biological years in the deer population increase phase (1989–1990 to 1991–1992) and decline phase (1992–1993 to 1993–1994) (see Chapter 17). We defined fecundity rate as the average number of live cubs produced per adult female monitored in each area during each biological year (August–July) (see Caughley 1978:72). The average fecundity rate in the Treatment Area during the deer increase phase was 1.6 ± 0.7; it was 2.0 in both years of the deer decline phase. In the Reference Area, the average fecundity rate was 1.4 ± 0.2 in the deer increase phase, and 1.3 ± 0.5 in the decline phase [2]. These statistics showed no pattern suggesting that puma reproductive output was affected by the declining prey base. However, the lowest fecundity rate of 0.9 occurred in the Reference Area in the last year of the deer decline phase and may be a harbinger of what could be expected during a severe and prolonged deer decline or population low. Cub production apparently was not sensitive to the decline in the deer population during our study. We speculated that the prey base had not yet reached a threshold low enough to trigger nutritional deficiencies in reproducing females

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and their offspring by late 1994. Hence, a time delay should be expected before puma reproduction declines in response to reduced food resources. Decline in productivity could be manifested in smaller litter sizes, longer birth intervals, increased age at first reproduction, increased mortality, or a combination of these properties. In comparison with the reproductive output of other puma populations studied in North America, mean postpartum litter size on the San Andres Mountains was among the largest. The only one slightly larger was a mean size of 3.1 ± 1.2 found by Spreadbury et al. (1996) in southeastern British Columbia where they examined seven litters that were two to ten weeks old. Florida panthers have produced the smallest litters, averaging 2.3 cubs in four litters that were less than fourteen days old (Maehr and Caddick 1995). Most other studies quantified litter sizes when cubs were older, after greater postpartum mortality had probably occurred, as was likely the case with the older weaned litters that we observed. In Idaho, where cubs were first observed at various ages, there was an average of 2.6 cubs per litter (Hornocker 1970). Average litter size of 2.2 cubs in Alberta was estimated from track sets when cubs were less than four months old (Ross and Jalkotzy 1992). In Wyoming, litters less than six months old had, on average, 2.9 cubs and litters older than six months had, on average, 2.3 cubs (Logan et al. 1986). In Utah, where 65 percent of the cubs were older than three months when examined, there were 2.4 cubs per litter (Lindzey et al. 1994). Again, Florida produced the lowest average litter size of 1.9 cubs when a total of twenty-five Florida panther litters of various ages was considered (Maehr and Caddick 1995). Natality rates are not normally reported in technical puma literature because data on mean litter size for nurslings and birth intervals are difficult to gather for wild pumas. We could compare natality rates in the San Andres Mountains puma population only after calculating rates from four other populations that provided data on both statistics, mean litter size and birth interval. A population in southeastern British Columbia (Spreadbury et al. 1996) had a natality rate of 0.17, identical to some of our rates. But natality rates for pumas in southwestern Alberta (Ross and Jalkotzy 1992), south-central Utah (Lindzey et al. 1994), and southern Florida (Maehr et al. 1991, Maehr and Caddick 1995) were lower, at 0.11, 0.10, and 0.10, respectively [3]. Because average litter sizes for Alberta and Utah used weaned litters that may have experienced greater mortality, we believe the computed natality rates for those areas are actually biased downward. However, the estimate for the endangered Florida panther used an average litter size based on young nurslings and may indicate a relatively low natality rate. Scant information on reproduction in other wild large solitary felids precludes

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comparisons with our puma data, except for the tiger. We calculated a natality rate of 0.14 for tigers by using the mean litter size of 3.0 and minimum mean birth interval of 21.6 months that Smith and McDougal (1991) found in Nepal’s Royal Chitwan National Park. Puma hunters, predator control agents, and wildlife managers often believe that first-time puma mothers normally produce smaller litters than experienced mothers. We were interested in the validity of this notion because of its implications on natality rate in suppressed or rebuilding puma populations where young-aged mothers may comprise a substantial proportion of breeding females. Our data contradicted this widely held belief. We examined all of the nursling cubs (nine to forty-six days old, x– = 30.7 ± 9.9) of eight known-age mothers and eight approximately known-age mothers that produced cubs for the first time in their lives. Mean litter size was 3.1 ± 0.7 cubs per litter, which was almost the same as the mean of 3.0 ± 0.7 nursling cubs per litter (eighteen to forty-nine days old, x– = 32.9 ± 9.0) in twenty-eight litters of nineteen females that produced their second to fourth litters. When we compared litter sizes for eight matrilineal mothers for which we had complete reproductive histories, all of which were progeny recruits that were philopatric (n = 6) or had home ranges adjacent to their natal areas (n = 2), we found the mean size of their first litters (3.4 ± 0.74) was about equal to the mean size of their twelve subsequent litters (3.2 ± 0.58). Our observations indicate that productivity of first-time mothers is about the same as experienced mothers. However, it is possible that older, more-experienced mothers have greater success at rearing their young to independence. The eight matrilineal mothers tended to have larger first litters than six known immigrant mothers (x– = 2.8 ± 0.75), although the difference was not significant [4]. We would expect matrilineal mothers to have greater knowledge of local resources (i.e., food, nurseries) and perhaps even greater social dominance compared to immigrant females, which might result in a reproductive advantage. If true, then philopatric females would be expected to have greater fitness, particularly if their cubs also exhibited greater survival, which they apparently do (see Chapter 8). We also wanted to see if litter size changed with the age of the mother. Five mothers that were 92–112 months old had six litters with an average of 2.8 ± 0.98 nursling cubs, which tended to be lower than the mean size of first litters of the eight matrilineal mothers (above); however, the difference was not significant [5]. Apparently, litter size was not substantially affected by the biological process of aging relative to the age distribution we observed in the San Andres Mountains puma population.

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Timing of Births We determined the month of birth for seventy-eight puma litters on the San Andres Mountains. Litters were born in every month of the year except February (Fig. 7-1). But there was a birth pulse during July, August, and September when ten, eleven, and eleven litters (41 percent in aggregate) were produced, respectively. The occurrence of puma litters in those three months was greater than expected with a uniform distribution [6]. The timing coincided with the birth period for mule deer fawns and the annual monsoon season, which occurs during mid-July through September. During this time, food and cover is most available for lactating does and their fawns, and, hence, probably enhances their survival (see Sinclair et al. 2000). Similarly, food for puma mothers is the most available and vulnerable at that time. On the San Andres Mountains, mule deer comprised 91 percent of prey animals that we found were killed by pumas, and 92 percent of the relative biomass of prey items consumed by pumas. Furthermore, fawns comprised more than one-quarter of the puma-killed deer that we examined (see Chapter 17), and they may be selected by puma mothers (Pierce et al. 2000a). During the fawning season, mule deer are more abundant than at any other time of the year, and small fawns are the most vulnerable component of the population to predators. The postparturition period is critical for puma mothers. Lactation is the most energy-demanding part of the reproductive cycle, because mothers must main-

FPO @ 80%

FIGURE 7-1. Distribution of births of seventy-eight puma litters by month, 1986–1994, San Andres Mountains, New Mexico.

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tain themselves as well as produce energy-rich milk for their offspring (Bronson 1989). Mothers must also restrict their movements around nurseries while they nurse and protect young. In addition, especially after the nursing period, the energetic demands of the family unit increase dramatically, primarily due to the rapidly growing cubs (Ackerman 1982), and must be satisfied by consuming prey. Hence, puma births timed for periods when food is predictably abundant and vulnerable would be an adaptive strategy. Mothers that produce litters at those times probably incur survival advantages and relatively high net reproductive success; hence, a trait for giving birth when food is most abundant would be expected to be favored by natural selection. We examined variation in timing of birth for individual mothers by inspecting the birth dates of twelve female progeny recruited as breeding adults on the San Andres Mountains (i.e., F1 generation females) relative to when they gave birth to nineteen litters themselves (i.e., the F2 generation). Ten (53 percent) of the litters were born during the July–September birth pulse. Of the F1 generation mothers, six were born in the birth pulse themselves and produced six birth-pulse litters. But four of those mothers also produced five litters outside of the pulse. Of the six remaining mothers, three were born in March, two in May, and one in December. Four of the females produced four birth-pulse litters, and three of the females produced four litters outside the pulse (one female produce one litter in and one litter outside the pulse). We also examined tendencies in birth timing for twelve other mothers that had immigrated onto the San Andres Mountains. Those females produced twenty-eight litters. Seven of the mothers produced thirteen (46 percent) litters in the July–September birth pulse. Six females were parents (i.e., P1 generation) to the twelve F1 mothers above; together they produced nine birth-pulse litters. Yet, seven of the mothers that had birth-pulse litters also produced thirteen litters outside of the pulse. Two other mothers had litters in October and December. If giving birth to cubs when food is abundant and vulnerable is so advantageous, why don’t all females have cubs during that time? An answer may partially lie with the fates of cubs and the fact that pumas are polyestrous, meaning that they cycle into reproductive receptivity continually throughout the year (Bonney et al. 1981). Some females that produce cubs lose the entire litter due to disease, infanticide, or predation. Those females can recycle into breeding condition within a few weeks or months (see “Mating, Gestation, and Birth Intervals”), and thus they produce cubs during another part of the year. For five mothers that lost their entire litters, then rebred successfully, we found that their doomed litters were born in March, April, August, October, and November. They had their subsequent successful litters in May (n = 4) and July. In addition,

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females may reach reproductive maturity at different times of the year. Specific mechanisms affecting this in pumas are unknown, but we presume they are similar to those affecting other mammals. Fertility is influenced by phenotype and environment. For example, genes influence somatic development and onset of fertility; nutritional stress during adolescence could delay puberty; and reproductive condition may be primed by pheromonal cues in the environment and social situations could stimulate or suppress it (Bronson 1989). A simple hypothesis may explain why there is an observed pulse in puma births. Pumas breed and give birth to litters year-round, but litters born during the period of food abundance have the greatest probability of survival. Lactation poses the greatest energetic challenge to mothers (Bronson 1989). Besides producing energy-rich milk, mothers must also sustain themselves and protect young from the ambient climate and predators. After weaning, cubs eat meat and grow rapidly; energetic demands (i.e., kcal / day) of the puma family unit increase dramatically to as much as six times that of a nonproducing female, depending upon the number and size of the cubs during adolescence (Ackerman 1982). Hence, litters born in periods of food abundance stand the greatest chance of surviving beyond the first two to four critical weeks that it takes field biologists to detect them. Comparatively, cubs born during other, less-favorable times of the year would be expected to have lower survival. In this scenario, no heritable trait for timing of birth is required. Considering the dispersal patterns of pumas (see Chapter 9), it is more adaptive for them to be polyestrous yearround instead of locking into a single birth season that has evolved from local environmental conditions. Pumas with the former trait are more fit because they can more successfully exploit changing environmental conditions. This has allowed the puma to evolve into a highly adaptable and colonizing species. The pattern of puma births on the San Andres Mountains conformed closely with the pattern observed in Ne vada (Ashman et al. 1983), but there the birt h peak occurred during June and July. In Wyoming, where 70 percent of puma cubs o b s e rved we re born from August to November, Logan (1983) suggested that mothers and weaned cubs took advantage of high concentrations of mule deer and elk on winter ranges during November to March. Similarly, of observed puma births, 78 percent occurred from June to November in British Columbia (Spre a db u ry 1989), 77 percent occurred from August to October in Utah (Lindzey et al. 1994), and 60 percent occurred during June to August in Alberta (Ross and Jalkotzy 1992). Anderson (1983) compiled data on fifty-three wild litters from fourteen sources and showed that 66 percent of births we re observed during June, July, September, October, and November. Florida panther repro d u c t i vecharacteristics support our hypothesis that observed birth pulses coincide with periods of food abundance. Most panther litters we re recorded between March and July. This

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overlapped the Fe b ru a ry to April white-tailed deer fawning season, which boosted the deer population to its highest annual levels (Maehr 1997b).

Mating, Gestation, and Birth Intervals By intensively monitoring radio-collared adult pumas, we were able to document the mating of thirty-six pairs (Appendix 2). Two pairings resulted in nonviable young from the same female; one litter was stillborn after eighty-five to ninety days of gestation, and one litter was aborted after fifty-six days of gestation. Once we located a pair of pumas together, we homed on their locations and found evidence of a potential breeding association. Evidence included tracks of the pair traveling together, kills that they shared, vocalizations, and visual observations of the pumas. Although we did not observe pumas actually copulating, the ultimate proof of a breeding association was the subsequent birth of cubs. We estimated the length of gestation by counting the number of days from our first observation of the pair together to the estimated birth date of the cubs. The mean gestation period that we calculated for the thirty-one pairings was 91.5 ± 4.0 days (range = 83–103). Considering the July–September birth pulse that we observed on the San Andres Mountains, the corresponding breeding period occurred during April–June. Quantitative information for length of puma gestation in the published literature mostly pertains to pumas in captivity. The mean gestation period that we observed was practically identical to the mean of 91.9 days that Anderson (1983) calculated from forty-two captive litters from eleven sources. Radio-tracking enabled Beier and Barrett (1993) to estimate a mean gestation period of ninety-three days for only four wild litters in Southern California. Estrus, the period of the reproductive cycle when ovulation occurs and the female puma is at maximum receptivity to the sexual overtures of males, ranges from three to twelve days for captive pumas (see sources in Anderson 1983). For pumas on the San Andres Mountains, we estimated estrus lasted one to ten days based on our radiotelemetry data on consort pairs. Successfully breeding pairs were together one to four days. We documented another pair in an apparent breeding association for six days, but it did not result in viable cubs. Four females associated with two different males during the same estrus period, indicating that female pumas can be promiscuous, a behavior that was typically exhibited by the male pumas. One of the females associated with one male for one day, with a different male two days later, then with the first male again seven days after that; this suggested a receptive period of ten days. A consort pair in a wild puma population in central Idaho traveled together for up to sixteen days (Seidensticker et al. 1973).

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During mating, puma pairs copulate ve ry fre q u e n t l y. Captive pumas have been observed to copulate as much as fifty to seventy times per day during e s t rus (Eaton 1976). Female pumas are apparently induced ovulators (Bonney et al. 1981), and thus, high copulation frequency may stimulate peak reproductive condition. Experiments with captive pumas by Me h rer (1975) is supp o rt i ve of this idea; the number of copulations contributed to ovulation. Eaton (1976) speculated that the high copulation rates evolved as a measure of male vigor and a means by which females can maximize repro d u c t i ve success. We believe that besides the ability to repeatedly copulate, vigor of adult male pumas is also rigorously tested during defense of territory or estrus females (i.e., access to mates) against other male interlopers (see Chapter 8). Thus, when an e s t rus female monopolizes the sexual favors, and hence the sperm, of a successful territorial male via an extended estrus period with frequent copulations, she is in essence mating with the most fit male and acquiring “good genes” for her offspring. Furt h e r m o re, these mating habits may enhance recognition betwe e n the pair and awareness of paternity by the male, and may reduce aggression by the male directed tow a rd the female or her cubs in subsequent encounters (see Chapter 8). The estrous cycle (i.e., reproductive cycle) in wild pumas is practically impossible to observe directly. But because we could estimate the frequency of estrus by using radiotelemetry, we estimated the length of the estrous cycle by noting the frequency of apparent estrus periods. We did this by marking the beginning of one estrus period to the beginning of the next as indicated by twelve apparent breeding associations between radio-collared adult males and five different females. They showed a mean estrous cycle length of 24.5 ± 6.8 days, with a range of fourteen to thirty-five days. Our estimated estrous cycle length was similar to a captive female that exhibited nine estrus periods that averaged 22.8 days apart (Rabb 1959). But estrous cycle lengths can be highly variable as was exhibited by two other captive females that averaged 59.5 days (range = 17–114) between a total of thirteen estrus periods (Mehrer 1975). We also quantified the length of puma birth intervals (i.e., time span between litter births). Birth intervals where at least one cub in the first litter survived to independence (n = 15) or to twelve months of age (n = 1) averaged 17.4 ± 2.5 months (range = 12.6–22.1). This time span represented the amount of time it took a mother to give birth, rear her cubs to independence, and then to rebreed and have another litter of cubs. For fifteen other intervals in which we did not know the fates of the first litter with certainty, intervals averaged 16.9 ± 3.4 months (range = 12.2–22.5). The close similarity in birth intervals between these two groups suggests that in most cases mothers in the latter group raised one or more cubs to independence. Because of inadequate samples, we did not

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compare birth interval lengths in the mule deer increase phase (n = 13, range = 12.6–22.1 months) and the decline phase (n = 3, range = 16.8–21.6 months). Five females that we monitored closely lost their first litters entirely, but they successfully bred again an average of 100.4 ± 116.9 days later (range = 23–307). The shortest interval of twenty-three days was for a female whose first cubs were stillborn. Two of these females lost their entire litters to cannibalism by territorial males; they rebred 74 and 307 days later (x– = 190.5 ± 16.5). The other three females that lost their litters to other causes rebred twenty-three to fifty-four days later (x– = 40.3 ± 15.8). Birth interval length is another statistic on puma reproductive biology that is difficult to document for wild pumas. But there is some limited information from disparate parts of the puma’s range. Twelve female pumas in Nevada exhibited a mean birth interval identical to what we found (i.e., 17.4 months), with a range of 11.5–24.0 months (Ashman et al. 1983). Generally, birth intervals on the San Andres Mountains were somewhat shorter than in other areas. In Utah, Lindzey et al. (1994) reported a mean birth interval of 24.3 months for seven intervals where one or more cubs survived twelve months or longer. In Alberta, Ross and Jalkotzy (1992) calculated a mean birth interval of 19.7 months for twelve intervals. However, they cautioned that in three cases (twenty-five, twenty-five, and thirty-two months) interceding litters may have been born and lost because of low monitoring frequency. If so, then actual birth intervals would be expected to be somewhat shorter. Closely monitored endangered Florida panthers exhibited a mean of 23.3 months in five intervals (Maehr et al. 1991).

Puberty and First Litters We used the timing of first associations between male and female pumas with known ages or approximately known ages to determine ages of puberty. We define puberty as the beginning of the adult stage in life when pumas are physiologically and socially ready to breed. Only females that eventually produced cubs were included in our analysis. Seven females with known birth dates associated with adult males for the first time when they were an average of 21.4 ± 3.1 months old (range = 18–27). Of those females, two produced litters that resulted from those associations; they were nineteen and twenty months old. Three other females had four subsequent associations with adult males that averaged 22.8 ± 8.7 days (range = 13–34) after the first association, which suggested the females were in estrus. In support of this, two of these associations resulted in litters. Another six females with approximately known ages apparently associated with adult males for the first time when they averaged 22.2 ± 7.6 months old (range = 15–36). Three of these associations resulted in litters; the females

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were about fifteen, seventeen, and twenty-five months old. Another female was impregnated when she associated with the same male twenty-six days later, thus suggesting that her associations were related to estrus periods. Based on these data, we generalized that female pumas on the San Andres Mountains reached sexual maturity at about twenty-one months old. To determine the ages when female pumas first successfully produced cubs, we analyzed data on twelve known-age females. These females conceived apparently for the first time at an average age of 26.1 ± 6.0 months (range = 19–37). They bore their first live litters at a mean age of 29.1 ± 6.0 months (range = 22–40 months). Another eight females of approximately known ages conceived successfully apparently for the first time at an average age of 26.0 ± 9.4 months (range = 15–42). They produced their first live litters at an average age of 29.0 ± 9.4 months (range = 18–45). The youngest female to bear cubs was approximately eighteen months old. When we captured her for the first time at about nineteen months of age, she had already given birth to three cubs, which were five weeks old. Her tawny pelage showed obvious light brown dapples on her forelegs, shoulders, hips, and thighs. This meant that she was about fifteen months old when she conceived. Philopatric females did not exhibit reproductive suppression as a result of residing within the home range of their mothers and territory of their fathers. Three philopatric females associated for the first time with adult males when they averaged 19.7 ± 1.5 months old (range = 18–21). Five philopatric females conceived for the first time when they averaged 26.8 ± 7.0 months old (range = 20–37) and produced their first litters when they averaged 29.8 ± 7.0 months old (range = 23–40). Two of these females actually bred with their fathers, one of them twice, for a total of ten cubs (five males, five females). Cubs from one of the litters survived to nine months old before we lost track of them. Cubs from the other two litters survived to the end of the study, when they were eight and ten months old. Similarly, six approximately known-age immigrant females associated for the first time with adult males when they averaged 22.2 ± 7.6 months old (range = 15–36). Three of those associations resulted in cubs; the females were about fifteen, seventeen, and twenty-five months old. These six females conceived for the first time at the average age of 26.0 ± 11.1 months (range = 15–42) and produced their first litters when they averaged 29.0 ± 11.1 months old (range = 18–45). Hence, it appears that adult females, whether they were recruited into the population as philopatric progeny or as immigrants, become reproductively active at about the same age. Information on age of first breeding from other parts of the puma’s range is scanty owing to the extreme difficulty in obtaining this information from observations of wild pumas. The youngest known-age, reproducing female puma that

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has been reported in the literature was a Florida panther; she conceived at sixteen months of age. Two other known-age Florida panthers conceived for the first time at eighteen and twenty-one months of age (Maehr 1997b). Ross and Jalkotzy (1992) had six known-age females in Alberta that had their first litters at an average age of 30.0 months, similar to our findings. In Utah, Lindzey et al. (1994) had six known-age females that first gave birth at an average age of twenty-six months. Because most of our radio-collared male progeny emigrated from the study area if they survived to independence and thus went on to occupy ranges where other radio-collared pumas were absent, it was practically impossible for us to determine when they became sexually mature. So, we had to rely mostly on information from approximately known-age males that immigrated onto the San Andres Mountains. One known-age male and five approximately knownage males averaged 24.3 ± 2.5 months old (range = 21–27) when they associated with adult radio-collared females for the first time. Males were slightly older than females when they first associated with the opposite sex [7]. At least two of those associations resulted in live litters ninety-one and ninety-two days later. These males were twenty-four and twenty-seven months old. We generalized that male pumas on the San Andres Mountains reached sexual maturity at about twenty-four months old. We suspect that timing of puberty in male and female pumas is probably influenced by physiological, social, and resource factors that relate to reproductive success. In our study area, where the puma population was rebuilding from low densities imposed by population control, reduction of puma density left ample space and resources for female recruits to establish home ranges where prey resources could support them during growth, maintenance, pregnancy, lactation, and cub rearing. As density increased, competition between adult female pumas for food likely also increased. Thus, their individual reproductive success would be enhanced if they began socializing with potential mates and breeding as soon as they were physiologically capable (Bronson 1989). This was characteristic of the San Andres Mountains puma population during a time of mule deer (i.e., their principal prey) increase and decline (see Chapter 17). However, a reasonable hypothesis is that after a lag period following prey collapse, new female recruits may delay sexually maturity to older ages. In contrast, adult male pumas competed directly with each other for mates (see Chapter 8). Reproductively successful males probably benefited from larger body size and superior strength, attributes that would enable them to achieve dominance over other males through fighting for access to mates and territory. Hence, it would be advantageous for males to become sexually mature when they had the physical ability to compete. In many other polygynous species, in

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which males compete directly with one another for access to mates, male maturation is delayed (i.e., relative to females) until they have attained greater mass (Stearns 1992). Our data on measured male puma masses supported this hypothesis. Independent males twelve to twenty months old had lower masses than males twenty-one to twenty-seven months old that were in the age bracket when males first associated with adult females [8]. In the first group, five males were captured in areas where they eventually established a territory, but four dispersed and three others were killed by territorial males. Males in the second group (n = 11) had masses only marginally lower than territorial males twentyeight to ninety-six months old (n = 16) [9]. Males in the second group demonstrated their competitive abilities; all of them were captured in the areas where they established territories.

Parental Investment Expenditure of energy and time by a parent in the care of its offspring in a way that increases fitness is called parental investment (Freeman and Herron 1998). In pumas, the end of the mating interlude is also the end of the sire’s direct parental investment in his offspring. In essence, the male has contributed only so much sperm in multiple copulations over a span of a few days. He takes no part in rearing the cubs. Instead, the male explores his territory seeking other mating opportunities. Yet, territorial males may contribute to survival of their offspring indirectly by dissuading activity of other males that could kill cubs (see Chapter 8). In contrast, the female’s direct investment in offspring is extremely high. Her reproductive success is dependent on her physical ability to produce mature eggs for fertilization, sustain pregnancy, and feed and protect young after birth (Bronson 1989). In time alone, she will invest about three months in gestation and eleven to sixteen months in rearing the cubs (see Chapter 9). A great deal of energy is expended in nursing, grooming, hunting and killing prey, teaching cubs how to hunt, and protecting them from weather, predators, and other hazards in life. Greater parental investment by female pumas relative to males is exhibited by over 90 percent of mammal species (Woodroffe and Vincent 1994). It is vital to the reproductive success of individuals in each sex and to the evolution of sex differences (Trivers 1985), which we expand upon in the next section.

Reproductive Success Darwinian fitness of individuals is directly exhibited by their ability to survive, breed, and successfully raise offspring so that they may breed and reproduce

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themselves; therefore, it is principal to the concept of evolutionary biology (Grafen 1988, Freeman and Herron 1998). More fit individuals leave proportionately more of their genes in descendants than do other individuals in the population. Genotypes of the more fit express phenotypes that are better adapted to the rigors of the environment. A measure of fitness for an individual is lifetime reproductive success, which is ultimately measured by the number of offspring produced in a lifetime that survive to breed (Thomas and Coulson 1988). Obtaining information necessary to quantify lifetime reproductive success for wild pumas would require monitoring the reproductive output for individuals throughout their lives as well as the number of their offspring that reach maturity. Such feats are practically impossible to attain because of the difficulty and costs of tracking adult pumas that can live over ten years and progeny until they reach puberty. The latter task is particularly problematic because a large proportion of puma progeny disperse long distances from natal areas. The best we could do in our study was to estimate short-term reproductive success for individual pumas by quantifying the number of litters and cubs they produced during the cross-section of their lives that we studied them. In addition, we looked at traits that might have affected their reproductive success. These traits shed light on our interpretation of the evolution of puma social organization. Quantifying short-term reproductive success in adult females was more reliable than in males. Females produced litters of altricial cubs that we were able to count and tag if they survived the first two to four weeks after birth. In contrast, we estimated reproductive success in males based on their breeding associations with females, which we determined from radiotelemetry. Because our opportunities to assess reproductive success in males was dependent on our radiotelemetry monitoring schedule, we no doubt missed some breeding associations that were less than one week in duration; hence, reproductive success as we quantified it for males was a relative index. In other words, we assumed that the males we observed to be the most engaged in breeding associations (confirmed by cub births) were the most reproductively successful males in the population. The most powerful method for identifying puma fathers is paternity exclusion, a technique that uses genetic material from tissue samples (e.g., blood, muscle, skin, hair) obtained from animals in the population. With the knowledge of genotypes of mothers, their offspring, and potential fathers, the observed inheritance of alleles by offspring (one from each parent) at highly polymorphic loci is the metric by which fathers are included or excluded as potential mates (Murphy et al. 1998a). Murphy’s research on puma reproductive success in Yellowstone National Park during 1988–1995 employed both paternity exclusion and radiotelemetry methods and showed that the two methods yielded the same estimates of paternity. Consequently, based on his findings

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and the gestation periods resulting from our observations of consorting pairs, we were confident in our paternity assignments based on radiotelemetry.

Females Most adult female pumas on the San Andres Mountains were raising cubs each year during 1988–1994. On the Treatment Area, an average of 52 ± 18 percent (range = 29–75) of adult females gave birth each year. Counting mothers with dependent cubs born in previous years, an average of 76 ± 21 percent (range = 44–100 percent) of adult females were raising cubs each year. Percentages were similar on the Reference Area. On average, 48 ± 18 percent (range = 21–73) of adult females gave birth to cubs each year, and an average of 74 ± 13 percent (range = 60–100 percent) were rearing cubs. In other parts of North America, large fractions of adult female pumas were rearing cubs each year. In the Big Horn Mountains of Wyoming, 55 percent and 86 percent of adult females raised cubs during two consecutive winters (Logan 1983). In southwestern Alberta, during each January 1981–1989, 42 percent of adult females were accompanied by cubs less than six months old (Ross and Jalkotzy 1992). And in south-central Utah, cubs were born to about half of the resident female population each year (Hemker 1982). Nonreproducing adult female pumas comprised 26 percent (n = 14) of the fifty-three adult females we monitored. Of those, seven died, three were removed from the Treatment Area (Ruth et al. 1998), and four were being monitored at the end of our study. The seven that died averaged 28 ± 4.4 months old (range = 21–34); we monitored them continuously via radiotelemetry for two to ten months. The three adult females we translocated averaged 29.7 ± 8.6 months old (range = 22–39). Radiotelemetry on two females was continuous for eight and twenty-two months. The third female was translocated upon her first capture as a new immigrant to our study area when she was twenty-two months old. Clearly, all these females were just reaching reproductive ages (see “Puberty and First Litters”) and might have reproduced had they survived or not been translocated from the study area. In fact, one of the translocated females (F31) produced a litter of five cubs in her new home range in northern New Mexico. The four females that we were still monitoring at the end of our study could also have produced cubs after our departure. They averaged 35 ± 8.2 months old (range = 26–42); we monitored them continuously for three to seventeen months. It is also possible that some of these females produced viable cubs that did not live long enough (i.e., two to four weeks) for us to detect them. Hence, except due to death, we did not document any adult female pumas that clearly demonstrated apparent physiological barriers to reproduction in the expanding puma population on the San Andres Mountains.

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We quantified short-term re p ro d u c t i ve success in the thirty-nine puma mothers we studied (74 percent of the total females). Mothers bore one to f i ve litters and a total of one to fifteen cubs each. Ten mothers (26 perc e n t ) had three or more litters during the study and produced 110 of the 220 cubs (50 percent) we documented and seventeen of twenty-four (71 percent) of the tagged progeny that we re re c ruited in the adult portion of the puma population on the San Andres Mountains. Productivity of three females was reduced because we translocated one and two died as a result of capture related injuries. The translocated female had produced three litters (eight cubs, two recruits) on the San Andres Mountains. Of the two females with reproduction abbreviated by us, one produced two litters (seven cubs, one recruit), and the other produced one litter (three cubs, ze ro re c ruits). Si x t y p e rcent (n = 46) of the litters were produced by prime age females (range = 37–94 months), 33 percent (n = 25) were produced by young females (range = 18–36 months), and 7 percent (n = 5) were produced by old females (range = 97–127 mo.)[10]. We did not know the ages of two females that pro d u c e d t h ree litters. Mothers that produced the most litters, and hence had the greatest reproductive success, were those that lived the longest lives. We found a highly significant relationship between the number of litters produced per adult female and the number of months that we monitored females by radiotelemetry. Female longevity explained about 79 percent of the variation in the number of litters produced (Fig. 7-2) [11]. The average number of litters produced per month by the twenty-eight adult females that we monitored for twelve or more months (range = 17–82 months) was 0.05 ± 0.02. Four mothers that each produced five litters were 92–112 months old (i.e., 7.7–9.3 years) at the birth of their last litters. On average, those mothers produced 2.2 ± 0.3 cubs per year (range = 1.8–2.5) during their reproductive life span that we monitored by radiotelemetry (i.e., from twenty-nine months old to their death or end of the study). The oldest reproducing female was about 127 months old at the birth of her last litter. Nine (23 percent) mothers produced seventy-nine cubs in twenty-seven litters, out of which twelve first filial generation (F1) females produced sixty-one cubs in twenty litters (i.e., second filial generation, F2). Consequently, the nine P1 females were related to at least 64 percent (i.e., 140 of 220) of the progeny that we documented on the San Andres Mountains. All but two of the mothers were matrilineal. The two included a P1 mother and her daughter, who dispersed 49 km south of her natal area before establishing a home range where she bred in the San Andres Mountains. Nineteen (49 percent) mothers that we monitored by radiotelemetry formed

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FIGURE 7-2. Scatter plot of the number of litters produced by adult female and male pumas monitored for at least twelve months by radiotelemetry, San Andres Mountains, New Mexico.

eight matrilines composed of mothers and their female progeny that established home ranges which overlapped or abutted their mother’s home ranges (see Chapter 13). Those females produced more litters (n = 43) and cubs (n = 127) than twenty other females that were not matrilineal or for which we did not know genetic relationships (ns = 36 litters, 93 cubs). Although there was no difference in the proportion of litters produced by the two groups, the number of cubs produced by matrilineal mothers relative to non-matrilineal mothers plus mothers of unknown status was greater than expected [12]. In this instance, our estimates of matrilineal mothers and their reproductive output are conservative

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because of the high probability that some females we caught early in the study were mothers or siblings of some of their female neighbors (i.e., matrilineal). More importantly, when we quantified survival rates of cubs to age of independence, we found that cubs of matrilineal mothers had a higher survival rate, 0.67, than cubs of non-matrilineal mothers, 0.56 (see Chapter 8). Hence, matrilineal mothers would be expected to have greater reproductive success than nonmatrilineal mothers. Furthermore, eight matrilineal P1 mothers, one philopatric F1 mother, and one adjacent F1 mother produced twenty-one of twenty-four (88 percent) of the tagged progeny that were recruited into the San Andres Mountains puma population. Three P1 mothers and one other philopatric F1 mother also produced four of thirteen (31 percent) of the known tagged progeny that emigrated to other puma subpopulations in southern New Mexico. Clearly, like Murphy et al. (1998a) discovered in pumas in the Northern Yellowstone Ecosystem, reproductive success in female pumas was highly variable. Yet, according to our findings, reproductive success favored matrilineal mothers. Female philopatry has been documented in puma populations in Colorado (Anderson et al. 1992), Alberta (Ross and Jalkotzy 1992), Utah (Laing and Lindzey 1993), and Idaho (Lopez-Gonzalez 1999). The Utah biologists, who also studied a protected puma population, recognized that philopatry resulted in “clusters of related females with overlapping ranges” (Laing and Lindzey 1993:1057). While studying how deceased residents were replaced, they found that seven out of ten deceased females were replaced by at least one of their independent daughters or a daughter of a neighboring resident female. However, they did not report the reproductive histories of those females. We extended this concept by recognizing that philopatric females and adjacent females were also closely related, and called the group a matriline. Furthermore, we realized that matrilineal mothers have the greatest reproductive success and are probably favored by natural selection. Those females probably have higher survival rates than dispersers (see Chapter 8), and upon reaching the physiological ability to reproduce, they raise cubs among familiar surroundings where they have already learned the locations of vital resources, such as food and nurseries essential for their cubs’ survival and physical development. A large proportion of their female progeny may then be recruited into the local population, while other surviving progeny, particularly males, disperse and may become recruited into other distant puma subpopulations or colonize available habitat (see Chapter 13). In addition, matrilineal females are socially familiar with the other adult pumas with whom they share the landscape; this may enhance the survival of their offspring by reducing infanticide (see Chapter 8). Female pumas do not aggressively exclude other pumas from their home ranges (see Chapter 12). Such behavior would lower their fitness by increasing risks of mortality or debilitat-

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ing injuries. Hence, direct and indirect fitness (i.e., inclusive fitness) should be enhanced for females that share resources with closely related females (see Armitage 1986). We hypothesize that matrilines are naturally characteristic of nonexploited puma populations. We would expect philopatry and matrilines to have similar fitness benefits in tigers, African leopards, snow leopards, and jaguars, but extant information linking these traits to reproductive success in those large, solitaryliving felids is sparse (Smith 1993, Bailey 1993). If philopatry in other large felid lineages is the result of homology (i.e., similarity between species that results from inheritance of traits from a common ancestor), we propose that philopatry and resulting matrilines could have provided a basis for the evolution of the pride in African lions (see Chapter 15). Matrilines that we documented had overlapping generations and longitudinal structure. The longevity of puma matrilines is unknown, but theoretically they could span several generations in unexploited puma populations. In six matrilines, parental-generation (P1) mothers raised cubs at the same time that they were neighbors with as many as three philopatric daughters and one adjacent daughter (i.e., home ranges abutted), which were born in as many as three different litters (see Plate 5). P1 mothers and one daughter raised cubs concurrently on ten occasions. Three P1 mothers raised cubs concurrently with one daughter on two occasions each. Two P1 mothers raised cubs concurrently with two of their daughters; two daughters were from the same litter and two were from different litters. The same two sisters from different litters raised cubs concurrently twice. In another instance, siblings from the same litter raised cubs concurrently. We documented two other matrilines in which daughters lived within their deceased mothers’ home ranges. Those daughters extended maternal lines by reproducing; two philopatric daughters resulted from one of the litters. Here again, the presence of older, closely related puma mothers did not trigger reproductive suppression in philopatric or neighboring female progeny and siblings. If anything, reproductive success may have been enhanced. Because these closely related groups of females also breed with territorial males overlapping their home ranges, presence of long-tenured territorial males may facilitate incest between fathers and daughters (see “Puberty and First Litters”). Two of the three father-daughter matings we recorded involved M88 and F107, both of which occurred in the Treatment Area after we experimentally removed 53 percent and 58 percent of adult and independent pumas (i.e., adults plus subadults) (see Chapter 10). Yet, it is possible that we partially facilitated inbreeding in that area by removing potential male competitors and mates of M88. In an unmanipulated puma population, we would expect intermittent turnover in territorial males and occasional breeding success of neighboring ter-

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ritorial males to increase variance in an individual male’s breeding success. In addition, most replacement males would likely immigrate from far away, even from other subpopulations, (see Chapter 9) and consequently promote outbreeding within local matrilines. Phenotypic traits, including a kink at the end of the tail and a distinctive whorl of hair (i.e., cowlick) on the back, are thought to derive from inbreeding in Florida panthers (Barone et al. 1994, Maehr and Caddick 1995, Maehr 1997b). Panthers also exhibit low fertility and heart defects thought to result from inbreeding depression (O’Brien et al. 1990, Barone et al. 1994, Roelke et al. 1993b, Hedrick 1995). On the San Andres Mountains, we found only three pumas with kinked tails (i.e., bends involving the last few vertebrae). Two were adult males, M14 and M153. M14 lived in the Reference Area until he was killed by M19. M153, who was born in the Reference Area, dispersed to the Treatment Area, where he established a territory. Female F96 was born on the Treatment Area. She was killed by adult male M88 when she was a twelvemonth-old subadult. One female cub, F63, apparently was born without a tail. She lived in the Reference Area, but died in adolescence. None of the live pumas we examined had a cowlick on the back. Non-matrilineal mothers and mothers with unknown relatedness to neighbors produced a relatively small fraction (22 percent) of the tagged progeny recruits on the San Andres Mountains. However, they produced nine of thirteen (69 percent) of the tagged emigrants we documented. Again, the proportion of emigrants attributed to this female group is probably biased upward because of the likelihood that some of the mothers were actually matrilineal but we did not know it. If this is the case, then non-matrilineal and matrilineal mothers may produce about equal proportions of emigrant offspring.

Males Reproductive success in male pumas depends on their ability to maintain physical condition, repel competitors, acquire territory, and mate successfully with estrus females. Such feats are not easy; males compete vigorously for access to mates. Sometimes the competition is lethal. In contrast, reproduction in adult females carries less variability of success. Estrus females merely have to advertise their favorable breeding condition and males appear to provide the requisite service. After fertilization, females can devote their energy beyond maintenance to parental investment. Of thirty-four adult males we monitored during the study, fifteen (44 percent) were documented in breeding associations with females that resulted in viable litters. Our ability to detect pairing between radio-collared adult males and females was influenced by the proportion of radio-collared adults in the

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population and our monitoring frequency, which was mostly dependent upon our weekly flight schedule. Hence, we treated our quantification of breeding pairs as an index to male reproductive success. All successfully breeding males were monitored as adults via radiotelemetry for six to eighty-seven months (x– = 48.5 ± 25.4). Only three of the males were monitored for less than twenty-four months (i.e., six, twenty-two, and twenty-three months). The fifteen males sired ninety-four live cubs in thirty-one litters, comprising 43 percent of all the cubs and 39 percent of all the litters we documented. In all cases, males bred with females within their territories. Territories of these males overlapped one to thirteen adult female pumas per year (x– = 5.0 ± 2.6, n = 27 puma-years). Six adult males (18 percent of adult males, 38 percent of documented breeders) had nine F1 offspring (eight females, one male) that produced forty-five F2 progeny in fifteen litters. Two adult males mated with their philopatric daughters on three occasions (i.e., three of thirty-six, 8 percent of consort pairs), resulting in ten cubs. The six P1 males were related to at least 45 percent (100 of 220) of the progeny we documented; they sired at least 54 percent (thirteen of twenty-four) of the recruits comprising tagged progeny on the San Andres Mountains, and they sired three of thirteen (23 percent) of the tagged emigrants we documented. Reproductive success of adult males was linked to their longevity, just as we found with females, albeit the relationship was weaker. Male longevity explained only 45 percent of the variation in the number of litters they sired (Fig. 7-2) [13]. Variation in male reproductive success is also influenced by the number of females within a male’s territory (Murphy et al. 1998a) and his ability to compete for estrus females. The average number of litters sired per month by nineteen adult males that were each monitored for twelve or more months was 0.03 ± 0.03 (range = 0–0.11). The high variation in the number of litters sired per month by individual males and the relatively small proportion of reproductive success explained by longevity was consistent with the idea that male reproductive success should be more variable for males than for females in a species with a polygynous mating system, which is exhibited by pumas (Seidensticker et al. 1973, see below), where male competition for mate access is intense (CluttonBrock et al. 1988, Le Boeuf and Reiter 1988, Packer et al. 1988; see Chapters 6 and 8). More importantly, this pattern was congruous with puma reproductive success determined by genetic markers for the puma population in the Northern Yellowstone Ecosystem (Murphy et al. 1998a). On four occasions (11 percent of consort pairs), more than one male associated with an estrus female (see Appendix 2). Male M36 associated with estrus females F41 and F68 two to five days after other territorial males (M29 and M38) had consorted with the females. Two other sires, M88 and M5, also associated with estrus females after another territorial male did on one occasion each

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(M3 and M38, respectively). In each of the four cases when estrus females were courted by two territorial males during the same estrus period, the males had overlapping territories. Female promiscuity and sexually induced ovulation creates the possibility that some puma litters may have more than one sire. So far, this has not been unequivocally tested in wild pumas because only one study has adequately estimated paternity using genetic markers. In his study of pumas in the Northern Yellowstone Ecosystem, Murphy et al. (1998a:95) observed that “radio-collared males singly accompanied females and only one father of each litter was identified using genetic methods.” Multiple paternity of offspring in the same litter has been found for other mammals, including California ground squirrels (Boellstorff et al. 1994), black bears (Schenk and Kovacs 1995), and even humans (Smith 1984). Although male pumas were polygynous and both sexes exhibited promiscuity, we documented some mate fidelity. Fidelity seemed to be partially dependent upon the position of the female in male territories and male longevity. It may have also been partially influenced by the degree of aggressiveness or dominance of a territorial male over other males. Two of female F21’s five litters were sired by male M3, and her last one was sired by M88. Two of F37’s three litters were sired by M7. F47 produced five litters: three were sired by M88, one by M3, and her last by M193. M88 also consorted with F47 during the same estrus that she first mated with M3. But M3 had died of old age four months before M193 sired F47’s last litter. Two of F107’s three litters were sired by her father, M88. Other females had different mates. Two of F15’s five litters were sired by M14 and M19; M19 killed M14 and usurped his territory, which contained F15. Two of F45’s five litters were sired by M52 and M151. Two of F41’s three litters were sired by M38 and M46. F149’s two litters were sired by M5 and M3. F27 had two nonviable litters, one sired by M20 and the other by M53. In all cases where female infidelity was demonstrated with contemporary territorial males, the male territories overlapped the female home ranges. Pumas in the Northern Yellowstone Ecosystem exhibited strong mate fidelity (Murphy et al. 1998a). In the protected puma population on the San Andres Mountains, prime and old-age territorial male pumas we re engaged in 90 percent of the know n breeding associations with females that resulted in viable litters. Prime-age males thirt y - s e ven to eighty-eight months old we re in 71 percent (n = 22) of associations. Old males 103–142 months old we re in 19 percent (n = 6) of breeding associations. But young males twenty-two to thirty-five months old we re in only 10 percent (n = 3) of them [14]. In heavily exploited puma populations, we would expect the age distribution of breeding males to shift tow a rd younger ages.

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Male M88 sired the most litters (n = 6) even though we disrupted his territorial tenure for 166 days by translocating him from the Treatment Area to northern New Mexico (Ruth et al. 1998). He sired his first litter at twenty-two months of age before we intervened. Thus, he might have sired even more litters as a young adult if we had not translocated him. After finding his way back to his original territory, an excursion that covered 494 airline km, he sired the other five litters when he was forty-five to sixty-seven months old. M88 was still the dominant male in his area through the end of the study and could have produced more litters thereafter. Male M3 was the next-most productive male with four litters that he sired when he was a prime to old male (i.e., 61–142 months). He died of old age in his territory only twenty-four days after he sired his last litter. Three other adult males (M7, M38, M46) sired three litters each. M7 and M46 sired all their litters when they were prime age (M7 when he was fifty to seventy-seven months old and M46 when he was thirty-five to eighty-six months old). M38 sired his litters when he was prime to old age (45–103 months). Of these three males, M7 was translocated; thus, we eliminated his further reproduction on our study area. M38 and M46 were still territorial at the end of our study and could have produced more litters. Two males (M88 and M5) also associated with estrus females after they had consorted with other males (see Appendix 2). The males were about 36 and 135 months old, respectively. During our study, seven male pumas with the greatest reproductive success (i.e., had sired two or more litters) were those that maintained territorial longevity for an average of 88.6 ± 30.5 months (i.e., 7.4 years; range = 41–128 months). And three of those were still vigorous territorial males at the end of the study. Six males that sired one or more viable litters and died of natural causes (i.e., three were killed by other territorial males, two died of complications of aging, and one died of disease) during our research had maintained territorial tenure for an average of 71.7 ± 43.4 months (i.e., six years; range = 21–128 months). In contrast, male pumas in moderately hunted populations may rarely achieve long territorial longevity. For example, in a population in north-central Wyoming, the oldest males were about seventy-two months old (Logan et al. 1986). Assuming that they acquired their territories at the age of twenty-four months, their longevity was about forty-eight months. The critical nature of longevity in a breeding range was perhaps best demonstrated by M88 and M49, both territorial males that we translocated 490 and 465 airline km, respectively, to northern New Mexico (Ruth et al. 1998). M88 returned to his original territory 166 days later and resumed breeding. M49 returned to his original territory 469 days later, killed a mule deer, then associated with his previous territorial neighbor, M3. We believe this encounter may have contributed to M49’s death about twelve days later. Both M88 and M49

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had endured months of uncertainty and travail as they navigated their way back to the areas where they had previously established social dominance and where they were familiar with vital resources. Two other adult males that we translocated also homed in the direction of the San Andres Mountains, but they died in between (Ruth et al. 1998). These adult male pumas exhibited strong fidelity to established territories, perhaps indicating that investing time and energy to establish dominance in an area increases fitness, both in opportunities to breed and in survival of offspring. Apparently it takes death or expulsion by a more dominant male to move an adult male from his established territory (see Chapter 12). It is likely that environmental conditions, such as severe restrictions in food or mates or increased access to mates, may also prompt an adult male to shift to a different area to improve his fitness, but empirical evidence for this is so far lacking. We did not document any breeding behavior involving males without territories. And in central Idaho, all breeding was done by resident adult males (Seidensticker et al. 1973). Similarly, all radio-collared sires in the Northern Yellowstone Ecosystem were residents; however, biologists there suggested that some untagged sires identified through genetic paternity analysis may have been “roaming nonresidents that sired litters during temporary visits to the study area” (Murphy et al. 1998a:90). If non-territorial male pumas (e.g., dispersers) are involved in breeding, we expect the frequency to be relatively rare in protected populations such as ours. Conversely, we would expect such incidences to increase in puma populations subjected to chronic severe exploitation where male longevity and territorial structure is disrupted by humans killing male pumas. We observed three other adult males in breeding associations with females, but the pairings did not result in viable litters. As previously mentioned, male M36 paired with estrus females twice after the females had already consorted with other males. Hence, we did not consider him to be the sire of those litters, although he could have been. M36 was about forty-six and ninety-four months old during those associations. Two other males, M20 and M53, consorted with F27 at the north end of our study area and sired nonviable litters. M20 sired F27’s first litter that was stillborn, and M53 sired the litter that F27 aborted just prior to her death (see Appendix 2). Both males were in prime ages (seventy-four and forty months old, respectively) when they sired the litters. M20 was monitored for forty-nine months; he spent about 90 percent of his time on the Oscura Mountains to the north of our study area. M53 was monitored as an adult for sixteen months; he spent about 66 percent of his time also on the Oscura Mountains. Consequently, both males could have sired other litters in the Oscura Mountains, where we did not radio-collar pumas.

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Sixteen other adult male pumas we re not documented as sires of viable litters on the San Andres Mountains. Most of the lack of documentation for re p ro d u c t i ve success for these males was due to re l a t i vely short monitoring periods and territorial tenure on our study area. In addition, our radiotelemetry monitoring schedule apparently missed paternal connections for some litters. Nevertheless, we documented seven of these males in potential breeding associations that did not result in viable litters. The number of times those individual males associated with adult females ranged from one to six (x– = 2.1 ± 1.9, median = 1). They associated with one to three different females during their tenure. The oldest male for which we did not document any associations with females on our study area was M1. He was about 145 months old when he died; but we monitored him for only forty-nine months. M1 spent about 40 p e rcent of his time on the Organ Mountains to the south of our study are a , where other pumas we re not monitored by radiotelemetry. M1 could have sired litters there. M1’s time on our study area was reduced as a direct result of new immigrant male M22, who usurped the part of M1’s territory there. M22 sired one litter during his twenty-two-month tenure before he was killed by neighboring territorial male M3. The remaining fifteen males were monitored as adults for durations ranging from one to fifty-one months (x– = 12.9 ± 12.0), considerably shorter than males that were documented sires [15]. The seven males that we documented in potential breeding associations with females were monitored for six to fifty-one months (x– = 17.7 ± 15.6). We inferred that all of these males had lower reproductive success than documented sires because of their relatively short tenure. Four of these males (M18, M23, M49, M114) were removed from the Treatment Area; hence, we directly affected their reproductive success. Two other males died. M73 was killed by another territorial male when he was 45.5 months old, and M192 died from capture-related injuries when he was about thirty-eight months old. Of these fifteen males, six were young (twenty-four to thirty-six months), six were young to prime (twenty-four to fifty-five months), and three were prime (thirty-seven to ninety-six months) ages during the time we monitored them. This relatively young age distribution tended to reflect low observed reproductive success. But, nine of the males were still present on the study area at the close of our research; thus they may have gone on to sire litters. Only male M73 seemed physiologically incapable of reproducing. When we initially marked him as a twenty-five-day-old cub we sexed him as a female based on external genitalia. But when we recaptured him as a 27.5-month-old adult, he was obviously a male. M73’s testicles had not descended into his scrotum; he was a bilateral cryptorchid. His body conformation reflected a lack of testosterone in his blood stream; he was more feminine, like a large sleek adult

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female than a robust male. And he probably lacked the aggressivity of normal adult male pumas (see Bronson 1989). M73 weighed only 45.4 kg, at least 10 kg lighter than male pumas normally weigh at that age (see Appendix 1). Moreover, during the two years we monitored him as an adult, his home range did not overlap any adult females. He was not competing with other territorial males for access to estrus females. M73’s case was the only time we observed cryptorchidism in adult male pumas on the San Andres Mountains (one of 33). This 3.0 percent frequency of cryptorchidism in our population was similar to the 3.9 percent that Barone et al. (1994) found in fifty-one male pumas sampled from Texas, Colorado, Latin America, and captive stock of uncertain genetic origin. However, those animals were unilateral cryptorchids (one testicle not descended). Comparatively, endangered Florida panthers appear to have an extraordinarily high frequency of unilateral cryptorchids, 43.8 percent, which may be the result of inbreeding depression (Barone et al. 1994). We inferred that reproductive success and hence fitness was greatest for territorial males with the greatest longevity, a conclusion also reached for male pumas in the Northern Yellowstone Ecosystem (Murphy et al. 1998a), African lions (Packer et al. 1988), and tigers in Nepal (Smith and McDougal 1991). It seems logical that traits that allow males to successfully compete for mates also help them to live longer lives, particularly if their greatest cause of death is intraspecies strife (see Chapter 8). We expect the largest, strongest, and most aggressive males to be the fittest to compete with other males and thus maintain long-standing dominance. This confers greater breeding opportunities with adult females residing within their territories (see Weckerly 1998). Male competition for mates is intense because low population density of adult females and their long birth intervals actually make estrus females rare. Even though female pumas are distributed at low densities in topographically and vegetatively complex habitats, individual estrus females can be defended sequentially during the puma’s year-round breeding season. This male-to-male competition for mates, which results in variable reproductive success and traits like sexual dimorphism, is known as sexual selection (Trivers 1985). Hence, sexual selection for traits, such as greater mass, strength, aggressivity, and other related traits that enhance survival and reproductive success, should improve the quality of genes passed by males to their offspring (Trivers 1985). Large body mass probably has been a strongly selected trait in male pumas because of the advantages it awards for overpowering competitors during territorial or mating challenges. In North America, adult male pumas, on average, outweigh females by 40 percent (see Chapter 2). Intense competition between males for mates has also been cited as a strong selective force for sexual dimorphism in other large mammals with polygynous mating systems, including large

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primates (Mitani et al. 1996), red deer (Clutton-Brock et al. 1988), and elephant seals (Le Boeuf and Reiter 1988, Hailey et al. 1994, Modig 1996). But if bigness is so advantageous to male pumas, why aren’t they normally two or three times larger than females? We suspect a trade-off favoring an optimal body size is involved. Extremely large males would require more energy for growth and maintenance. Consequently they would need to hunt and kill more frequently, which would diminish the time and energy they could allot to searching for and defending mates, engaging in copulation marathons to impregnate estrus females, and defending territory. Hence, extremely large size would lose out to optimally scaled males. Female pumas, on the other hand, have evolved an energy-efficient size that allows them greater parental investment to raise more offspring successfully. Part of that efficiency is the ability to kill large prey to feed rapidly growing offspring. Next, we examine how rigors of puma life affect pumas’ abilities to survive and breed.

LP > >

KX

1. Nursling litter size averaged about three cubs. Weaned litter size averaged about two cubs. Average litter size of nurslings was among the highest reported for pumas. The natality rate (i.e., average litter size / birth interval) averaged 0.17 and was also among the highest for puma. Fecundity rate (i.e., average number of live cubs / adult female / year) in the Treatment Area and the Reference area during the deer increase phase was 1.6 and 1.4, respectively; during the deer decline phase, it was 2.0 and 1.3, respectively. Fecundity was not obviously sensitive to the declining prey base. Sizes of mothers’ first litters and subsequent litters did not differ, nor did litter sizes of first-time mothers and old mothers. 2. Puma births occurred year-round but primarily during July–September, coinciding with the mule deer fawning season. We hypothesize that cubs born during a period of food abundance have the greatest chance of survival. 3. The puma gestation period averaged about ninety-two days. Birth dates minus gestation periods put the corresponding breeding period during April–June. We estimated estrus periods lasted one to ten days. Females exhibited promiscuity. We estimated an average estrous cycle length of about twenty-four days. Birth intervals on the San Andres Mountains averaged 17.4 months, among the shortest reported for pumas. Mothers that lost all their cubs successfully bred again an average of about one hundred days later. 4. Puberty was reached at about twenty-one months in female pumas and

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5.

6.

7.

8.

111

about twenty-four months in males. Females conceived successfully for the first time at an average age of about twenty-six months and produced their first litters at the average age of twenty-nine months. Philopatric females did not exhibit reproductive suppression. In the growing San Andres Mountains puma population, philopatric female progeny and female immigrants became reproductively active at about the same age. Other than the actual breeding activity, puma sires have no other direct parental investment. In contrast, mothers expend fourteen to nineteen months in time and tremendous energy feeding and caring for the cubs. The number of adult females giving birth to cubs each year in the Treatment Area averaged 52 percent; an average of 76 percent were raising cubs each year. In the Reference Area, these amounts averaged 48 percent and 74 percent, respectively. Reproductive success was variable for females but greatest for mothers that lived the longest lives. Mothers and recruited philopatric or neighboring female progeny normally formed matrilines. Females in matrilines had the highest reproductive success; hence, philopatry should be adaptive. Reproductive success for males was even more variable, and again it was greatest for fathers that lived the longest lives. Males with the greatest reproductive success maintained territorial longevity that averaged over seven years. Variation in male reproductive success was also affected by the number of adult females in his territory and his ability to compete with other males for estrus females. Sires bred with females within their territories, and mates occasionally exhibited fidelity. Adult males competed directly for territory and mates. We propose that in pumas, sexual selection resulted in sexual dimorphism and male aggressiveness.

LN N5LN5)L 1. Test for difference in litter size in the Treatment Area, pre- and post-treatment. Two-sample t-test, t = –1.7635, 15 d.f., P = 0.10. 2. Puma annual fecundity rates in mule deer population increase phase (1989–1990 to 1991–1992) and decline phase (1992–1993 to 1993–1994). Treatment Area: increase phase = 1.4, 1.0, 2.3, respectively; decline phase = 2.0, 2.0, respectively. Re f e rence Area: increase phase = 1.6, 1.2, 1.4, respectively; decline phase = 1.6, 0.9, respectively. 3. Natality rates (mean litter size / mean birth interval in months): British Columbia = 3.1 / 18.3; Utah = 2.4 / 24.3; Alberta = 2.2 / 19.7; Florida = 2.3 / 23.3. 4. Test for difference in sizes of first litters in eight matrilineal mothers and six immigrant mothers. Two-sample t-test, t = 1.341, 12 d.f., P = 0.21.

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5. Test for difference in sizes of litters of six old mothers and first litters of eight matrilineal mothers. Two-sample t-test, t = 1.177, 12 d.f., P = 0.26. 6. Test for the occurrence of puma litters during July–September relative to what is expected in those three months (19.5) and October–June (58.5). Chi-square test, c2 = 10.68, 1 d.f., P = 0.0012. 7. Test for differences in ages of seven known-age female pumas and one known-age and five approximately known-age male pumas at first association with the opposite sex. Mann-Whitney U test, U = 8.5, P = 0.17. 8. Test for differences in mass (kg) in twelve independent male pumas eleven to twenty months old (x– = 15.3 ± 3.2 months) that averaged 39.5 ± 8.4 kg, 90 percent CI = 35.1–43.8, median = 39.9, and eleven adult male pumas twenty-one to twenty-seven months old (x– = 24.1 ± 2.0 months) that averaged 53.1 ± 4.3 kg, 90 percent CI = 50.8–55.5, median = 52.2. MannWhitney U test, U = 124, P = 0.0003. 9. Test for difference in mass (kg) in eleven adult male pumas twenty-one to twenty-seven months old (see [8] above) and sixteen adult male pumas twenty-eight to ninety-six months old (x– = 44.7 ± 17.8 months) that averaged 56.4 ± 5.4 kg, 90 percent CI = 54.1–58.8, median = 56.4. MannWhitney U test, U = 53.5, P = 0.09. 10. Number, percentage, and mean ages of mothers in young (eighteen to thirty-six months), prime (thirty-seven to ninety-six months), and old (97–156 months) age classes. Young: twenty-five, 33 percent, 26.9 ± 5.2; prime: forty-six, 60 percent, 60.6 ± 17.4; old: five, 7 percent, 109.2 ± 11.5. 11. Linear regression of the number of litters produced per adult female puma (monitored by radiotelemetry for twelve months or more each, n = 28) on the number of months that each female was monitored (as an index to longevity): Number of litters = –0.3733 + 0.0651 (number of months monitored), P < 0.0001, r2 = 0.79. 12. Test for differences in number of litters and cubs produced by matrilineal mothers and non-matrilineal mothers with unknown status mothers. Number of litters produced by matrilineal mothers versus non-matrilineal mothers and mothers of unknown status was not different than an expected even distribution. Chi-square test, c2 = 1.268, 1 d.f., P > 0.10. Number of cubs produced by matrilineal mothers was greater than expected in an even distribution: c2 = 7.278, 1 d.f., P = 0.007. 13. Linear regression of the number of litters sired per adult male puma (monitored by radiotelemetry for twelve months or more each, n = 19) on the number of months that each male was monitored (as an index to longevity): Number of litters sired = –0.4111 + 0.0427 (number of months monitored), P = 0.002, r2 = 0.45.

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14. Number, percentage, range, and mean ± SD ages of territorial male pumas involved in thirty-one successful matings with female pumas: Young (twenty-four to thirty-six months) – n = 3, 10 percent, range = 22–35 months, x– = 28.0 ± 6.6; Prime (thirty-seven to ninety-six months) – n = 22, 71 percent, range = 37–88 months, x– = 60.7 ± 14.5; Old (97–156 months) – n = 6, 19 percent, range = 103–142 months, x– = 118 ± 17.3. 15. Test for difference in monitoring duration in fifteen sires and fifteen nonsires. Mann-Whitney U test, U = 208.5, P < 0.0001.

Chapter 8

Mortality and Survival

Human-Caused Mortality As we discussed previously, some puma deaths were caused by our own research activities (see Chapter 4). Four adult pumas, three females (F27, F145, F87) and one male (M192), died due to injuries they sustained while captured in our foothold snares (F27 on 9 April 1990, F145 on 5 February 1992, F87 on 15 February 1993, M192 on 14 February 1994). The three females were successful mothers ranging in age from sixty to sixty-nine months; they represented 5 percent of all the adult females we documented on the San Andres Mountains during our study. When F87 died, she was raising about four newborns that we never got to see. At the time of F145’s death, she was raising three fourteenmonth-old cubs; at least two (both females) survived to adulthood. The adult male represented 3 percent of all adult males we documented; he was about thirty-eight months old. Nine cubs also died as a result of our research efforts, representing 4 percent of all cubs we observed on the San Andres Mountains. They ranged in age from newborn to six months. One was a male, two were females; we did not handle the remaining six to determine their sex. Even presumably inviolate wild lands like the San Andres Mountains are not totally immune from poachers. They had a good excuse to be nearby; about 93 km2 of our study area on the northwest edge lay outside of White Sands Missile Range boundaries and was subjected to legal sport-hunting and furbearer trapping. Outfitters that came to hunt that tiny strip of land, even knowing that all tagged pumas were legally off-limits, hoped to catch a rare untagged puma and 115

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undoubtedly knew their dogs could end up within our study area where all pumas were protected. Even if they did catch a tagged cat, at worst, they would experience an exhilarating hunt. An unmarked female, about twenty-four months old (we inspected the skull and skin) was killed by a puma hunter on 10 March 1988. We assumed this female had recently immigrated onto the study area, perhaps coming from mountains to the west. Even though the outfitter took us to the very tree where the puma was shot, on Whites Sands Missile Range, neither he nor the hunter was prosecuted by authorities. Twice after that, as we were locating radio-collared pumas from an airplane, we circled this outfitter’s hunting party at puma locations. We figured his dogs had the cats bayed in trees. In the second instance, he was clearly on White Sands Missile Range. We even ground-tracked the hunting party and caught one of the dogs, complete with a tag identifying the outfitter. According to the outfitter, the continual presence of our research team in the mountains finally discouraged him and other puma hunters from hunting there for the duration of our study. Before the crash in fur prices in the early 1990s, a few trappers worked the northwest foothills of our study area. A trapper, no doubt trying for coyotes and bobcats, caught radio-collared female F9 when she was thirty-one months old. F9 escaped the steel foothold trap, but not before it ripped off two toes from her left forefoot, exposing the remaining phalanges. She died, apparently from septicemia, on 14 January 1989. We knew F9 since she was a nursling. As an adult, she had consorted with at least one male, but she did not produce cubs before her death. We also knew radio-collared female F181 since she was a nursling. On 12 November 1994 a mule-deer hunter snapped her spine with a .25 caliber bullet. We found her prostrate body on the ground where she expired, clawing at the grass. She was twenty-six months old and had not yet bred. During necropsy, we found she had been living quite well with an abdominal hernia that we had initially diagnosed when we recaptured her at age 12.5 months. Apparently, this condition was congenital because her sister (F183) also had an abdominal hernia, but their mother F68 did not. There was copious fat on her kidneys, pericardium, mesenteries, and subcutaneous areas, signifying that she was well nourished. These three females killed by humans represented another 5 percent of the adult females we documented on our study area. All but one of these human-caused deaths, that of a cub, occurred in the Reference Area. Deaths of the adult pumas occurred sporadically. One death occurred in each of the years 1988, 1989, 1990, 1992, and 1993, and two adults died in 1994. In Chapter 10, we address the potential effects that those losses had on the dynamics of the puma population in the Reference Area.

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Natural Mortality Natural mortality factors were independent of direct human influences. And because we studied a protected puma population, most documented puma deaths were from natural causes. By examining and quantifying natural puma deaths, we were able to better understand how natural selection forces impacted the puma population and individual reproductive success.

Cubs We estimated cub mortality rates by quantifying changes in litter sizes over time. We accomplished this by sneaking up on families with radio-tagged members to count cubs and by finding track sets of radio-tagged families and noting attrition in the number of cub tracks. Radio-tagged cubs provided us with direct mortality data, but we relied on intensive ground tracking and luck to help us find non-collared cubs that died. Most of the latter simply vanished from family groups, with no clue of their demise. In a few instances, entire litters of suckling cubs vanished before we even had a chance to examine them. We estimated mortality and survival rates using data only from cubs that we initially recorded as nurslings and that were born before January 1994; this way, the cubs could have reached the extreme age of independence (i.e., sixteen months) before the end of our study in March 1995. Cub surv i val rate in the Treatment Area was slightly lower than in the Reference Area. Out of sixty-nine cubs born on the Treatment Area, about twenty-eight died, twenty-seven from natural causes and one from research-related activities. This produced a surv i val rate of 0.59 (i.e., mortality rate = 0.41). In the Re f e rence Area, about thirty-four out of ninety-three cubs died (thirty from natural causes, four from research-related causes), producing a surv i val rate of 0.63. When we considered only natural deaths, surv i val rates increased slightly to 0.60 in the Treatment Area and to 0.66 in the Reference Area. By combining cubs (n = 157) subjected to natural death (n = 57) in the Treatment Area and Re f e rence Area, the survival rate was 0.64. From this subset of cubs, we also estimated surv i val rates of ninety-seven cubs we knew we re born to matrilineal mothers and fifty-seven cubs born to mothers that we were fairly certain were not matrilineal mothers. Cubs of matrilineal mothers had a higher rate of surv i val to independence, 0.67, than cubs of non-matrilineal mothers, 0.56. Although the probability of surv i val of cubs in each maternal category would be expected to be equal at P = 0.20 [1], we believe a tendency for higher surv i val rates of cubs born to matrilineal mothers is biologically vital. Matrilineal mothers would tend to have greater fitness, and philopatry as a trait, at least in females, would be strongly favored.

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We further estimated cub survival rates in the Treatment and Reference Areas during the mule deer increase (1989–1990 to 1991–1992) and decline (1992–1993 to 1993–1994) phases while considering only cubs starting as nurslings and subjected to natural causes of death. In the Treatment Area, cub survival rate during the deer increase phase was 0.64 (i.e., twenty-three of thirtysix), but it declined to 0.57 (i.e., thirteen of twenty-three) during the deer decline phase. The Reference Area exhibited an upward change from 0.66 (i.e., thirty-one of forty-seven) in the deer increase phase to 0.72 (i.e., twenty-one of twenty-nine) in the deer decline phase. Overall, cub survival did not appear to be sensitive to the deer population dynamics during our research. We believe it may take a sustained low deer population to trigger a steep decline in cub survival on the San Andres Mountains. These observations further support the expectation for a time delay before the puma population declines in response to a reduced prey base. We combined cubs from the Treatment Area and Reference Area to develop a survival curve from birth to thirteen months, approximately the age at which cubs became independent of their mothers (see Chapter 9). Most of the mortality (65 percent) occurred when cubs were less than or equal to three months old (Fig. 8-1). This age span includes the time that cubs are suckling and confined to nurseries, usually from six to eight weeks old, and the first month that mothers are moving their cubs away from nurseries to prey kills that they made to feed the now carnivorous cubs. Cubs are highly vulnerable during both of these periods. Nurseries are the focal point of activity of mothers as they sortie away to hunt and return, usually on a daily basis, to nurse and care for the cubs. This high-frequency activity can work to the disadvantage of cubs since other predators, including male pumas, detect visual, auditory, and olfactory cues that can lead them to nurseries. Unless the small, helpless cubs can hide out of reach of teeth and claws, they can easily become prey. As cubs leave the familiar surroundings of the nursery to make their way to their mother’s kills, they still are highly vulnerable to predation because of their small size and inexperience; and they are vulnerable to accidents that may befall them while traversing rugged terrain. Furthermore, their relatively immature immune systems make them vulnerable to diseases (Saunders 1970, Coe Clough and Roth 1998). Sex-related survival rates (calculated by excluding cubs of unknown sex that were born and disappeared) generated similar survival curves for males and females. But female cubs seemed to be more vulnerable at older ages and had only a slightly lower survival rate than males (Fig. 8-1). Few other data sets on puma cub survival rates were available from other parts of North America for us to compare. In an unhunted puma population with a very low density of 0.5 pumas per 100 km2 in south-central Utah, sur-

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FIGURE 8-1. Puma cub survival rates from birth to thirteen months, San Andres Mountains, New Mexico.

vival of eighteen cubs monitored from contact (i.e., two to ten months old) to dispersal had a survival rate of 0.67 (Hemker et al. 1986). Survival rates from birth to independence were probably lower than this because survival of cubs less than two months old was not estimated. In a human-dominated landscape in Southern California that effectively isolated and fragmented puma habitat, an annual survival rate for nineteen cubs was 0.52. But biologists in that study pointed out that they normally counted cubs “several weeks” after birth of litters and that other cubs probably died; hence, they suggested that the actual survival rate was probably 0.45–0.52 (Beier and Barrett 1993). Puma cubs in naturally fragmented habitat in southern Idaho had similarly low survival rates (Lopez-Gonzalez 1999). There, survival for about sixty cubs studied from one month old to dispersal was 0.42. The survival rate for males was higher, 0.58, than for females, 0.45. In Alberta, forty-two cubs monitored from first contact to independence had an extremely high survival rate of 0.98. But the biologists cautioned that actual mortality levels were likely underestimated because some cubs were not detected until they were at least 0.6 year old, and more postnatal mortality probably occurred at younger ages (Ross and Jalkotzy 1992). Survival rates in Florida panther cubs are likewise tenuous but are more serious for this endangered population (see Maehr 1996: Appendix C). The differential between mean litter sizes for four litters less than fourteen days old and twenty-

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one litters four to twelve months old suggested a first-year survival rate of 0.84 (Maehr and Caddick 1995). However, this method underestimates mortality because it excludes entire litters that might have been lost. Another estimate of 0.87 was based on thirteen survivors out of fifteen radio-collared panther cubs “older than 4 months but less than 12 months” (Maehr and Caddick 1995:1295). Again, this underestimates cub mortality because probable losses of cubs less than four months old were excluded. If Florida panther cubs had the same distribution of deaths from birth to independence as we observed (Fig. 81), then it is possible that only 26 percent of the total mortality occurred in panther cubs five to twelve months old. If these proportions are reasonable, we could expect as much as 74 percent of the mortality to occur in cubs up to four months old. Thus, about 60 percent of panther cubs may have actually survived to independence. Su rv i val curves from our study and Lopez-Gonzalez (1999) suggest a possible pattern of higher surv i val rates for male cubs than female cubs. If this characteristic is real, higher surv i val in males may be due to greater maternal i n vestment in male offspring. As mentioned previously, male cubs are generally larger than female cubs; furt h e r m o re, surv i val in the sexes begins to d i verge in weaned cubs four or more months old in southern Idaho (LopezGonzalez 1999) and eight or more months old in our study. Larger male cubs may dominate choice feeding sites at nipples and carcasses, avoid predation better, and more efficiently traverse rugged terrain, all of which could give them surv i val advantages over female siblings during the period of parental investment. Although thirty-five cubs disappeared from unknown reasons on our study area, we were able to assign cause of death to twenty-seven other cubs (Fig. 8-2). Infanticide and cannibalism was committed only by male pumas; they killed twelve cubs in six litters (44 percent). In all cases, plundering males apparently were not sires of the cubs. We know that in one case, the sire was another male. Ages of puma-killed cubs ranged from 1.1 to 5.0 months old (x– = 2.1 ± 1.1). Eleven of the cubs were eaten by male pumas, including two entire litters with three and four cubs that were sixty-six and thirty-four days old, respectively. In the former case, M88 consumed the nurslings of his daughter F107, who was about 1.8 km away from the cubs at the time. In the latter case, M52 ate the nurslings of F45 while she was 1.3 km away feeding on a mule deer kill. A 3.5-month-old cub was not eaten; she died as a result of canines penetrating the braincase. In an instance where two five-month-old siblings were killed, the mother (F61) was also killed by the male puma, probably as she futilely tried to defend her cubs. Starvation apparently claimed ten cubs (37 percent). Starvation of five cubs in two litters that were about one week and five months old, respec-

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FPO @ 80%

FIGURE 8-2. Causes of death in puma cubs, San Andres Mountains, New Mexico. The numbers represent the number of cubs that died in each category of mortality (death).

tively, occurred because their mothers (F15 and F86) were killed by male pumas. Three 36-day-old nurslings starved eight days before their mother (F4) died of an undiagnosed disease. Two five-month-old cubs probably starved not long after their mother (F195) died from injuries sustained while trying to kill a deer. We never found evidence of the cubs again. Disease that caused diarrhea and dehydration killed three cubs in one litter when they were around fifty-seven days old (11 percent). A fall from a cliff killed one 59-day-old cub (4 percent), and coyotes killed one six-month-old cub (4 percent). Two female cubs that were orphaned at ages 7.5 and 9.8 months survived. The younger puma (F68) and her male sibling (M67) scavenged their mother’s carcass after she died from undetermined causes. This provided them nourishment that probably improved the cubs’ chances of survival. If M67 survived, he apparently emigrated from our study area; we never found evidence of him again. But F68 became a matrilineal mother by establishing her adult home range on her natal area. Later, two of her own female offspring (F181 and F183) exhibited philopatry after independence. The older orphaned female (F10) used an area adjacent to her mother’s (F2) home range, and mostly in the Organ Mountains south of our study area. But she was killed by a male puma (M22) when she was eighteen months old, the same male that apparently killed her mother.

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PHOTO 18. Orphaned puma F10 at ten months of age and nine days after her mother, F2, died.

Subadults We estimated survival rates for twenty-five radio-collared subadult pumas that we monitored after independence from mothers and until they became adults or died. Their ages ranged from eight to twenty-seven months. Nine males were monitored for 1,797 days and sixteen females were monitored for 2,590 days. Subadults males had a finite survival rate of 0.56, which was significantly lower than the female finite survival rate of 0.88 [2]. Four males and two females died when they were 14.3–18.0 months old (x– = 15.7 ± 1.5). All of them were killed by male pumas. They all died as a result of bites that penetrated the brain case, the frontal region of the skull, or the cervical vertebrae. Only one individual was fed upon slightly, suggesting to us that most of these cats probably were regarded as competitors. Two male subadults were killed on their natal areas in the Treatment Area, both by the same male. Male M64 was independent at twelve months old. When he was 14.5 months old, he encountered a newly arrived immigrant, twenty-four-month-old M88, at the cache of a yearling mule deer buck that M64 had killed four days before. M88 was also the puma that apparently killed M64’s mother (F60) sixteen days prior, also in an incident apparently involving direct competition for food (see “Adults”). When we captured M88 three days

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after M64’s demise, he still had wounds from battles with mother and son. His head and neck were swollen from claw punctures and scratches, and he had both fresh and mending claw scratches on his face and head. There were also claw scratches on his left foreleg, shoulder, and hip. M64 still had hair of his foe stuck to his foreclaws, but he had taken mortal punishment. Canine punctures to the braincase were fatal. He also had massive bites to his forearms, triceps, shoulders, and lumbar region. A canine punctured the right ileum. Claws had penetrated skin on his chest. M64 had been making a living well on his own. He had moderate amounts of subcutaneous fat along the midline of his abdominal and inguinal regions; there were dense fat deposits on his mesenteries, kidneys, and pericardium. But he was clearly subordinate to the older and heavier M88 (56.7 kg vs. 41.7 kg). Twenty months later, M88 again fought over another mule deer kill. This time he encountered his own 14.3-month-old son M108, who had been independent for only 1.7 months. Either M108 was investigating M88’s kill, considering the potential for a free meal, and triggered M88’s aggression, or M88 sensed M108’s kill and proceeded to usurp it by killing its inexperienced defender. Canine punctures to the braincase were fatal. M88 did not get away wholly unscathed; tufts of puma hair were scattered about, and on the battleground we found M88’s eartag, which had been ripped from his pinna. In this case too, M108 was no match for his experienced, larger father (63 kg vs. 39 kg). In the encounters with M64 and M108, M88 was certainly directly competing for food. In addition, since both subadults were killed in the core of his territory, M88 may have also been exerting his dominance over these males in the area where he acquired both food and mates. M88 had all the tactical advantages to win these contests. He was older and more experienced, and he far outweighed the subadults 41 to 63 percent [3]. The other two males were killed after they dispersed from their natal areas. M140 was 15.6 months old when his braincase was crushed and his spinal cord severed between the atlas and axis by another male puma. He had been independent for only nineteen days and in the interim had dispersed 42.2 km north of his natal area, going from the Treatment Area to the Reference Area. His death, too, may have been associated with food; M140’s stomach was full with remains of a newborn calf oryx. We suspected, but could not prove, that M140 was probably killed by new immigrant male M192, who was about twenty-seven months old at the time M140 died. Prior to his demise, M140 was healthy and robust, weighing 50.8 kg. He had copious subcutaneous fat along the midline of his thorax and abdomen all the way to the inguinal region, on his shoulders, along the midline of his back, on his flanks, and along the entire length of his tail. There were extensive fat deposits on his mesenteries and kidneys.

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Subadult M122 was independent at 14.5 months old and almost immediately emigrated from the San Andres Mountains. During the next eighty-two days he dispersed 134 km northeast of his natal area by traversing the comparatively desolate Tularosa Basin and onto El Capitan Mountain. When he was seventeen months old, he encountered a male puma on this new terrain. In an ensuing fight, M122 received canine punctures that penetrated the frontal area of the skull, damaged the right orbit, and broke the right zygomatic arch. Although we found tracks of the dominant male puma, we could not find any evidence of a prey kill in the vicinity of the death site, and M122’s stomach was empty. This direct competition may not have been over food but instead may have been about dominance in that area. As a long-distance disperser, M122 was apparently finding enough food; he weighed 49.9 kg at death and had subcutaneous fat along his back and abdomen. As mentioned previously, subadult female F10 was orphaned at 9.8 months of age, when her mother was killed by a male puma (probably new immigrant M22). F10 was killed by M22 at the age of eighteen months as a result of a bite that crushed the frontal region of her skull. She died 16.3 km southwest of her natal area at the southern end of the Treatment Area. The male did not consume F10 but bit chunks of skin from her back and left shoulder. F10’s stomach was empty, and there was no evidence of a prey kill in the vicinity. However, F10 was apparently at the onset of puberty. Her uterus was engorged with blood vessels, suggesting that she was in proestrus or estrus. Vocalizations by F10 during either period could have summoned the attention of M22 (see Mehrer 1975). Multiple bites to the back of F10’s neck causing subcutaneous hemorrhaging suggested that M22 attempted to mount her. Males of the larger species of the Felidae usually use the neck bite as a vestigial behavior at the climax of copulation. Canines are clearly lethal weapons, and presumably the delayed neck bite evolved to minimize the danger of the mating act accidentally turning into an attack. Selection would have favored males who did not harm their mates. In pumas, the neck bite is variable (Ewer 1973) and may not be used at all during mating (Mehrer 1975). We wondered if M22 may have used the neck bite far too aggressively, triggering a defensive counterassault by the inexperienced F10, which escalated to M22’s fatal attack. The other subadult female, F96, was independent at about twelve months of age. Her activities centered in her natal area in the Treatment Area until she met her demise, at the age of 14.5 months, in the jaws of the notorious M88. This was the third puma he had killed since his arrival on the San Andres Mountains ten months previously. As in the prior two instances, the pumas directly competed for a mule deer kill. Judging from F96’s stomach full of deer tissues, she had fed on the deer at least once. M88 had crushed F96’s braincase and clawed

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her back, stripping skin down the right side from the shoulders to the hips. He consumed a small amount of muscle tissue along the spine. In both instances that subadult females were killed by territorial males, the battles were probably no contest. The males were 68–117 percent greater in mass and probably easily overwhelmed the females [4]. Male M198 was born in the Treatment Area and dispersed north into the Reference Area. His decomposed body lay in the bottom of a canyon 84 km north of his natal area. He may have been dispersing or decided to try to establish a territory in the area when he died at about twenty-four months of age. Damage to the left orbit of his skull indicated an injury that could have occurred in a fight with another puma or by accident. Even his eye may have been avulsed or destroyed. If the injury itself was not fatal, then infection may have killed him. An untagged twenty-month-old male puma had just immigrated to the south end of the Treatment Area, perhaps from the Organ Mountains, when he encountered territorial male M1. We followed tracks on the ground with both pumas running or trotting where M1 chased the young male out of a rugged canyon, and about 2 km across grass-covered flats dotted with bushy mesquites, prickly pear, and ephedra. Finally, the subadult futilely sought to escape his nemesis by climbing an electrical utility pole. It was either that or make a stand on the desert floor; no boulder piles or crevasses were nearby to offer safety. There was only one set of claw marks ascending the utility pole. Upon topping the pole, the cat’s front feet and face completed the circuit, and he was electrocuted. The body fell to the ground, apparently at the feet of M1, who walked around it, then traveled back to the canyon where the episode began. M1, about 115 months old, was certainly the most experienced and the most physically dominant, weighing at least 27 percent more than the young male [5]. The young male’s stomach was full of deer tissues, so it is possible that this aggressive encounter was the result of direct competition for food. We also found decomposed remains of two female pumas that died independently of each other in the Reference Area when they were about twelve and nine months old. Causes of death were unknown, but their skeletons did not indicate trauma. No ear tags were found at the sites, but if present, they could have been carried away by scavengers such as pack rats, foxes, or ravens. We had noticed the disappearance of ear tags from carcasses of other marked pumas after such scavenger activity. Pumas endure a harsh life from birth to adulthood. As cubs, they must survive disease and accidents, and must avoid predation, including being eaten by their own kind. It appears that cubs born to matrilineal mothers may have a greater chance of survival than cubs born to mothers that are not members of a

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matriline. If male cubs have a slightly better chance of survival than female siblings, the scale changes during the stage of independence. As subadults, pumas must be skilled enough to kill prey to sustain their rapidly growing bodies, and if they disperse, must tolerate long-distance moves, sometimes across inhospitable habitat, before they establish a new home. Most of all, they must avoid encountering territorial male pumas, clearly their greatest threat as cubs and subadults in populations unexploited by humans. This source of death provides strong selective pressure for female pumas who avoid males outside of mating, and for offspring to disperse from natal areas where a territorial male (usually their father) resides. But dispersal has other costs, particularly for subadult males, because practically all of them disperse long distances from natal areas (see Chapter 9) and explore terrain with unpredictable resources and risks, including other tenant male pumas determined to exert their dominance. We suspect that survival rates of female subadults would have been lower than we observed if females had the same propensity for long-distance dispersal as males. In our rebuilding study population, only one of the sixteen radio-collared female subadults dispersed clear of her natal area. All the other females either were philopatric (n = 11) or dispersed only a short distance and established their home ranges adjacent to their natal areas (n = 4). Considering that female dispersal may be partially density dependent (see Chapters 10 and 13), greater subadult female mortality may occur at high densities. Male and female subadult surv i val rates may be more equivalent in those conditions. If philopatric females tend to have higher survival rates than dispersers, and cubs of matrilineal mothers are favored, we would expect philopatry to be the favored female strategy. Quantitative data on survival rates of independent subadults in other puma populations is practically nonexistent, primarily because most pumas monitored in this age class dispersed from study areas and biologists lost contact with them. Some information comes from Colorado’s Uncompahgre Plateau where Anderson et al. (1992) estimated an annual survival rate of 0.64 for pumas twelve to twenty-four months old. He used data from twenty male and twenty-two female pumas and combined the sexes to estimate the rate using the product limit (i.e., Kaplan-Meier) procedure (Pollock et al. 1989). Although this rate falls between our estimated rates for subadult males and females from the San Andres Mountains, a direct comparison is tenuous because the Colorado study did not indicate the social status of the monitored pumas. Younger-aged pumas could have been dependent cubs or independent subadults, whereas older-aged pumas may have been dispersers or resident adults. Life for a puma born on the San Andres Mountains was very risky, even though the population was protected from human exploitation. The chance of

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a male surviving to the age of adulthood was about 36 percent (i.e., 100 x 0.64 x 0.56) and that of a female with philopatric tendencies was about 56 percent (100 x 0.64 x 0.88). If a female emigrated from the San Andres Mountains, we would expect her chance of surviving to adulthood to be about the same as for a male, 36 percent. These different survival rates partially explain the tendency for fewer adult males than adult females in puma populations. Lower survival rates for males further contribute to greater variability in reproductive success in comparison to females, because a greater proportion of males do not even survive to have a chance to breed. As adults, life was still harsh, but the scales of survival tipped again in favor of males.

Adults Our information of survival and mortality in adults came from thirty-four male and fifty-one female radio-collared pumas. They ranged in age from 18 to 152 months old. We used Micromort, a survival analysis software package (Heisey and Fuller 1985a,b). This software takes input data on the number of days that radio-collared pumas were monitored in an interval (in this case a year starting with 1 January), the number of pumas that died of specific causes in the interval, and then computes the survival rates and agent-specific mortality rates for each interval. By using this technique, we were able to compare rates between male and female adult pumas each year during the eight-year span from 1987 to 1994 (Table 8-1). We considered the possibility that survival rates for adult pumas may differ in the Treatment Area and the Reference Area, perhaps related to the population flux caused by our experimental removal of pumas. But annual survival rates of adult males living in the Treatment Area and Reference Area differed in only one of the eight years (1989) [6]. Similarly, for adult females in the Treatment Area and Reference Area, annual survival rates differed in two of the eight years (1991, 1993) [7]. Because of the overriding tendency for comparable survival rates of adults in the Treatment Area and Reference Area, we combined adult pumas in each sex from both areas to examine survival rates for adults on the San Andres Mountains as a whole. Consequently, we were able to analyze survival and agent-specific mortality rates for adults during 1987–1994 when we monitored nine to twenty radio-collared males and seven to twenty-four radiocollared females each year (Table 8-1). Annual survival rates for males and females differed during the first four years (1987–1990), but not during the last four years (1991–1994) [8] and in general favored males (five of the eight years). Annual survival rates for males averaged 0.91 ± 0.08, and for females averaged 0.82 ± 0.14. These data (Table 8-1) did not suggest a declining trend in adult survival rate during the mule deer decline that began in the 1992–1993 biolog-

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Table 8-1. Annual survival rates for adult pumas, 1987–1994, San Andres Mountains, New Mexico.a Year Puma-days 1987b 1988b 1989b 1990b 1991 1992 1993 1994

2685 3675 4305 4381 3340 4184 4656 4909

Males Females Rate 95% C.L. Puma-days Rate 0.87 1.0 0.84 1.0 0.90 1.0 0.79 0.86

0.67–1.0 1.0–1.0 0.67–1.0 1.0–1.0 0.72–1.0 1.0–1.0 0.61–1.0 0.70–1.0

1689 2735 4672 6179 5296 6353 6057 5199

0.52 0.76 1.0 0.79 0.87 0.94 0.84 0.87

95% C.L. 0.25–1.0 0.53–1.0 1.0–1.0 0.63–1.0 0.72–1.0 0.84–1.0 0.68–1.0 0.72–1.0

aSurvival rates and 95 percent C.L. (Confidence Limits) were computed using Micromort software (Heisey and Fuller 1985a,b). bSurvival rates of males and females were significantly different (all P 0.06).

ical year, particularly in females, who affect population growth the most (see Chapter 10). Survival rates for adult pumas in other parts of their range are limited. Biologists studying a low-density puma population in southern Utah estimated survival rates for three to eight resident adult radio-collared pumas per year during 1980–1986 (Lindzey et al. 1988). Like us, they used Micromort software. They defined “resident adults” as pumas “ 16 months of age that demonstrated continuous and predictable use of an area for 6 months” (Lindzey et al. 1988:665). Annual survival rates for females averaged 0.71 and ranged from 0.45 to 1.0. Because only one male could be monitored in some years, the biologists pooled males and females to estimate adult annual survival rates with a mean of 0.72 and a range of 0.52–1.0. For a puma population in fragmented habitat in Southern California, biologists used the product-limit procedure (Pollock et al. 1989) for twenty adult pumas (Beier and Barrett 1993). They pooled males and females because of small numbers and estimated an adult annual survival rate of 0.75. In Colorado, biologists used that same method for twenty males and twenty-two females, and estimated annual survival rates of 0.69, 0.92, and 0.80 for pumas in age classes twenty-four to thirty-six months, thirty-six to fortyeight months, and forty-eight to sixty months, respectively (Anderson et al. 1992). In a puma population in southeastern Arizona subjected to extremely heavy predator control and sport-hunting, biologists used Micromort software to

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estimate survival rates for a small sample of four males and two to five females each year over a three-year period. Annual survival rates ranged from 0.12 to 1.0 for males and from 0 to 0.81 for females. The biologists pointed out that female survival rates were higher than males except during one year when only two females were sampled. The higher male mortality rate was associated with a greater number of males killed for depredation control (i.e., sixteen males versus six females) (Cunningham et al. 1995). Using Micromort software, we computed agent-specific mortality rates for radio-collared adult pumas during the eight-year span 1987–1994. Results showed that intraspecies strife (i.e., pumas killing other pumas) was the chief agent of death for adult male and female pumas (mortality rates were 0.39 and 0.39, respectively). Accidents, chiefly during attempts to kill prey but including one snakebite incident, was the next most important agent of death for females (0.20). But males did not die from similar accidents. Disease was a greater agent of death in females (0.16) than males (0.08). As would be expected, males were more likely to die of old-age-related physiological problems (0.08) than females (0.01). Although we could categorize all male deaths, we could not determine agents of death for two females (0.04). During our entire study from 1985 to 1995, we examined the remains of thirty adult pumas, including eleven males and nineteen females, to try to determine causes of death (Table 8-2). On average, males died at older ages (90.0 ± 38.7 months) than did females (53.3 ± 32.6 months)[9]. Females that actually produced litters during their lives (n = 13) died at the average age of 64.8 ± 33.7 months. Intraspecies strife was the greatest cause of mortality, comprising 46 percent of male deaths and 53 percent of female deaths. Ages of adults killed by other pumas were highly variable (Table 8-2). Males killed fourteen of the pumas; the sex of a puma that killed one adult female was unknown. Through radio-tracking, then retracing pumas’ movements from tracks, as well as through examining wounds on dead pumas and their perpetrators we caught soon after battles, we were able to assess circumstances in which pumas kill other pumas. Adult females were killed while defending their cubs, while competing directly for food, and as prey themselves. Two females died apparently while trying to defend their cubs. F2 (eighty-four months old) was probably killed by M22 (twenty-two months old), a new immigrant male to the Treatment Area. F2 may have been protecting her three ten-month-old cubs at the time of her encounter. M22 inflicted fatal bites that crushed F2’s braincase and broke cervical vertebrae. At least two of the cubs survived the attack; female F10 established a home range adjacent to her natal area (and later was killed by M22), but the fates of her two brothers were unknown. F61 (twenty-five months old) was probably trying to defend her two five-month-old cubs when

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Table 8-2. Number, percentage, and ages of adult pumas that died of natural causes on the San Andres Mountains, New Mexico, 1985–1995. Cause of death

No.

Strife Disease Accidents Old age Unknown Snakebite Total deaths

5 3 0 2 1 0 11

Males % Age (mo.) x– ± SD 46 27 0 18 9 0

80.2 ± 41.5 74.7 ± 9.3 147.5 ± 6.4 81.0

No. 10 2 3 1 2 1 19

Females % Age (mo.) x– ± SD 53 11 16 5 11 5

50.5 ± 33.6 78.0 ± 15.6 45.0 ± 22.5 122.0 30.0 ± 5.7 34.0

she was killed, probably by a new immigrant male puma (possibly M29, twentyeight months old) in the Reference Area. Canine punctures to her braincase were fatal. The male had killed and almost entirely consumed at least one of the cubs. The male did not feed on F61. Multiple scats on scrapes made by the male puma in the vicinity instead suggested he probably ate both cubs. Two other females were killed while competing directly with males for food. F60 (forty-three months old) and a new immigrant male to the Treatment Area, M88 (twenty months old), fought fiercely, probably over a mule deer killed by F60. Massive multiple bites and claw punctures to F60’s legs and back eventually killed her. F15 (105 months old) was killed by a male puma in the Reference Area where she had killed a buck mule deer. At the time of her death, F15 had three suckling cubs; the nursery was only about 0.6 km away. F15 died from canine punctures to the braincase. After her death, the male puma consumed the remains of the deer. We suspect the male was M29 (fifty months old) who had inflicted mortal wounds to M19 only three months prior in an area where their territories overlapped. Four adult females, and possibly a fifth, were clearly victims of puma predation. F40 (twenty-five months old) was a new immigrant to the Reference Area when she was killed and eaten by resident male M19 (fifty-four months old). M19 killed F40 by crushing her braincase, then proceeded to consume about 90 percent of her mass, leaving only her head, distal parts of the legs and tail, the stomach, and part of the intestines. M19 covered F40’s remains with grass twice between feedings, just as pumas normally do when feeding on ungulate prey. F86 (thirty-nine months old) was killed and eaten by a male puma in the Reference Area. Apparently the male encountered F86 and her two five-month-old

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PHOTO 19. Puma F15’s skull, showing fatal bite wounds to the braincase and old damage to the zygomatic arch (arrow).

cubs at their cached mule deer fawn. Tracks in the area indicated that the cubs survived the attack, probably because F86 defended them. She succumbed to canine punctures to the braincase. The male consumed about 90 percent of her mass, leaving only the head, feet, tail, and a segment of the intestines. This male too had covered F86’s remains with grass between feedings. We did not expect the cubs to survive for long; inexperienced, and weighing only 11–14 kg each, they probably would not be able to provision themselves with food sufficiently. After a while, evidence of them disappeared. In another act of predation, F57 (104 months old) was killed and eaten by a male puma in the Reference Area. We suspected M46 (60 months old), who was in the process of extending his territory there. About 95 percent of F57’s mass was consumed; all that remained were her feet, a strip of skin, a 2-m length of intestine, and bone fragments. F185 (twenty-nine months old) was killed and eaten by resident male M29 (sixty-six months old). Canine punctures to the braincase were fatal. About 95 percent of F185’s mass was consumed. Only the anterior portion of the skull, the feet, tail, stomach, pieces of skin, and tufts of hair remained. Again, the male had covered the puma’s remains between meals. We noted that F185 was in M29’s territory for the first time when she was killed. Another female may have been the intended victim of predation in the Treatment Area. New immigrant

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F39 (twenty-two months old) was apparently driven off a 6-m-high limestone cliff to her death by advances of M22 (now thirty-five months old). We found tracks of both cats on top of the cliff, but we could not fathom why F39 jumped or fell. She died of massive head trauma. Her small undeveloped uterus suggested she was not in proestrus or estrus, and competition for prey did not appear to be involved. In most instances where adult female pumas were killed by adult male pumas, the relationships between the individuals were new. In particular, the pumas did not have any previous breeding associations with each other. Both of the females (F61, F86) that died defending their cubs were apparently killed by immigrant males that eventually established territories there. Similarly, both females (F60, F15) that died in food competition fought males with whom they were unfamiliar. In five of the instances where females were preyed upon or possibly pursued as prey, the females were either new immigrants to areas occupied by territorial males (F39, F40, F86, F185), or a territorial male was expanding his territory into the home range of the female (F57). These females had little chance of surviving violent attacks of males that were 60–150 percent greater in mass [10]. Not surprisingly, we never found an adult male killed by a female puma. These incidents stress the jeopardy of adult females in puma society, the strong selective pressure for females that actively avoid male pumas, and that local social transitions from immigration or territorial shifts can also have deadly consequences. Male pumas were killed by other males in disputes over territory or breeding females. M22 (forty-five months old) was killed by M3 (eighty-one months old) in the Treatment Area. At the time, M3 had been consorting with the apparently estrus adult female F47 for four days in an area where the territories of both males overlapped. M22 died of severe trauma caused by massive bite wounds that penetrated sacral vertebrae and the right ilium, broke the radius of the left foreleg and the fibula of the right rear leg, and punctured and tore muscles and ligaments in those areas. In this fight, there was no injury to M22’s skull. Earlier in life, he may have learned the hard way the virtue of guarding his head. After cleaning his skull, we found old mended wounds, some with hair imbedded, including two punctures to the right frontal, one puncture at the junction of the left frontal, nasal, and maxilla, and one puncture on the posterior edge of the left frontal—all wounds that were probably caused by canines of another puma. Quite likely, when M22 immigrated onto the San Andres Mountains, he vigorously defended his intentions to establish his territory there. Perhaps he fought M1, the old male that he apparently displaced from the area, or his neighbor M3 (see Chapter 12). After M22’s demise, M1 started using that portion of his former territory

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PHOTO 20. Puma M22’s skull, showing mended canine puncture wounds.

again. But this time he localized his movements to a relatively tiny area of about 20 km2, which also overlapped M3’s territory. His small range probably was due to a combination of his advanced age and an apparent infection of coccidioidmycosis that left numerous granulomatous lesions on his limb bones (discovered after he died) and may have infected other vital organs (Adaska 1999). When he was about 144 months old, M1 fought M3 (eighty-eight months old) and suffered puncture wounds to the frontal region of the skull that also caused damage to inner surfaces of both orbits. He died a few days after the battle, recumbent in the shade of juniper trees beside a mountain spring. He apparently succumbed from infection that caused necrosis of the damaged skull bones. M14 (seventy-one months old) was killed by M19 (forty months old) in the Reference Area. The males fought in an overlap zone of their territories. M14 died at the edge of the churned-up battle ground from fatal bite wounds that punctured the frontal of his skull and caused severe trauma and bleeding in both forelegs. M19 did not get away unscathed; he received multiple claw scratches to his face, head, shoulders, and thorax, and he had canine punctures to his left foreleg above the elbow. But he lived to usurp all of M14’s former territory. M19 (ninety-six months old) was killed by M29 (forty-eight months old), apparently over breeding female F15 (see Chapter 14). He probably died from

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infection that attacked his body via canine punctures to both frontals and the left maxilla and nasal. We found his body just beyond the north edge of his territory, but not far from where he had been spending time in an overlap zone with M29’s territory (see Fig. 14-3). M29 also suffered, but much less severely, with multiple claw scratches on his face and forelegs and canine punctures to both elbows. M73 never was to leave a legacy. He was an unusually small, feminine-looking adult male, traits that were probably affected by his bilateral cryptorchidism. When he was forty-five months old, he was killed by another male puma at the southern edge of his home range. There were a few suspects, M52 (seventy-eight months old), M161 (sixty months old), or new immigrant M219 (thirty months old), whose territories M73’s overlapped. M73 died at the edge of the battle ground from canine punctures to the braincase. Other bites penetrated the frontals, avulsed the left eye, and pierced the right zygomatic arch. In four of these five cases of male-to-male contests, victorious pumas were 10–30 percent greater in mass than the losers [11], supporting the hypothesis that larger males have greater fitness. Only M1 (64.4 kg) was larger than M3 (60.3 kg), but he was disadvantaged by old age and a fungal disease that probably affected his physical prowess. Two of the losing males, M1 and M19, were past their prime. Of the three in their prime, one (M73) was physically outmatched and incapable of reproducing. As puma deaths from intraspecies strife began to accumulate in our study, we hypothesized that their frequency would be related to puma population density. That is, as population density increased, then direct competition among adult and subadult pumas also would increase as they vied for essential resources such as food, mates, and territory. We predicted that evidence for this hypothesis would be a strong monotonic association between the annual frequency that independent pumas (i.e., adults plus subadults) were killed by other pumas and year-round adult puma density. In the Treatment Area (January–December, 1988–1994) the frequency of deaths was associated with adult male density but not with total or female adult density [12]. In the Re f e rence Are a (January–December, 1989–1994), there was no association between deaths and any of the three adult density categories [13] (Fig. 8-3). We rejected the hypothesis that the frequency of intraspecies strife is affected by adult puma density. In addition, intraspecies strife occurred during years of mule deer population increase and decline. We recorded seventeen adult and subadult puma deaths on the San Andres Mountains from 1987 to January 1992 when the deer population increased (see Chapter 17) and three such deaths during 1993–1994 when the deer population declined. The actual frequency with which intraspecies killing in pumas occurs is probably largely influenced by chance events such as

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FIGURE 8-3. Relationship of adult puma density to frequency of independent puma deaths from intraspecies strife in the Treatment Area (TA) and Reference Area (RA), San Andres Mountains, New Mexico.

estrus periods of females, timing of immigration of male competitors, contests between neighboring competing males, and opportunistic competition for prey carcasses. All this suggests that intraspecies strife should be expected in any puma population, regardless of population density and prey trends. And since this pattern held for both our Treatment Area and our Reference Area, deaths from intraspecies strife should be expected to occur in exploited and nonexploited populations. Pumas killing other pumas was clearly the dominant mortality factor in the adult portion of the population, just as it was with the cubs and subadults. Infanticide, cannibalism, and intraspecies strife in pumas is not unique to the San Andres Mountains. In fact, these modes of death have been documented

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across the puma’s North American range, including Florida (Maehr 1990a), Texas (McBride 1976), Colorado (Anderson et al. 1992), Idaho (Hornocker 1970), Montana (Williams 1992), Alberta (Ross and Jalkotzy 1992), British Columbia (Spreadbury et al. 1996), California (Beier and Barrett 1993), Arizona (Cunningham et al. 1995), and Utah (Hemker 1982). Although the toll of these deaths on puma populations has not been quantified in most cases, intraspecies strife was identified as the single-greatest natural cause of death of Florida panthers (Maehr 1997a) and of pumas in California (Beier and Barrett 1993) and Utah (Lindzey et al. 1988). Furthermore, fighting has occurred in puma populations with a wide range of adult puma densities among them, such as in Alberta (1.5–2.2 / 100 km2, Ross and Jalkotzy 1992), British Columbia (0.93–1.1 / 100 km2, Spreadbury et al. 1996), Wyoming (1.4–1.5 / 100 km2, Logan et al. 1986), and Utah (0.3–0.6 / 100 km2, Lindzey et al. 1988). Disease was the second most important mortality factor in adult pumas on our study area. The pathogen could not be determined in four of five deaths, primarily because of tissue autolysis. Dry, hot desert conditions made it imperative that tissues from dead animals be collected and preserved in less than twenty-four hours to be useful in diagnosis. Septicemic plague (Yersinia pestis) was diagnosed in F68 (sixty-seven months old). We found her only about twelve hours after she died beside a spring-fed pool in which she was observed lying the day before. The septicemic form is a direct result of the bacteria Y. pestis multiplying rapidly in the victim’s blood and quickly producing blood poisoning. An animal with septicemic plague can pass from a healthy state to collapse and death within a few hours (Rail 1985). Besides this occurrence of Y. pestis in a puma on our study area, the disease was also diagnosed in two female pumas found dead within 100 m of each other in the Sandia Mountains in central New Mexico in 1994 (New Mexico Department of Agriculture Veterinary Diagnostic Services, Albuquerque). It has also been diagnosed in pumas in California (W. Boyce, DVM, and B. Chomel, DVM, University of California, Davis, personal communication). The disease is not endemic to the Western Hemisphere; apparently it was introduced in about 1899 by Chinese immigrants traveling from Hong Kong to San Francisco, California (Gregg 1985). By the middle 1930s, plague had spread from California eastward across the Rocky Mountains and has been periodically active in fifteen of the seventeen contiguous Western states (Thorne et al. 1982). Effects of Y. pestis on puma populations is presently unknown, but there is a real probability that significant morbidity and mortality may occur in localized areas, especially in New Mexico, which has the highest incidence of the disease in North America (Rail 1985). Y. pestis is especially pathogenic in felids (Thorne et al. 1982). The disease may become increasingly infectious in pumas during

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low populations of their principal ungulate prey, when smaller prey items, such as rodents and rabbits, become more important in the diet. In these conditions, pumas may be more susceptible to infection by ingesting plague-infected animals or from bites from disease-carrying fleas on those hosts (Rail 1985). Thus, it may be significant that the two females from central New Mexico and F68 died in 1994 and 1995 at the height of a drought that triggered a mule deer population crash on our study area and elsewhere in the state. Occurrence of the disease in deer apparently is rare. Biologists handling plague-afflicted animals should be aware that they can contract the disease through the bite of an infected flea or through direct contact with an infected carcass (Thorne et al. 1982). We suspected, but could not confirm, that Y. pestis was also involved in the death of M29 (sixty-seven months old). He too may have been trying to cool a fever in a water trough. But we examined him six or seven days after death; warm spring temperatures had already taken their toll on tissue autolysis. M29 died exactly two years earlier than F68 and 7 km away. His territory included F68 and he even sired a litter with her. We wondered if that area of the San Andres Mountains could have been a focus for the disease. Although we got to F4 (eighty-nine months old) only twelve to twenty-four hours after death, a veterinary diagnostic laboratory could not isolate a pathogen. F4 had suffered severe wasting. She lost about 34 percent of her normal body mass. Her condition, rendering her mammary glands nonproductive, no doubt caused her to abandon her three nursling cubs two weeks before she died. Killing large prey is a dangerous way for pumas to make a living. Three accidental deaths to adult females occurred apparently during botched attempts to bring down mule deer. All three appeared to be in excellent physical condition prior to death. Two of these, F13 (thirty-one months old) and F128 (seventyone months old), suffered massive body blows that severely bruised the chest and thorax and caused the lungs to bleed. F13 also had three broken ribs that punctured the right lung. We suspect that these pumas may have been kicked, slammed against rocks or trees, or pinned beneath falling prey. F195’s (thirtythree months old) injury was extraordinary. Apparently, in a defensive counterattack, a mule-deer buck’s antler impaled F195’s left eye and penetrated the left side of her braincase. Sometimes pumas survive broken bones. In adults that died from a variety of causes, we found two females (F128, F195) and three males (M1, M3, M53) that each had one to four ribs that had been broken earlier in life but had since mended. Male pumas on our study area rarely suffer fatal injuries of this type, probably because their greater mass enable them to more effectively subdue deer before defensive blows can be effectively landed. We would expect puma moth-

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ers to be more susceptible to this type of mortality because they have to kill prey more frequently to satisfy the energetic demands of the family (see Ackerman 1982). Inexperience in subadults probably also makes them vulnerable. Chances of death for both male and female pumas probably increase where principal prey are larger, such as elk. Pumas fatally wounded in struggles with prey have also been documented in other populations in Utah, Idaho, and Alberta (Gashwiler and Ro b i n e t t e 1957 and Lindzey et al. 1988, Hornocker 1970, Ross and Jalkotzy 1992, respectively). In Alberta, three females and one male died in bungled pre y - c a pture attempts. These deaths comprised 27 percent of the natural mortality. The three females suffered injuries while killing a mule deer, an elk, and a bighorn sheep. The male puma, while attacking a bighorn sheep, slipped over a cliff with its prey. The most unusual death we documented was of F141 (thirty-four months old). She was apparently bitten by a rattlesnake on her left foreleg. Three species of rattlesnakes, including the western diamondback, black-tailed, and rock rattler, are fairly common on the San Andres Mountains. F141 was bitten in March when rattlesnakes were emerging from winter dens. Particularly in protected populations, a few pumas have the opportunity to live out their entire biological life span until processes of aging bring them down. Three pumas on our study area died when they were about 122–152 months old. We attributed their deaths to complications of old age, although we could not isolate the exact cause. M3 killed his last mule deer when he was 143 months old. He had already eaten the deer’s liver and had started plucking hair from another part of the carcass when he suddenly collapsed beside the deer. M5 was 152 months old when he reposed for the last time under the shade of a desert willow tree. F21 died at 122 months of age, orphaning her three ninemonth-old cubs. But she may have raised them just long enough for some of them to survive. One of the last signals we got from F21’s radio-collared cub F194 was when she was dispersing eastward across the Tularosa Basin at the age of eleven months. Three adult pumas died of unknown causes. F30 was thirty-four months old when she died in the back of a narrow cave. Due to abnormal Army restrictions on the area at the time, we could not reach her for about three weeks after her death. By that time, tissue autolysis was extreme. F66 was twenty-six months old when she died. Although we got to her about three days after death, her two eight-month-old cubs, M67 and F68, had almost completely scavenged her carcass, leaving only part of the skull, the feet with the stripped leg bones attached, and the lumbar vertebrae and pelvis. M49 died at the age of eighty-one months and shortly after he had returned from a 469-day absence from the San Andres

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Mountains resulting from translocation to northern New Mexico (Ruth et al. 1998). About nine days after his return, M49 killed a mule deer in his original territory. There, he associated with M3, a territorial male who was M49’s neighbor before translocation and who took over the open area left by M49’s departure. M49 immediately vacated the area of the encounter and traveled north about 45 km, where he died about twelve days later. Unfortunately, we found him about five days after death, much too long, for the intensely hot midsummer sun had mummified his carcass into skin and bones. We could only speculate that he may have been fatally wounded in the encounter with M3.

Why Do Pumas Kill Other Pumas? Because intraspecies killing was the single most important cause of death in all classes of pumas, we asked if such a behavioral trait could be adaptive. What benefits are there to males that kill and eat cubs or females? What is the advantage to males that engage in mortal combat? Are such aggressive interactions merely pathological? Not surprisingly, there are fitness benefits to individual male pumas. But in some instances, such as with M22 and F10, the killings may be the result of a fatal mixture of social miscues and puma weaponry. There is no mystery as to why pumas might fight over a deer carcass; the winner acquires substantial nourishment. But competition for food does not seem to be an overriding reason for combat; otherwise, we would have expected greater frequency of killing during the deer decline phase. Because the loser may be killed or fatally injured in fights, natural selection should favor pumas that actively avoid other pumas and cover their prey to avoid detection, traits that are common in pumas. Another downside is that the aggressor puma might also be injured, perhaps even debilitated to the extent that he cannot effectively provision himself. Hence, when pumas engage in direct competition for food, the cost of fighting should be less than the alternative, which is to ignore the food of another puma, and instead hunt and kill another prey animal. In our study, we learned that whenever male pumas competed with other pumas for prey, the other puma was always considerably smaller, and likely easily overwhelmed. We would expect incidences where adult male pumas of similar mass compete directly for a carcass to be quite rare. Certainly, pumas that prey on other pumas are also acquiring nourishment, particularly if they devour entire carcasses, such as those we saw. In every case, large males consumed smaller females or cubs. Still, on the surface, it does not make sense that an adult male should kill and eat a female puma with which it might sire offspring. His fitness would seem to be reduced. But if the male is hungry and the interloping female is not a recognized breeder or recognized kin

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(i.e., as in a matriline), if she competes with him for food, and if she competes for food with mothers that are raising his offspring or his daughters in a local matriline, then this type of cannibalism could enhance the male’s fitness. The male that eats cubs is gaining nourishment, but more importantly he may also increase his reproductive success if the cubs are not his offspring. By killing unrelated cubs, the male can stimulate the female to cycle into breeding condition earlier than if the female raised her young to the normal age of independence (i.e., about thirteen months). For example, F45 and F107 lost their entire litters to cannibalism when cubs were thirty-four and sixty-six days old, respectively. These mothers bred again successfully 307 and 74 days later. On average, the loss of their litters accelerated the time for the females to breed again by about five months. If the average of 100 days to rebreed is representative (for litters lost to all causes, see Chapter 7), then the loss of litters with newborns to two-month-old cubs may accelerate breeding access to females by eight to ten months. By providing a male an earlier opportunity to sire a litter, this strategy should enhance the male’s fitness. In fact, both males that killed and ate entire litters in our study subsequently sired litters with the mothers of the ill-fated cubs. Similar observations have been made for the leopard (Bailey 1993). Convincing evidence for this hypothesis in felids comes from African lions where coalitions of males take over prides and kill unrelated cubs less than six months old and generally evict older cubs. As a result of this genocide, pride females return to sexual receptivity, on average, eight months sooner, bear offspring of the new males, and thus enhance the males’ fitness (Packer and Pusey 1983, Packer et al. 1988). On the other hand, infanticide should be expected to lower the female’s fitness by reducing the number of offspring she raises to independence during her lifetime, especially if she is killed in an attempt to defend her cubs. In f a n t i c i d e by new immigrant males may even trigger a period of infertility until the female becomes familiar with the new male, similar to African lion females when their prides are taken over by new male coalitions (Packer and Pusey 1983). Our data suggest this may occur in puma, though our samples are limited (see Chapter 7). We did not observe any cases in which female pumas killed cubs. Puma mothers we studied exhibited behaviors that could increase their fitness by reducing the threat of infanticide. As we quantify and discuss later in Chapter 15, avoidance of other pumas by females seemed to be the most important strategy. We will never know how many times mothers sensed other pumas and simply trailed their families away, completely evading potentially dangerous encounters. Also, promiscuity during estrus would be adaptive if it cultivated amicable social relations between males and females, and if it confounded pater-

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nity and thus made it less likely for males to kill cubs. Nonviolent associations fostered through breeding courtships seemed vital to reproductive success and stability in puma society. Occasionally mothers opted to defend their cubs. Clearly, this choice was extremely risky, sometimes causing the death of mothers and cubs alike. But there were at least two instances when defense may have saved cubs and mothers. F90 may have defended her three forty-five-day-old cubs, sired by M38, from territorial male M46. One cub (F204) was killed, but the other two survived. Similarly, F147 may have defended her three eighty-day-old cubs from territorial male M161. Again, one of the cubs (F207) was killed, but two survived. Aggressive defense, whether intended to protect cubs or food, can still bear severe physical costs. We examined twenty-four adult female pumas (age range = 22–122 months, x– = 52.2 ± 30.4) after death. This sample included two that we translocated from the Treatment Area (Ruth et al. 1988). We discovered two (8 percent) had suffered severe cranial injuries earlier in life. F15 and F37 were productive mothers; they bore five and three litters, respectively. Old skull injuries, now healed, were consistent with massive bites inflicted by other pumas, probably males. F15’s skull was actually laterally lopsided from trauma to both frontals, the left maxilla, and both zygomatic arches. F37 had canine punctures to both frontals. It was remarkable that they had survived such injuries. In addition, we noted that 24 percent (eleven of forty-five) of adult females we captured had scars, apparently from aggressive encounters with other pumas. The relatively low frequency of such injuries in these samples suggested to us that adult female pumas generally choose to avoid confrontation, a strategy that would increase their fitness. When they do defend, females seldom survive such encounters. Natural selection is against those phenotypes. Adult male pumas, however, are a different story. Fitness of adult males is closely linked to their longevity; hence, mate and territory defense should be strongly conserved strategies. Individual males that successfully defend their right to breed with an estrus female can influence the fitness of themselves and other male pumas directly, such as when M3 fought M22. Indirectly, territorial males that successfully dissuade activity of other males may also contribute to survival of their own offspring by reducing the risk of infanticide. But there are also physical costs to the winners of battles. We examined thirteen territorial males (age range = 28–152 months, x– = 88.6 ± 40.2) after their deaths. This sample included three males translocated from the Treatment Area (Ruth et al. 1998) and one that, as a subadult, emigrated northeastward across the Tularosa Basin and established a territory on the Carrizo Mountains. We found that six (46 percent) had survived cranial injuries that were consistent with bites from other male pumas. These injuries all appeared to

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be canine punctures that penetrated the anterior part of the skull involving mostly the frontals, but also the nasals and maxillae. Moreover, of the adult males we captured, 97 percent (twenty-eight of twenty-nine) had wounds inflicted during fights with other pumas. Again, we submit that a trait such as large mass, which would confer an advantage to a male in combat, should be strongly selected. No one has been able to document behavioral interactions such as posturing in unfettered pumas challenging each other for food, mates, or territory. But we suspect that large mass conveys advantages to males before a single blow is struck. It is likely that in some cases prospective challengers retreat from perilous encounters because they perceive their nemesis to be too big and powerful. In those instances, victors win without a fight and potentially debilitating injuries. Extended longevity of territorial males should benefit male and female reproductive success by encouraging recognition among resident adults and by discouraging activity of new males. But, we would expect population perturbations, such as sport-hunting, that disrupt social relationships by reducing tenure length of territorial males to increase chances that females will encounter unfamiliar males that threaten their fitness. Biologists studying pumas in Alberta came to a similar conclusion after they observed that stability (i.e., long tenure) of adult males was apparently associated with decreased infanticide (Ross and Jalkotzy 1992). In addition, observations made in British Columbia support this; non-sires were involved in two separate infanticide incidents (Spreadbury et al. 1996). Survival of tiger cubs has also been linked to adult male stability. Smith and McDougal (1991) estimated 90 percent of cubs survived to dispersal and no infanticide occurred when resident males were stable. But only 33 percent of cubs survived and infanticide was rampant when new males were taking over territories of former residents.

LP > >

KX

1. Although we tried to minimize human impacts to our study population, 5 percent of all the pumas we studied died as a result of poaching or research accidents. Survival rates of cubs (including natural and human-caused deaths) were 0.59 in the Treatment Area and 0.63 in the Reference Area. Excluding human-caused deaths, survival rates for each area were 0.60 and 0.66, respectively. Cubs of matrilineal mothers had higher survival rates (0.67) than cubs of non-matrilineal mothers (0.56). Cub survival rates were not sensitive to the deer population decline. Cubs are most vulnerable to mortality when they are less than or equal to three months old. Survival rates of male cubs may be slightly better than female cubs. Infanticide and

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cannibalism combined as the principal causes of cub death, followed in importance by starvation, disease, accidents, and coyote predation. 2. Subadult females had a higher survival rate (0.88) than subadult males (0.56). All the subadult pumas that died were killed by male pumas. We propose that females survive better because of their tendency to be philopatric or disperse short distances, in contrast to males that disperse long distances. 3. Adult male pumas had a higher average annual survival rate (0.91) than did adult females (0.82). Intraspecies strife was the greatest cause of mortality for adult males and females. In order of importance, accidents, disease, and aging also caused female deaths. For males, other causes of death included disease and aging. The most unusual cause of death was snakebite. 4. Male pumas in particular kill other pumas and enhance reproductive success because they acquire food, mates, and dominance over territory. Female pumas avoid aggressive encounters with other pumas and enhance their reproductive success by enhancing the survival of themselves and of their cubs.

LN N5LN5)L 1. Test for difference in finite survival rates (i.e., number of pumas surviving / number of pumas monitored) for ninety-seven cubs from matrilineal mothers and fifty-seven cubs from non-matrilineal mothers. Chi-square test of homogeneity (2 ¥ 2 contingency table): c2 = 1.82, 1 d.f., P = 0.20. 2. Test for difference in finite survival rates for nine radio-collared male and sixteen radio-collared female independent subadult pumas. Chi-square test of homogeneity (2 ¥ 2 contingency table): c2 = 3.22, 1 d.f., P = 0.08. 3. Puma masses: M64 at death = 41.7 kg, M88 three days after killing M64 = 59.0 kg, M108 at death = 39.0 kg, M88 nine months before killing M108 = 63.5 kg and two months after = 62.6 kg. 4. Puma masses: M22 = 52 kg, M88 = 63 kg, F10 = 31 kg, F96 = 29 kg. 5. Puma masses: M1 = 64.4 kg, subadult male M300 = 50.8 kg. 6. Survival rates for adult male pumas in the Treatment Area (n range = 5–9) and Reference Area (n range = 5–14) were compared using Z-tests (Heisey and Fuller 1985a). Rates differed only in 1989: Z = 1.688, P = 0.05. All other years: Z range = 0.68–1.145, P range = 0.13–0.5. 7. Survival rates for adult female pumas in the Treatment Area (n range = 4–12) and Reference Area (n = 3–17) were compared using Z-tests. Rates differed in 1991: Z = 1.573, P = 0.06, and in 1993: Z = 1.992, P = 0.02. All other years: Z range = 0–1.038, P range = 0.15–0.5.

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8. Survival rates for adult male and adult female pumas were compared using Z-tests (refer to Table 8-1). Rates differed for 1987: Z = 1.535, P = 0.06; 1988: Z = 1.621, P = 0.05; 1989: Z = 1.560, P = 0.06; 1990: Z = 2.221, P = 0.01. Rates for all other years: Z range = 0.057–1.018, P range = 0.15–0.48. 9. Test for differences in ages of adult male (n = 11) and adult female (n = 19) pumas that died. Two-sample t-test: t = 2.853, 28 d.f., P = 0.008. 10. Masses (kg) of adult pumas involved in intraspecific killing. Females: n = 7, x– = 31.8 ± 3.9, range = 27.2–38.6; males: n = 5, x– = 58.6 ± 7.0, range = 52.2–68.9. 11. Masses (kg) of adult male pumas involved in intraspecific killing. Winners: n = 6, x– = 61.2 ± 4.9, range = 54.9–68.9; losers: n = 5, x– = 56.4 ± 8.9, range = 43.5–64.4. 12. Test for association between annual frequency of intraspecies killing (adult plus subadult pumas) and year-round (January–December) density of total adults, adult males, and adult females in the Treatment Area (1988–1994, n = 7). Spearman correlation coefficients (1-tailed test): total adult density rs = 0.09, P > 0.25; male density rs = 0.62, P = 0.08; female density rs = –0.09, P > 0.25. 13. Test for association between annual frequency of intraspecies killing (adult plus subadult pumas) and year-round (January–December) density of total adults, adult males, and adult females in the Reference Area (1989–1994, n = 6). Spearman correlation coefficients (1-tailed test): total adult density rs = 0.06, P > 0.25; male density rs = 0.29, P > 0.25; female density rs = 0.06, P > 0.25.

Chapter 9

Independence of Puma Progeny, and Philopatry, Emigration, and Immigration

By tagging a large number of dependent progeny (i.e., offspring produced by mothers on the San Andres Mountains) we were able to discover for the first time how behaviors of philopatry, dispersal, emigration, and immigration affected puma population dynamics. We published our findings earlier in Con servation Biology (Sweanor et al. 2000). Therefore, in this chapter we only reiterate the results that pertain to population dynamics and how these behaviors affect fitness. We discuss the implications of these behaviors to puma conservation further in Chapter 20. We defined philopatric pumas as progeny whose adult home ranges overlapped their natal area by 5 percent or more (based on the 90 percent minimum convex polygon method of home range estimation; see Chapter 13). Dispersers were progeny that established independent home ranges that overlapped less than 5 percent of their natal area. Dispersal began when a subadult made its first movement outside its natal home range and did not return. Dispersers that departed from the puma population on the San Andres Mountains study area altogether were emigrants. Immigrants were pumas that originated from populations outside of the San Andres Mountains before establishing residency on our study area. Hence, recruits into our study population consisted of progeny born on the San Andres Mountains and immigrants that entered the resident adult portion of the population. Fundamentally then, philopatry, emigration, and 145

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immigration were vital components of population growth. All of the information that we gleaned on philopatry, dispersal, and emigration came from pumas that we captured and tagged while they were still dependent on mothers. After cubs achieved independence from mothers, we followed their movements by radio-tracking them and by receiving news of their fates from hunters, predator control agents, or automobile drivers who killed them, and we identified individual pumas by their ear tags, tattoos, or radio collars. In addition, our intensive and extensive capture efforts on the San Andres Mountains helped us to detect the arrival of new immigrants that were recruited into the population.

Independence of Progeny We studied fates of forty-three tagged progeny that reached independence. We estimated age at independence for thirty of those. For six males and six females that we radio-tracked before and after becoming independent of their mothers, age at independence averaged 13.7 ± 1.6 months (range = 11.1–16.0). Our sample size was small, but males appeared to be dependent on mothers (x– = 13.8 ± 1.8) for about the same duration as females (x– = 13.5 ± 1.6). Siblings became independent within zero to twenty-eight days of each other (x– = 10.0 ± 14.0, n = 5 comparisons of seven siblings in three litters). For eighteen other progeny, our data were less accurate because we could not radio-track the animals during separation; either the cubs were not radio-collared or their mother’s radio collar had malfunctioned at the time. Hence, we estimated a puma’s age at independence based on the age when we recaptured it as an independent subadult (n = 5), the age at which radio-collared siblings became independent (n = 3), the age at which mothers appeared to no longer associate with cubs based on attrition in tracks (n = 2), the age at which siblings separated from one another (n = 3), and the timing that their mother gave birth to her next litter minus the gestation period (n = 5). For this last group, we calculated a range of ages based on the range of days that offspring associated with mothers before and after estimated conception dates. Ranges of average ages at independence were 13.7 ± 2.6–14.5 ± 2.4 months for seven males and 13.7 ± 3.0–14.8 ± 2.4 months for eleven females. Because of the five offspring (three males, two females) that were already independent when we radio-collared them, these ages are biased upward. In general, we considered offspring to be independent of their mothers after they were about thirteen months old. Independence seemed to be initiated by the mother’s inattentiveness to her young, either by abandoning them at the edge of natal range or by not returning to them at a rendezvous site within the natal range (see Chapter 12). Similar behavior at separation has been reported for pumas in central Idaho (Sei-

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densticker et al. 1973) and Southern California (Beier 1995). After independence, we observed siblings associating for up to 1.7 months. Puma littermates have been known to associate for up to three months after independence in Alberta (Ross and Jalkotzy 1992). By the age that puma cubs are becoming independent, they are physically capable of killing deer-size prey; females are approaching the size of adult females and males may exceed it (see Appendix 1). In addition, their permanent teeth are in place and canines are almost fully extended. Of seventeen offspring for which we determined the month of their separation from mothers, eleven (five males, six females) became independent during the July–August mule deer fawning season when their principal prey were most abundant and vulnerable; three others were independent shortly thereafter in October. This pattern would benefit survival of young, but it may be an artifact of our small sample size. Information on the age at which puma offspring separate from mothers in other populations is limited. Comparable data come from a hunted puma population in southern Alberta where thirty-six offspring became independent throughout the year at the average age of 15.2 ± 3.0 months (Ross and Jalkotzy 1992). Other studies did not differentiate ages at independence and dispersal. Timing of independence in nine cubs from six litters that we followed closely with radiotelemetry was linked with resumption of breeding behavior in their mothers. Offspring became independent within one to forty-four days of the mother consorting with an adult male puma (x– = 19.1 ± 15.5). In four events cubs were independent thirteen to twenty-one days (x– = 16.0 ± 3.6) before the mother consorted with a male, and in five events cubs were independent one to forty-four days ( x– = 21.6 ± 21.2) after the mother consorted. As a result of those unions, three of the six mothers produced new litters one gestation period later. Two other mothers bred with males eleven and forty-seven days after the first association, then produced new litters one gestation period later. The sixth mother consorted with adult males on two occasions twenty-five days apart, but apparently was not impregnated. In the first intensive field study of pumas in the early 1970s, biologists observed that “In the months before and just after the young become independent, the female associates with (tolerates?) adult males and even adult females more frequently and for longer periods than at any other time.” They postulated that “this is related to hormonal changes associated with the onset of estrus” (Seidensticker et al. 1973:40,41). Our data support their conclusions. Hypothetically, independence of offspring at this critical time may be adaptive for at least three reasons: (1) large cubs would not be direct competitors for the mother’s time and energy required for mating, pregnancy, and rearing new cubs; (2) offspring would not be close to their estrus mothers and potential tar-

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gets for aggressive male mates; (3) male offspring would avoid inbreeding with their mothers. Of these, the first hypothesis seems the most plausible; this timing of independence would contribute to the lifetime reproductive success of puma mothers by ending maternal care for offspring that no longer require it and enabling her to devote her energy to raising a new litter. In the second hypothesis, we would expect a large majority of the cubs to become independent before the mother began to attract adult males that could easily kill the cubs. But results from our small data set were equivocal. Less than half of the offspring became independent before their mother resumed breeding activity and more than half became independent afterward. The third hypothesis does not seem likely because we found that young males generally reach puberty at about twenty-four months of age, several months after becoming independent of mothers. In males, inbreeding is avoided principally by dispersal (see Chapter 13). Moreover, this hypothesis does not explain timing of independence for female cubs.

Philopatry and Dispersal Following independence, progeny either remained within the natal area (i.e., they were philopatric) or they dispersed. Only a fraction of females dispersed; the remainder were philopatric. Thirteen females exhibited philopatry and four dispersing females established home ranges adjacent to their mothers. Together these females formed eight matrilines (see Chapter 13, Plate 4). Three other subadults did not disperse from their natal areas. As we discussed in Chapter 8, two subadult males (M64, M108) and one subadult female (F96) were killed by male pumas on natal areas about seventy-five, fifty-two, and eighty-seven days, respectively, after independence. Based on the histories of tagged subadults, we suspected that the males would have eventually dispersed if they had survived; but the female may have been philopatric. Dispersal from natal areas for eight known-age progeny occurred at the average age of 15.2 ± 1.6 months. Our small samples suggested that males tended to disperse at older ages (n = 6, x– = 15.7 ± 1.4, range = 14.0–17.0) than females (n = 2, x– = 13.6 ± 0.9, range = 13.0–14.3). Both sexes dispersed from natal areas before reaching puberty (see Chapter 7). During the subadult life-stage, energy is invested in growth, movement away from natal areas, and socializing directly and indirectly with other pumas, not in reproduction. For pumas, lower fitness would be expected if dispersal occurred during the reproductive stage of life when energy and time budgets should principally be allotted to mating and parental investment. Ages of pumas from other populations fit a pattern of dispersal prior to puberty. In southwestern Colorado, a slightly larger sample size

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Slide @171%

PHOTO 21. Three eleven-month-old siblings F107, M108, and F109 with Ken Logan and Frank Smith (right). M108 (held by Ken) was killed by his father, M88, as a subadult. Both daughters were philopatric, and F107 (held by Frank) bred with her father twice.

indicated that eight males and four females dispersed at mean ages of 11.8 ± 1.0 months and 20.0 ± 8.9 months, respectively (Anderson et al. 1992:63). Twelve females and five males dispersed from natal areas in an Alberta population at the average age of 16.0 months (range = 10–22) (Ross and Jalkotzy 1992). In a Utah population with a relatively low density of pumas (mode = 0.4 total pumas / 100 km2) twelve cubs dispersed when they were sixteen to nineteen months old (Hemker et al. 1984). In a puma population in Southern California that was practically surrounded by urbanization, six known-age males dispersed at a mean age of 18.0 ± 2.8 months (Beier 1995). This was practically the same as the mean of 17.9 ± 4.0 months for seven male Florida panthers in a population constricted by their limited habitat (Maehr et al. 1991). In the Florida population, dispersal for only one female was described, but it was peculiar for pumas because she dispersed after reproducing. The panther raised her first litter within her natal home range, then at about thirty-three months old she dispersed 16 km away (Maehr et al. 1989). We traced straight-line distances for twenty-seven offspring that dispersed from their natal home ranges (Table 9-1). Of those, six males and six females

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moved minimum distances of 47.1 and 5.6 km, respectively, before establishing adult home ranges within the San Andres Mountains study area. Another ten males and three females dispersed so far that they emigrated from our study population (Fig. 9-1). Two other males were dispersing within the San Andres Mountains when a male puma killed one and the other shed his radio collar at the southern border of our study area. We assumed the latter puma either died or emigrated because we never recaptured him on the study area. On average, male offspring dispersed 8.1 times the distance of females from their natal home

Table 9-1. Dispersal distances for independent pumas born on the San Andres Mountains, New Mexico (n = 40), and for pumas with origins outside the San Andres Mountains (n = 3), 1986–1994 (adapted from Sweanor et al. 2000). Distance estimatora

Male dispersal distance (km) n x– ± SD Range

Progeny NAC to IACb 8 NAC to IAC (P) 0 NAC or CS to 5 AMS CS to IAC 0 CS to IAC (P) 0 NAC or CS to 5 LLS or SMSc TOTALd 13 Origin outside study area CS to LL or IAC

1

101.3 ± 57.7

47.1–192.5

139.8 ± 68.7

Female dispersal distance (km) n x– ± SD Range 28.3 ± 26.1 3.2 ± 2.6

56.0–214.9

7 12 0

67.2 ± 37.5

53.1–133.8

1 1 1

36.6 2.2 76.6

116.1 ± 62.5

47.1–214.9

21

13.1 ± 19.5

0.7–78.5

2

96.3 ± 31.0

74.4–118.2

175.7

5.6–78.5 0.7–9.9

aOrigins and endpoints of distance estimators: NAC—natal home range arithmetic center; IAC— independent home range arithmetic center; P—philopatric; CS—capture site; AMS—adult mortality site; LLS—last location as a subadult; SMS—subadult mortality site; LL—last location, status unknown. CS for progeny was within the natal home range. bMales dispersed significantly farther than females (Mann-Whitney U test: U = 49.0, P = 0.02). cNot included in analysis of sex-related dispersal distances. dMales dispersed significantly farther than females (Mann-Whitney U test: Z = 4.56, P < 0.001). Total includes only pumas that probably completed their natal dispersal moves and those that were philopatric into adulthood. We assumed that pumas that had reached adulthood prior to death or loss of radio contact had completed their dispersal moves, whereas subadults had not.

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FPO @ 65%

FIGURE 9-1. Dispersal moves of pumas from the San Andres Mountains to other habitats in New Mexico.

ranges to adult home ranges. Effective dispersal for thirteen male progeny averaged 7.3 home range diameters, with extremes of 3.0–13.6 (based on home range estimates in Chapter 12). None of these males settled adjacent to its mother or siblings on the San Andres Mountains. In contrast, twenty-one female progeny (including dispersing and philopatric females) effectively dispersed an average of 1.4 home range diameters, with extremes of 0.1–8.5. Dispersal directions of male progeny were bimodally distributed with a diameter line oriented at 347 degrees, while directions for females were random (Sweanor et al. 2000). In general, males and females tended to disperse along the northto-south axis of the San Andres Mountains, reflecting the pumas’ affinities to favorable habitats during initial stages of dispersal and emigration. Some pumas traversed broad sweeps of non-puma habitat extending 45–65 km across desert basins to the east and west, making unidirectional moves to other large patches of mountainous terrain in periods of fewer than seven days. Pumas have been known to travel long distances in relatively short time spans. A male dispersing in Southern California covered about 29 airline km in 48 hours (Beier 1995),

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and an orphaned eight-month-old female translocated in southwestern Colorado covered 43 airline km in about 10 hours (Anderson et al. 1992). In our situation it appeared that dispersing pumas we re simply moving to other mountain ranges that they spied across the basins. They used smaller patches of puma habitat to link their dispersal moves to more distant habitats (see Chapter 13). Pumas dispersing from the San Andres Mo u n t a i n s reached puma habitats throughout the southern half of New Mexico (Fig. 91). In addition, we caught one male and two female subadult pumas that we re apparently born elsew h e re and had immigrated into our study area temporarily, then left it as they continued their dispersal moves. Their behavior demonstrated how pumas from other patches sometimes use the San Andre s Mountains as a “stepping stone” to other habitat patches as well as the transient nature of some individuals that really we re not members of the local population. The longest dispersal movement yet re c o rded for pumas was about 483 airline km for a male tagged as a cub in the Big Horn Mo u n t a i n s in north-central Wyoming and killed at thirty months of age by a hunter in Black Hawk Canyon, west of De n ve r, Colorado (Logan and Sweanor 2000). Dispersal of male subadults from natal areas was obligatory even at low population densities. Ac c o rd i n g l y, male dispersal was density-independent. Bu t because some female progeny dispersed and some did not (i.e., they we re philopatric), we interpreted female dispersal to be partially density dependent. In the rebuilding puma population on the San Andres Mountains, there apparently was ample food and room for female progeny to establish their adult home ranges overlapping or adjacent to their natal areas, as well as for immigrant female re c ruits. But because of the programmed termination of our study, we we re unable to quantify how female dispersal or philopatry changed in re l ation to puma population density and prey abundance. Additional long-term re s e a rch is needed to understand these relationships. A reasonable hypothesis is that rates of dispersal in female progeny increase as per capita food resources decline. If dispersal of female progeny is affected in this way, then competition b e t ween pumas for food may be a population-regulating mechanism. We would expect a greater dispersal rate to slow the population growth rate (see Chapter 10). Hornocker (1970) first observed that puma progeny on a winter study area dispersed from it. He reported dispersal distances for three tagged progeny that were killed by hunters: a male moved 161 km and two females moved 64 and 113 km. While extending that study, Seidensticker et al. (1973) observed that dispersal of subadult puma progeny was independent of adult density: no progeny seemed to settle as adults within their study population. Immigrant pumas, which they called “transients,” replaced adults that died in the study population. Immigration was also noted as an important source of recruits in puma popula-

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tions in Alberta (Ross and Jalkotzy 1992), Utah (Laing and Lindzey 1993), and Wyoming (Logan et al. 1986). Numerous studies have now shown that dispersal in puma progeny is sex-biased; male dispersal is generally obligatory, and males disperse consistently farther than females (see Anderson et al. 1992), characteristics that are common in polygynous or promiscuous mammals (Dobson 1982 see Chepko-Sade and Halpin 1987, Stenseth and Lidicker 1992). In his summary on dispersal patterns of sixty-five North American pumas, Anderson et al. (1992:66) found that on average males dispersed 2.7 times (n = 33, x– = 85.0 km, range = 29–274 km) farther than females (n = 32, x– = 31.4 km, range = 9–140 km). Although the importance of dispersal to the dynamics of local puma populations was previously recognized by other puma biologists, its effects on rates of emigration and recruitment were not quantified until our study. In Chapter 13, we examine the adaptive significance of dispersal in pumas (see “Why Do Pumas Disperse?”).

Emigration As pumas dispersed beyond the San Andres Mountains, they emigrated from the local population. We estimated total successful emigration spanning a 5.1-year period from 1 February 1990 to 23 February 1995 by using our capture information on tagged progeny that survived to adulthood and estimating cub and subadult survival rates. Total successful emigration from our study area during that time span was about 27.5–43.7 progeny, including about 19.1 males and 8.4–24.6 females (depending upon the survival schedule used for females, i.e., 0.56 or 0.88). This would equate to 5.3–8.5 emigrants per year, about 3.7 males and 1.6–4.8 females. Of the estimated total progeny that would have survived to adult ages, we estimated that 83 percent of males and 33–59 percent of females emigrated from the San Andres Mountains (Sweanor et al. 2000). These were pumas that were raised by mothers on the San Andres Mountains, emigrated from the area, and survived long enough to be recruited into other puma subpopulations in New Mexico. Based on the reproductive success of immigrant pumas to the San Andres Mountains, we surmised that emigrants became productive members of other subpopulations as well. While pumas were leaving the San Andres Mountains and moving to other subpopulations in southern New Mexico, pumas were emigrating from those subpopulations and making their way to our study area.

Recruitment of Progeny and Immigrants We estimated recruitment during 1 February 1990–23 February 1995 by counting the tagged progeny and immigrants that reached adulthood within the San

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Andres Mountains. Immigrants were identified as such, because they did not have tags when we initially captured them. About twenty-one progeny, including four males and seventeen females (1 male:4.2 females), were recruited, for an average rate of 0.8 male and 3.3 females per year. During the study, twelve females but no males (57 percent in aggregate) produced offspring themselves. It is possible that three of the males sired litters without us detecting their contribution. The fourth male was infertile (M73). For the same time period we estimated that about twenty-two immigrating pumas, including fourteen males and eight females, were recruited into the San Andres Mountains population, at an average rate of 2.7 males and 1.6 females per year. Of these immigrant recruits, at least five males and five females (45 percent in aggregate) produced offspring. Again, it is likely that more males sired litters without our knowledge. These statistics indicated that recruitment into the growing San Andres Mountains puma population was dependent equally upon both progeny (4.1 / year) and immigrants (4.3 / year). In addition, they showed recruitment of males and females was affected by differential dispersal patterns in the sexes. We calculated that 78 percent of male recruits were immigrants, whereas 68 percent of female recruits were progeny. Together, progeny and immigrant recruits (8.4 / year) balanced or exceeded the estimated number of progeny that successfully emigrated (5.3–8.5 / year). The contribution of immigrants to population growth exemplifies the importance of considering puma distribution in the context of a source-sink metapopulation structure. This subject, along with puma density and population growth, will be discussed in our next chapter.

LP > >

KX

1. Puma offspring became independent of their mothers at an average age of about fourteen months. Mothers sometimes initiated independence by abandoning the offspring. Independence was associated with the resumption of breeding behavior in the mothers. Independence seemed to occur at a time when cubs could be self-sufficient and the mother could devote time and energy to more reproduction. 2. Some female progeny were philopatric, while others dispersed. Mothers, philopatric daughters, and daughters that established adjacent home ranges formed eight matrilines on the San Andres Mountains. 3. Puma offspring that dispersed left their natal areas at the average age of about fifteen months. Both sexes dispersed before reaching puberty. On average, males dispersed about 101 km, and females about 28 km, from natal areas. Effective dispersal was about 7.3 home range diameters for males and about 1.4 home range diameters for females. Male dispersal was

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density independent. We hypothesize that female dispersal is partially density dependent. 4. Surviving puma progeny emigrated from the San Andres Mountains at the rate of about 5.3–8.5 pumas per year, of which about 3.7 were males and 1.6–4.8 were females. Of the total surviving progeny, about 83 percent of males and 33–59 percent of females emigrated and were potential recruits to other puma populations. 5. Growth of the adult segment of the puma population was dependent upon progeny and immigrant recruits. Progeny were recruited at the rate of about 4.1 per year and immigrants were recruited at the rate of about 4.3 per year. The male:female ratio of progeny recruits was about 1:4, while for immigrant recruits it was roughly 2:1.

Chapter 10

Puma Population Density, Growth, and Metapopulation Structure

Experimentally Removing Pumas A powerful way of learning how quickly a puma population can grow, and about the patterns of replacement of breeding adults, is through experimentally removing animals. We were already learning valuable things about those properties by studying the dynamics of a rebuilding population. But by experimentally reducing a portion of the population in the 703-km2 Treatment Area, we could test if the patterns we initially saw in the Treatment and Reference Areas were real and also gain estimates of variation. Consequently, we removed thirteen pumas from the Treatment Area in a 6.5-month period from 9 December 1990 to 22 June 1991. Five were adult males (mean age = 64.0 ± 32.8 months, range = 30–102), six were adult females (mean age = 46.0 ± 28.9 months, range = 22–102), and two were subadult females (mean age = 16.5 ± 0.7 months, range 16–17). We translocated those pumas to northern New Mexico (Ruth et al. 1998). During the same period, two 2- to 3-month-old siblings (M117 and F118) died of natural causes on the Treatment Area. We believe another female cub (F102), which disappeared at about 10.5 months old, also died. Of the pumas we translocated, two adult males returned to their original territories on the Treatment Area. Puma M88 was back on 21 July 1991, 166 days after removal. He remained the dominant male there through the end of the study. M49 returned on 7 July 1992, 469 days after removal. But his stay on his 157

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original territory was brief, only about nine days. Possibly driven from the area by an encounter with M3, M49 subsequently traveled north into the Reference Area and died. Consequently, M88 contributed to the post-treatment (i.e., after removal) puma population on the Treatment Area, but M49 did not. At the end of the experimental removal, the entire puma population in the Treatment Area had been reduced by 47 percent. Adult pumas had been reduced by 53 percent, and all independent pumas (adults plus subadults) had been reduced by 58 percent (Table 10-1). By January 1994, thirty-one months posttreatment, the adult segment of the puma population had practically recovered to the 1991 pre-removal level, with a difference of –0.27 pumas (Table 10-2). The actual rates of increase for adult pumas in the Treatment Area during preand post-treatment periods and in the Reference Area will be discussed in detail

Table 10-1. Puma population, number of pumas removed, and post-removal population in the Treatment Area, December 1990–July 1991, San Andres Mountains, New Mexico. Population description

Adults Male Female

Pre-treatment (Dec. 1990) Pumas present 7 Treatment (Dec. 1990– June 1991) Pumas removeda 5 % Removedd 71 Post-treatment (July 1991) Pumas present 3b d % Removed 57

Subadults Male Female

Male

Cubs Female Unk. Sex Total

10

0

2

4

5

2

30

6 60

0

2 100

1c 25

2c 40

0

16 53

5 50

0

0 100

3 25

3 40

2 0

16 47

aIndependent pumas were removed alive and translocated to northern New Mexico from 9 December 1990 to 22 June 1991 (see Ruth et al. 1998). bOne adult male (M88) that was removed returned to his original home range 166 days later (21 July 1991). He remained as a member of the Treatment Area population through the end of the study. cDuring the removal period, two cubs (one male, one female) from the same litter died, and one female cub from another litter disappeared. dPercentage of pumas removed from each category. All adults were reduced by 53 percent. All independent pumas (adults and subadults) were reduced by 58 percent. The total puma population was reduced by 47 percent.

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later in this chapter. Sex ratios of the adult pumas in January 1991 and January 1994 were identical (i.e., 1 male:1.4 females), suggesting that adult pumas were replaced numerically by same-sex recruits. Our findings further confirm a pattern of replacement of adult pumas in-kind that has been observed by other biologists studying puma populations in Idaho (Seidensticker et al. 1973) and Utah (Laing and Lindzey 1993). This tendency points to the strong influence of the mating system and social behavior in the structure of puma populations (see Chapters 12 through 15). Recruits into the Treatment Area after the removal originated from three sources. Three females (F107, F109, and F149) were progeny born to Treatment Area females (F47 and F21) that were not removed during the treatment. Of those, two were philopatric siblings (F107 and F109), and one (F149) established a home range adjacent to her natal area. Three pumas, including two males (M124, M153) and one female (F103), were progeny of females (F65, F28, and F87) in the Reference Area. Six pumas, including five males and one female, immigrated to the Treatment Area from outside the San Andres Mountains. The origin of one other recruited female was unknown. In the last year of the study, we traced her movements by ground-tracking her and visually observed her three large cubs. But we never got to see if she was tagged. In general, proportions of female recruits from progeny born on the Treatment Area and immigrants (either from the Reference Area or from elsewhere in New Mexico) were about the same as we saw in the San Andres Mountains puma population as a whole. However, all of the male recruits immigrated even though at least eight tagged male offspring that were born in the Treatment Area reached independence during the treatment and post-treatment period. One of those (M108) was killed in his natal area by his father (M88). Two others died as they dispersed north through the Reference Area. One of them (M140) was killed by a male puma, and the other (M198) apparently died of a head injury. All the rest, if they survived, apparently emigrated from the San Andres Mountains. Biologists studying a puma population in south-central Utah were the only others to experimentally reduce a population. Their objective was “to monitor the response of a [puma] population with known characteristics to removal of individuals, simulating a harvest” (Lindzey et al. 1992:224). Six pumas, including two male and one female that were 1.5 years old, and one male and two females that were 3.5 years old, were removed from a 1,900-km2 central core area within a 4,500-km2 study area. In addition, two other adult pumas (unspecified sex and age) died from natural causes. The combination of removals and deaths comprised 36 percent of the “harvestable population,” which the biologists defined as the number of pumas older than one year. With the possible exception of one adult male, the adult segment of the population

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recovered in nine months. The rapid recovery was probably facilitated by pumas living in the large adjacent protected area (i.e., hunting was banned). By the second year after the removal, the number of adult males had recovered fully, but the number of adult females had declined by one as a result of three deaths that were replaced by two recruits. In that manipulated population, recovery of adult female pumas was from progeny and immigrants, and all of the males were replaced by immigrants, just as we had observed for our study area.

Density Pumas are large, warm-blooded vertebrates that are obligate carnivores. They occupy the third trophic level, above producers and herbivores. Because energy is inefficiently transferred between trophic levels (see Ricklefs 1990), pumas must acquire sufficient energy for maintenance, behavioral activity, reproduction, and rearing of young by pursuing mobile vertebrate prey in large areas. A consequence of these energetic constraints and movement patterns is that pumas live at relatively low population densities. The puma population on the San Andres Mountains increased during the study. Our January population point estimates for the puma population in the Treatment Area and Reference Area are given in Table 10-2. Density of adult pumas in the Treatment Area increased from 1.16 to 2.10 per 100 km2 during the pre-treatment and treatment years (1988–1991) and from 0.84 to 1.99 per 100 km2 in the post-treatment years (1992–1995; Table 10-3). By January 1994, thirty-one months after the removal of 53 percent of the adults, the Treatment Area population had almost recovered to its pre-treatment density. However, by January 1995, adult puma density on the Treatment Area declined by 4 percent because of the death of one female. Density of adults post-treatment still increased to the pre-removal level even though the deer population declined precipitously (see Chapter 17). Density of all pumas, including adults, subadults, and cubs, in the Treatment Area ranged from 2.01 to 3.91 per 100 km2 in the pre-treatment and treatment years and from 2.78 to 4.25 per 100 km2 in the post-treatment years. January population estimates for the Reference Area indicated that adult puma density increased from 0.94 to 2.01 per 100 km2 between 1989 and 1995 (Table 10-3). Density of all pumas ranged from 1.72 to 3.90 per 100 km2. For our entire San Andres Mountains study area during January each year from 1989 to 1995, the number of adult pumas ranged from twenty-five to forty-two, and the total number of pumas ranged from forty-two to eightytwo (Table 10-4). We examined the potential effects of unintended removals of pumas from the Treatment and Re f e rence Areas on January point estimates of adult pumas. These

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Table 10-2. Estimated puma population each January in the Treatment Area (1988–1995) and Reference Area (1989–1995), San Andres Mountains, New Mexico.a Year

Adults Males Females

Subadults Males Females

Cubs

Total

1988 1989 1990 1991b 1992 1993 1994 1995

5.14 5.94 4.47 6.34 2.67 4.08 5.32 5.78

3.02 6.04 8.82 8.47b 3.22 8.20 9.20 8.20

Treatment Area 0 0 6 1 2.59 2.89–4.67 1 2 4.19–9.01 0 1b 7–11.68 0.68 4 10 2–3c 0–1c 6.20–14.60 0 0 5–8 0 0 9–15

14.16 18.46–20.24 20.48–25.30 22.81–27.49 20.57 21.48–29.88 19.52–22.52 22.98–28.98

1989 1990 1991 1992 1993 1994 1995

6.81 7.04 7.84 8.33 9.66 8.97 11.16

5.96 11.18 10.53 14.28 14.80 14.54 16.10

Reference Area 1 0.41 9.11–12.33 1 1 10–14 0 1 9–17.32 0.32 1 8.50–14.50 2 3 13.80–23.40 2 2 9–16.48 1 1 6

23.29–26.51 30.22–34.22 28.37–36.69 32.43–38.43 43.26–52.86 36.51–43.99 35.26

aRadio-collared

pumas that lived along either the Treatment Area–Reference Area boundary or the study area boundary were included in the Treatment Area or Reference Area based on the proportion of their aerial locations in the area during each year. Cubs were included in areas in identical proportions as their mothers (see text for details). bPumas were experimentally removed from the Treatment Area from 9 December 1990 to 22 June 1991. The January 1991 estimate reflects the absence of one adult female and one subadult female that were removed in December 1990. cSubadults present in January 1993 consisted of either three males, or two males and one female.

removals included one adult male that was translocated from the Treatment Area on 6 April 1989 because he killed three desert bighorn sheep, and seven humancaused puma deaths (i.e., one male, six females) in the Re f e rence Area during 1988–1994 (see Chapter 8). We did this by assuming that each puma would have survived re l a t i veto the annual surv i val probabilities (i.e., rates) that we calculated (using Mi c ro m o rt software) for adult males and females in the respective area. In

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Table 10-3. Estimated density of pumas each January in the Treatment Area (1988–1995) and Reference Area (1989–1995), San Andres Mountains, New Mexico. Pumas / 100 km2 Adult Females Total Adults

Total Pumasa

Year

Adult Males

1988 1989 1990 1991 1992c 1993 1994 1995

0.73 0.84 0.64 0.90 0.38 0.58 0.76 0.82

Treatment Area 0.43 0.86 1.25 1.20b 0.46 1.17 1.31 1.17

1.16 1.70 1.89 2.10 0.84 1.75 2.07 1.99

2.01 2.63–2.88 2.91–3.60 3.24–3.91 2.93 3.06–4.25 2.78–3.20 3.27–4.12

1989 1990 1991 1992 1993 1994 1995

0.50 0.52 0.58 0.61 0.71 0.66 0.82

Reference Area 0.44 0.82 0.78 1.05 1.09 1.07 1.19

0.94 1.34 1.36 1.66 1.80 1.73 2.01

1.72–1.96 2.23–2.52 2.09–2.71 2.39–2.83 3.19–3.90 2.69–3.24 2.60

aTotal

pumas includes adults, subadults, and cubs. January 1991 estimate reflects the absence of one adult female that was removed in December 1990. cPumas were experimentally removed from the Treatment Area from 9 December 1990 to 22 June 1991. bThe

other words, we estimated when these pumas would have been members of the population if they were only subjected to natural causes of mort a l i t y. Each adult puma was added to the January point estimate for each year if the product of its survival rates was greater than 0.50 for that ye a r. The puma was considered dead and expunged from the estimate when the product of its survival rates was less than 0.50. We also assumed that the lone translocated male in the Treatment Area would have been removed with the rest of the pumas after January 1991. Given these assumptions, adult male density in the Treatment Area during 1988–1991 ranged from 0.73 to 1.04 males per 100 km2, while total adult density ranged from 1.16 to 2.39 adults per 100 km2 ( c o m p a re with Table 10-3). In the Re f e rence Area, four of the females would have died in the interval, while the male and

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Table 10-4. Estimated puma population each January, 1989–1995, San Andres Mountains, New Mexico (2,059 km2). Year 1989 1990 1991 1992 1993 1994 1995

Adults Males Females 13 12 15 11 14 15 17

12 20 19 17 23 24 25

Subadults

Cubs

Total

5 5 2 6 7 4 2

12–17 14–21 16–29 20–26 20–38 14–25 15–21

42–47 51–58 52–65 54–60 64–82 57–68 59–65

three females would have surv i ved to January 1995. By adjusting adult puma numbers in the Re f e rence Area, Ja n u a ry point estimates during 1989–1995 we re 0.50–0.90 per 100 km2 for males; 0.51–1.41 per 100 km2 for females; and 1.02–2.31 per 100 km2 for all adults. Hypothetically then, maximum adult male densities in the Re f e rence Area (January 1995) and realized densities in the Tre a tment Area (January 1991) would have been equivalent (0.90 males / 100 km2). Howe ver, in 1995 the female density in the Re f e rence Area (1.41 females / 100 km2) would have exceeded the maximum female density realized in the Tre a tment Area in 1994 (1.31 females / 100 km2), and the maximum total adult density in the Re f e rence Area (2.31 adults / 100 km2) would have exceeded the maximum adult density realized in the Treatment Area (2.10 adults / 100 km2). Still, the maximum hypothetical adult puma densities in the Treatment and Reference Areas were ve ry similar. We believe these hypothetical Re f e rence Area puma densities are sensible given that the population there was not experimentally reduced, as was the Treatment Area population, and thus had a longer uninterrupted period to grow. These human-caused deaths we re also additive because they apparently suppressed adult puma density. Our estimates of adult puma density, based on the number of adult pumas present year-round (January–December) in a 100-km2 area, increased over time. The annual density on the Treatment Area increased from 1.36 to 2.01 adults per year per 100 km2 during the pre-treatment years (1988–1990) and from 1.09 to 1.87 adults per year per 100 km2 during the treatment and post-treatment years (1991–1994). In the Reference Area, density of adult pumas increased from 1.13 to 1.79 during 1989–1994 (Table 10-5). As would be expected, our adult puma density estimates for the biological

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Table 10-5. Yearly (January–December) adult puma density estimates for the Treatment Area (1988–1994) and Reference Area (1989–1994), San Andres Mountains, New Mexico. Year

Males

1988 1989 1990 1991 1992 1993 1994

5.14 4.91 5.55 2.67 3.66 4.45 4.82

1989 1990 1991 1992 1993 1994

7.14 7.62 8.41 8.77 9.28 9.10

Pumas / yeara Females Total 4.46 7.48 8.57b 4.96 6.96 8.62 8.33 8.10 10.49 11.25 13.35 14.67 15.20

Pumas / year / 100 km2 Males Females Total

Treatment Area 9.60 0.73 12.39 0.70 14.12b 0.79 7.63 0.38 10.62 0.52 13.07 0.63 13.15 0.69

0.63 1.06 1.22 0.71 0.99 1.23 1.18

1.36 1.76 2.01 1.09 1.51 1.86 1.87

Reference Area 15.24 0.53 18.11 0.56 19.66 0.62 22.12 0.65 23.95 0.68 24.30 0.67

0.60 0.77 0.83 0.98 1.08 1.12

1.13 1.33 1.45 1.63 1.76 1.79

aPumas

/ year = sum of proportions of a given year that each adult puma was present on a particular area (see Chapter 5 for details). bAssuming that the one adult female we removed on 9 December 1990 would have been present to 31 December, females / year would equal 8.63, and the total would equal 14.18. We used these values in rates-of-increase calculations for 1990 to control for removing the puma.

year (August–July) also showed increasing trends. In the Treatment Area, biological year density increased from 1.24 to 1.89 adults per year per 100 km2 in pre-treatment years (1987–1988 to 1989–1990), and from 1.12 to 1.83 adults per year per 100 km2 in post-treatment years (1991–1992 to 1993–1994). Reference Area biological year density estimates increased from 0.94 to 1.73 adults per year per 100 km2 during 1988–1989 to 1992–1993, and declined slightly to 1.71 adults per 100 km2 in 1993–1994 (Table 10-6). Clearly, puma deaths caused by predator control and sport-hunting during 1979–February 1985 severely suppressed the puma population on the San Andres Mountains. Of the fifty pumas that were killed, about forty were adults. In the Treatment Area, fourteen were killed for predator control and three by

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Table 10-6. Biological year (August–July) adult puma density estimates for the Treatment Area (1987–1988 to 1993–1994) and Reference Area (1988–1989 to 1993–1994), San Andres Mountains, New Mexico. Year

Pumas / yeara Males Females Total

Pumas / year / 100 km2 Males Females Total

1987–88 1988–89 1989–90 1990–91 1991–92 1992–93 1993–94

4.77 5.44 4.72 4.20 2.91 4.34 4.17

3.96 6.84 8.58 7.12 5.02 8.20 8.75

Treatment Area 8.73 12.28 13.30 11.32 7.93 12.54 12.92

0.68 0.77 0.67 0.60 0.41 0.62 0.59

0.56 0.97 1.22 1.01 0.71 1.17 1.24

1.24 1.74 1.89 1.61 1.12 1.79 1.83

1988–89 1989–90 1990–91 1991–92 1992–93 1993–94

6.07 7.66 8.23 8.34 9.40 8.57

6.63 10.19 10.48 13.17 14.10 14.62

Reference Area 12.70 17.85 18.71 21.51 23.50 23.19

0.45 0.56 0.61 0.62 0.69 0.63

0.49 0.75 0.77 0.97 1.04 1.08

0.94 1.31 1.38 1.59 1.73 1.71

aPumas / year = sum of proportions of a given year that each adult puma was present on a particular area (see Chapter 5 for details).

sport-hunters. And in the Reference Area, twenty fell to predator control and three to sport-hunters. Overall, this kill rate of 11.2 adult pumas per year exceeded the recruitment rate of 8.4 pumas per year that we observed during February 1990–February 1995. The rate of removal by predator control alone, 9.5 adults per year, also exceeded the observed recruitment rate. Moreover, after February 1985, when the puma population was protected for our research, the puma population increased. It took from three years (in the Treatment Area) to ten years (in the Reference Area) for the puma population to reach the relatively high density of about two adults per 100 km2. We believe the pattern of a lower puma density in the Reference Area relative to the Treatment Area was affected principally by three factors: intensive predator control on the Oscura Mountains, habitat quality, and human-caused mortality. During October 1980–October 1981, a total of thirteen pumas,

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including eleven adults, were killed for predator-control reasons on the 673-km2 Oscura Mountains, which are just to the north of the Reference Area. The kill rate of 1.6 adults per 100 km2 per year probably severely reduced the puma population on those mountains; consequently, dispersal of subadults from the Oscura Mountains and the attendant immigration of pumas into the Reference Area would have been reduced. The northern portion of the Reference Area, from Silvertop Mountain north to Mockingbird Gap, consists of a fragmented assemblage of mountains and low hills separated by desert flats and basins. In contrast, the Treatment Area is relatively contiguous. In addition, the southern portion of the Reference Area, from Hembrillo Canyon north to Cottonwood Canyon, appeared to have a lower abundance of mule deer than we observed in other parts of the San Andres Mountains. We believe this was influenced primarily by the high distribution of tall and low mixed desert shrub and grass communities in those canyons that offered relatively low-quality deer foods. Both fragmented habitat and lower prey abundance would lower habitat quality for pumas. As we explained above, the deaths of seven adult pumas at the hands of humans during our research also probably lowered the adult puma density. Trying to compare puma densities on the San Andres Mountains with densities estimated in other puma populations is risky. Different studies have applied different estimation methods and varying degrees of intensity in research efforts, and therefore yield a varying degree of accuracy. For example, biologists in Alberta used intensive capture-mark-recapture and radiotelemetry techniques to quantify the puma population (Ross and Jalkotzy 1992), while biologists in Southern California relied about equally on radiotelemetry and tracks presumably of non-tagged pumas to estimate the total population (Neal et al. 1987). In addition, puma study areas are usually contiguous with other puma habitat, causing population density estimates to be affected by individuals having partial spatial and temporal use of the study area (Neal et al. 1987). Studies that exerted intensive capture-mark-recapture and radiotelemetry techniques on study areas where puma movements were restricted by deep snow in winter, or where habitat conditions caused natural constraints in the distribution of pumas (e.g., the San Andres Mountains surrounded by desert basins), have provided the most accurate estimates of population composition and density. Therefore, we limited our comparisons to those. Ranges of adult puma density estimates made in January each year (adults / 100 km2) on the Treatment Area and Reference Area were most similar to the range of adult densities reported for a lightly hunted puma population in central Idaho (Table 10-7). A moderately hunted population in north-central Wyoming had densities at about the middle of our range. An Alberta popula-

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tion with light to moderate hunting pressure with three interceding years of zero off-take had densities in our upper range. Yet in southern British Columbia, where pumas were not hunted but suffered significant accidental mortality from automobiles, densities were in our low range. Only the unhunted population in south-central Utah exhibited a density well below our range and that of all other studies. Our total puma density ranges include the ranges for the Idaho and British Columbia puma populations. The Alberta and Wyoming populations reached slightly higher extremes. Again, the Utah population had a lower range for total population density than all other studies. Some similarities in puma densities were apparent even though the environments where studies were conducted were different. The puma population on the San Andres Mountains was not influenced by severe winter weather that caused seasonal population concentrations or migrations by pumas and their prey. Thus, these factors did not trigger within-year fluctuations in abundance of adult pumas. However, puma populations in Idaho, Wyoming, Alberta, British Columbia, and Utah were censused in winter when pumas and their ungulate prey were concentrated on low-elevation winter ranges because deep snow constricted their movements at higher elevations. As snow receded in summer, pumas followed ungulate prey to higher elevations. As a result, puma home ranges either enlarged or pumas occupied summer home ranges distinct from winter home ranges (Seidensticker et al. 1973, Hemker 1982, Logan and Irwin 1985, Ross and Jalkotzy 1992, Pierce et al. 1999). Puma population densities have not been estimated on summer ranges in those environments. Identifying reasons why puma populations are similar or different in disparate areas is difficult. Yet, such efforts are important to help us understand factors affecting density. In general, it is logical to consider that densities would be affected by variations in prey biomass—essential energy required to fuel pumas. For example, studies of wolves (Fuller 1989, Messier 1995) and leopards (Stander et al. 1997) have shown that prey density (i.e., prey biomass) is a very important predictor of densities of these carnivores. But because of complications in attaining estimates of puma prey biomass, comparative data do not exist. Therefore, we could not make inferences about its effect on density across the sample of study areas. Other limiting factors such as predator control and sport-hunting that occurred around practically all of these study areas to various degrees might have affected density of pumas thereon by influencing the number of dispersers available as potential recruits. In addition, pumas use habitat features selectively to attain food and security for offspring (Logan and Irwin 1985, Belden et al. 1988, Laing and Lindzey 1991). Structure of puma habitat—its continuity or fragmentation, its physiography and vegetation, and how

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these characteristics influence prey distribution, abundance, and vulnerability to predation—also affect density.

Rates of Population Increase We were able to estimate realized rates of puma population growth because we obtained annual censuses of a puma population that was protected after it was severely reduced by predator control actions during the early 1980s. We also experimentally removed 53 percent of the adult pumas and 58 percent of independent pumas (i.e., adults plus independent subadults) from the Treatment Area, and then monitored recovery. At the same time, we quantified rate of population increase for the protected Reference Area. The severe reduction in the puma population before our research and our experimental removal in the Treatment Area, coupled with protection of the puma population and its prey during our research, should have given us a good indication of the maximum realized rate of increase of the puma population in the prevailing environmental conditions. We calculated observed exponential rates of increase for adult pumas in the Treatment and Reference Areas separately using three population density estimators: (1) January point estimate, (2) each annual period January–December, and (3) each biological year August–July (Table 10-8). Observed exponential rate of increase (r) was calculated for each estimator by linear regression of the natural log of the estimated number of adult pumas each time period (i.e., the dependent variable) on the units of time numbered sequentially starting with zero (i.e., the independent variable) (Caughley 1978, Van Ballenberghe 1983). The slope of the regression line is r; it represents the average rate at which the puma population changed per year. The puma population grows if r is positive; it declines if r is negative. Puma population growth rates are an index to how interactions of population density and habitat quality affect reproduction, mortality, immigration, and emigration. Several patterns in r emerged that we explain with biological and environmental phenomena. We also ventured some predictions based upon our knowledge of puma population dynamics and behavior: 1. The puma population grew relatively rapidly after it was severely reduced, then protected, during a time when per capita food resources (i.e., principally deer) increased (refer to Table 10-8). Rates of increase for all adults were highest during time spans beginning with low puma density, regardless of the area or estimator. This indicates that puma populations have a high potential to increase when intraspecies and interspecies competition

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for resources and other limiting factors (e.g., human-caused mortality) are weak. In addition, given the high puma population growth rate in the Treatment Area during the deer decline, the puma’s numerical response lagged behind the numerical response of the prey (see Chapter 17). 2. Maximum observed rates of increase in the Treatment Area and the Reference Area were variable. January point estimates for the Treatment Area pre(r = 0.21) and post-treatment (r = 0.28) and the Reference Area during 1989–1992 (r = 0.17) averaged 0.22 ± 0.06 (Fig. 10-1). 3. The Reference Area growth rate during 1989–1995 (r = 0.11) was for the longest time span for which any puma population growth has been quanti-

FIGURE 10-1. Observed exponential rates of increase for adult pumas in the Treatment Area (TA) and Reference Area (RA) using January population estimates, San Andres Mountains, New Mexico.

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fied (Fig. 10-1). Moreover, it represents a period with varied ecological conditions. Relatively high growing-season precipitation and an increasing mule deer population characterized years 1985–1991, but growing-season drought and a declining deer population characterized years 1992–1995 (see Chapter 17). Additionally, potential immigration of progeny recruits was reduced due to the experimental removal of pumas from the Treatment Area. 4. Re f e rence Area growth rate during 1992–1995 declined (r = 0.05). We believe the reduced r was affected primarily by at least three factors: a decline in food re s o u rces, reduced re c ruitment of immigrants from the Treatment Area, and seven human-caused deaths. We would expect intraspecies competition for food to be the highest during times of declining prey resources and increasing puma density. The puma population continued to increase, albeit at a slower rate, creating a time lag. Eventually, we would expect the puma population to decline and be subjected to mechanisms resulting in lower puma surv i val rates, lower reproductive rates, greater subadult female dispersal, and possibly lower settlement rates of immigrants. Unfortunately, our re s e a rch ended too soon for us to observe how the puma population responded. No tagged progeny born in the Treatment Area were recruited into the Re f e rence Area during this period, while three tagged progeny born in the Re f e rence Area were re c ruited in the Treatment Area. This indicates that severe reduction of pumas in one area can affect population growth in an adjacent area. Without population reduction in the Treatment Area (including six adult females), we would have expected more progeny to be available as potential re c ruits into the Re f e rence Area. 5. To estimate the effect of seven adult puma deaths (one male, six females) due to human causes on the Reference Area, we recalculated rates of increase using hypothetical January point estimates assuming that the seven pumas would have been subjected only to natural causes of death. With this adjustment, the r for all adults during 1989–1995 was 0.11 ± 0.02 (SE ), identical to the realized rate (compare with Table 10-8). In each four-year segment, rates increased slightly. During 1989–1992, r for all adults was 0.19 ± 0.05, and during 1992–1995 it was 0.06 ± 0.04. For adult males during 1989–1995, r was 0.09 ± 0.01. Male r during 1989–1992 remained exactly the same because there was no change in density, but during 1992–1995, r i n c reased to 0.11 ± 0.05. For adult females during 1989–1995, r declined slightly to 0.13 ± 0.04. During 1989–1992, female r increased slightly to 0.28 ± 0.09, and during 1992–1995 it remained the same at 0.03 ± 0.04. Although the seven deaths reduced density, they apparently occurred too infrequently to change the rate of population increase substantially. Still it is possible that the deaths of the adult females in par-

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6.

7.

8.

9.

10.

173

ticular might have affected r more than we realized. Had they lived, some of their progeny, especially females, might have been recruited into the Reference Area population. This could have boosted density and rates of increase, unless density-dependent mechanisms increased in strength (e.g., greater female emigration). Adult male puma rate of increase based on January point estimates for the Treatment Area during 1988–1991 was affected by the removal of one adult male in 1989. Assuming that he would have survived to January 1991, adult male r would have increased substantially to 0.10 ± 0.05 (compare with Table 10-8) and would be closer to the r for adult male pumas in the Reference Area during 1989–1992. However, r for all adults in the Treatment Area increased only slightly to 0.23 ± 0.04. Adult female rates of increase were generally higher than for males. This phenomenon is due to the tendency for some female subadults, which have relatively high survival rates, to become philopatric adults. Inversely, subadult males have lower survival rates and most emigrate. Adult male recruitment into the local population relies primarily upon immigrants coming from some other population. Female rates of increase appear to be sensitive to puma density and trends in deer numbers. Female rates were highest during the period of low puma density and increasing deer numbers. However, female rates declined during deer loss. Decline in the rate was particularly precipitous in the Reference Area. The greatest changes in puma population density appear to occur in the adult female segment. We hypothesize that during times of food abundance, philopatry in surviving female progeny is relatively high, and dispersal is low. But when food is limiting, female dispersal rates increase. Hence, competition for food may regulate dispersal in surviving female progeny. Male rates of increase in the Treatment Area did not parallel the declining deer numbers, but in the Reference Area male rates of increase were about equivalent in the January point estimate and declined in the other two estimators. The tendency for male r in the Treatment Area population to be less sensitive to changes in food abundance may be related to two factors. First, the adult male takes no part in raising offspring; hence, his total energy demand may be up to one-third that (estimated in kcal / day) of a female raising cubs (Ackerman 1982). Secondly, males were establishing in a population with a drastically reduced puma density, and hence competitors, which resulted from removal. In the Reference Area, we hypothesize that the decline in male rates of increase for the two year-round estimators may be the result of increased male-to-male competition for mates. The January–December and biological year (i.e., August–July) estimates of

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r, which represented the number of adult pumas present throughout each twelve-month period, indicated declining rates of increase for all adult categories in the Reference Area during deer decline years. In the Treatment Area, the rate of female population growth declined during the deer population decline. This would be expected if puma density was ultimately limited by food. 11. For all adult categories, rates of population increase generated by the January point estimator were fairly consistent with rates from the biological year estimator ending five months prior. Other than our estimates, quantitative data on rates of increase of puma populations are practically nonexistent in scientific literature. However, in examining population estimates from other intensive, long-term studies on puma population dynamics, we found that biologists in southern Alberta (Ross and Jalkotzy 1992) and south-central Utah (Lindzey et al. 1994) presented data showing increasing populations. We used their data to calculate observed exponential rates of increase for adult pumas in each population to compare with our findings. In Alberta, population estimates were made on 31 March each year; biologists defined adults as pumas that were older than 2.5 years. During three consecutive years (1984–1986) the number of adult pumas on the 780-km2 study area increased from twelve or thirteen to fourteen. The r ranged from 0.04 ± 0.02 (SE ) to 0.08 ± 0.002. This was a hunted population where three pumas were killed the first year, representing 16–20 percent of the estimated number of adults and subadults (i.e., pumas 1.6–2.5 years old). But no pumas were killed the following two years. Density of adult pumas during the three years ranged from 1.5 to 1.8 adults per 100 km2, which was within the high range of densities that we found on the San Andres Mountains (Table 10-7). In Utah, population estimates were made during January–March each year. Biologist there defined adults as pumas more than 1.5 years old that showed continuous use of a predictable area for more than six months. In four consecutive years (1984–1987) during which no adult pumas were removed, the number of adults on the 1,900-km2 study area increased from six to twelve, and r was 0.24 ± 0.03 (SE ). Density of adult pumas during the four years ranged from 0.32 to 0.63 per 100 km2, well below the lowest densities on the San Andres Mountains. Given the different criteria for defining an adult puma by the Alberta and Utah researchers, direct comparisons of rates of increase with those we calculated for the San Andres Mountains are tenuous. There may have been some “subadults” in the Alberta population that were sexually mature and hence met our definition of adult. On the other hand, some individuals in the Utah study may have been subadults. Still the range of ages of adult pumas on the San

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Andres Mountains certainly included the range of ages of pumas classed as adults in both the Alberta and Utah studies. It is at least noteworthy that the rates of increase were inversely related to puma density. In other words, the relatively high-density Alberta puma population exhibited the lowest rate, while the very-low-density Utah population had the highest rate. This was the basic relationship that we found in the San Andres Mountains. As we mentioned previously, the lower rate of population increase associated with higher puma densities in the Reference Area was partially affected by a declining mule deer population, low recruitment of pumas from the Treatment Area, and human-caused deaths. It is important to realize, however, that some puma populations apparently do not grow during extended periods even though their prey base does. The lightly hunted puma population studied over eight years in the central Idaho wilderness declined slightly due to puma deaths and emigration and coincident with increasing mule deer and elk populations, which constituted the puma’s major prey (Hornocker 1970, Seidensticker et al. 1973). The biologists hypothesized that the puma social organization, via a land tenure system, limited the density of adult pumas (Seidensticker et al. 1973). The adult segment of the puma population in Utah was relatively constant for the first seven years (1979–1985), changing by ± 0–2 adults per year even though the deer population increased throughout the study. But the magnitude of the deer population increase was not ascertained directly. Biologists found only a weak relationship between puma numbers and a fecal pellet group index to deer abundance. They suggested this might support the hypothesis initially established by the Idaho researchers, or it was possible that the deer population did not increase enough to cause a numerical response in the puma population (Lindzey et al. 1994).

Metapopulation Dynamics A fundamental concept we developed about the puma population on the San Andres Mountains is that it is a subpopulation (i.e., a local population) in a constellation of puma subpopulations in the Southwest (Sweanor et al. 2000). The basin and range physiography of the landscape naturally fragments puma habitat and the attendant puma population. Pumas live mostly in the mountains and foothills where there are large prey, including desert mule deer, desert bighorn sheep, javelina, white-tailed deer, elk, and a variety of smaller prey, such as wild turkey and porcupine. But in the broad intervening areas of non-habitat, or matrix, the desert is so harsh that prey occurs in extremely low densities or not at all. Hence, puma longevity there is low, as is their ability to successfully raise cubs. By studying the movements of dispersing pumas, we learned that emi-

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grants were a critical link between puma subpopulations and they contributed substantially to subpopulations. In the San Andres Mountains, about 78 percent of male recruits and 32 percent of female recruits were immigrants that made their way from other subpopulations. We documented that at least 45 percent of immigrant recruits produced offspring, including males and females. Similarly, emigrants from the San Andres Mountains were contributing recruits to other puma subpopulations. Because of these dynamics, we inferred that the puma population structure in southern New Mexico generally met the definition of a metapopulation—“a network of semi-isolated populations with some level of regular or intermittent migration and gene flow among them, in which individual populations may go extinct but can then be recolonized from other populations” (Meffe and Carroll 1997:678). Even though each subpopulation is dependent upon the immigration of pumas for numeric and genetic augmentation, we expect that the dynamics of each subpopulation is not necessarily correlated with other subpopulations. Pumas on the San Andres Mountains were principally dependent upon mule deer for food; consequently, a steep decline in deer abundance, triggered initially by severe drought, would likely result in a decline in puma numbers, albeit after a lag period (see Chapter 17). The same drought would not necessarily affect puma numbers in the same way in the Sacramento Mountains across the Tularosa Basin to the east, where the climate was somewhat wetter and the environment supported both mule deer and elk as principal puma prey. The same could be said for the Black Range and the wilderness mountains of the Gila River drainage in southwestern New Mexico where mule deer also declined, but elk and javelina numbers seemed stable or even increased. In those areas, pumas could alter their hunting patterns to kill the more locally abundant prey. If pumas switched to using elk and javelina more frequently than they did when mule deer were more abundant, the puma population might not decline at all. Pumas could also switch to killing domestic livestock, and thereby maintain their numbers (Cunningham et al. 1995). Furthermore, management practices impact puma population dynamics. Pumas and large prey on the San Andres Mountains were mostly protected from human off-take for the sake of our research, and therefore the population was mostly affected by natural dynamics. But sport-hunting pressure in the Sacramento Mountains and especially in the Black Range–Gila complex could have been impacting puma population dynamics by altering mortality rates, although the extent was unknown. In some regions, management objectives are to purposely reduce puma density to minimize predation on domestic livestock, such as in the Guadalupe Mountains in southeast New Mexico. On the other hand, local puma population densities can be reduced inadvertently by chronic annual

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heavy hunting. Yet other puma subpopulations may be stable or growing as a result of relatively light hunting pressure. Differential dynamics where some subpopulations are increasing while others are declining create a source-sink metapopulation structure. Source subpopulations are increasing or stable; recruitment via local reproduction and immigration outpace mortality. Source populations produce emigrating progeny that immigrate into other subpopulations, augmenting them numerically and genetically, and can rescue declining populations or colonize empty habitat patches. Stable populations, especially if they have high densities, can be sources of emigrants that can be recruited into other subpopulations. Source populations, particularly if they are large or persistent, stabilize the metapopulation. In contrast, sink populations are those where mortality outpaces recruitment; thus, puma numbers decline. Comparatively, they contribute few emigrating progeny as potential recruits for other subpopulations. If not rescued, sink subpopulations could go extinct. Large sinks could affect the dynamics of nearby subpopulations by reducing potential recruits that might otherwise offset or exceed mortality, and contribute to population decline over a larger region. Furthermore, immigrants to sink populations have lower survival rates and reduced chances of reproducing thereon or escaping to other more secure subpopulations. Sink subpopulations could destabilize the metapopulation. Whether they do or not will probably depend upon their size, number, and distribution. As emigrants move from one subpopulation to another and breed, genetic structure of pumas in the metapopulation is affected. High rates of gene flow among populations are possible in carnivores that exhibit high rates of dispersal and disperse long distances (Wayne and Koepfli 1996). Male pumas in particular, because of their tendency to disperse long distances and across matrix, enhance nuclear gene flow between widely separated subpopulations, including ones with vastly different habitats (e.g., from the Chihuahua Desert to coniferforested mountains and vice versa). Our radiotelemetry data on a sample of study area progeny indicated that most (seventeen of twenty females, eight of thirteen males) did not disperse more than five home-range diameters, the distance that may be necessary to disrupt genetic adaptations to regional environmental conditions (Shields 1982). Yet, the few progeny that did disperse beyond those distances could promote an outbreeding population structure (Templeton 1987). Outbreeding can introduce new alleles to a population, thereby increasing genetic variation, with the prospects of enhancing fitness of individuals in contemporary or future environments. Outbreeding may be a vital reason why pumas have adapted so well to a broad range of habitats in the Western Hemisphere. Puma immigration on the San Andres Mountains greatly exceeded the one-to-five per generation (Sweanor et al. 2000:Table 2), which is suggested by

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genetic theory to ensure effective transfer of genetic variation (Crow and Kimura 1970, Lacy 1987). With such high rates of gene flow, we expect little genetic subdivision among puma subpopulations in southern New Mexico. In a source-sink structure, dispersing pumas have critical consequences to the persistence of subpopulations. They can reduce the size of each subpopulation needed to maintain viability (Beier 1993). Furthermore, environmental variation, such as weather patterns that trigger severe prey depletion, or localized severe puma exploitation, is not as powerful an extinction force when populations are spread across space (Shaffer 1987, Noss et al. 1996). We estimated the San Andres Mountains chain (about 3,000 km2 of puma habitat), which includes the San Andres Mountains plus the Organ Mountains to the south and the Oscura Mountains to the north, supported thirty-six to sixty adult pumas during 1985–1995 (Sweanor et al. 2000) and a genetically effective population size (Ne—based on the actual number of breeding individuals and the distribution of offspring among families, Meffe and Carroll 1997) as low as half the adult density (Nunney and Elam 1994). This area easily exceeds the 1,000–2,000 km2 critical patch size needed for a 98 percent probability of persisting for one hundred years (Beier 1996). Not surprisingly, we learned through model simulations that the San Andres chain should be able to withstand the threat of extinction for one hundred years as long as it supports the puma demographics that we documented (Sweanor et al. 2000). Yet, to achieve recruitment rates we observed, the population relied upon both progeny born within the subpopulation and immigrants from other subpopulations. Smaller subpopulations inhabiting smaller habitat patches, such as the Caballo (about 200 km2) and Fra Cristobal (about 100 km2) Mountains, would have much smaller Ne. Without gene flow via immigrants, such populations could eventually lose genetic variability by genetic drift or inbreeding and hence the ability to adapt to altered environmental conditions (Chepko-Sade et al. 1987). Eventually, they could go extinct (Saccheri et al. 1998), particularly populations that undergo a rapid decline in size and that lack histories of severe fluctuations (Gilpin 1987, Lande 1988). Even with gene flow, smaller habitat patches have high probabilities of puma extinction. We found that twelve of one hundred simulated puma populations went extinct during a 100-year period for patch areas the size of the Organ Mountains (about 270 km2), even when using the productive population parameters and high immigration rate for pumas on the San Andres Mountains (Sweanor et al. 2000). Still, this does not mean that large puma habitat patches, such as the Sacramento Mountains (about 6,200 km2), are immune to extinction. Certainly, if negative population growth rates persist in large patches and surrounding patches to the extent that immigration does not offset mortality, then pumas in

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large patches can disappear. This may have occurred in the Sacramento Mountains in recent history. By the 1940s, state-sanctioned bounties and unregulated killing had confined pumas in New Mexico mainly to natural refuges in the remote mountains west of the Rio Grande (Young 1946) where hunters could not kill out the last pumas as they were able to do with the Mexican wolf and grizzly bear (Brown 1984, Brown 1985). However, regulations on puma killing since 1972 probably allowed remaining pumas to increase in numbers and to produce dispersers that recolonized or stabilized patches east of the Rio Grande. On a much grander scale, we know that pumas went extinct from almost all of their eastern North American range during the early 1900s. And even more remarkable, if Melanie Culver (1999) is right, pumas in North America may have gone extinct at the end of the Pleistocene; then immigrants coming from South America recolonized the continent. Puma population dynamics and life history strategies are inextricably linked. Clearly they contribute to the puma’s high adaptability. As we have pointed out in this chapter, they are influenced greatly by the environment and the way pumas interact with one another. In Part 3 we discuss adaptations in puma behavior and social organization.

LP > >

KX

1. We experimentally removed pumas from the 703-km2 Treatment Area during 9 December 1990–22 June 1991. The entire population was reduced by 47 percent. Adults were reduced by 53 percent, and independent pumas (i.e., adults plus subadults) were reduced by 58 percent. Post-treatment, it took thirty-one months for the adult segment of the population to recover to its pre-removal density. Adult pumas were replaced by same sex recruits, thus restoring the pre-removal sex ratio. Recruits came from within the Treatment Area, the Reference Area, and from other puma populations. 2. We estimated puma density using three estimators: (1) a point estimate of adult pumas and total pumas in January of each year, (2) an estimate of the number of adult pumas present year-round from January to December, and (3) the number of adult pumas present in each biological year from August to July. January point estimates for the Treatment Area pre-treatment and treatment years increased from 1.16 to 2.10 adults per 100 km2 and total pumas ranged from 2.01 to 3.91 per 100 km2. In the post-treatment years pumas increased from 0.84 to 1.99 adults per 100 km2 and total pumas ranged from 2.78 to 4.25 per 100 km2. Reference Area density increased during the seven-year period 1989–1995 from 0.94 to 2.01 adults per 100 km2 and total pumas ranged from 1.72 to 3.90 per 100 km2. Densities of adult and total pumas were in the moderate to high range for pumas in

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other western North America puma populations. The predator control and sport-hunting that occurred during 1979–1985 prior to our research had suppressed the puma population. Off-take exceeded the recruitment rate that we observed. 3. Except for our experimental removal of pumas from the Treatment Area, the puma population on the San Andres Mountains increased. Using January point estimates in the Treatment and Reference Areas, the average maximum observed exponential rates of increase (r) for adult pumas was 0.22 ± 0.06. For a seven-year span in the Reference Area that included the deer increase and decline phases, r was 0.11. During the mule deer population decline, r in the Reference Area was 0.05. Adult females had a tendency to grow at a faster rate than adult males. Female recruitment was more sensitive to the deer decline than male recruitment. 4. We inferred that pumas living in the basin and range configuration of habitat in the Southwest form a source-sink metapopulation structure. Subpopulations are linked to one another via dispersing pumas. Immigrants are vital for the numeric and genetic augmentation of subpopulations. Large source populations contribute to metapopulation persistence, while sink populations contribute to instability. Actual dynamics of the metapopulation will probably depend upon the size and distribution of source and sink populations. Gene flow between subpopulations probably enhances the puma’s ability to adapt to a wide range of environmental conditions and should result in little inter-subpopulation genetic subdivision.

P a rt I I I

Puma Behavior and Social Organization

Chapter 11

How Should Desert Pumas Behave?

Social organization is the manner in which individuals of the same species interact and are arranged in space and time relative to one another. Although pumas, and all other known species of cats except the African lion and cheetah (Schaller 1972, Caro 1994), live a solitary existence, this mode of life does not equate with absence of social structure (see Leyhausen 1965). Solitary simply means individuals do not cooperate with one another to rear young, forage, achieve matings, or defend against predators (Sandell 1989). Besides our descriptive study of puma social organization in the desert, we examined two hypotheses that explain the function of the puma’s social system. It is widely believed that the mating and spacing patterns we observe evolve from the different behavioral strategies that males and females employ to maximize individual reproductive success (Trivers 1972, Wrangham 1980, Sandell 1989, Caro 1994). We call this the two-strategies hypothesis. It has also been postulated that the social system functions to limit puma numbers within a given population (Hornocker 1969, 1970, Seidensticker et al. 1973). We term this the selflimiting hypothesis.

Two-Strategies Hypothesis How should pumas behave to maximize individual reproductive success? In pumas, as in other solitary carnivores, females typically provide greater parental investment (i.e., pregnancy, lactation, uni-parental care) than males. Thus, a female’s re p ro d u c t i ve success should principally be limited by access to resources, her own reproductive condition and survival, and the survival of her 183

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cubs. Female pumas should compete more with one another than with males for resources that are necessary to successfully rear offspring, while at the same time avoiding potentially dangerous pumas. In contrast, unencumbered males are free to seek breeding opportunities because female pumas can breed year-round. But because receptive females are relatively rare at any point in time, a male should compete with other males for mates. His reproductive success is limited by his own reproductive condition and longevity, the number of females to whom he has access, and by other males with whom he has to compete (Emlen and Oring 1977; Wrangham 1980, Macdonald 1983, Erlinge and Sandell 1986, Clutton-Brock 1989, and Chapters 7 and 8). If male and female pumas on the San Andres Mountains were conforming to these two strategies to maximize individual reproductive success, the following predictions should hold: 1. Each adult male should attempt to breed with as many females as possible. Males should maintain large home ranges to increase encounter rates with females. 2. Males should treat females as a critical defendable resource because breeding opportunities are rare (see Chapter 6). Hence, males should fight for breeding opportunity. 3. Removal of male competitors should allow remaining males to expand their home ranges to breed with more females. Removal of females should cause males to expand or shift their home ranges to seek breeding opportunities. 4. Females should attempt to successfully raise as many offspring as possible. To do this they must maximize their reproductive attempts and survival of themselves and their young (see Chapter 7) by avoiding competitors and evading predation. 5. Female home range fidelity should be high even when other adults are experimentally removed. This way, females cultivate knowledge of vital resources and minimize dangerous encounters with other predators and competitors. 6. If resources allow, females should share portions of their range with female offspring. This would increase inclusive fitness. 7. We expect reduced intersexual competition because critical resources are different for the sexes. Therefore, adult pumas should exhibit more spatial exclusion within than between sexes.

Self-Limiting Hypothesis Hornocker’s and Seidensticker’s research in central Idaho laid the foundation for what is understood about puma social organization, and it introduced the con-

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cept of self-limitation for the species (Hornocker 1969, 1970; Seidensticker et al. 1973). After five years of study, Hornocker described a relatively peaceful, polygamous society, where adult pumas occupied territories (loosely defined by Hornocker as an attraction to a particular locality) that were relatively exclusive in males and overlapping in females. Mutual avoidance behavior, aided by visual and olfactory cues, helped to distribute pumas in both space and time. This peaceful mechanism for spacing individuals was adaptive, Hornocker argued, because solitary predators cannot risk debilitating injuries that may result from fighting. Hornocker (1970:37) concluded that “intraspecific relationships, manifested through territoriality, acted to limit numbers of [pumas] and maintain population stability.” After three more years of research on the same puma population, during which radiotelemetry techniques were employed, Seidensticker et al. (1973) shied away from the term “territoriality,” instead using the less ambiguous, more descriptive term “home area” to characterize the area over which resident pumas roamed. Tenure of these home areas, they argued, was based on prior rights. A puma could claim a home area only when it became vacant, and once it established a home area, its simple occupancy would deter new individuals from settling there. They surmised that the presence of adult resident males was the primary factor limiting adult male density, and the presence of resident, breeding females limited the female breeding population. These conclusions were supported by the following observations: a resident male’s death resulted in the establishment of a home range by a new immigrant male as well as a shuffling of space by the remaining resident males; transient males rarely bred; no new males moved in to claim ranges made vacant by the deaths of resident adult females; and breeding in young adult females was apparently suppressed. Since Seidensticker and colleagues did not observe a positive correlation between puma density and prey numbers during their eight-year study (overall, the puma’s major prey increased while the puma population declined slightly), they also surmised that “the land tenure system maintains the density of breeding adults below a level set by food supply in terms of absolute numbers of mule deer and elk” (1973:59). After further examination of the social structure of pumas, bobcats, and leopards, Hornocker and Bailey (1986:218) concluded that the social “system’s primary function was population regulation through a spatial distribution of individuals.” In other words, the social structure was adaptive because the predator did not harm itself by overpopulating and depleting its food supply. The idea that Hornocker (1969, 1970) and Seidensticker et al. (1973) developed has been the model for how many wildlife biologists and managers alike view puma social organization and its influence on prey. Puma studies in Alberta, British Columbia, and Utah (Ross and Jalkotzy 1992, Spreadbury et al.

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1996, Lindzey et al. 1994, respectively) have described similar behavioral patterns, although evidence of fighting (i.e., scarring in males and puma deaths) indicated other puma societies were not as peaceful as the Idaho research suggested. These studies did not refute Seidensticker et al.’s (1973) thesis that the social system maintains the density of breeding adults below a level set by the food supply. However, none could adequately test it. In Utah, Lindzey et al. (1994) documented an increase in prey numbers while puma numbers remained somewhat stable; unfortunately, they could not determine the magnitude of the increase. In fact, they believed the increase in prey numbers may have been insufficient to provide an adequate test of the self-limiting hypothesis. Only one study, conducted in the Sierra Nevada of California on the distributions of pumas and their major prey (Pierce et al. 2000b), has seriously challenged the self-limiting hypothesis. Pierce and colleagues surmised that for a land tenure or territorial system to limit a puma population below the level set by the prey, territorial individuals would have to sequester more prey than necessary for reproduction, as well as limit the availability of prey to other pumas. They tested this primarily by examining the distribution of pumas in relation to the distribution of their major prey. They concluded that the puma’s land tenure system did not limit the population of pumas in their study area via partitioning of prey; instead, the puma population was limited by food supply. Because we were able to manipulate the puma population and we could ascertain the trend in the deer population, we were able to develop some predictions for pumas on the San Andres Mountains if they conformed to the selflimiting hypothesis. 1. The puma population exhibits stability when the prey base is increasing. Stability is maintained through a peaceful, land-tenure mechanism. The presence of resident adult males limits the density of resident males, and the presence of resident breeding females limits the female breeding population. Consequently, transient males should not successfully breed, and breeding in young adult females should be suppressed. All progeny emigrate unless space is made available within the population by the death of a same-sex adult. There should be no increase in density, decrease in home range size, or increase in spatial overlap to accommodate more adult pumas. 2. Given a stable or increasing prey base, new pumas will be able to claim vacant ranges after experimental removal. New adults should reoccupy the area in the same numbers, arrangement, and sex ratio as before the removal. 3. A substantial decline in the prey base should trigger a socially induced adjustment to puma population density, such as emigration of resident adults. Some vacated ranges (because of death or translocation) should not

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be re-occupied by new pumas. Otherwise the puma population will hasten the prey’s decline. In the next four chapters, we examine the social organization of pumas in the San Andres Mountains, and we test the ideas presented here. In the final chapter of Part 3, we synthesize the information from studies across the puma’s range to obtain a clearer understanding of the adaptive significance of the puma’s social structure. We also examine the puma’s social structure in relation to other large felids.

Chapter 12

Adult Home Range Characteristics

An animal’s home range is the area in which it chooses to live because it provides vital services, including food, mates, and a secure place to rear young (Burt 1943). Home range implies predictable use of an area over time. However, home range can vary seasonally as an animal moves between feeding or breeding areas; it can also change as the animal matures. The size, constancy of use, and orientation of the home range can give valuable insights into how pumas are influenced by other pumas as well as their environment. In this chapter, we present information on home range size and degree of home range fidelity in adult pumas.

Delineating the Home Range Although the definition of home range seems simple enough, delineating the actual boundaries, and hence area, is difficult. We used two methods to estimate home range: the minimum convex polygon (MCP; Hayne 1949) and the adaptive kernel (ADK; Worton 1989) methods in CALHOME software (Kie et al. 1994). We chose the MCP because of its graphic simplicity, wide historical use, and ease of calculation (Jennrich and Turner 1969, White and Garrott 1990), and because of its comparative value to the many other studies that have used the MCP to describe puma home ranges. In the MCP method, the peripheral locations of an animal are connected in such a way that the internal angles of the polygon thus generated do not exceed 180 degrees. Because home-range size calculated using the MCP is greatly influenced by outlier locations (Ackerman et al. 1989, White and Garrott 1990), we calculated a 90 percent MCP (the 189

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smallest area encompassed by 90 percent of the points) in addition to the 100 percent MCP. We also used the ADK, a non-parametric method for estimating an animal’s utilization distribution (UD; Worton 1989, Kie et al. 1994), because it was a flexible, probabilistic model that was considered to provide a more realistic representation of a home range (Worton 1989). The UD estimates where an animal is during the times between locations as well as the amount of time it spends in any particular place (Seaman and Powell 1996). Contours connecting areas of equal densities of observations can describe any usage area of the home range. For this study, we defined the home range and core area as the smallest area containing 90 percent and 60 percent of the UD, respectively. Although many studies report the 95 percent UD, we found that the distribution of puma locations in the long, narrow San Andres Mountains caused the 95 percent contour to balloon outside the study area boundary where pumas normally did not range. Of the 126 radio-collared pumas, we monitored eighty-six as adults on the study area. On average, we obtained 137 locations (range = 1–569) over a monitoring period of 28.8 months (range = 0–102) on each of these adults. Pumas were known to be traveling during 5 percent of locations for which we could identify activity; the rest were at day beds, nurseries, or prey caches. We gener-

Slide @318%

PHOTO 22. Aerial telemetry was critical to estimating puma home ranges and determining puma interrelationships.

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ally located pumas that utilized areas surrounding one of our camps more frequently than ones residing in other parts of the study area. Because home range estimators are strongly affected by the number of locations used and time between locations, we selectively chose location data to ensure successive locations were spatially independent and reliable comparisons between individuals were made. Consequently, we calculated home ranges using locations from the weekly flights (during which all radio-collared individuals were generally located) augmented with ground locations, as long as all locations were more than three days apart. This way we could bolster our aerial sample with ground locations during the weeks we were unable to fly. Tests to determine independence of animal-movement data (Schoener 1981; Swihart and Slade 1985, 1986) still indicated serial autocorrelations in some cases. We disregarded this for two reasons: individual movements likely were dependent on past experience and knowledge of resources in the home range, and pumas were capable of traversing their home range in a single day. Home ranges can provide unbiased estimates of space-use patterns when successive points are not independent statistically, as long as they are biologically independent (Lair 1987).

Seasonal and Annual Home Range We did not calculate seasonal home ranges because our earlier analyses (Sweanor 1990) did not indicate puma home ranges were highly influenced by seasonal changes. We found that an adult puma’s home range size did not change in any predictable pattern based on the two seasons (spring-summer: April to September; fall-winter: October to March) that we delineated. Furthermore, pumas did not exhibit a tendency to use seasonal home ranges. Instead, they typically used the same area year-round. We expected these results, because the puma’s prey did not migrate and winter movements were not restricted by deep snow. Annual home ranges were calculated for each adult puma that was present for at least ten months of any particular twelve-month period (1 January to 31 December). We used thirty-two to fifty-three (x– = 43.9 ± 3.9) locations to calculate each annual home range. Although the ADK home range estimator required a greater number of locations than did the MCP method, sample sizes appeared adequate to depict annual home range sizes (Appendix 3, Fig. A3-1). We obtained seventy-two annual estimates of home range size for twentyfour adult male pumas and seventy-one annual estimates for thirty adult female pumas (Appendix 3, Table A3-1). Annual home range size (90 percent ADK) for males and females averaged 193.4 km2 (range = 59.3–639.6) and 69.9 km2 (range = 13.1–287.4), respectively (Fig. 12-1). Females used between 33 and 38 percent of the average area used by male pumas, depending on the home range

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FIGURE 12-1. The means and standard deviations of annual, birth interval, and lifetime home range sizes, based on the 90 percent adaptive kernel home range estimator, for adult pumas on the San Andres Mountains, New Mexico, 1986–1994. Annual home range is mean of means.

estimator used [1]. The larger home range size of the male was reflected in his daily movements. Our earlier analyses (Sweanor 1990) found that males and females traveled, on average, 4.1 km and 1.5 km (linear distance) between locations one day apart, respectively.

Birth-Interval Home Range For females, we calculated home range over a biological time scale: an entire birth interval (the birth date of one litter to the birth date of the next litter). The birth interval (BI) was then split into three consecutive cub-rearing periods, each six months long. During each period, the female was raising young cubs (six months or younger), large cubs (seven to twelve months) or no cubs (i.e., cubs

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were, or became, independent and the female had not yet produced another litter). Because fewer locations were obtained in these shorter time periods, we only used the MCP to calculate cub-rearing home range size. We calculated home ranges for nine females over eleven birth intervals where females were radio-monitored without interruption and at least one cub from the first litter survived to independence. The average BI was 17.6 ± 1.9 months long and BI home range size averaged 64.9 ± 37.8 km2 (90 percent ADK; Table 12-1). The annual home range size for the same nine females averaged 58.9 ± 29.2 km2. Although the BI involved a longer time period, only one of the four home range estimators (100 percent MCP) indicated BI home range size was larger than annual home range size [2]. When we further examined female home range size in relation to the presence and age of cubs, we found a female’s home

Table 12-1. Female puma home range size during a birth interval (birth of one litter to the birth of subsequent litter, n = 11), San Andres Mountains, New Mexico.

Puma no. 4 15 21 37 37 41 45 47 47 65 91 Mean ± SD aBirth

Home range estimator (km2)d Minimum Adaptive kernel convex polygon

Birth yeara

No. No. monthsb locationsc 90% (–)

1986 1987 1991 1988 1989 1988 1991 1990 1993 1990 1992

16.9 18.3 19.0 16.0 18.3 18.0 17.8 14.0 16.8 17.1 21.6 17.6 ± 1.9

66 68 75 61 69 71 66 57 69 60 81

60% (–)

30.8 11.0 56.0 17.6 115.6 45.4 131.2 62.8 105.0 33.2 63.6 25.5 26.0 6.7 17.7 5.1 40.4 13.8 70.9 24.0 57.0 24.4 64.9 ± 37.8 24.5 ± 17.4

100% (+) 90% (–) 50.8 27.5 74.2 38.1 116.1 88.0 116.5 84.8 105.0 33.2 75.1 47.2 35.6 20.0 22.7 14.7 47.2 31.7 79.6 24.0 66.2 41.1 71.7 ± 31.5 40.9 ± 24.3

year = birth year of first litter. of months from the birth of first litter to the birth of the next litter. cAll aerial locations augmented with ground locations that were more than three days apart. dADK = adaptive kernel; MCP = minimum convex polygon. A (+) indicated the cyclic home range size was significantly larger than the annual home range size (P = 0.01) and a (–) indicated that there was no significant difference in cyclic and annual home range sizes (P > 0.1). bNumber

FIGURE 12-2. Home range size (mean and standard deviation based on the minimum convex polygon) for female pumas (n = 8) during three consecutive cub-rearing periods on the San Andres Mountains, New Mexico, 1986–1994. During the no-cub period, progeny were thirteen to eighteen months old; they typically became independent at the start of, or early in, this period. Females did not give birth to new litters during this period.

FIGURE 12-3. The home range (90 percent minimum convex polygon) of puma F15 during three consecutive cub-rearing periods, San Andres Mountains, New Me x i c o. F15 gave birth to a litter of three cubs on 17 May 1987 (star), and she bore her next litter 18.3 months later. F15’s cubs from her 1987 litter became independent at ten to fourteen months of age; consequently, she was solitary for at least four of the six months that comprised the “no-cub” period. Her home range sizes for the three consecutive periods were 17.5, 30.6, and 45.0 km2, respectively.

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range size generally increased as the age of her cubs increased and was largest during the period when she regained solitary status (Fig. 12-2)[3]. Puma F15’s behavior after the birth of her litter in May 1987 is a clear example (Fig. 12-3).

Lifetime Home Range Cumulative or “lifetime” home ranges were obtained for pumas monitored for continuous periods in excess of forty-eight months as resident adults. We chose forty-eight months because it represented such a substantial portion of an adult puma’s life. Based on the average age of death of thirty radio-collared adult pumas (nineteen males, eleven females) on the study area (see Chapter 8), a forty-eight-month period would typically comprise 73 percent or more of an adult male’s life and 100 percent of an adult female’s life. Lifetime home ranges were estimated for sixteen pumas (Table 12-2). Although each puma’s lifetime home range was larger than the average area it utilized over an annual period, the differences were less pronounced using the ADK versus MCP home range estimator [4]. Based on the 90 percent ADK method, ten males monitored for an average of 71.1 ± 18.2 months utilized areas that were 70 percent ± 42 percent larger than the average areas they occupied on an annual basis. The difference was not quite as large for females; the six females followed for periods averaging 63.8 ± 12.7 months used areas about 45 percent ± 23 percent larger than their average annual home ranges. However, some pumas used areas during individual annual periods that approached the size of their lifetime home range (this was not observed using the MCP estimator). For example, ten pumas used lifetime home ranges that were three to eight percent larger (n = three males, three females), or 1 to 14 percent smaller (n = two males, two females), than their largest annual home ranges (e.g., Plate 1). The average lifetime home range size for females (n = 6) was 22 percent the size of lifetime ranges used by males (n = 10).

What Factors Influence Adult Home Range Size? In the San Andres Mountains, there was wide variation in the size of the area a puma used from year to year (as indicated by the large standard deviations in Appendix 3). Annual variation in a puma’s range size was probably influenced by a number of factors, including (1) changes in energy demands, (2) changes in food availability, and (3) responses to the presence or absence of other pumas. The first factor pertains most to females. A positive relationship between the size of a female’s range (or at least her mobility) and the age of her cubs has been observed in other puma populations, notably Alberta (Ross and Jalkotzy 1992) and Utah (Hemker et al. 1984). This behavior has been linked both to increasing energy demands (Ackerman 1982) and to the improved traveling capabili-

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Table 12-2. Cumulative home ranges for ten adult male and six adult female pumas that were radio-monitored for forty-eight consecutive months or longer on the San Andres Mountains, New Mexico. Home range estimator (km2) Adaptive kernel Minimum convex polygon Puma Months no. monitored Males 1 48 3 101 5 86 7 57 18 50 19 55 36 86 38 85 46 69 52 74 x– 71.1 SD 18.2 VS ANNUALb Females 15 28 41 45 47 54 x– SD

63 50 62 81 76 51 63.8 12.7

VS ANNUALb

No. locationsa

90%

60%

100%

90%

169 400 304 215 181 190 286 314 269 253 258.1 72.0

279.7 317.5 227.3 353.2 677.4 274.8 559.2 451.5 444.4 132.8 371.8 163.1 1.7x

99.4 122.0 60.9 129.7 192.7 106.3 185.8 189.7 167.5 48.9 130.3 52.6 1.6x

364.3 459.2 341.4 452.8 772.5 382.2 1077.0 815.4 575.8 195.3 543.6 268.2 2.5x

220.2 300.4 192.7 228.8 487.7 205.4 526.0 398.3 366.1 117.5 346.0 210.9 2.2x

229 192 247 301 307 197 245.5 49.7

76.5 127.0 84.6 58.6 44.2 105.2 82.7 30.2

29.2 69.2 40.0 16.2 12.8 29.8 32.9 20.4

119.2 209.4 125.5 87.3 93.6 182.4 136.2 49.2

67.2 108.3 70.1 54.6 51.0 82.4 72.3 21.0

1.5x

1.7x

2.4x

1.9x

aIncluded

are locations from all flights as well as any ground locations that were obtained more than three days from any other location. bAverage lifetime home range size relative to mean annual home range size.

ties of older cubs. Even during the “no-cub” phase, the size of the female’s range may be influenced by her offspring, since many cubs actually become independent during the early part of this period. However, it is also possible that the female is utilizing a larger area in an attempt to distance herself from newly inde-

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pendent cubs and to locate prospective mates. The influences of the second and third factors (food availability and other pumas) on an individual’s annual home range size are examined later in this chapter. In the course of an adult puma’s life, it may traverse a much larger area than it will cover over any particular annual period. We believe this occurs for two main reasons. First, home range size increases with an increasing number of locations, even though we tried to minimize this effect on our study animals. For example, F47’s cumulative home range size based on the 90 percent adaptive kernel estimator and 307 locations (about fifty-one locations per year) was 44.2 km2 (Plate 1). If we included all radio locations that were at least one day apart (n = 462 locations or about 77 per year), F47’s cumulative home range was 12 percent larger, or 49.3 km2. However, an individual’s lifetime home range size was nearly equivalent to, or smaller than, its largest annual home range size for ten out of sixteen pumas. As we will show when we examine fidelity, some of the increases in home range size probably resulted from a second cause: home range expansions or shifts over time. We also noted wide within-gender differences in annual home range size . Although the majority of adult males (n = 14) used average annual home ranges of 150–250 km2, the rest used larger (n = 4) or smaller (n = 6) ranges. Si m i l a r l y, most females (n = 16) used average annual ranges of 50–100 km2, but the rest used ranges that we re larger (n = 5) or smaller (n = 9). These diff e rences in range size we re undoubtedly amplified by variations in habitat quality throughout the mountain range. The southern third and north-central p o rtions of the study area contained re l a t i vely contiguous segments of ru g g e d terrain and abundant mountain shrub and piñon-juniper cover. As a consequence, we believe it provided better stalking cover and supported more deer. Conversely, the central portion of the range (Hembrillo and Su l p h u r Canyons) appeared to be drier and contain more desert shrub cover (i.e., poorer-quality deer habitat). Our observations, though not quantitative, supp o rted this notion; we saw fewer deer and less deer sign in these areas. The n o rth end of the study area had mountainous patches fragmented by intervening desert flats that also provided less cover and seemed to support fewe r deer. Pumas use features of the habitat selectively (Logan and Irwin 1985, Belden et al. 1988, Laing and Lindzey 1991), and specific habitat features confer advantages to pumas in hunting prey (Logan 1983). Consequently, larger home ranges probably are essential in areas with poor or fragmented habitat patches. We documented our largest home ranges (M18, M20, M151, M161, F147, F160; see Appendix 3) in the central (poor) and northern (fragmented) portions of the study area, as well as in the Malpais (a rugged lava flow east of the study area with extremely poor deer habitat). Si m i l a r l y, in

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female tigers (Smith et al. 1987) and leopards (Bailey 1993), large variation in home range size is believed to be associated with habitat quality, part i c u l a r l y as it is influenced by prey abundance. Although habitat variability may partly explain variations in range size of same-sex individuals, what accounts for the notable differences in home range size between the two sexes? Studies across the West have consistently reported larger home ranges for male pumas (Table 12-3). Within the same population, male home ranges generally average 1.5 to 5 times the size of female ranges. The same trend is found for other large, sexually dimorphic felids, including the leopard (Bailey 1993; Stander et al. 1997), jaguar (Schaller and Crawshaw 1980), and tiger (Schaller 1972, Sunquist 1981). In carnivores, there is a strong linear relationship between home range size and body mass, indicating individuals use areas that satisfy their metabolic demands (Gittleman and Harvey 1982, Lindstedt et al. 1986). Consequently, larger-bodied or pack-forming animals should have greater metabolic needs, and should generally require larger areas, than smaller-bodied or solitary animals. But in sexually dimorphic felids, larger males do not necessarily have greater metabolic needs than smaller females (Ackerman et al. 1986, Sandell 1989). Ackerman (1982) found that puma mothers with two or three yearling cubs needed to procure 12 kg of food per day, whereas a solitary male needed only 4 kg. Considering energetics alone, females with offspring should have larger home ranges than males. Why then are male ranges so much larger? Home range size differences are probably related to disparate strategies to maximize reproductive success. Trivers (1972) was the first to suggest that female behavior should be directed toward raising young successfully, while male behavior should be directed toward mate acquisition. Because only female pumas rear young, they must singly acquire critical resources such as food, cover, and security for cubs. Unencumbered male pumas are free to seek out breeding opportunities. In species that occur in low densities, have no set breeding season, and are well dispersed over the landscape (all of which apply to pumas), males must traverse large areas to increase their chances of finding mates. Hence, the home range of a male in a polygynous mating system should be larger than that required to meet energetic demands (Sandell 1989, Lott 1991, Frank and Heske 1992, Minta 1993). For example, male badgers increase home range size during the breeding season but reduce it to meet energetic demands during the non-breeding season (Goodrich and Buskirk 1998). Since pumas breed year-round, male puma home range size should remain large. Although many studies have used radiotelemetry to produce home range estimates on pumas, differences in the methods used to analyze home range data (Hopkins et al. 1986, Neal et al. 1987), as well as sample size and duration of

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observation, make comparisons difficult. Puma home range sizes reported in the literature vary widely. Some of the largest home ranges have been reported in Utah; in this extremely low-density puma population, annual home range size exceeded 800 km2 for one male and averaged over 600 km2 for four females (Hemker et al. 1984). In contrast, and based on the same method of estimating home range (100 percent MCP), some of the pumas on the San Andres Mountains used some of the smallest documented home ranges. Three adult males and two adult females in our puma population utilized areas under 80 km2 and 20 km2, respectively, during annual periods. O verall, puma home ranges in the San Andres Mountains we re intermediate to small in size compared to those re c o rded elsewhere in North America (Table 12-3) and we re most similar to those re p o rted for the Diablo Range in California (Hopkins 1989) and the Guadalupe Mountains in New Mexico (Smith et al. 1986). Two environmental factors probably had an influence on the smaller range size. First, in all three areas, the major prey source did not migrate. Annual home ranges that must encompass different summering and wintering areas should typically be much larger. For example, annual home range size for four females that followed migrating prey in Idaho averaged 268 km2 (100 percent MCP; Seidensticker et al. 1973), which was almost four times the size of the annual female range size in the San Andres Mountains. Second, the San Andres Mountains are a long, narrow band of puma habitat (where stalking, nursery and resting cove r, and adequate numbers of a large prey species are available) surrounded on two sides by wide, re l a t i vely inhospitable desert basins. It is possible that the isolated nature of the mountain range forced individuals to use smaller areas in an effort to both utilize the best habitat and avoid one another. Only when habitat conditions became poor (during the drought and subsequent deer decline in 1993 and 1994) did a few pumas (generally males in the Re f e rence Area) extend their movements fart h e r into the adjacent desert flats (see Fig. 4-1).

Home Range Size, Prey Abundance, and Puma Density Assuming that male and female pumas employ different strategies to achieve reproductive success, we should see different behavioral responses by each sex to changes in prey abundance. Because a female puma’s reproductive success is dependent on her ability to secure adequate food for her young, her home range size is expected to be directly affected by the density, dispersion, richness, and vulnerability of prey (Seidensticker et al. 1973, Macdonald 1983, Sandell 1989). The relationship of male home range size to food abundance should not be as clear-cut, because although a male must obtain adequate food resources for sur-

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vival, his level of reproductive success is dependent on securing matings. Consequently, we hypothesized that in the San Andres Mountains, female home range size would be inversely related to prey abundance, whereas there would be no clear relationship between male home range size and prey abundance.

Does Prey Abundance Affect Home Range Size? Correlations between prey abundance (generally density or biomass measures) and home range size have been found in some felids, including bobcats (Litvaitis et al. 1986), Canadian lynx (Ward and Krebs 1985) and African lions (Van Orsdol et al. 1985). Unfortunately, the difficulty of obtaining detailed information on both variables simultaneously has precluded such an analysis in pumas. However, a strong negative relationship between population density and female home range size has been observed across species of solitary carnivores, indicating a relationship between both of these parameters and food abundance (Sandell 1989). Since a few studies can provide reliable estimates of both puma home range size and puma density, we tried a two-level approach to examining puma home range size and prey abundance. First, within the San Andres Mountains, we compared puma home range size to relative deer abundance based on the mule deer population model we developed (see Chapter 17). The model indicated relatively low deer abundance during 1987, 1993, and 1994, and high deer abundance during 1990 and 1991; thus, we compared puma home range sizes between these two sets of years. This approach had limitations because we could only estimate the relative abundance of deer on the study area; we could not determine deer densities within individual puma ranges. We also looked for a relationship between puma home range size and puma density across populations in western North America. There was no relationship between the home range size of pumas (male or female) and relative deer abundance in the Treatment or Reference areas of our study population (Table 12-4)[5]. Our home range estimates each year often included different sets of individuals (i.e., some pumas died, new individuals were caught, and radio collars on others failed), which may have contributed to the lack of a relationship. Still, we obtained home range estimates on the same six individuals during at least four of the five years, and they did not show any consistent changes relative to deer abundance. For example, M38 used home ranges of 199 and 296 km2 in 1990 and 1991 (years of high deer abundance), and 168 and 264 km2 during 1993 and 1994 (years of low deer abundance), Similarly, F47 used home ranges of 44.8 and 24.4 km2 in 1990 and 1991, and 16.8 and 42.8 km2 in 1993 and 1994. She was also raising cubs during each of those years. Obviously, prey abundance did not explain the variation we observed in home range size. It is likely other factors, especially changes in deer

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Table 12-4. Annual home range sizea (mean ± SD) for adult pumas during years of relatively low and high deer densities, San Andres Mountains, New Mexico. Sex

Low deer densityb n HR size (km2)

Sex

High deer densityb n HR size (km2)

M F

10 10

Treatment Area 140.8 ± 51.3 M 56.0 ± 29.0 F

5 8

136.4 ± 42.4c 69.0 ± 29.0

M F

15 13

Reference Area 236.4 ± 86.6 M 52.6 ± 27.3 F

10 13

197.4 ± 87.6 68.6 ± 36.1

aHome

range (HR) size based on 90 percent adaptive kernel method. deer densities occurred during 1987, 1993, and 1994. High deer densities occurred during 1990 and 1991. Mean home range sizes of pumas for each of these years are reported in Table 12-5. cWe only estimated home range size for one male (M3) in the Treatment Area in 1991. Because his home range in 1991 was strongly affected by the removal of all other males, we did not include it in the overall average. bLow

distribution, negated any relationship that might occur between prey abundance and puma range size. For example, if deer concentrate around critical water sources during drought, a female puma’s home range size might shrink, even though overall deer density has declined. It is possible this occurred with F21. In 1993 (drought year) her home range size was 58 percent the size it was in 1991 (non-drought year). But during 1993, 63 percent of her locations occurred within 1 km of active springs, whereas only 36 percent of her locations were that close to water sources in 1991. An apparent lag in the pumas’ response to changes in prey abundance also undermined the relationship. Puma densities in the San Andres Mountains continued to increase during 1993 and 1994, even as drought took hold and prey abundance declined (see Chapter 17). This is contrary to the expectation of a positive correlation between these two variables (Sandell 1989). Such a positive relationship has been demonstrated in the ecologically similar African leopard (Stander et al. 1997). We suspect it might take a severe reduction in overall prey abundance to trigger a notable increase in the average home range size of pumas. When we plotted home range size on density for five North American puma

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FIGURE 12-4. Adult puma home range size correlated with adult puma density in five study areas (Alberta, British Columbia, Idaho, New Mexico, and Utah) in North America. Winter home range sizes are used in Idaho and Utah because that was when the best density estimates were obtained.

populations with the most reliable estimates of both variables—Alberta, British Columbia, Idaho, New Mexico, and Utah (Ross and Jalkotzy 1992, Spreadbury et al. 1996, Seidensticker et al. 1973, our study, Hemker et al. 1984, respectively)—we found no relationship between puma home range size and puma density (Fig. 12-4)[6]. Home range sizes were notably larger only at the lowest reported densities (the Utah data point). In a similar analysis of leopard populations from ten different regions in sub-Saharan Africa, Stander et al. (1997) found home ranges were notably larger only at very low leopard densities and rainfall; there was no linear relationship between the parameters. Unfortunately in our analysis on puma, the minimal numbers of data points and the tendency to average density and home range estimates across years (during which time prey abundance may fluctuate) may obscure any relationship.

Does Puma Density Affect Home Range Size? Our analysis of puma densities and range sizes across populations suggests that puma home ranges become notably larger only when puma densities (and thus apparently prey densities) are very low. But what if we examine this relationship within a single puma population? Although a negative relationship between puma home range size and its population density may imply a negative relationship between range size and prey abundance, it may also connote a response by one puma to the presence or absence of another. We examined this possibility in a two-step manner. First, we looked for correlations between mean home

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Table 12-5. Mean annual home range size (90 percent adaptive kernel) and density for adult male and female pumas on the San Andres Mountains, New Mexico, 1988–1994.

Year

n

Males Home range Density 2 a (km ) (no./100 km2)b

n

1987 1988 1989 1990 1991 1992 1993 1994

3 3 4 5 1 4 3 4

184.4 ± 59.8 189.4 ± 36.8 150.1 ± 65.6 136.4 ± 42.4 295.8 170.1 ± 29.6 138.1 ± 9.9 110.1 ± 47.7

Treatment Areac 2 0.73 1 0.70 4 0.79 5 0.38 3 0.52 4 0.63 4 0.69 4

1988 1989 1990 1991 1992 1993 1994

2 7 6 4 6 7 6

312.2 ± 71.6 164.2 ± 50.5 217.8 ± 87.6 167.0 ± 28.4 194.0 ± 91.7 229.6 ± 90.9 219.0 ± 85.5

Reference Areac 1 0.53 5 0.56 7 0.62 6 0.65 11 0.68 7 0.67 5

Females Home range Density 2 a (km ) (no./100 km2)b 81.4 ± 60.4 127.1 93.4 ± 64.0 70.4 ± 24.3 66.5 ± 41.8 50.6 ± 23.2 46.4 ± 25.0 53.0 ± 11.0

0.63 1.06 1.22 0.71 0.99 1.23 1.18

41.2 61.0 ± 11.3 51.8 ± 26.2 88.2 ± 38.1 57.8 ± 19.6 51.6 ± 30.6 56.3 ± 27.8

0.60 0.77 0.83 0.98 1.08 1.12

aMean

± SD. from Table 10-5. cExcludes any individual whose home range was not at least 60 percent within the designated area. bObtained

range size (male and female) and adult puma density (male, female, and total) in the study area each year. Second, we plotted average puma range sizes, puma densities, and deer population trends in the study area each year. We examined the Treatment Area over a seven-year period (1988–1994) and the Reference Area over six years (1989–1994). Each year one to five males (x– = 3.4 ± 1.3) and one to five females (x– = 3.6 ± 1.3) provided the home range estimates used to examine the relationship of home range size to density in the Treatment Area. Another three to seven males (x– = 5.8 ± 1.5) and five to eleven females (x– = 7.0 ± 2.1) provided the home range data for the Reference Area (Table 12-5). We used puma densities reported in Table 10-5 and deer population trends from

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Chapter 17 (Fig. 17-6, Table 17-7) in the comparisons. Based on population modeling, the mule deer population was increasing during most of the study but then declined sharply in 1993 and 1994, even as puma numbers remained high. FEMALE RESPONSE TO CHANGES IN PUMA DENSITY

We found negative relationships between female home range size and female density in both the Treatment and the Reference Areas, albeit these relationships were not significant [7]. A weak, negative correlation also occurred between female home range size and male density in the Reference Area, but this characteristic was reversed in the Treatment Area. The consistent negative relationships between female range size and density suggested, unlike our initial analysis, that overall prey abundance might have had some effect on female range size. However, it could not tell us whether or not intraspecific interactions could have had a compounding influence. For example, if female pumas compete most with other females, it is plausible they may try to avoid one another by reducing their respective range sizes. This way, they will not compete for the same prey, spoil one another’s hunt, or subject their cubs to undue risk. Accommodation of related females would also increase inclusive fitness if food were abundant and risks of dispersal were high. Chapters 9 and 13 describe at least eight matrilines that formed on the study area. Similarly, reductions in female densities may result in increasing home range sizes as the potential for encounters decreases. Consequently, we might conclude that a negative relationship between female density and home range size is the result of intrasexual interactions as well as changes in prey abundance. How can we separate these two effects? If females try to accommodate and avoid one another by reducing range size, we would expect female ranges to be smaller when both prey densities and puma densities are high than when prey densities are high and puma densities are low. By removing pumas during a period of high prey abundance, we could look for this relationship. Additionally, if prey densities declined without a corresponding increase in female range size, we could suspect that females were exhibiting a degree of avoidance. After the removal of 71 percent of the adult males and 60 percent of the adult females from the Treatment Area during December 1990 through June 1991, only three of the original females and one of the original males remained exclusively in the Treatment Area. Home range sizes of the remaining females actually declined slightly during the year of removal (Fig. 12-5). During that same period, deer densities continued to increase. Hence, the removal of competitors did not cause female home range expansions; in fact, the increasing deer densities may have allowed females to use even smaller areas. It is likely that appreciable increases in home range size did not occur at low female densities

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because females already had access to adequate resources to raise their young. Any increase in home range size would only increase the potential for unwanted intraspecific encounters with unfamiliar females and males (prediction 5 of the two-strategies hypothesis). However, once puma densities were high, a drop in prey densities (beginning in 1992–1993) did not produce an immediate increase in female range size. At this point, females may have been responding more to the presence of other pumas (i.e., trying to avoid them) than to the declining density of prey. Consequently, females may have been at risk of using too small of an area to supply the minimum amount of food and cover necessary to successfully raise young. An alternate hypothesis (as discussed earlier) is that deer distributions became more clumped in vulnerable areas (e.g., at springs) as the

FIGURE 12-5. Changes in annual home range size (90 percent adaptive kernel) and density of adult pumas in the Treatment Area, San Andres Mountains, New Mexico. Superimposed is the mule deer population trend over biological years, based on model 2 in Chapter 17 (gray line with open boxes, scale not given). The decline in puma density in 1991 corresponds to the removal of thirteen independent pumas.

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drought took hold. Females could use similar-sized areas and still obtain adequate food, at least to a point. Once overall prey densities declined far enough, these clumps would not be sufficient. We may have been seeing this response in 1994; female puma densities were starting to taper off (Reference Area) or decline (Treatment Area), and female home range sizes were starting to increase. All the information suggests that female pumas were influenced more by prey abundance and distribution than the numbers of other females. This supports the two-strategies hypothesis. However, the relationship was not a direct one, because the deer decline did not generate an immediate and opposite response from the pumas. Additionally, avoidance of other females by reducing home range size may not be feasible if prey resources are clumped. Instead, females may use shared areas at different times. This will be addressed in Chapter 14. MALE RESPONSE TO CHANGES IN PUMA DENSITY

Analyses of how male home range size related to puma density produced conflicting results. The only significant relationships were found in the Treatment Area, where male home range size was inversely related to both female and total density. A weak, negative relationship was also found between male home range size and male density [8]. No strong correlations were found in the undisturbed Reference Area, but the pattern of correlation was reversed from what we found in the Treatment Area. Male home range size increased with increasing puma density (male, female, and total) [8]. Although a male puma also requires food for survival, his reproductive success is ultimately determined by the availability of estrus females and the number of other males with whom he competes. Consequently, we might expect changes in male range size to better reflect responses to changes in numbers of other pumas than prey abundance. If so, which affects males more, the number of mates or the number of competitors? To try to determine this, we developed three alternative hypotheses where male home range size is influenced most by (1) deer density, (2) female mates, or (3) male competitors. If the first hypothesis is correct, then male range size should decrease with increasing deer density, even if concurrently the number of mates and competitors is decreasing. Similarly, male range size should increase with declining deer density, even in the face of a growing puma population (and the increasing number of mates and competitors it implies). In hypotheses 2 and 3, deer densities should be secondary. In hypothesis 2, a male’s range size should decrease with increasing densities of females, more so than with increasing densities of males, whereas in hypothesis 3, his range size should decrease with increasing densities of males, more so than with increasing densities of females. In the Treatment Area, one male (M3) had a profound effect on the result-

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ing negative correlations between home range size and density (Fig. 12-5). After the experimental removal from December 1990 through June 1991, only M3 remained exclusively in the Treatment Area. When all male competitors as well as most potential mates were removed, M3 greatly expanded his home range (Fig. 12-6). In the three years prior to puma removal, M3’s annual home range size contracted from 227 km2 to 141 km2, a reduction of about 22 percent per year. During this same time interval, both puma and mule deer densities were increasing, suggesting either could have influenced his home range size (Fig. 125). Then in 1991, the year we removed pumas, M3’s annual home range size ballooned by 110 percent, to 296 km2. That same year the deer population continued its increase (contrary to hypothesis 1). M3 also mated successfully with two of the remaining females (both familiar to him) and associated with two other females with whom he had no prior contact. This was his best breeding

FPO @ 80%

FIGURE 12-6. Puma M3’s annual home range (90 percent adaptive kernel), 1988–1990 (a), and 1991–1993 (b), in the Treatment Area, San Andres Mountains, New Mexico. M3’s home range declined in size each year until 1991. We removed all of his male neighbors (n = 5, black dots) as well as eight independent females from the Treatment Area from De c e m b e r 1990 through June 1991. That year M3’s range expanded by 110 percent, and he courted four females (white dots); two produced his cubs, and the other two we re translocated in June, after they we re caught courting with him. M3’s home range declined in size and shifted north during the following two years. One of his neighbors (M88) returned to his former home range south of M3 in July 1991, possibly encouraging M3’s nort h w a rd shift.

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success in the eight years for which we had annual home range data. As pumas repopulated the Treatment Area in the following years, M3’s home range contracted again. In 1993, when M3 was twelve years of age, his home range size was almost identical to what it was the year prior to puma removal (146 km2). That same year female density had rebounded to a level equivalent to that found prior to puma removal (1.23 per 100 km2 in 1993, 1.22 in 1990), but deer density was declining (Fig. 12-5). If food supply was of primary importance to M3, his range size should have decreased during times of plenty and increased as the deer population entered its decline. Instead, M3 responded most to the presence and absence of other pumas. Because we reduced the density of male and female pumas at the same time, we could not determine which sex had the most influence on M3’s home range size. M3’s mating behavior and the strength of the correlations [8] suggest that M3 was most affected by the density of females (i.e., potential mates); however, his best breeding success occurred when he had the least male competition. These results support the two-strategies hypothesis. We suspect a negative association was not found between male home range size and density in the Reference Area because interactions were more complex than in the Treatment Area. There were more male pumas in the Reference Area, and each male had to respond to the behaviors of all of his neighbors. As we will see when we examine fidelity, males may exhibit shifts in their home ranges in response to other males. Such shifts may result in a larger annual home range size because the annual home range includes areas used before and after the shift. For example, average male home range size in the Reference Area (n = 6) increased from 164 to 238 km2 between 1989 and 1990. During that same period, male density also increased from 0.53 to 0.56 males per 100 km2. As we will later illustrate, two of the males with the largest home ranges in 1990 (M38, M46) exhibited home range shifts that year. Excluding these males, average male home range size for 1990 is 159 km2, slightly lower than the mean home range size for 1989. If males are shifting in response to increasing puma densities, then a positive correlation between home range size and density may occur.

Does Home Range Size Reflect an Attempt at Population Self-Limitation? If pumas are self-limited, as Seidensticker et al. (1973) hypothesized, we would expect both males and females within the puma population to stabilize at a density well below a limit set by the prey population. Under these circumstances, all puma home ranges should become occupied and no longer constrict to accommodate more pumas. If prey densities subsequently decline, pumas should respond in kind; otherwise, their high densities and attendant predation will further push the prey population downward. In the Treatment Area, the absence and subsequent reappearance of com-

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petitors may have first freed M3 to claim vacant areas, then forced him to relinquish them. Consequently, adjacent males may have restricted M3’s movements, which suggests that the presence of adult male pumas does influence adult male density. However, M3 also appeared to expand and contract his sphere of influence in direct response to availability of potential mates. These combined behaviors suggest males were attempting to maximize breeding opportunities. Thus, we concluded that males were simply attempting to maximize individual reproductive success, not seeking to protect the food supply from being overutilized. The absence of any clear response by females to the removal of other pumas, as well as the tendency for pumas to accommodate more individuals even as the prey density declined, also indicated that the pumas in our study population were not limiting themselves below the level set by the prey as Seidensticker et al. (1973) reported for pumas in Idaho. It is important to emphasize that many of the relationships we found between puma home range size and adult density were weak, probably because of the dynamic nature of the society (e.g., each individual is responding to arrivals, deaths, and breeding condition of its immediate neighbors). We clarify some of these dynamics as we examine home range fidelity later in this chapter and puma interactions in Chapter 14. Additionally, habitat quality, prey density, and prey distribution among individual home ranges vary and were not measured in our study. These variables undoubtedly affect home range size. Prey distribution was found to be an important factor determining the spatial distribution of pumas in the Sierra Nevada in California (Pierce et al. 2000b).

Adult Home Range Fidelity Fidelity is the degree to which an individual uses the same area from one time interval to the next. It is an important way of gauging how adult pumas may be affected by a changing environment, changing physiological needs (as with females raising cubs), or other pumas. We hypothesized that female pumas would exhibit strong home range fidelity because the main prey, mule deer, did not migrate, and familiarity with an area should enhance cub survival. Fidelity would remain high unless shifting resulted in increased inclusive fitness (i.e., more young are produced by that individual female or her close kin). Abandonment should occur only under the most severe conditions. In contrast, we hypothesized that male pumas would exhibit greater variability in fidelity because the resource they seek (receptive females) is widely dispersed in space and time. Home range shifts, or even roaming behavior, should result as a consequence of poor mating probabilities within the home range or increased competition for mates. We assessed fidelity over annual and six-month intervals as well as during the

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different phases of a female’s reproductive cycle. We did not examine fidelity on a seasonal basis because the puma’s major prey was nonmigratory (Sweanor 1990) and pumas do not have a specific breeding season (see Chapter 7). Fidelity was determined using two methods. In method 1, we calculated a fidelity index (FI) for each adult puma during pairs of years (one, two, and three years apart) where annual home range estimates (90 percent ADK and 90 percent MCP) were obtained. We modified the simple ratio of Ginsberg and Young (1992) for quantifying association patterns: FIx = n1 + n2 / N1 + N2 ¥ 100 where x is the time span between pairs of years, n1 and n2 are the number of locations recorded within the overlap zone of the two years in question, and N1 and N2 are the total number of locations recorded within each annual home range (Fig. 12-7). For individual pumas with greater than one FI1, FI2, or FI3 (i.e., pumas monitored for more than two, three, or four consecutive years), we treated each FI value as an independent measure of fidelity. The indices were grouped based on sex and length of time between pairings. We assumed a puma made a home range shift if the overlap zone for the pairing was less than 40 percent. We plotted sex-specific frequency distributions of FIx and then tested for

FIGURE 12-7. A simplified example of a fidelity index (FI). The polygons and dots represent a hypothetical puma’s home range and locations over consecutive annual periods. In this example, FI = 13 / 21 x 100 = 62 percent.

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normality in each of the distributions. We also tested for differences between the distributions of FIx for male and female pumas. In method 2, we used the location data to calculate the mean x and y UTM coordinates for an individual during specific time intervals and then measured the distances moved between successive mean locations. This method eliminated the biases associated with home range estimators (White and Garrott 1990). First we examined changes in mean locations between consecutive years. If, from one year to the next, an individual moved a distance greater than one standard deviation above the mean distance moved by members of the same sex, we calculated the distance moved between mean x and y coordinates during successive six-month intervals. This helped to pinpoint the time of a suspected home range shift. We also calculated distances between mean locations for the phases of a female’s reproductive cycle. The cycle was divided into four consecutive periods when the female was: (1) raising cubs from birth to six months of age; (2) raising cubs seven to thirteen months of age (which included cubs to the average age of independence or to known independence; (3) without cubs; and (4) raising her subsequent litter of young (birth to six months) cubs. These periods were not identical to ones used to calculate home range size because we did not have the sample size constraint inherent to using home range estimators. For example, a female that was without cubs (period 3) for less than six months would have too few locations for adequate home range analysis but sufficient locations to generate an arithmetic center of home range use. Once a shift was detected, we looked for possible explanations for the shift.

Method 1—Fidelity Index We monitored seventeen adult male and twenty-one adult female pumas from two to seven years each and obtained eighty-seven measures of FI1, sixty-one measures of FI2, and twenty-nine measures of FI3. Similar patterns of fidelity were found using both the 90 percent ADK and the 90 percent MCP home range estimators, except that the 90 percent MCP produced slightly lower estimates of fidelity. For simplification, we re p o rt only results obtained using the 90 percent ADK. Distributions of FI2 and F I3 did not differ from normal for either males or females, nor did the distribution of FI1 for females [9]. Although the distribution of FI1 for males differed from normal [9], a visual exam of the frequency distribution did not indicate a bimodal distribution (Fig. 12-8). A bimodal distribution would suggest two distinct behaviors: high fidelity, and abandonment or strong home range shifting. Such dual behaviors have been documented in female martens (Phillips et al. 1998). When distributions of male and female pumas we re compared, FI1 distributions we re almost identical (Fig. 12-8)[10]. Both sexes showed high fidelity to their home ranges; F I1 for males (n = 48) and females (n = 39) averaged

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FPO @ 80%

FIGURE 12-8. Frequency distribution of the fidelity index (FI1) for adult male and female pumas, based on the 90 percent adaptive kernel home range estimator, San Andres Mountains, New Mexico, 1986–1994. Each 10 percent increment in fidelity corresponds to a range (e.g., 60 percent includes the range 60.0–69.9 percent).

75.1 ± 14.2 percent and 74.4 percent ± 16.6 percent, respectively (Fig. 12-9 and Fig. 12-10). However, as the length of time between annual home range estimates widened, fidelity declined (Fig. 12-9). For example, M36 slowly moved nort h w a rd over time. Although his consecutive annual home ranges overlapped, within four years he was utilizing an area completely outside his first estimated annual home range (Fig. 12-11). Although differences in male and female distributions for FI2 and F I3 were marginally nonsignificant [10], the decline in fidelity was more dramatic with males. Be t ween F I1 and FI3, fidelity declined, on average, by 32.0 percent in males and only 8.9 percent in females. There was also greater variability in the fidelity of males (Fig. 12-9). Home range shifting occurred three times in F I1 (4.2 percent of male F I, 2.6 percent of female FI; Fig. 12-12), nine times in FI2 (25.8 percent of male F I, 5.0 percent of female F I), and twenty times in FI3 (42.1 percent of male F I, 10 percent of female FI). There were three cases (9.7 percent) in FI2 and five cases (26.3 percent) in FI3 where males utilized areas that ove rlapped by less than 10 percent (Fig. 12-11).

Method 2—Distances between Mean Locations A total of eighty-nine (forty-nine male, forty female) distances between consecutive mean annual locations were calculated for thirty-six pumas (sixteen males, twenty females). Distances between mean annual locations averaged 5.3 ± 4.8 km for adult males and 2.6 ± 2.1 km for adult females. Males moved greater dis-

FIGURE 12-9. Fidelity index (mean and standard deviation) for adult pumas on the San Andres Mountains, New Mexico. Fidelity was estimated between annual home ranges (90 percent adaptive kernel) that were one, two, and three years apart. Sample sizes are indicated at the top of each line.

FIGURE 12-10. Examples of strong annual home range fidelity in adult pumas on the San Andres Mountains, New Mexico. Between consecutive years shown above, pumas M19 (a) and F45 (b) had fidelity indexes of 82 percent and 75 percent, respectively. Home ranges are depicted using the 90 percent adaptive kernel estimator. For simplicity, only four out of six of F45’s annual home ranges are shown. Grey dots indicate mean locations for each year.

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FPO @ 70%

FIGURE 12-11. Puma M36’s annual home ranges (90 percent adaptive kernel) during six of seven consecutive years, San Andres Mountains, New Mexico. M36’s fidelity indexes during pairs of years one, two, and three years apart averaged 71 percent, 51 percent, and 47 percent, respectively. However, his mean location each year (depicted sequentially) slowly moved northward, and after five years (1988 to 1993), his annual home ranges no longer shared common area.

tances than females [11]. Five males (10.2 percent) and two females (5.0 percent) moved distances greater than one standard deviation above the mean distance moved for their respective sex; four pumas (three males, one female) moved distances greater than two standard deviations above the mean. This analysis identified annual home range shifts for two of the same individuals that FI1 did (M18, F21; Fig. 12-12); however, it also indicated possible annual shifts in five pumas that were not identified in FI1 (M3, M7, M38, M53, F28), and it did not indicate shifting in one male that FI1 did (M46). This method also did not identify pumas that may have taken longer periods of time (two to three years) to make a home range shift.

Home Range Shifts in Pumas Based on the two fidelity indices, eight individuals (eight males, two females) made home range shifts within one annual period. For these individuals, we cal-

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FIGURE 12-12. Examples of home range (90 percent adaptive kernel) shifts exhibited by adult pumas over consecutive years, San Andres Mountains, New Mexico. Puma M18 (a) shifted south between 1987 and 1988 as indicated by a fidelity index (FI1) of 37 percent and a linear distance between home range centers (gray dots) of 23.3 km (greater than three standard deviations above the mean distance moved by all males). M18’s FI between 1987 and 1990 (FI3) was 0 percent. Puma F21 (b) shifted north between 1991 and 1992, then shifted back south between 1992 and 1993. Her FI1 for those years were 41.2 and 22.1 percent; corresponding distances between home range centers were 9.9 and 10.0 km (greater than four standard deviations above the mean distance moved by all females).

culated distances moved between mean locations over consecutive six-month intervals. Of the six males, four shifted one time and two shifted twice. One of the two females shifted three times, while the other shifted only once. MALE SHIFTING BEHAVIOR

The six males shifted during specific six-month periods when immigrant adult males arrived within or adjacent to their home ranges (M7, M18, M38, M46, M53), when the only resident female within the male’s territory died (M53) and/or when neighboring adult males died or were experimentally removed (M3, M46). Five males shifted away from new male arrivals, suggesting that new individuals can usurp space from established residents. For example, M7’s home

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range center from January to June 1990 was in San Andres Canyon. In October 1990, new immigrant M114 was captured about 1 km north of this location, and he spent the next 2.5 months in close proximity to San Andres Canyon. M7’s apparent response was to shift 13.3 km south during the period July–December 1990. Similarly, M161 arrived within M53’s home range in May 1990 and began establishing his own home range. During the following six-month period (June to December 1990), M53 shifted 14.7 km north and spent the majority of his time north of the study area boundary. M53’s shift may also have been precipitated by the lack of females within his home range. F27, the only known female to reside within the north end of the study area in 1990, died in April of that year. Consequently, M53 may have been searching for other potential mates. M18 showed a substantial southward shift (11.9 km) during the six-month period (January to June 1988) after two new males (M36, M38) arrived in the northern part of his home range. He made an even larger southward shift during the next six-month interval (24.8 km), possibly in continued response to those new males. Likewise, M192 arrived within the southern end of M46’s home range in April 1993 and may have induced M46 to shift 14.6 km north during June–December 1993. M46 was able to shift into an area that had become vacant after M29’s disease-related death in May 1993. M38 shifted 17.1 km north after the arrival of M173 in midsummer 1992. Four males (M18, M36, M173, M192), which were captured or recaptured during or soon after the times of documented shifts, bore recent scratches and bite wounds that we believe were inflicted as males sorted out dominance relationships through fighting. As we indicated earlier in this chapter, M3 shifted in response to the re m oval of neighboring residents in the Treatment Area (Fig 12-6). He shifted 11.7 km to the north during the six-month interval (June to December 1991) after all of his male neighbors we re re m oved, and he began frequenting areas formerly used by four of those neighbors. Initially, this may have been an expansion of his home range rather than a true shift, because he continued to visit the southern portions of his home range and to breed with the females that resided there. When M88, M3’s southern neighbor, returned to his former home range at the end of July 1991 (166 days after being translocated to n o rthern New Mexico), M3 may have continued to shift due to his presence. The two males apparently fought in October 1991 at which time M3 bit into, and destroyed, the radio transmitter on M88’s collar. We do not know what injuries M3 sustained, but in a later recapture his head, neck, and forearms we re grizzled with white flecking, an indication that teeth and claws had found their mark. From January to June 1992, M3’s home range center shifted another 8.5 km north. Although his new home range center was less than 10.1

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km north of his prior center (less than 1 S D + mean distance moved), M3 was only located two times within M88’s 1992 home range (90 percent ADK). Two other home range shifts probably occurred, but we could not accurately measure them. M1, who lived at the south end of the study area, apparently made a shift after the arrival of new immigrant male M22 inside his home range (Plate 2). Because M1 began using an area south of the study area boundary, where air space and ground access were restricted by White Sands Missile Range, we could not adequately monitor his movements. M22 was later killed by his northern neighbor, M3, during a time when M3 and F47 were in a suspected breeding association. M1 returned north to his former haunts within one month of M22’s death. The other suspected shift was by M46; he apparently made a southward shift after a fight with resident M19 along a shared home range boundary in July 1991. Unfortunately, his collar was ripped off in the fight and we could not obtain the necessary relocations over the subsequent six months to measure the shift. However, during the year after his recapture in 1992, he used an area 14.5 km to the south of the area he had used during the two years prior to the fight (see Chapter 14). We found when short-term home range shifts occurred, they were associated with the arrival of new immigrant males, the removal of other resident males (either through death or translocation), or the reduction in available mates within a male’s home range. Male home range shifts after the death or removal of an adjacent male resident have been reported in other puma studies (Seidensticker et al. 1973, Hopkins 1989, Maehr et al. 1991), as well as in lynx (Schmidt et al. 1997), bobcats (Anderson 1988) and leopards (Bailey 1993). In Florida, a male panther’s northward shift may have been influenced by the presence of a new male within the southern end of his range as well as the presence of two adult females within the northern half of his range (Maehr et al. 1991). We suspect more gradual shifts have similar causes, except that possible disputes between male neighbors may take longer to settle (also see Chapter 14). Multiple responses to various stimuli (e.g., new immigrants, deaths of residents, and estrus females) may complicate and slow the shifting process. It is important to note that we were looking for significant shifts in home range use; such measurements do not reflect subtle responses between individuals or the fact that some individuals do not shift for the simple reason that they are killed by other males. For example, M3 did not shift to accommodate less-tenured resident M22 along his southern border; instead, M3 killed M22. New immigrants M19 (see Sweanor 1990) and M219 both usurped area from resident males they killed. Almost all adult males exhibited scars from fighting at one time or another during the course of the study, evidence that they occasionally tested one another and directly competed for space and mates.

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FEMALE SHIFTING BEHAVIOR

Only two females showed strong shifting tendencies between consecutive annual periods. F28’s home range center shifted 7.3 km north between the first and second six-month periods of 1991, coinciding with the independence of her cubs. She successfully bred in January 1992 at a location 8.2 km north of what was her home range center during the first half of 1991. We did not document the arrival of any new females to the south of F28 during the period she shifted. However, we do know her mother, F6, whose range overlapped the south end of F28’s, produced a new litter of cubs in November 1991. The other female, F21, made shifts over three consecutive six-month intervals. In 1992, as her cubs aged from two to fourteen months, F21 made two northward shifts in her home range center totaling 12.1 km. These shifts coincided with the arrival of an unrelated female (F103, daughter of F87), who, in September 1992, produced her first litter within the boundaries of F21’s 1991 home range. In January 1993, F21 left her cubs at the northern extreme of her home range, where her daughter from a previous litter was just beginning to take up residency. Afterward, F21 shifted 11.8 km back south, where she shared the western flank of her range with F103 and successfully bred with the resident male. This prompts the question, do females usually shift their home range as their reproductive status changes? We radio-tracked ten females over fourteen cycles as they raised young cubs (period 1) and older cubs (period 2), regained solitary status (period 3), and then produced new litters (period 4). We found that, overall, females did not show any greater shifting tendencies in their mean locations based on their reproductive status [12]. Distances between mean locations averaged 2.6, 2.8, and 1.9 km between periods 1 and 2, periods 2 and 3, and periods 3 and 4, respectively. We documented five apparent shifts (i.e., distance moved was greater than the mean + 1 SD for the period) out of forty-two distance measures (11.9 percent). Two shifts were by F21, discussed above. F37 also shifted twice. First she shifted south at the time her cubs became independent, similar to the behaviors of F21 and F28. As she raised older cubs from her next litter, she shifted back north. This shift coincided with the time that her daughter, F44, established an independent home range and produced her first litter within the southern end of F37’s home range. The only other shift was by F107. She shifted 8.7 km north between the time M88 killed and ate her twomonth-old cubs in December 1993 and the time she produced her next litter in May 1994, which M88 sired (Plate 3). An adult female moved, on average, 3.7 ± 2.8 km between mean locations from the time she was raising one young litter of cubs (period 1) to the time she was raising her consecutive young litter (period 4) (Table 12-6). This distance was greater than the distances moved over shorter intervals (i.e., periods 1–2,

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Table 12-6. Distance between a female puma’s mean locations (n = 10 females over 14 birth intervals) during consecutive six-month periods as she raised young cubs (period 1), older cubs (period 2), regained solitary status (period 3), and raised her subsequent litter of young cubs (period 4), San Andres Mountains, New Mexico. Distance between mean locations (km) Female Period 1 to Period 2 Period 2 to Period 3 Period 3 to Period 4 Period 1 to Period 4 15 0.4 21 10.2 37 1.5 37 6.0 41 2.3 41 1.3 47 0.8 47 3.2 65 1.9 91 2.7 54 1.5 54 0.6 103 1.9 107 1.4 Mean ± SD 2.6 ± 2.6

2.3 10.1 7.5 1.4 2.2 2.1 0.1 3.0 5.3 0.5 2.0 1.1 1.5 0.4 2.8 ± 2.9

1.6 3.8 0.5 1.9 1.8 0.8 1.3 1.7 1.6 0.8 0.4 0.2 1.7 8.7 1.9 ± 2.2

3.5 4.8 8.8 2.8 2.9 1.7 2.0 2.0 3.1 2.9 3.7 0.6 1.8 10.4 3.7 ± 2.8

2–3, and 3–4) [13] and indicated some females may not raise small cubs from consecutive litters in the same localities. However, we documented two cases in which females gave birth to consecutive litters at the same nursery. Additionally, the few females we could follow continuously over long periods generally did not shift in one direction over time but instead returned to places they had previously occupied (see Fig. 12-12). On the San Andres Mountains, where prey did not migrate, female home range shifts appeared to benefit fitness. Reproductive success may be enhanced through avoidance of other females; for example, a shift may result when a female with vulnerable young accommodates an unrelated female (e.g., F21’s shifting behavior after the arrival of F103). Shifts can also increase inclusive fitness when resources are abundant, dispersal risks are relatively high, and the individuals that are accommodated are close relatives (e.g., F37 accommodating daughter F44, the matrilineal structure described in Chapter 7). Similarly, Hopkins (1989) speculated that maternal partitioning may have caused a shift in one

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of his resident female pumas in a coastal range of California. Such motherdaughter behavior also has been documented in tigers (Sunquist 1981, Smith et al. 1987). A female puma may also shift away from conditions that produced poor reproductive success. We suspect F107 shifted because her young cubs (father unknown) were cannibalized by resident male M88 three days after he was in a fight with a relatively new immigrant, M193. The heightened state of aggression probably exhibited by the two males during this period, and more importantly the loss of her litter, probably prompted F107 to move (Plate 3). She successfully produced her subsequent litter (fathered by M88) within an area located deeper within M88’s home range. Since she did not return to her former home range after her cubs were born, this could be considered home range abandonment. Although other studies have documented shifts of adjacent resident females into vacated areas (Maehr et al. 1991, Laing and Lindzey 1993, Spreadbury et al. 1996, Maehr 1997b), complete abandonment of an established home range is apparently quite rare. We could only find two probable cases in the literature: an adult female in British Columbia abandoned her home range and moved about 15 km south to an area within prime elk winter range that was vacated by another female (Spreadbury 1989), and an adult female in Florida moved to an adjacent but vacated home range created by the removal of a nonreproductive female (Maehr 1997b). A female may also shift away from maturing offspring, possibly to force independence (e.g., F21, F28, F37 in our study; Beier 1995). SHIFTS IN RELATION TO A CHANGING FOOD BASE

Although a declining food resource may eventually stimulate home range shifts or possibly abandonment as pumas seek more productive habitats, we did not observe any significant shifts that could be attributed to changes in food abundance. Only two home range shifts (M46, F21) occurred during the years of dramatic deer declines, and both could be attributed to intraspecific interactions. Even during the last full year of the study, both male and female pumas showed strong fidelity. For females, the deer decline apparently was not severe enough or did not occur over a long-enough period of time to force abandonment. Males with access to mates apparently had no reason to abandon an established territory.

Homing by Translocated Pumas Perhaps the most dramatic exhibitions of home range fidelity were displayed by pumas we translocated from the Treatment Area to northern New Mexico (Ruth et al. 1998). Eight of fourteen pumas (57 percent) exhibited homing behavior after translocation, and two (M49, M88) actually returned to their original

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home ranges. Of the translocated pumas, the ones that exhibited the greatest movements and homing tendencies after release had been prime, reproducing residents on the San Andres Mountains. The considerable value of the home range is indicated by the attempts of these residents to return to it. Familiarity with resources (including mates), dominance status over neighboring pumas, and the ability to protect dependent progeny from those neighbors may all be factors that drive a puma to return home. The two returning males had been adult residents on the study area for one to three years prior to being translocated 465–490 km to northern New Mexico. M88 and M49 took 166 and 469 days, respectively, to make the return trip to their former ranges. Although M88 maintained his home range through the end of the study and successfully bred at least six times with three different females (once before translocation and five times after returning), M49 was not as fortunate. Within two weeks of his return, M49 made a 45-km northward movement outside his former home range and died. M49’s home range abandonment and death coincide with an association he had with M3, who had claimed most of M49’s home range after his long absence. It is possible M3 inflicted mortal injuries, but, because M49’s carcass was badly decomposed, we could not determine cause of death. M88 may have been more successful at reclaiming his former range because he was not absent for as long a period as M49. Consequently, he was probably not as physically stressed, and it is possible his male neighbor still recognized his dominance.

Benefits of Fidelity and the Two-Strategies Hypothesis Prior to the New Mexico research, only limited analyses of home range fidelity in pumas had been conducted. Seidensticker et al. (1973:17) stated that it was “clear that resident adults reused definite areas, although there were seasonal patterns, changes over time, and individual variations.” Strong fidelity by adults would be expected under the land tenure system described for central Idaho pumas. Other biologists who examined fidelity did so to determine whether pumas shift seasonally in response to migrations of prey. Seidensticker et al. (1973) found that pumas left winter home ranges to follow prey to summer ranges and then returned to the same winter home ranges the following year. In a more-detailed analysis of pumas in southwest Colorado, Anderson et al. (1992) found that directional shifts in a puma’s center of activity from one season to the next mimicked the directional movements of migrating mule deer and elk. Pierce et al. (1999) found two patterns for pumas and prey that migrated in California’s Sierra Nevada. Some pumas slowly moved with prey but did not utilize distinct winter and summer home ranges; others showed distinct seasonal shifts. Two females that made seasonal shifts exhibited strong fidelity:

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over a combined total of twelve seasons, summer and winter home range overlaps averaged 63.4 percent and 86.4 percent, respectively. Directional home range shifts of African leopards have also been attributed to seasonal (wet and dry) density, distribution, and behavior of impala (Bailey 1993). Puma studies in areas where ungulate prey were generally nonmigratory (Hopkins 1989, Ross and Jalkotzy 1992, Maehr 1997b, our research), found no such seasonal shifts. Resident adult Florida panthers appeared to exhibit home range stability, with the exception of shifts owing to panther deaths; however, fidelity was not quantified (Maehr et al. 1989, Maehr 1997b). Pumas in California (Hopkins 1989) maintained relatively stable home ranges; out of thirteen distance measurements between consecutive annual harmonic mean centers (three distances for two males, ten distances for five females), there were only two apparent shifts (33 percent of male, 10 percent of female measurements). The amount of annual home range shifting in the San Andres Mountains (with a larger sample size of eighty-nine distance measurements between mean annual locations) was even lower (10.2 percent of male, 5.0 percent of female measurements). Most adult female pumas show strong site fidelity over long periods. The a rea used by a resident adult female was apt not to change much, even after three years. Female tigers also exhibited strong site fidelity (Sunquist 1981, Smith et al. 1987). The long-term stability of female home ranges is adaptive , since familiarity with the home range is advantageous in the exploitation of food re s o u rces, especially for females raising cubs. Females also become more knowledgeable about the best nursery sites and possibly escape routes, which can be important when facing aggre s s i ve male pumas and other predators. In addition, fidelity results in increased recognition between the female and local resident males. These males are probably less apt to harm females or their cubs than new immigrants (see Chapter 8), and they may deter potentially dangerous males from settling in the area. All these reasons should enhance fitness, and they explain why the translocated female pumas showed such strong homing tendencies. Most adult male pumas also showed strong home range fidelity, at least between consecutive years. Fidelity must provide advantages, considering the arduous journeys undertaken by M88 and M49 to return to their former home ranges after translocation. Long-term fidelity should enhance the male’s recognition of potential mates and paternity. It also provides opportunities for resident males to become familiar with one another and thus establish clear dominant-subordinate rolls. This may reduce the number of potentially debilitating fights between neighbors as well as enable the resident to quickly identify and challenge new immigrants (who could potentially harm the re s i-

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dent male’s current mates or offspring). Conve r s e l y, roaming behavior subjects males to more potential fights with unknown males, does not ensure paternity, and puts both females and progeny at greater risk. Although there was a g reater decline in male fidelity over time (in our sample, 42 percent of males and 10 percent of females made home range shifts between annual periods that we re three years apart), such slow shifts would allow most females time to raise a given male’s litter before his area of influence shifted completely outside her home range.

Fidelity in Desert Pumas and the Self-Limiting Hypothesis Some of our observations on puma home range fidelity and shifting behavior do not support the self-limiting hypothesis. First, a new immigrant male sometimes contested an established male’s prior rights to an area, forcing the resident to yield by shifting his home range. Second, resident females sometimes shifted to accommodate other female pumas, including daughters and new immigrants. These shifts facilitated an overall increase in the puma population over time, even as the deer population declined precipitously. Consequently, the behaviors we observed did not ensure that the puma population would keep its numbers below the levels set by the prey.

LP > >

KX

1. We radio-monitored eighty-six adult pumas on the San Andres Mountains for an average of 28.8 months (range = 0–102) each, and obtained an average of 137 locations (range = 1–569) on each individual. 2. Adult pumas did not exhibit seasonal movements, probably because their prey did not migrate and winter movements were not restricted by deep snows. 3. The annual home ranges of adult male pumas ranged from 59.3 to 639.6 km2. Annual home range size for twenty-four males averaged 193.4 km2, or about 2.8 times the size of the average adult female’s home range. This supports prediction 1 of the two-strategies hypothesis. Within their ranges, males moved about 4.1 km (linear distance) each day. 4. Adult female pumas used annual home ranges of 13.1–287.4 km2. Annual home range size for thirty females averaged 69.9 km2. Females tended to move shorter distances (1.4 km) each day than males. 5. Females used home ranges over annual periods similar in size to those used during entire birth intervals. However, females’ home ranges enlarged with the increasing age and mobility of their cubs and were largest during the periods when they were without cubs. 6. An adult male’s lifetime home range was about 70 percent larger than his

226

7. 8.

9.

10.

11.

12.

PART III. PUMA BEHAVIOR AND SOCIAL ORGANIZATION

average annual home range. Females also used larger areas over their lifetimes than those they used over annual periods, but the increase was not as large (45 percent) as for males. The larger lifetime ranges were attributed, in part, to individuals making home range shifts. Habitat quality, sex, reproductive status, and responses to other pumas influenced home range sizes of adult pumas. Although there was no direct relationship between puma (male or female) home range size and deer density, a weak negative relationship between female density and female home range size suggested that females used smaller areas when prey was more abundant. The relationship was probably clouded by uneven distributions in the deer population, especially as the drought took hold and deer began to concentrate around limited water sources. Home ranges of remaining adult female pumas did not expand in response to the removal of six female competitors and five potential mates from the Treatment Area. Expansions were apparently unnecessary because the females were obtaining all of the necessary resources within their home ranges prior to competitor removal. They also did not have to search for mates because the remaining adult male located and mated with all estrus females. In the Treatment Area, adult male home range size was strongly and inversely affected by puma density. Behavior of the one remaining male before and after the removal of six potential mates and all male competitors indicated that he responded to the presence and absence of both male and female pumas but not to changing deer densities. Although the correlations suggest that the male was most affected by the density of his potential mates, his best breeding success occurred when he had the least male competition. This supports prediction 3 of the two-strategies hypothesis. Adult female pumas exhibited strong home range fidelity over long periods. Between consecutive years each female used ranges that overlapped by an average of 74.4 percent. Even after three years, the proportion of a female’s initial range that was still utilized averaged 65.5 percent. The distance between the arithmetic centers of a female’s consecutive annual home ranges averaged 2.6 km. This supports prediction 5 of the two-strategies hypothesis. Adult male pumas also exhibited strong home range fidelity between consecutive years ( x– = 75.1 percent); however, male home range fidelity declined more rapidly over time than did female fidelity. In the fourth year, males were still using, on average, only 43.1 percent of the same area utilized in the first year. The average distance between arithmetic centers of a

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male’s consecutive annual ranges was also greater than that found for females (5.3 km). 13. Females were less prone to make home range shifts than males. Identified causes of shifts included avoidance of neighboring females raising new litters, abandonment of cubs that had reached independence, accommodation of a philopatric daughter, and abandonment of an area where dependent progeny were cannibalized. 14. Males were more likely to exhibit home range shifts than females we re. Causes of shifts that occurred over short intervals (six months) included avoidance or re t reat from new immigrant males, a low density of available mates within the present home range, and the death or removal of a neighboring resident male. A few males also exhibited directional shifts over much longer periods. We suspect these shifts may have resulted from a combination of causes, including neighborly disputes that simply took longer to settle. 15. Fidelity was displayed by translocated pumas. Eight of fourteen exhibited homing behavior, and two adult males returned to their original home ranges. One of these males maintained this same home range for the next three years (through the end of the study).

LN N5LN5)L 1. Annual home range sizes (90 percent and 60 percent ADK, 100 percent and 90 percent MCP) of adult males (n = 71 estimates for twenty-four males) and adult females (n = 72 estimates for thirty females) were different. Mann-Whitney U tests, Z 9.36, P < 0.001, all tests. 2. Annual and birth interval home range sizes (90 percent and 60 percent ADK, 100 percent and 90 percent MCP) for the same females (n = 11 estimates for nine females) were only different based on the 100 percent MCP. Wilcoxon signed-rank tests, Z = 0.889, P = 0.374 for the 90 percent ADK; Z = –0.889, P = 0.374 for the 60 percent ADK; Z = –2.223, P = 0.026 for the 100 percent MCP; Z = –0.356, P = 0.722 for the 90 percent MCP. 3. A female’s home range sizes (100 percent and 90 percent MCP) during each of three consecutive six-month periods within a birth interval (n = seven females during eight birth intervals) were different. Kruskal-Wallis test, H = 13.934, 2 d.f., P < 0.001 for the 100 percent MCP; H = 13.139, d.f. = 2, P = 0.001 for the 90 percent MCP. For six other females during seven periods when they were raising small cubs and seven consecutive periods when they were raising large cubs, home range sizes were larger when they were raising large cubs. Wilcoxon signed-rank tests, Z = 3.30, P < 0.001 for both the 100 percent and the 90 percent MCP. 4. Mean annual and cumulative home range sizes for ten adult males moni-

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tored from 48 to 101 months ( x– = 71.1 ± 18.1 months) each, were different. Wilcoxon signed-rank test, Z = 3.92, P < 0.001, based on all home range estimators (90 percent and 60 percent ADK, 100 percent and 90 percent MCP). Mean annual and cumulative home range sizes for six adult females monitored from fifty to eighty-one months ( x– = 63.8 ± 12.7 months) each, were different. Wilcoxon signed-rank tests, Z = 3.06, P = 0.002, for all four home range estimators. Test for difference in puma home range size (90 percent ADK) during years of low deer abundance (n1) and years of high deer abundance (n2), using Mann-Whitney U tests. For Reference Area males, n1 = 15, n2 = 10, U = 96.0, P = 0.24; for Treatment Area males, n1 = 10, n2 = 4, U = 22.5, P = 0.77; for males in the Reference and Treatment Areas combined, n1 = 25, n2 = 14, U = 197.5, P = 0.43. For Reference Area females, n1 = 13, n2 = 13, U = 65.0, P = 0.32; for Treatment Area females, n1 = 10, n2 = 8, U = 29.0, P = 0.33; for Reference and Treatment Area females combined, n1 = 23, n2 = 21, U = 186.0, P = 0.19. Test for linear relationship between puma home range size (100 percent MCP) and puma density across populations of pumas. Linear regression of female home range size on female density, n = 5, female home range = 156.0612 – 38.7590 (female density), r2 = 0.09, P = 0.62. Linear regression of male home range size on male density, for n = 4, male home range = 493.2500 – 158.2692 (male density), r2 = 0.31, P = 0.45. Test for associations between adult female annual home range size (90 percent ADK) and year-round density of adult males, adult females, and total adults in the Reference Area (RA, 1989–1994) and Treatment Area (TA, 1988–1994). Spearman correlation coefficient (2-tailed test) for the RA: female range size and male density, rs = –0.543, P > 0.20; female range size and female density, rs = –0.429, P > 0.20; female range size and total density, rs = –0.429, P > 0.20. For the TA: female range size and male density, rs = 0.643, P = 0.125; female range size and female density, rs = –0.536, P = 0.2; female home range size and total density, rs = –0.214, P > 0.2. Comparisons using the 90 percent MCP resulted in slightly weaker but similar correlations in both the RA and the TA; they are not reported here. Test for associations between adult male annual home range size (90 percent ADK) and year-round density of adult males, adult females, and total adults in the Re f e rence Area (RA, 1989–1994) and Treatment Area (TA, 1988–1994). Spearman correlation coefficient (2-tailed test) for the RA: male range size and male density, rs = 0.429, P > 0.20; male range size and female density, rs = 0.371, P > 0.20; male range size and total density, rs =

CHAPTER 12. ADULT HOME RANGE CHARACTERISTICS

9.

10.

11.

12.

13.

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0.371, P > 0.20. For the TA: male range size and male density, rs = –0.429, P > 0.20; male range size and female density, rs = –0.821, P = 0.03; male range size and total density, rs = –0.964, P = 0.002. Comparisons using the 90 percent MCP resulted in slightly weaker but similar correlations in both the RA and the TA; they are not reported here. Lilliefors test (Lilliefors 1967) to determine if distributions of FI differed from normal. For males: FI1, D = 0.14, n = 48, P = 0.07; FI2, D = 0.12, n = 31, P = 0.27; FI3, D = 0.15, n = 19, P = 0.34. For females: FI1, D = 0.12, n = 39, P = 0.15; FI2, D = 0.17, n = 20, P = 0.15; FI3, D = 0.17, n = 10, P = 0.61. Test for differences between the distributions of FI for male and female pumas. Two-sample Kolmogorov-Smirnov test: for FI1, nmale = 48, nfemale = 39, D = 0.09, P = 0.98; for FI2, nmale = 31, nfemale = 20, D = 0.32, P = 0.11; for FI3, nmale = 19, nfemale = 10, D = 0.45, P = 0.13. Test for differences in distances moved between mean annual locations of males (n = 49 distance measures for 16 males, x– = 5.3 ± 4.8 km, range = 0.2–23.3 km) and females (n = 40 distance measures for 20 females, x– = 2.6 ± 2.1 km, range = 0.3–10.0 km). Mann-Whitney U test, U = 1435, P < 0.001. Test for differences in distances moved between mean locations by females during consecutive periods (1, 2, 3, and 4; see text) of their reproductive cycle. Distances between mean locations: period 1–2 = 2.56 ± 2.60 km; period 2–3 = 2.83 ± 2.90 km; period 3–4 = 1.90 ± 2.15 km, n = 14. Kruskal-Wallis test, H = 1.41, 2 d.f., P = 0.49. Test for differences in distances moved by females between mean locations over consecutive periods of their reproductive cycle (i.e., periods 1–2, 2–3, and 3–4) and distances moved between mean locations while raising young cubs of two consecutive litters (i.e., periods 1–4), n = 14. Mann-Whitney U test: for periods 1–2 and 1–4, U = 55.0, P = 0.048; for periods 2–3 and 1–4, U = 67.0, P = 0.15; for periods 3–4 and 1–4, U = 36.5, P = 0.005.

Chapter 13

Subadult Ranging Behavior

Subadults are important to the establishment, maintenance, and growth of puma populations as well as to the spread of genetic material between populations. Consequently, it is important to understand how they behave. In our analysis, we used the following definitions. Natal home range was the area occupied by a cub’s mother for the twelve-month period after the cub’s birth. Inde pendent home range was the area occupied by an independent progeny during the twelve-month period after site attachment. Site attachment was exhibited when a puma stopped making one-way directional movements and used a predictable area into adulthood. Subadult home range only included the area used by a puma after it showed site attachment and before it was classified as an adult; therefore, it was typically of shorter duration than the independent home range. A philopatric puma used an adult home range that overlapped its natal range by 5 percent or more, based on the 90 percent minimum convex polygon. A transient home range was an area that an animal used after leaving its natal range but later abandoned (Beier 1995). Duration of transient behavior was the time between independence and subsequent site attachment with no further dispersal. Subadult and transient home ranges generally spanned short periods and were represented by minimal numbers of radio locations; consequently, we only depicted them using the MCP home range estimator. To avoid confusion, all home range sizes in this chapter are based on the 90 percent MCP. We documented the fates of forty-three progeny after independence (twenty males, twenty-three females). Of these, thirteen remained philopatric into adulthood, twenty-seven dispersed, and three died within their natal home ranges shortly after independence. Obtaining detailed information on ranging behav231

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ior during the entire period a puma was a subadult was difficult because only fourteen pumas wore radio collars from the time they became independent until the time they either died as subadults (n = 5) or reached adulthood (n = 9). We learned about the fates of tagged (but not radio-collared) cubs either by recapturing them on the study area post-independence (n = 23) or from tag returns (n = 6). Tags were returned to us by the New Mexico Department of Game and Fish (from pumas killed by hunters), by depredation control officers, and by drivers involved in automobile-puma collisions.

Philopatry in Females All thirteen philopatric pumas were females, and ten of those were sister pairs. We radio-tracked three philopatric females from independence to adulthood: F183 was born on the Reference Area and became independent during the deer decline; siblings F107 and F109 became independent about three months after we stopped removing pumas from the Treatment Area and at the apex of the deer population. These three females became independent between 11.1 and 15.1 months of age and were classified as adults when eighteen to twenty-eight months old. Although they were philopatric, at least one of these females (F109) made a dispersal attempt. F109 dispersed 66 km north in a twenty-one-day period immediately after independence. However, she then spent the next twenty-eight days traveling back to her natal home range, where she remained into adulthood. F183 made one foray 12 km south of the southern border of her natal range when she was twenty-three months old, but she returned within seven days. It is possible both F109 and F183 were assessing the prospects of dispersal and philopatry, which suggests the behaviors are somewhat flexible and not completely innate. F107 did not show any dispersal behavior (see Plate 3). These three females occupied subadult home ranges for an average of 8.0 ± 4.0 months that encompassed areas averaging 35.6 ± 16.0 km2 (90 percent MCP). Their subadult home range sizes were similar to the average annual home range for adult females (44.6 ± 18.5 km2, see Appendix 3). F107 and F109 subsequently produced cubs in areas encompassed by their subadult home ranges. Although we do not know whether other philopatric females attempted subadult dispersal moves before they were recaptured and radio-collared as subadults or young adults, they subsequently exhibited strong natal range fidelity. The average distance between the arithmetic centers of a philopatric female’s natal range and independent home range was 3.2 km (see Table 9-1), similar to annual distances moved by resident adult females (see Chapter 12). Home range sizes of newly established adult females were also consistent with those of older adult females. Seven philopatric females radio-tracked during the

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twelve-month period immediately after adult onset had a mean home range size of 45.6 ± 15.4 km2, whereas the annual home range size of different females that were at least three years old (n = 55 annual measurements from twenty-seven females) averaged 42.9 ± 28.7 km2 [1]. Philopatry resulted in the formation of eight matrilines (see Chapter 7 and Plate 4). We documented as many as five related females (i.e., mothers, daughters, sisters) that inhabited abutting or overlapping home ranges in a given area of the mountain range at the same time (Plate 5).

Female Dispersal Some female progeny dispersed. In fact, of the females that survived to adult ages, we estimated 33 to 59 percent actually emigrated from the San Andres Mountains (see Chapter 9). Nine dispersing females traveled an average of 34.6 km from their natal ranges to their last locations or independent home ranges (see Table 9-1). Of those, three (F9, F10, F54) were radio-monitored during the entire period between independence and adult onset. F9 and F10 were born in the Treatment Area in 1986; F54 was born in the Reference Area in 1988. These females became independent between 9.8 and 14.3 months of age; the youngest, F10, was orphaned when her mother was killed by an immigrant male. F10 and F54 dispersed an average of 11 km within seven days of independence, then displayed site attachment to areas adjacent to their natal home ranges. F9 spent about twelve days in the vicinity of her natal range post-independence, then dispersed 81 km north in under forty-one days and began to show site attachment near the western boundary of the Reference Area. The distance between the centers of her natal and independent home ranges (78.5 km) was almost identical to the distance she traveled during her dispersal move, suggesting that she settled quickly. For the 6.5 ± 1.2 months that these three females showed site attachment as subadults, they used home ranges averaging 66.6 ± 43.1 km2 (range = 24.5–110.6 km), all within the limits of home range sizes found for adult females. All three females showed subsequent breeding activity (i.e., associations with resident males) within the areas encompassed by their subadult home ranges. Although F9 and F10 died before producing cubs, F54 bore three litters and was still alive at the end of the study. Four other natal dispersers provided information to suggest female dispersal was often of brief duration and ceased prior to adulthood. F160 was captured and radio-collared within her natal home range at about eighteen months of age, four months after her mother (F145) died. Genetic testing supported our contention that she was indeed F145’s daughter. Within five days of capture, F160 emigrated from the study area. Less than forty-six days later, she showed site

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Slide @171% PHOTO 23. Brian Spreadbury with four-month-old puma F54. As an adult, F54 established a home range adjacent to her mother and bore three litters.

attachment to an area 37 km to the east of her capture site. She became pregnant at the age of twenty-five months, 182 days after showing site attachment. Another female, F150, whom we suspect was also orphaned (her mother disappeared), began dispersing at nine months of age. She moved 27 km to the west edge of the San Andres Mountains within ten days, and then spent about twelve days at this western border before trekking 51 km across the Jornada del Muerto to the Caballo Mountains. Until she shed her radio collar 119 days later, F150 used a 57-km2 area (n = 13 locations) in the Caballo Mountains. Because of the short monitoring period, we cannot be sure whether this was a transient home range or she was showing site attachment. Two other tagged females (F28, F149) had completed dispersal moves of 17–20 km before they were recaptured and radio collared at 17.7 to 18.5 months of age. Both displayed strong site fidelity post-capture and produced their first litters when twenty-three to thirty-six months old. One female displayed dispersal behavior over a long period (Plate 6). F148 was captured and radio-collared near the study area’s southern border at eighteen months of age. We suspect she was born in the adjacent Organ Mountains.

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F148 used two overlapping transient home ranges during a 185-day period after capture. Five other adult female home ranges overlapped F148’s transient ranges; two gave birth to cubs during F148’s short tenure, and the litters of two others had recently become independent. F148 then dispersed 35 km north over ten days (and through the home ranges of two other adult females). In the following seven days she abandoned the San Andres Mountains and traveled 56 km southwest, across the desert flats to the Red House Mountains. After having exhibited transient behavior for 202 days, F148 finally showed site attachment. She established an independent home range of 108.6 km2 over the next year that included naturally fragmented puma habitat in the Red House and Caballo Mountains. Ten months after showing site attachment, and at the age of thirty months, F148 localized in a 1- to 2-km2 area for forty-two days. Her behavior suggested she had given birth to cubs. Duration of transient behavior in subadult females (n = 9: F9, F10, F54, F107, F109, F148, F150, F160, F183) was typically short, averaging 49 ± 79 days (range = 0–202). However, the average independent home range size of six progeny that remained within the study area (F9, F10, F54, F107, F109, F183) was much smaller (x– = 48.1 ± 31.2 km, range = 19.8–101.1) than the independent home range size of two females that emigrated (F148, F160; x– = 161.6 ± 75.0, range = 108.6–214.7). F160 established a home range in the confines of the Malpais, an expanse of sharp igneous rock and deep crevices formed by an ancient lava flow between the Oscura and Sacramento Mountains. F148’s home range encompassed mountainous habitat patches fragmented by desert basins. We had explored both areas and found them to be relatively prey-poor as compared to the San Andres Mountains. The rapidity with which most females established independent and adult home ranges on the study area, as well as the high degree of philopatry, suggested that females were quickly finding sufficient resources to survive and procreate and also that competition from other pumas was generally insufficient to deter settling. During the early stages of the study, when puma density was low and deer numbers were increasing, it was easy to understand how females could settle quickly. The behavior of F148 also suggests that it was becoming more difficult to settle as the area filled up with females and their young. However, we documented philopatry as late as August 1994, when two siblings (F181, F183) in the Reference Area were just reaching adulthood. F181 was illegally killed within her natal area in December 1994, but her sister remained philopatric through the end of the study. During this time, female puma density in the Reference Area was at its highest level and the deer population was well into its decline. So, why did F183 stay and F148 leave? Both dispersal and philopatry are

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adaptive strategies for female pumas. Philopatry may be a better strategy under some circumstances because it has the potential of increasing individual as well as inclusive fitness (see Chapter 7). F183 may have put herself at greater risk by dispersing through unfamiliar and potentially hostile country instead of staying in a food-poor environment. A dead subadult leaves no progeny. Her mother should also be willing to share resources with her daughter if her inclusive fitness increases. A similar benefit would not accrue to a female that shared minimal resources with an unrelated female such as F148 (who was not born on the study area). Although we did not document fighting between females, and we found no greater level of associations between independent females and their mothers as between unrelated females, some of the largest spatial overlaps of annual home ranges were between related females (see Chapter 14). Two sisters (F107, F109) remained philopatric and produced litters within one month of each other at nurseries that were less than 600 m apart. This suggests related females may be more tolerant of one another. The behavior of three pumas (F10, F150, F160) that dispersed even though their natal ranges were vacated by the deaths of their mothers indicates that philopatric and dispersal behaviors also have innate components. A more thorough discussion of why pumas disperse is presented later in this chapter.

Male Dispersal No males that survived to the average dispersal age of about fifteen months exhibited philopatry. Male progeny dispersed an average of 102.6 km (n = 18; see Table 9-1). We radio-tracked three progeny (M26, M82, M92) during the entire period from independence to adulthood. Both dispersal onset and dispersal duration were quite variable in these three males. M26 dispersed at fourteen months, immediately after independence. In contrast, M82 and M92, who became independent at twelve to sixteen months of age, remained within their natal areas 52 to 238 days before successfully dispersing. M26, M82, and M92 showed site attachment 145, 259, and 43 days, respectively, after initiating successful dispersal moves and emigrating from the study area. M26 and M92 were younger (18.8 and 19.2 months old, respectively) than M82 (28.7 months) when they began establishing independent home ranges. Distances between natal and independent home range centers averaged 167.2 ± 29.9 km (range = 134.2–192.5) for the three males. The use of transient home ranges also varied between males. M92 made one swift dispersal movement to the area where he established an independent home range northeast of the study area. In contrast, M26 and M82 each used one to three transient ranges prior to showing site attachment. At 15.6 months of age,

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M82 made a circuitous dispersal attempt south of his natal area that spanned twenty-eight days and covered 114 km. He started a second, successful dispersal move at 20.2 months of age. After dispersing 90 km to the south end of the study area over a thirty-eight-day period, M82 spent ninety-seven days in a 46km2 transient home range in the Organ Mountains. Further dispersal was impeded to the south by minimal mountainous terrain and the town of El Paso, whereas dispersal to the east and west entailed crossing wide desert basins. We were unable to radio-locate M82 for eighteen days; then, by expanding our flight search eastward, we found him in the Sacramento Mountains. He had dispersed 74 km across the stark expanse of the Tularosa Basin. During the subsequent 106 days, M82 traveled 73 km east-southeast through broken mountainous terrain, where he initiated site attachment in the Guadalupe Mountains (see Plate 7). M26 used three transient home ranges prior to showing site attachment. He spent forty-nine days in the Organ Mountains (immediately adjacent to his natal area), fourteen days in the Doña Ana Mountains, and twenty-seven days in the Caballo Mountains during his 145-day dispersal move to the Black Range. All three transient ranges were in mountainous patches surrounded by flat desert basins. M26 may have abandoned his transient range in the Doña Ana Mountains because of its size (about 25 km2), which was considerably smaller than the home ranges of resident males on the San Andres Mountains. Our cursory survey also indicated a sparse prey base, an absence of resident pumas, and considerable recreational use by people from Las Cruces. Although the Caballo Mountains (his third transient range), encompassed about 200 km2 of mountainous habitat, M26 was only located there three times as he moved north, then west to the Black Range (Sweanor et al. 2000, Fig. 3). M82 and M26 both used transient home ranges when they reached mountainous patches surrounded by flat desert basins, suggesting that either the males examined the sites, found them unsuitable, and continued their dispersal moves, or the desert basins imposed temporary dispersal barriers. Evidence also suggests resident males may encourage continued dispersal. We suspect M26 was persuaded to leave his first transient range in the Organ Mountains by M1, a resident that used an area overlapping M26’s natal range. For three days the two males confronted each other in a jumble of boulders on Antelope Hill, where the mountains terminate and the Tularosa Basin begins. On the fourth day, M26 evaded M1 and dispersed west to the Doña Ana Mountains. The seriousness of the encounter can be conveyed by recounting the fate of a less-fortunate subadult six months previously. M1 pursued subadult M300 for about 2 km along the southern flank of Black Mountain. In an attempt to escape, M300 bounded up a power pole and was promptly electrocuted. Another subadult, M221, who was born outside the study area, used a small

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transient range of about 10 km2 for two months after his capture. Within three days of being located near resident M124 and a fresh deer kill, he made a 14 km northward movement. Over the next seven days, M221 traveled another 40 km further north. Detailed information from M92, as well as less-complete data from two other male progeny (M23, M122), indicated that subadult males could disperse long distances and begin showing site attachment over a short time period. M23 became independent and dispersed between the ages of 10.8 and 14.4 months. After his recapture at 14.4 months and a dispersal move of 73 km, he showed site attachment. He utilized a 115-km2 subadult home range until we classified him as an adult at twenty-two months of age. Less than a month later, we translocated him. A second male, M122, dispersed at 14.5 months, seven days after independence. In twenty-six days, M122 dispersed 118 km northeast across the Tularosa Basin and onto the Capitan Mountains. Over the next fiftysix days and until he was killed by another male puma, he used a 22-km2 area (n = 6 locations), indicating he was either using a transient home range or showing site attachment. The duration of transient behavior in four males (M23, M26, M82, M92) averaged 211 ± 192 days (range = 95–497). Males took longer than females to settle because they typically dispersed longer distances and probably had to locate an area where they were competitive with other males for breeding females. The competition in particular would require that subadult males grow in mass and experience (see Chapter 8), which would also take time. The independent home range size of three males (M26, M82, M92) that emigrated from the study area averaged 490.7 ± 217.5 km2 (range 356.5–741.7). This was much larger than the 115-km2 area used by M23, a non-emigrating male, over the 8.5 months he was monitored after site attachment. The behavior of two other male progeny (M73, M124) also suggested that dispersers remaining within the study area had smaller home ranges than newly established emigrants. M73 and M124 were recaptured and radio-collared on the study area at an average age of 28.2 ± 1.1 months, and they had already completed dispersal moves of 47.0–69.9 km. During the year following recapture, they used home ranges of 61.3 and 129.5 km2, which were within the limits found for adult males on the study area (see Appendix 3). We suspect the larger areas used by emigrant males were most likely caused by the presence of fewer competitors or mates, or fights that resulted in home range shifts. The behavior we observed in resident M3 after our experimental removal in the Treatment Area indicates that a reduced density of pumas (males and/or females) can cause the expansion of a male’s home range. In Utah, the extremely large home range size of the male puma, and the corresponding density that was one of the low-

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est reported for pumas (Hemker et al. 1984), also suggest low densities may cause (or allow) males to use large areas. We also documented several cases in which fights resulted in large home range shifts. The behavior of M82, the only emigrant we followed for two full years after site attachment, suggests that his large home range may have been the result of a fight and subsequent shift into better habitat (i.e., more mates). M82 showed site attachment for about four months; then, over the next seven months, his home range center (mean x and y coordinates) shifted 13.3 km to the east. During the year after that, his home range center shifted only 3.9 km (less than the average distance between consecutive annual home range centers of resident males on our study area; see “Adult Home Range Fidelity” in Chapter 12) and his range size shrank from 356.5 to 96.6 km2 (Plate 7).

Frustrated Dispersal Male philopatry appears to be exceptional in pumas. It has only been documented in Florida, where extensive agricultural and urban development isolated the panther population. Philopatry was essentially forced because panthers could no longer freely disperse north out of southern Florida. All male subadult panthers attempted to disperse, but most (53 percent) were killed by other males. Although some of the subadult males temporarily resided in poor-quality habitat apparently devoid of adult females, survivors eventually returned to the vicinity of their natal areas (Maehr 1997a). Similarly, dispersal of male pumas born in the Santa Ana Mountains of Southern California has been frustrated by a burgeoning human population along the periphery of those mountains (Beier 1995). All eight male progeny studied there attempted dispersal. Male dispersers moved rapidly between one and four small, elongate, transient home ranges along the wildland–urban interface. One male returned to establish a transient range abutting his natal range, and two others returned to their natal ranges for seven and ten days, then departed without returning. Although Beier suggested that these behaviors were probably due to attempts by dispersers to avoid conflict with territorial adult males, we believe that they may also have been influenced by urban barriers to dispersal. We also documented the use of transient home ranges, but they always occurred along the mountain–desert basin interface and were used prior to dispersal movements to mountainous patches on the other side of the basin. If the Santa Ana Mountains were not surrounded by urbanization, we think the males would have dispersed farther than they did, and probably most of them would have emigrated from the entire mountain range toward more distant puma habitats before attempting to establish home ranges. Only two of the males (25 per-

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cent) survived to adulthood and established home ranges 56 to 75 km from their natal areas. One was along the eastern edge of the Santa Ana Mountains study area; the other was mostly on the northern end of these mountains but included the small Chino Hills to the north (Beier and Barrett 1993). Both the San Andres (2,059 km2) and Santa Ana Mountains (2,070 km2) study areas were of similar size; correspondingly, the six males that remained within the San Andres Mountains into adulthood dispersed distances similar (x– = 66 ± 15 km) to those of the two California males. However, seven other male progeny from the San Andres Mountains dispersed an average of 159.5 ± 53.5 km to areas outside the San Andres Mountains. In contrast to Southern California, human development surrounding our study area posed few artificial barriers to dispersal (Sweanor et al. 2000). It took the two surviving California males an average of 434 days to establish stable home ranges, whereas the average transient phase for four male progeny born on the San Andres Mountains was 211 days. This suggests males from the San Andres Mountains could cover more distance and consequently find suitable habitat more quickly. In Beier’s study, dispersal of the only radio-collared female probably was also thwarted by the extensive human development. She covered 342 km or more and changed directions at least five times upon encountering urban areas. Four months after initiating dispersal, she returned to her natal area. She bedded near her mother, then died near that location five days later from undetermined causes (Beier 1995).

Why Do Pumas Disperse? Theoretically, the ultimate adaptive significance of dispersal in pumas is to increase individual reproductive success (Morris 1982). There are three leading hypotheses on proximate causes of dispersal in large mammals: (1) competition for mates, (2) competition for resources, and (3) avoidance of inbreeding (Sinclair 1992). We address each of these in turn as they pertain to pumas. If competition for mates influences dispersal, then it is theorized that subordinate individuals of the sex in which competition is most intense should disperse (Dobson 1982). In naturally functioning puma populations, adult males vigorously compete for a limited number of estrus females, whereas there are ample mates available for females (see Chapter 7). Subadult males also tend to disperse greater distances than females, and only females commonly exhibit philopatry; consequently, mate competition appears to be a probable explanation for male, but not female, dispersal. It seems beneficial for male progeny to disperse away from areas that are dominated by their fathers. The cost of staying in the natal area can be extreme, since sons, who may be indistinguishable

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from other male competitors, can be killed by fathers. We documented just such a fight between M88 and his subadult son M108. Although dispersing subadults risk being killed by unrelated males encountered during dispersal moves (e.g., the deaths of subadult males M140 and M122), it is probably most adaptive for them to continue dispersing until they are physiologically competitive (i.e., larger, more experienced, and sexually mature). The possibility of altercations with larger, dominant adult males could be strong motivations to keep moving. Settlement might be triggered by finding suitable mates in an area with relatively little competition from other males, and the onset of puberty. This all supports the competition for mates hypothesis; however, other findings do not. Males should disperse only as far as necessary to avoid competition and find suitable mates. Since new males were continually coming into our population and establishing residency, there were apparently adequate resources and tolerable competition. Consequently, most of the male recruits in our growing population should have been progeny born on the San Andres Mountains. They were not. Also, once males established their adult home ranges, direct competition did not trigger the kind of long-distance dispersal exhibited by subadult males. Instead, the loser of a conflict, if he survived, tended to shift his home range just far enough to avoid the victor (see Chapters 12 and 14). Competition for food does not adequately explain dispersal in males either. Most male progeny were not just dispersing beyond their natal areas to the nearest vacant territory but were emigrating entirely from the growing puma population on the San Andres Mountains. We know there was adequate space and food for male progeny, particularly when the deer population was growing, because male immigrants were recruited into the population. If dispersing males were striving to reduce competition for food with their own mother and philopatric sisters, which would enhance inclusive fitness, we would expect males to exhibit a pattern of dispersing just beyond the ranges of related females. Hence, males would reside adjacent to close relatives. But so far, there is little or no evidence for this in puma populations unbound by human development. Even so, males would have to compete with other nonrelated pumas. There must be some other explanation compelling them to engage in long-distance moves with the relatively high risk of mortality. Unless the fitness of dispersing males is benefited directly by some other means, we would expect the dispersal trait to be selected against. On the other hand, competition for resources may adequately explain dispersal in some female pro g e n y, particularly if other females are philopatric and cause a rapid increase in the local density of adult females (see Chapter 10). Re p ro d u c t i ve success of some females could be enhanced if they left their natal areas and dispersed just far enough to find suitable habitat with

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reduced competition. This may explain the shorter dispersal distances for females re l a t i ve to males, and the tendency for some females to disperse just b e yond the natal area. Re s o u rce competition may also explain why some females disperse long distances (i.e., for females). They may have to keep m oving until they find an area with adequate habitat and where competition is tolerable. Clearly, dispersal behavior in female pumas is more flexible than that exhibited by males. Dual behaviors (i.e., philopatry and dispersal) have been documented in female puma siblings in Alberta (Ross and Jalkotzy 1992). Although we could only assume that sisters of some philopatric females dispersed (because we never recaptured them as adults), we observed where female cubs from different litters but the same mother (n = 2) showed alternate behaviors. The tactic adopted is probably influenced by local environmental conditions. Female dispersal may be due to resource competition with a partial density-dependent effect. Considering that dispersing females probably have lower survival rates (see Chapter 8) and lower reproductive success (see Chapter 7), we would expect females to become philopatric or settle adjacent to their natal area if there was an adequate food supply. But as competition for food intensifies, and especially when food is limited, dispersal costs may be less than the costs of philopatry. Hence, dispersal could become a more successful tactic. Some threshold of competition may have to be perceived by individual female progeny to trigger dispersal. The payoff could come later if the female were able to settle in a more favorable environment for rearing cubs. Competition with other carnivores may similarly affect dispersal in subadult female pumas. A puma’s reproductive success may be higher in areas with reduced interspecific competition. This relationship may be manifested on ranges where pumas and wolves are sympatric; wolves have been known to usurp puma prey kills and to aggressively pursue and even kill pumas (White and Boyd 1989, Boyd and Neale 1992, T. K. Ruth, personal communication). It is possible that female dispersal is socially mediated in some way. For example, dominant female progeny may tend to be philopatric while subordinate female siblings tend to disperse. Because of the near-impossibility of observing behavior among family members, there are no empirical data to support this notion. Whatever the cause, female dispersal would have the added benefit of expanding puma populations, particularly with obligatory male dispersal. Puma natural history has provided ample opportunities for such expansions (see Chapter 2). Climatic changes during interglacial periods certainly created more habitat in North America. Moreover, drying of the isthmus linking North and South America opened an entire continent to puma colonization. If Culver’s (1999) scenario about a late Pleistocene extinction of puma in North America is cor-

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rect, then population expansion into the continent may have occurred more than once. Much more recently, beginning about the mid-1960s, pumas apparently recolonized historical habitats in western North America following protective legislation that ended the era of indiscriminate killing that extirpated local puma populations. Avoidance of inbreeding seems to be the best explanation for dispersal in male pumas. If female matrilines are naturally characteristic of puma populations as we believe they are, then opportunities for inbreeding would abound for philopatric males. They could breed with their mother, sisters, daughters, and granddaughters. Breeding with close relatives can reduce reproduction and survival of offspring in two ways: (1) by increasing homozygosity in individuals, which can result in the expression of deleterious, recessive alleles, and (2) by hastening the loss of heterosis—the superiority of a heterozygote over either homozygote for a specific trait (Pusey and Wolf 1996). Ultimately, fitness of animals is reduced. This condition, called inbreeding depression, has repeatedly been shown to be a cost of inbreeding in animals and can increase extinction risk (Jiménez et al. 1994, Saccheri et al. 1998, DeRose and Roff 1999). The Florida panther—with its reduced genetic variation, its males having an extremely high rate of cryptorchidism and poor seminal characteristics, and high rate of heart defects—may be the living expression of inbreeding depression in pumas (O’Brien et al. 1990, Barone et al. 1994, Roelke et al. 1993b, Hedrick 1995). Culver et al. (2000) considered the Florida panther to be a “highly inbred” species because it had eight fixed microsatellite loci out of ten used to study genetic variation in the puma across its entire Western Hemisphere range. Similarly, two other small, isolated, inbred populations of big cats—African lions in Tanzania’s Ngorongoro Crater (about 75 to 125 animals) and Asiatic lions in India’s Gir Forest (about 250 animals)—have reduced genetic variation, high rates of sperm abnormalities, and reduced circulating testosterone, all of which are traits that could reduce fitness (Packer et al. 1991, O’Brien et al. 1987, Wildt et al. 1987). We believe the long-distance dispersal of male pumas is an adaptive strategy to avoid inbreeding because the male moves away from his mother and philopatric sisters, and usually well beyond his dispersing sisters. Reciprocal effects are just as vital; this dispersal pattern promotes outbreeding, particularly when immigrants from other subpopulations and environments are recruited into local breeding populations. This avoids inbreeding depression and can enhance viability of offspring by increasing their genetic variability (Shields 1987). Fitness benefits from inbreeding avoidance and outbreeding may have been so powerful as to fix dispersal as a trait in male pumas. Of course, dispersal in males, just as in females, would have the added benefit of population expansion.

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Transient Behavior in Pumas Transient is synonymous with wanderer, nomad, floater, and roamer. It implies that the individual travels widely and has no stable home. The term fits subadult pumas that are dispersing from natal ranges in search of a permanent place to live. Transient behavior has been documented in some adult felids, including cheetahs and African lions. Male cheetahs that traveled widely, rarely marked in conspicuous places, and only spent short periods in any given area before moving on were considered nonterritorial or floaters, by Caro (1994). Floating appeared to be an alternative behavioral tactic (to territorialism) to obtain breeding success. In lions, individuals that wandered widely, often following the movements of migratory prey, were considered nomadic. Adult males could shift from nomadic to resident behavior and vice versa during their lifetimes, depending on whether they could exert dominance over other pride males or whether they were ejected themselves (Schaller 1972). Four conditions might result in transient behavior in adult pumas: (1) population isolation; (2) an extremely low, patchy, or migratory food base; (3) an extremely diffuse puma population; and (4) inability to compete. If a population experiences the first condition, natal dispersers are unable to emigrate. In isolated puma populations in California and Florida, subadults typically s h owed transient behavior over longer periods but either established residency or died prior to adulthood (Beier 1995, Maehr 1997a). Some surviving yo u n g adult males in the Florida panther population apparently showed site attachment to areas that we re within poor puma habitat and along the periphery of resident male ranges. Maehr (1997a) described them as transients, nonre s idents, or subordinates because they apparently did not successfully breed, and adjacent resident males did not shift home ranges in response to their deaths. Howe ve r, since these males showed site attachment, it may be less equivocal to avoid the transient label. The second and third conditions may often be interrelated. Long prey migrations could trigger seasonal transiency, where a s extended prey population lows could cause adults to abandon home ranges in s e a rch of more pro d u c t i ve habitats. An extremely diffuse puma population resulting from either poor habitat or ove rkill could cause adults to wander widely in search of mates (Sandell 1989). Fo u rth, males may be unable to compete due to their small mass, inexperience, or infirmity caused by illness, injury, or old age. Hence, they may move until a time when they can compete or find a more secure habitat. In the process they could avoid challenges by resident males and possibly encounter a few estrus females. Such a strategy has been o b s e rved in male lions and cheetahs that failed to form (or lost members of ) coalitions, and in male cheetahs that we re in poorer physical condition

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(Schaller 1972, Caro 1994). Although this behavior may occur in old, possibly infirm pumas, we did not observe it in the San Andres Mountains. Instead, old males lived out their last days within their home ranges. For example, M1, an old male who apparently suffered from coccidiodmycosis, used a small area (i.e., about 20 km2) within his home range for a six-month period prior to being killed by neighboring male M3. Likewise, in the six months prior to his old-age-related death, M5 used an area that was within, but only 60 percent the s i ze of, the area he had used in the year before that. We believe that transient behavior in adult pumas is rare. Although transient adults have been reported in other populations, this may often be the result of differences in the term’s definition. Transient has sometimes been used to describe any puma of unknown origin or fate; consequently, an adult “transient” may in fact be (1) a resident from outside the study area boundaries that either made a foray or shifted his home range into the study area, (2) a resident that was not observed during subsequent field seasons, not because it left the study area but because it died, or (3) an incorrectly aged subadult. In the latter case, such an error is most likely if the animal is independent but remains in its natal area for a long period before dispersal (similar to M82 in our study population). Although transient adults have been reported in Idaho (Hornocker 1970, Seidensticker et al. 1973), Wyoming (Logan et al. 1986), and British Columbia (Spreadbury 1989), we suspect most fit one of the above categories and were not true nomads.

LP > >

KX

1. Female progeny often remained philopatric into adulthood. Although philopatric females sometimes made brief exploratory dispersal moves after independence, their subsequent subadult home ranges were similar in size to the annual home ranges of adult females. The distance between the centers of a philopatric female’s natal and independent home ranges averaged 3.2 ± 2.6 km and was similar to the annual distances moved by resident adult females (2.6 ± 2.1 km). Philopatry resulted in the formation of eight matrilines. 2. Females that dispersed traveled, on average, 34.6 km from natal ranges to their independent home ranges or last locations. Dispersal duration in females was typically brief and ceased prior to adulthood. Only one female displayed dispersal behavior over a long period and used short-term transient home ranges. Females that dispersed but remained within the San Andres Mountains used independent home ranges that were similar in size (x– = 48.1 km2) to those of resident adult females but much smaller than those of females that emigrated (x– = 161.2 km2). Subadult females (both

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dispersing and philopatric) exhibited transient behavior over shorter periods (x– = 49 days) than subadult males. 3. All surviving male progeny dispersed, and they dispersed much longer distances (x– = 102.6 km) than subadult females. Dispersal onset and duration were highly variable, occurring from 0 to 238 days after independence, then lasting from 43 to 259 days. Subadult male transient behavior lasted an average of 211 days. Males appeared more likely to use small transient ranges during dispersal moves than females. Transient ranges were typically used when the male encountered the mountain–desert basin interface. Independent home ranges of males that emigrated from the San Andres Mountains were larger (range = 356.5–741.7 km2) than the home ranges of subadult or young adult males that remained within the study area (range = 61.3–115.0 km2). 4. We deduced that male progeny disperse from natal areas principally to avoid inbreeding and that female progeny disperse to avoid excessive competition for resources. Dispersal in both sexes hastens colonization of available habitats. 5. No adult pumas exhibited transient behavior.

LN N5LN5) 1. Mean home range size for seven philopatric females during the twelve months immediately after reaching adulthood (minimum age 18.5–21 months; maximum age 30.5–33 months) was 66.4 ± 20.1 km2, 27.0 ± 13.9 km2, 72.0 ± 19.8 km2, and 45.6 ± 15.4 km2 for the 90 percent ADK, 60 percent ADK, 100 percent MCP, and 90 percent MCP home range estimators, respectively. Comparable home range sizes for twenty-seven mature females (thirty-six months or older at start of annual period) over fifty-five annual periods based on the same home range estimators were 67.4 ± 43.4 km2; 21.9 ± 13.0 km2; 68.9 ± 41.2 km2; and 42.9 ± 28.7 km2.

Chapter 14

Interactions between Pumas

An understanding of puma social organization and its function requires that we examine how pumas use space in relation to one another. We can visualize this social arrangement by determining the degree of spatial overlap in puma home ranges, whether or not they use shared areas at the same time, how frequently pumas associate and why, and how pumas communicate their presence and intentions to one another.

Spatial Relationships Pumas appear to show some flexibility in their spatial arrangement. Although puma studies generally report extensive overlap between females and little or no overlap between males (Table 14-1), there is variation. In British Columbia and the Diablo Range of California, female pumas exhibited minimal spatial overlap (Spreadbury et al. 1996, Hopkins et al. 1986), whereas male pumas in Monterey County and the Sierra Nevada of California, as well as in Colorado, have displayed extensive spatial overlap (Sitton and Wallen 1976, Neal et al. 1987, and Anderson et al. 1992, respectively). Unfortunately, a variety of problems plagued most of these studies, including small sample sizes, the use of different home range estimators, high human-caused mortality, and the inability to capture all adult individuals within the study population. These problems most likely result in reports of exclusivity when perhaps some overlap is the norm. For example, although relatively exclusive ranges are reported for a sample of four male pumas in the Guadalupe Mountains along the Texas–New Mexico border, population

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Table 14-1. Spatial relationships between adult same-sex pumas in other North American study areas. Location Alberta British Columbia California Monterey Co. Diablo Range Sierra Nevada Colorado Florida Idaho New Mexico Utah Wyoming

Male Overlapa nb

Female Overlap nb

0.2; female R and density, rs = –0.612, P = 0.106, for male-female R and density, rs = 0.795, P = 0.025. Spatiotemporal overlap indices between M-M and F-F dyads were similar in 1989, 1990, and 1993 (P 0.44) but greater in males in 1992, based on the 90 percent ADK home range estimator (Mann-Whitney U test, U = 221.5, P = 0.014, nm-m = 17, nf-f = 32). Test for differences in the number of associations among M-M (n1), F-F (n2), and M- F (n 3) dyads during each of four years (1989, 1990, 1992, 1993). Kruskal-Wallis test with 2 d.f.: for 1989, H = 14.481, P = 0.001; for 1990: H = 4.575, P = 0.101; for 1992, H = 14.469, P = 0.001; for 1993, H = 4.769, P = 0.092. Follow-up Mann-Whitney U tests indicated M-F associations were greater than M-M or F-F associations for all years, P

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0.10. M-M and F-F associations were not different in 1989, 1990, or 1993 (P > 0.382), but F-F associations were greater than M-M associations in 1992 (P = 0.096).

Chapter 15

Adaptive Significance of Puma Social Organization

Pumas, like most felids, are solitary. Within the solitary framework, pumas are able to find one another to breed and successfully rear young. This lifestyle has proven very successful for pumas; historically, they may have had the largest geographic distribution of any land-dwelling mammal in the Western Hemisphere other than humans. Even today, their social system can prove adaptive, as long as pumas have moderate protection from human exploitation and large, interconnected habitat patches. In this chapter we first describe the social structure within the desert puma population we studied. Then we examine the evolved function of puma social organization. Is the social organization a two-strategy approach by which male and female pumas maximize individual reproductive success? Or did it evolve to limit the population?

The Social Structure of Desert Pumas The puma population is composed of breeding adults, subadults, and cubs. When cubs and subadults are successfully integrated as breeding adults into a puma population, they represent the re p ro d u c t i ve success of their pare n t s . Because breeding adults have the most immediate effect on fitness, and a re consequently the ones subject to the most intense selection pre s s u re s , their social relationships are highly significant (Wrangham and Ru b e n s t e i n 1986).

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Female Structure Adult female pumas rear offspring without the aid of their mates. After independence, many female offspring move away from their natal ranges in search of adequate habitat to raise their own young; however, some subadults settle close to their mothers. In areas where puma populations are unexploited by humans and the habitat is relatively rich in resources, females may form a matrilineal structure whereby mothers increase their inclusive fitness by sharing habitat with daughters. A matrilineal structure may be more prevalent in areas where dispersal entails higher than average risks. Such may have been the case in the San Andres Mountains, where females that attempted to disperse to the east or west encountered large expanses of terrain that could not support a puma. As matrilines develop and densities increase, females may also become more aggregated. Rapid turnover in adult populations resulting from human off-take probably hinders matriline formation and may explain why they have not been well documented in other puma populations. In our study population, where pumas were protected from chronic human exploitation, resident females showed strong fidelity to their home ranges over long periods. However, established females did make occasional home range shifts to accommodate daughters or even unrelated females. A female’s range also tended to expand and contract as her reproductive status and food requirements of her family changed. As a consequence, range boundaries were not rigid. Abandonment of an established home range appears to be extremely rare in female pumas but might occur if a female is unable to successfully produce offspring and she detects better opportunities elsewhere. If abandonment occurs, we expect females to rapidly reestablish elsewhere. The puma literature provides no evidence of transient or nomadic behavior in adult female pumas. Still, we have no way of knowing how females might behave if the prey base they depended on declined dramatically and then remained depressed for an extended period. In the San Andres Mountains, we documented small increases in female home range size but also continued site fidelity during a drought. Unfortunately, we were unable to determine the drought’s long-term effects. Female home ranges, which are generally much smaller than male ranges, can also vary from being relatively exclusive to exhibiting extensive spatial overlap. When overlap is extensive, females usually use shared areas at different times. Over time, and probably as neighbors became more familiar with one another, overlap between pairs may diminish. As a result of this mutual avoidance behavior, associations are infrequent and of short duration. On the occasions when females do meet, they appear to behave nonaggressively. It is unclear how females are able to avoid one another as well as they do, especially since they typically leave no markers, such as scrapes, that humans can

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detect. However, we still know very little about the use and effectiveness of olfactory cues; these, as well as vocalizations, may play important roles in female spacing. Because pumas are most active in dense cover and in darkness, visual cues may be the least effective method of avoidance. However, it is possible that females have brief encounters with one another more frequently than our records indicated. Although we radio-tracked a few individuals continuously over twenty-four-hour periods (Sweanor 1990), we generally located individuals at most once per day, and the majority of these locations were at day beds. We would easily miss most associations if they were fleeting and during the periods when pumas were traveling. Adult females typically share most of their home ranges with one or more adult males, and at least one of these males sires her progeny. Although spatial overlap is extensive, and females associate with males more than with any other class of independent puma, associations involve great risk for the female and her progeny. Consequently, mutual avoidance is the norm. On relatively rare occasions, females associate with males to breed, reinforce pair bonds, and confuse paternity. All these behaviors may reduce infanticide. A female may cue on scrapes to find mates when she is in estrus, and to avoid males, especially when she is raising cubs.

Male Structure Within the population, resident adult males are responsible for most, if not all, of the breeding. Male progeny disperse from their natal areas, and as subadults they usually move long distances to avoid inbreeding and adult males. As a consequence of their dispersal instincts and avoidance behavior, they often traverse habitats that contain few, if any, pumas. When they do enter an area that supports resident pumas, they do not typically advertise their presence. Those that do may be killed. Sometimes, as they try to avoid resident males and garner strength for another long-distance move, subadults may localize in temporary, transient ranges. As transients, they grow and gain experience. An increase in sex hormones, as well as the presence of breeding females, probably causes the young male to stop dispersing or shirking resident males. If no resident male is there to contest him, the change from transient to resident is easy. However, in most instances, a resident male is probably present. Now the transient must decide whether to challenge or keep moving. A successful challenger will usurp part, or all, of an established male’s home range, whereas an unsuccessful one moves on—or is killed. As do resident females, resident male pumas on our study area showed site fidelity. Howe ve r, male fidelity had a greater tendency to decline with time. This occurred because of home range shifts, which we re often motivated by

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challenges from new male competitors or the reduction in available mates. Responses to changes in the number of competitors and available mates result in ranges with dynamic borders. Howe ve r, adult males probably rarely exhibit transient or nomadic behavior. T h e re are no known cases of a resident male abandoning his home range, but we know that seve re reductions in the number of available mates as well as competitors has resulted in large range expansions. Consequently, if all females we re re m oved from a male’s range, it is plausible he would begin to search farther afield for breeding opport u n i t i e s . Whether or not he occupies a range completely disconnected from his prior range will be largely determined by the presence of females and competing males. Male home ranges are typically one and one-half to three times the size of female ranges; hence a male’s range often overlaps the ranges of several females. Although overlap between adjacent males can be quite variable, more studies have reported exclusivity in male ranges than in female ranges. When male overlap is observed within a population, it is often less than the overlap found for resident females, but there are many exceptions (including our study in the San Andres Mountains). Regardless of the amount of spatial overlap, resident males appear to avoid other males. In our study area, adult males used shared space at different times and were seldom in direct contact. As male neighbors became more familiar with one another over time, overlap between them also declined, but this phenomenon was not as prevalent as it was between neighboring females. Since resident females do not have a set breeding season and only a few are receptive at any given time, resident males must constantly patrol their home ranges to assess the changing reproductive status and availability of females. Consequently, a resident male must always be in breeding condition. A resident male communicates his presence, and likely his dominance, by scraping throughout his home range. Scrapes may be more prevalent along shared borders or travel ways in overlap zones of male home ranges. When range boundaries are dynamic, shared travel routes may be the best places to communicate with neighbors. The scrapes also help females find males when they are ready to breed. Unlike encounters between females, direct meetings between males are occasionally violent. Fights between males can result in death, home range shifts, or continued dispersal.

The Self-Limiting Hypothesis The self-limiting hypothesis holds that land tenure and territoriality are mechanisms by which pumas limit their own numbers, and, hence, keep a puma population from harming its food supply (Hornocker 1969, 1970, Seidensticker et

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al. 1973). Because of the importance of land tenure and territoriality to self-lim itation, we examine these concepts in detail.

Land Tenure and Territoriality Seidensticker and his colleagues introduced the concept of tenure in pumas when they stated that pumas in their Idaho study area exhibited “a land tenure system based on prior rights” (1973:53). As a consequence, a puma that established a home range in a particular area was guaranteed the use of that area over its lifetime. Neighbors as well as transients did not contest an established puma’s rights to its home range. Instead, neighbors retreated from shared areas if they detected the presence of another resident, and transients moved on to unoccupied ranges. This was a peaceful way for pumas to space themselves over the available habitat. Their concept of land tenure implied a degree of stability within the puma social structure. One could envision a fixed number of home ranges available for occupancy by resident pumas; once the vacancies were filled, nonresidents (typically subadults looking for a place to establish residency) moved elsewhere. The concept of territoriality implies social dominance over a specific geographical area. It is used to describe the behavior of many carnivore species. Territorial behavior is linked to acquisition of resources and is selected for only when the individual’s resulting increased access to resources (and, subsequently, fitness) outweighs the accompanying expenditure of time and energy and the increased risk of injury and predation (Brown and Orians 1970, Kaufmann 1983, Mace et al. 1983). Territory was first used to describe avian social systems. As the term was applied to other taxa, definitions became increasingly inclusive. Consequently, the term is now difficult to clearly define. In their final paper on the Idaho pumas, Seidensticker et al. (1973:54) avoided the term altogether “because of the semantic conflicts and muddled concepts brought to mind.” Early definitions stated simply that territory was a defended area, with the implication that defense could be exhibited through attack, threat, or advertisement (Noble 1939, Burt 1943). Later, Pitelka (1959) introduced the concept of exclusive range use. More recent authors typically define territoriality as the “area occupied more or less exclusively by an animal or group of animals by means of repulsion through overt defense or advertisement” (Wilson 1975:256).” However, Emlen (1957) presented a somewhat different concept that was later supported and expanded on by others (e.g., Owen-Smith 1977). He believed an animal was territorial if, in a given area, it showed supreme dominance over intruders. Consequently, territories need not be exclusive. Etkin (1964:24–25) may have provided the least-restrictive definition of territoriality: “any behavior on the part of an animal which tends to confine the movements of the animal

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to a particular locality.” In this case, territories need not be defended or exclusive. This was the interpretation adopted by Hornocker (1969) when he first analyzed the winter relationships of pumas in Idaho. More recently, Kaufmann (1983:9) synthesized the different concepts of territoriality and developed his own definition: “a fixed portion of an individual’s or group’s range in which it has priority of access to one or more critical resources over others, which have priority elsewhere or at another time. This priority of access must be achieved through social interaction.” His definition also did not require overt defense or exclusive use.

Do Desert Pumas Exhibit Land Tenure or Territoriality? Female pumas in the San Andres Mountains could only be considered territorial under Etkin’s (1964:24–25) broad definition of the term. Females did not exhibit the two behaviors most often cited as components of territoriality: exclusive use and defense. On the contrary, spatial overlap between female ranges was often extensive, and they did not attempt to repulse other females through fighting or advertisement. However, females exhibited mutual avoidance behavior and tended to use shared areas at different times; consequently, it might be argued that a female using a shared area was territorial because she had “supreme dominance over intruders” (Emlen 1957), or “priority of access” (Kaufmann 1983). Because we had no way of determining which puma retreated from a shared area upon detecting the presence of the other, we could not adequately assess this argument. Since dominance was not reinforced through advertisement (e.g. scraping) or fighting, it is likely that individual females often made the judgment whether to leave or stay based on the prospect of hunting success, risks to vulnerable cubs, and possible recognition of kin or nonrelatives, and not on which puma was there first. Consequently, we conclude that female pumas in the San Andres Mountains were not territorial but simply exhibited mutual avoidance behavior. If land tenure is interpreted to mean long-term fidelity to a particular site, then female pumas on the San Andres Mountains exhibited this behavior. However, the term implies prior rights to an area and is integral to the argument of self-limitation in puma populations (Seidensticker et al. 1973). In this context, there are a fixed number of home ranges that can be filled by adult females; young adults cannot establish home ranges unless vacancies become available. This was not the case in the San Andres Mountains. Young females often established adult ranges in areas already occupied by long-established females. Similar behavior by female pumas was observed in Alberta, where subadult females sometimes “established residency adjacent to their mothers, squeezing between the home ranges of two or more older residents” (Ross and Jalkotzy 1992:424).

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We also documented cases where established residents made home range shifts to accommodate daughters and even unrelated newcomers. If females remained neighbors for long periods, the amount of spatial overlap between them tended to decline, but this may have been a result of mutual recognition and avoidance and not necessarily an acknowledgment of prior rights. We did not document any overt aggression between females that might have caused dispersal in newly independent females. The argument that the San Andres Mountains housed a rebuilding population, hence not all vacancies within a land tenure structure were filled, may have been true during the early years of the study, but it was not supported during later years. New females continued to establish adult home ranges in areas that overlapped the ranges of well-established adults, even as the mule deer population was rapidly declining. In the San Andres Mountains, land tenure “based on prior rights” (Seidensticker et al. 1973:53) did not accurately fit male behavior, either. Resident males certainly encouraged young subadult males to move on, unless they killed them first. However, males that had just reached adulthood and had no established range sometimes contested a resident male’s rights to his home range. And sometimes the resident lost the battle. If the system were based strictly on prior rights, a young male would not challenge a resident but would keep moving until he found a place that was void of resident males. Fights between residents also resulted in a realignment of range boundaries. One resident sometimes gained ground while the other lost it. Such give and take made for fuzzy boundaries and contributed to the spatial overlap we observed on our study area. In contrast to decisions made by females, a new male’s decision to remain in an area or move on was probably strongly affected by the presence and perceived dominance of resident males. We suspect a newcomer only instigated a fight if he believed he could successfully challenge the dominance of a resident. We believe it is appropriate to consider male pumas in the San Andres Mountains, and perhaps in most populations, as territorial. Males often exhibit one or both of the behavioral components typical of territoriality: repulsion of other males through advertisement (scraping) and fighting; and exclusiveness (in time if not in space) of home ranges. Adult males in all puma populations probably mark their home ranges with scrapes, even though only a few studies (Seidensticker et al. 1973, Hemker 1982, our study) have actually provided much detail on the behavior. Evidence of fighting between males has also been reported across the puma’s North American range. Even in central Idaho, where male pumas initially appeared to peacefully maintain exclusive ranges (Seidensticker et al. 1973), fighting has recently been documented (Holly Akinson, Hornocker Wildlife Institute, personal communication). At least some fights in the San Andres Mountains occurred because males were competing for a breed-

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ing female or trying to maintain or obtain territory that contained breeding females. Although exclusive ranges have been reported for male pumas, several studies (including ours) have also reported some degree of spatial overlap; consequently, if territoriality is strictly viewed as a spatial concept, male pumas cannot generally be considered territorial. However, we found that males in our study area practiced mutual avoidance by using shared areas at different times. This is similar to the way females behaved except it is more likely that males exhibited “supreme dominance over intruders” or “priority of access,” at least when intruders were neighboring resident males. Neighboring resident males were probably very familiar with each other’s strengths because of prior confrontations. A male that entered a shared area conceivably determined whether or not his neighbor was nearby based on the age of scent left in scrapes. A male that remained in an area already occupied by his neighbor risked death. Death would mean the loss of his entire territory, including a lot of area not shared with his combatant. Consequently, it was probably in the intruder’s best interest to retreat until another day. On the San Andres Mountains, female and male pumas exhibited mutual avoidance, and male pumas were territorial. However, we found no evidence that these behaviors were mechanisms that limited the population, particularly during a period of severe deer decline.

The Two-Strategies Hypothesis This hypothesis holds that male and female pumas have evolved different strategies for maximizing individual reproductive success. In this hypothesis too, mutual avoidance and territoriality are important mechanisms. Mutual avoidance enables females to successfully rear young, and territoriality enables males to successfully compete for mates. However, these mechanisms do not function to limit the puma population below the level set by the prey.

Female Strategy A female puma’s reproductive success is limited by the number of offspring she can raise to independence in her lifetime (see Chapter 7). To be successful, the female must survive as long as possible and provide adequate nourishment and security for her cubs. Two ways she accomplishes this is by maintaining high home range fidelity and practicing mutual avoidance behavior. If a female puma can enhance her progeny’s survival and opportunity for procreation after independence, all the better. Consequently if she resides in an area that provides an abundance of both security and food, she should not discourage daughters from settling there, too. As long as the benefits of philopatry exceed the costs of shar-

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ing resources with daughters, the mother’s inclusive fitness will increase. This explains how female philopatry and the resulting matrilineal structure could evolve (see Plate 4). Unlike males, females do not need to compete directly with one another for access to mates. Female pumas also do not aggressively compete with one another for food resources. Instead, they avoid one another in time and space. However, some independent female progeny that perceive competition for food is too high in the natal area may choose to disperse and search for better habitat (see Chapters 10 and 13). Dispersing females can colonize other suitable habitats or recolonize previously occupied habitats. Given that a female’s reproductive success is so dependent on habitat quality, habitat quality should have a great influence on female range size. Adult female home ranges are generally much smaller than those of adult males. The size of a resident female’s home range is probably determined most by the distribution and abundance of prey needed to support her and her cubs, as well as cover to successfully stalk prey and ensure security. In the San Andres Mountains, some of the largest female home ranges were in areas where we suspected deer densities were lowest. An examination of puma densities, prey abundance, and puma range sizes each year suggested that prey distribution (if not abundance alone) probably had an important role in determining female range size. The juxtaposition of potential mates may also have had some influence on female range size, since females generally utilized larger areas when they were solitary (and probably in breeding condition) than when they were raising cubs. This behavior may benefit the female because she has greater opportunity to establish positive relationships with all of the males that share or abut her home range, and consequently confuse paternity. Our observations indicated that a female’s subsequent encounters with these males, even when accompanied by cubs, were generally not aggressive. Such meetings with unfamiliar males, however, sometimes proved deadly. Overlap in female ranges should be influenced by habitat characteristics, particularly as it affects prey abundance, distribution, and stability (Brown and Orians 1970, Hixon 1980, Sandell 1989). Low to moderate prey numbers, fluctuations in those numbers, and a patchy prey distribution probably contributed to the spatial overlap we observed in resident female home ranges. Seidensticker et al. (1973:57) suggested that the highly mobile nature of the puma’s prey made it seem “unlikely that a female could maintain an exclusive area of sufficient size to provide food for herself and her kittens throughout their development.” We also observed variations in habitat characteristics throughout the San Andres Mountains; elevation, aspect, and slope, as well as springs, had a tremendous impact on the type of vegetation that occurred at a site, and consequently, on

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the site’s suitability as deer habitat. Thus, patchiness in habitat probably corresponded to variability in the spacing of the deer. In the Sierra Nevada of California, pumas had overlapping home ranges where deer were more abundant (Pierce et al. 2000b). If prey varies in space and time, the female’s range must be larger to provide for her at all times. Consequently, the area may contain more than enough food during part of the year, allowing more than one female to use the same area. It is also possible that given relatively low prey densities and a patchy distribution, no individual patch would be large enough to support a female. In this case, she would have to visit several patches that might be well spaced in order to survive and procreate. To maintain such an area to the exclusion of all other females would require large daily movements (to patrol and mark) and possibly physical defense. Energy expenditure alone would probably exceed any benefits derived from exclusive use of an area. Patrolling would also mean more time away from her vulnerable young and less time for prey acquisition so she could feed those young. The added risks of injury from fighting would be intolerable. Together, these costs would lower the female’s fitness. Consequently, the best tactic would be avoidance of other pumas that use the same area. In summary, a female puma maximizes her reproductive success by maintaining a home range in which she is familiar with vital resources, practicing mutual avoidance, raising as many cubs as she can in her lifetime, cultivating a matrilineal structure, and fostering amicable relationships with territorial males. These behaviors increase a female’s own survival and her ability to raise cubs to independence. In the San Andres Mountains, the matrilineal structure and nonaggressive behavior of females apparently allowed female density to increase even as the main food base—mule deer—declined. The rate of deer population decline was strongly influenced by puma predation (see Chapter 17).

Male Strategy A male’s reproductive success is more variable than a female’s (see Chapter 7). Because an adult male is always in breeding condition and does not have to care for dependent young, he has the capacity to produce many progeny in his lifetime. But first he must secure access to mates. Breeding opportunities are limited because females are dispersed in low numbers over the landscape, in estrus at variable times, and not available for breeding during the time they are raising young. To successfully breed with as many females as possible, the male must traverse a large area. Yet the area cannot be too large, since the male must frequently visit the different parts of his range to assess the reproductive status of resident females and to defend against incursions from other males. The latter could not only threaten his chances to breed but also kill the cubs he has sired.

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Consequently, if he can, it is in the male’s interest to exclude other males from an area that contains his mates. On the other hand, the male that kills another male’s offspring can benefit his own reproductive success by causing the mother to re-cycle and thus provide him with an opportunity to mate. Dominance in shared areas can be obtained by repeated scent marking, direct confrontations, and fighting. The maximum size of a male’s range is affected by the density of adult females, his mobility, and his aggressiveness. The latter two characteristics have probably contributed to selection for larger body size of male pumas (see Chapter 7). Competition from adult males and the avoidance of inbreeding have influenced the behavior of the subadult male. By dispersing a long distance, he minimizes the chance of mating with closely related females, particularly those that may form a matriline. Such matings could have immediate as well as long-term repercussions on individual fitness. Long-distance moves also give young males time to gain the body mass and experience needed to compete with other males, and may help them locate areas with few competitors and many mates. The added benefit of dispersal is that pumas can colonize other suitable habitats or recolonize places from which they were previously extirpated. It has been argued that actual fighting among highly specialized carnivores is not advantageous to their physical well-being and surv i val (Ewer 1968,

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PHOTO 25. Male pumas were responsible for all of the killing of other pumas on the San Andres Mountains.

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Hornocker 1969). However, male pumas are (1) equipped with formidable fighting machinery, (2) in a continued state of reproductive readiness and consequently heightened aggression, (3) competing for a rare resource (females in breeding condition), and (4) rarely in direct contact with other pumas, so they may not have evolved behavioral mechanisms that prevent injuries during intraspecific encounters (Lorenz 1971). Consequently, it is easy to understand why fights sometimes occur. An adult male may try to dispatch a young subadult within his territory because an inexperienced subadult is not a formidable (e.g., risky) opponent; however, if ignored, he could become one. Young adult males that are just reaching maturity may also instigate fights; they feel aggressive but probably lack the caution of residents because they have no territory to lose. Fights between established residents should occur less frequently, since they have become familiar with each other’s strengths and are unwilling to risk the loss of territory (or their life) in a skirmish. Still, given the rarity of breeding opportunities, fights between resident males may be provoked by an estrus female. Since male pumas are competing for a limited resource, and they fight to protect or gain rights to breed, we might expect male ranges to be exc l u s i ve. Yet many populations re p o rt some spatial overlap between adult males. In our population, spatial overlap between pairs of neighboring adult males averaged 24 p e rcent. Why was the overlap so high? In solitary carnivo res, males are affected by the abundance, distribution, and mobility of females. Sandell (1989) h y p o t h e s i zed that male ranges should be exc l u s i ve when females are dense and e venly distributed, and overlapping under all other circumstances. We can easily argue that in many populations (including the San Andres Mountains), females occur at low densities and are patchily distributed. Patchiness results f rom an uneven distribution of re s o u rces and resulting overlapping female ranges. Additionally, even though puma populations throughout their range indicate a pattern of more adult females than adult males, many females are actually unavailable for breeding because they are pregnant or raising yo u n g . Consequently, the operational sex ratio (i.e., the ratio of adult males to females that we re available for breeding) may approach 1:1 or even favor males. That was the case in the San Andres Mountains. Besides being a rare re s o u rce, re c e ptive female pumas are also very mobile and spatially unpredictable within their home ranges. Consequently, it is often difficult for males to monopolize a number of fertilizable females. All of these characteristics should lead to widely overlapping male home ranges (Lott 1991, Sandell 1989, Waser and Wi l e y 1979). In Sandell’s (1989) analysis of the spacing behavior in solitary male carnivores, he believed they could adopt two different strategies to achieve matings:

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stay in exclusive ranges and monopolize a number of females; or roam over large, overlapping ranges and compete for each single female that comes into heat. Even when females are evenly distributed, there should be a threshold density below which the payoff is greater when the male roams in search of receptive females than when he tries to defend an area with a depleted number of females. Both behaviors have been observed in martens (Taylor and Abrey 1982), North American lynxes (Bailey et al. 1986), ermines (Sandell 1986), and cheetahs (Caro 1994). Based on Sandell’s (1989) premise that the patterns of roaming behavior show a continuum, from extremely wide-ranging behavior to spatial overlaps between male pairs as low as 10 percent (measured on convex polygons), male pumas in the San Andres Mountains exhibited a degree of roaming behavior. Pairs of males with overlapping ranges also directly competed for breeding rights with resident females that were in estrus. But throughout the literature, a roaming strategy typically implies transience. For example, in cheetahs, roaming (or floating) males showed no consistent or predictable use of a home range over time. Although territorial males probably obtained greater breeding success, floaters were also successful at times (Caro 1994). In contrast, there are no confirmed cases of a floating male having reproductive success in any puma population. Adult male pumas on the San Andres Mountains exhibited strong home range fidelity, and although they occasionally made excursions outside their home ranges, we observed successful breeding only between resident males and the females whose home ranges they overlapped. The only other study to examine reproductive success in pumas occurred in Yellowstone National Park, and it reported similar results. Adult male pumas often established overlapping ranges; these residents were responsible for all successful breeding (Murphy et al. 1998a). In summary, a male on the San Andres Mountains maximized his reproductive success by being territorial. Benefits of territoriality included priority in mate access and protection of offspring and mates from other potentially cannibalistic males. These outweighed potential benefits (i.e., possible increased encounters with estrus females) that could have been derived from wide-ranging or floating behavior. But given the low densities, and the very mobile and spatially unpredictable nature of females, a male simply could not maintain an exclusive territory. The male puma strategy was not a clear case of either territorial defense or mate defense, but a combination of both. Although territorial behavior sometimes caused the death or expulsion of a competitor and thus affected male puma density, we do not believe the function of territoriality was to limit the population below the level set by the prey (i.e., the self-limiting hypothesis).

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Pumas and Other Big Cats—Similar Strategies? Pumas share many behavioral characteristics with other large, solitary felids, including the leopard, tiger, and jaguar. These species inhabit similar environments: cover is dense and terrain is often rugged, thereby inhibiting movement and providing poor visibility over long distances; prey also occur at relatively low densities and are well dispersed. These environmental and prey characteristics encourage a hunting style that relies on stealth and concealment. Hunts typically consist of stalking to within a close distance of prey, followed by a short charge (Hornocker 1970, Leyhausen 1979, Bailey 1993, Stander et al. 1997). Conditions where these felids live, with the resulting high costs of sociality, may explain why they remain solitary. Group living requires the sharing of food resources (Packer et al. 1990); consequently groups must spend more time foraging or kill larger prey (Caro 1989). Larger congregations around carcasses also increase the risk of detection and attendant competition from other carnivores (Stander et al. 1997, Sunquist and Sunquist 1989), and heighten predation risk to offspring (Packer and Pusey 1983). Only the social structures of the African leopard and tiger have been studied extensively enough to provide clear comparisons to the puma. More limited information is available on the jaguar. Studies of all three felids indicate similar behavioral patterns to pumas: home ranges are much larger in adult males than in adult females, and male ranges overlap the ranges of more than one female (Bailey 1993, Stander et al. 1997, Sunquist 1981, Rabinowitz and Nottingham 1986). Of the three species, the leopard may be the puma’s closest ecological equivalent. It also inhabits a wide variety of habitats and had a wide, but recently reduced, distribution (Schaller 1972, Bailey 1993). Recent radiotelemetry studies of leopards in both South Africa and Namibia, spanning two and three years, respectively, indicate leopards behave similarly to pumas. Although both studies found that leopards shared parts of their home ranges with adults of the same sex (pair overlap in Namibia leopards during each of two years averaged 29 to 46 percent for males and 35 to 43 percent for females; for South African leopards it averaged 19 percent for males and 18 percent or more for females), there was temporal avoidance of shared space (Bailey 1993, Stander et al. 1997). Direct associations between adult leopards were also rare and most probably occurred for the purpose of breeding (Bailey 1993). Mutual avoidance was enhanced through the use of scrapes and other olfactory cues and vocalizations; fighting appeared to be rare. Although subadult males appeared to disperse more slowly from their natal ranges than pumas, female leopards had a tendency to remain philopatric, similar to female pumas on the San Andres Mountains (Bailey 1993).

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Tigers apparently have a greater tendency to use exclusive home ranges and may be the most territorial of the solitary felids. Tigers in Chitwan National Park, Nepal, have been studied for well over a decade (Sunquist 1981, Smith et al. 1987, Smith 1993). In that population, both males and females established territories from which other same-sex individuals were excluded. Male territorial behavior was most pronounced when females were in estrus, whereas females appeared to compete for food, cover, and a secure place to raise young (Sunquist 1981, Smith et al. 1987). Exclusion was obtained by scent marking, mostly along territorial borders, and by fighting. Fights generally resulted in either one individual (typically a subadult) leaving the area, or a shift in range boundaries. Adult females exhibited long-term fidelity, although they sometimes made territorial shifts to accommodate philopatric daughters. Philopatry was common in females. Although males attempted to disperse long distances, man-induced isolation of the population (similar to circumstances experienced by male Florida panthers) sometimes forced males to return to their natal ranges (Smith 1993). The jaguar is the only large felid that is sympatric with pumas. Only three studies provide limited quantitative information on the movements of few adult jaguars over an extended period of time (Crawshaw and Quigley 1991, Rabinowitz and Nottingham 1986, Núñez et al. in press). Radiotelemetry research suggests variability in home range overlap between adults of the same sex. In populations in Brazil and Mexico, females tended to inhabit overlapping ranges (Crawshaw and Quigley 1991, Núñez et al. in press); unfortunately, spatial relationships between males could not be determined because either no information was provided or only one adult male was radio-collared. In Belize, the ranges of four radio-collared adult males overlapped, but sign (tracks and visual observations) suggested that two uncollared females had exclusive ranges (Rabinowitz and Nottingham 1986). However, there is no way to ascertain whether this exclusivity was indicative of the population as a whole, or even whether other females may have been present. As with the puma and leopards, jaguars appear to practice mutual avoidance and utilize areas of overlap at different times. The degree of marking by scrapes and feces in jaguars also varies but appears to be most common in areas of high male overlap (Rabinowitz and Nottingham 1986). The data are sketchy, yet philopatry in female offspring may be a common trait. The four adult females studied in Brazil apparently consisted of two mothers and their daughters (Crawshaw and Quigley 1991). How do the solitary felids differ from the social ones? “Social behavior evolves as an adaptation to maximize fitness, given a particular set of ecological pressures” (Wrangham and Rubenstein 1986:452). The African lion and cheetah, which are the only known wild felids to exhibit sociality, generally occupy open environments where prey occur in large, concentrated herds. In cheetahs,

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females are solitary but males may form coalitions of two or three individuals that defend a territory where females aggregate for the purpose of feeding. Coalitions are typically composed of littermates or of two brothers and a nonrelative (Caro 1994). In African lions, females live in permanent prides, which consist of one to eighteen related females, their dependent offspring, and a coalition of one to nine adult males that are not related to the females (Schaller 1972, Packer et al. 1988). Coalitions of male lions defend female prides rather than a specific territory, and large coalitions can defend more than one pride simultaneously (Packer and Pusey 1983). Smaller coalitions (two or three individuals) may be composed of unrelated male lions, but coalitions larger than three are composed entirely of close relatives (Packer et al. 1991). In his analysis of cheetah social structure, Caro (1994) concluded that intense male competition resulting from high densities and localized female distributions provides the conditions necessary for the formation of male coalitions. Since most felid species (including the puma) rarely encounter both conditions, competition is less intense, and males remain asocial. Coalitions are typically larger in male lions than in cheetahs, because male lion cubs, which are often born to several female pride members simultaneously, usually disperse together (Pusey and Packer 1987). Larger male groups appear to be further encouraged by the behavior of pride females. During the period when one male alliance is ousted by another, dependent offspring are killed and females come into breeding condition. However, females also exhibit temporary infertility. The combination of high sexual activity and temporary infertility attract more coalitions, incite further competition, and typically result in a pride takeover by the largest-available coalition. This benefits the pride females because larger coalitions are capable of retaining tenure longer than smaller coalitions. Since it may take twenty-five months after a pride takeover for a pride female to successfully raise a litter of offspring, longer tenure enhances her reproductive success (Packer and Pusey 1983). The reason larger coalitions are made up entirely of close relatives can again be measured in reproductive success. Packer and colleagues assert that most members in larger coalitions do not get to breed, so if they are unrelated to the breeding members, they do not realize any fitness benefits. In contrast, non-breeding relatives reap inclusive fitness benefits (Packer et al. 1991). The fundamental reason for pride or group living in female felids is not well understood. Caro (1994) discusses two related hypotheses that suggest that the presence of large prey at least enables females to be social. In one, the habitat simply supports enough prey of a large-enough body mass (e.g., the same size as the female or up to twice her body weight) for a female to feed additional members. In an alternative hypothesis, females living at high densities improve their inclusive fitness by sharing carcasses with kin when prey are large and highly vis-

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ible. The large carcass provides enough food for more than one individual, and the larger number of group members provides better defense of an easily detected carcass from unrelated females as well as competitors of other species. In their examination of why lions form groups, Packer and colleagues (1990) agree that large prey size permits individuals to forage together, but other factors provide the positive advantages of living in groups. These include cooperative defense of young against infanticidal males and of territory against intruding females. As we proposed in Chapter 7, philopatry could have been the basis for the evolution of the pride in African lions. Resulting matrilines would have made it easier for related females to associate in high-density prey areas and at kills of large prey. Behavioral strategies that involved cooperative hunting and defense of food and cubs would have enhanced the inclusive fitness of related females that formed prides. The social organization found in pumas as well as the other large felids indicates the flexibility of these cats in the face of different environmental conditions and the type, distribution, and density of prey that those environments support. Other large cats have many of the same behaviors as the puma, which is not unexpected since they share a common ancestor. As more research is conducted on the jaguar, the African leopard, and the more-elusive species such as the snow and clouded leopards, biologists will probably observe additional behavioral similarities. We may also see changes in the behavior of these naturally outbred species as their habitats become more fragmented and isolated through human development. Changes are already occurring, since, in some populations, individuals that want to disperse are not able to do so (Beier 1995, Maehr 1997a). In his synthesis of solitary felid behavior, Bailey (1993) speculated that fighting might occur more frequently in isolated populations. Perhaps isolation of Chitwan National Park has encouraged the greater levels of aggression observed in both the male and female tigers that live there. In pumas, it appears that the social organization is a behavioral expression of the life-history strategies used by individuals to maximize reproductive success. If these behavioral patterns are adaptive because they maximize fitness, what effect does that have on their major prey? We address that question in Part 4.

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1. The social organization of pumas on the San Andres Mountains apparently enhanced individual reproductive success. Pumas employed two strategies—one by females and another by males. Adult females exhibited strong home range fidelity, practiced mutual avoidance behavior, cultivated a matrilineal structure, and fostered amicable relationships with territorial males. These behaviors increased a female’s ability to produce cubs and

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ensured her and her cubs’ survival. Adult males were territorial. Benefits of territoriality included priority in mate access and protection of offspring and mates from other, potentially cannibalistic males. These outweighed potential benefits (i.e., possible increased encounters with estrus females) that could have been procured from floating behavior. 2. Puma social organization apparently did not function to limit the population below the level set by the prey. 3. Pumas behave in similar ways to leopards, jaguars, and tigers, which also live in habitat with closed vegetation and/or rugged terrain and a dispersed prey base. Puma behavior may help biologists to better understand how other less-studied, solitary-living felids may behave.

P a rt I V

Puma–Prey Relationships

Chapter 16

Puma Diet

Patterns of Pumas and Prey Pumas opportunistically take advantage of the most abundant and vulnerable prey. This generalist strategy probably enabled pumas to thrive after the late Pleistocene extinctions that doomed their more specialized competitors and to adapt to a wide range of habitats. In addition, prey size probably imposed selective pressures on puma body size, thus shaping the pattern in which pumas are smallest in equatorial regions and increase in body size with latitude. The largest pumas are in the extreme northern and southern portions of their distribution (Kurtén 1973, Iriarte et al. 1990). Mean mass of vertebrate puma prey has been positively correlated with puma body mass at different latitudes (Iriarte et al. 1990) and even within the same population (Murphy et al. 1998b). In other words, larger pumas tend to kill larger animals. In an evolutionary sense, as larger prey became more available and vulnerable farther from the equator, larger puma variants were probably selected because they could kill larger animals and more efficiently convert acquired energy and nutrients into greater reproductive success than could smaller pumas. By contrast, smaller pumas living in equatorial regions more efficiently used smaller prey that were relatively more available and vulnerable to them than larger prey. Sympatry with the larger-bodied jaguar in those habitats may have imposed additional selective pressure on the puma to adapt to using smaller prey (Iriarte et al. 1990) and thereby reduce exploitation and interference competition. In tropical regions pumas tend to prey on relatively small and taxonomically 301

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diverse prey. In Belize, Peru, Paraguay, Argentina, and parts of Chile, pumas thrive on prey that, on average, weigh less than 15 kg (Iriarte et al. 1990, Branch et al. 1996, Taber et al. 1997). This includes a long list of animals in diverse orders: pudus (the smallest deer) and peccaries, marsupials, carnivores, lagomorphs, rodents, armadillos, anteaters, primates, and bats (Iriarte et al. 1990). Larger ungulates become more important as their numbers and distribution increase in puma habitat along a latitudinal scale (Iriarte et al. 1990). For example, in southern Chile (Franklin et al. 1999), the guanaco (Lama guanicoe) was the most important prey item by biomass (59 percent), followed by the humanintroduced European hare (Lepus capensis) (25 percent). In western Mexico, white-tailed deer comprised the greatest prey item by biomass (66 percent). The nine-banded armadillo (Dasypus novemcinctus) was second in importance (11 percent), with the collared peccary not far behind (9 percent) (Núñez et al. 2000). Pumas in temperate North America prey principally upon mule deer, whitetailed deer, and elk, with adults of these species weighing well over 15 kg. Elk, the largest common puma prey in North America, weigh 225–350 kg, which is easily three to ten times the mass of pumas that hunt them. Other ungulates are used where they are locally abundant and vulnerable, such as peccary, moose, and bighorn sheep. Smaller prey, such as rodents (e.g., porcupines, beaver [Cas tor canadensis]), lagomorphs, and carnivores (e.g., coyotes, striped skunk, raccoon [Procyon lotor]) are eaten opportunistically (Logan and Sweanor 2000, and references therein). In localized areas, pumas also prey on livestock, usually sheep and cattle, which may make up 0–34 percent of their diet (this study, Cunningham et al. 1995). Pumas infrequently prey on domestic horses, and they occasionally prey on domestic dogs and cats where residential areas invade puma habitat (Aune 1991, Beier and Barrett 1993, Torres et al. 1996).

Puma Diet on the San Andres Mountains Given the propensity for pumas in North America to rely on ungulate prey, we expected the desert mule deer to be the mainstay of pumas on the San Andres Mountains (Table 16-1). Out of 525 dead prey animals we found that showed evidence that they had been killed and eaten by pumas, over 90 percent (n = 479) of them were deer. Of those, seventy-seven wore radio collars. We found only ten desert bighorn sheep (1.9 percent) killed by pumas during our ten-year study. This was partially a reflection of their very low numbers and the extremely low chance of finding kills in the rugged terrain inhabited by the sheep. All the sheep we found wore radio collars. Pronghorns rarely (1 percent) fell victim to hunting pumas. Those that did were killed at springs with heavy vegetation and

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low visibility in the foothills and canyons at the north end of the mountains. The pronghorns were clearly out of their usual habitat of relatively flat terrain with short vegetation, where they ordinarily were not vulnerable to puma predation. We found only three oryx (0.6 percent) killed by pumas—all of them calves about the size of an adult mule deer doe. This low number, again, was probably partially a function of the very low number of oryx ranging in puma habitat. In addition, adult male and female oryx, weighing over 200 kg and possessing spear-like horns reaching 150 cm long, are probably a formidable challenge to pumas. All other species of prey that we found consumed by pumas, including coyote, striped skunk, badger, ringtail, jackrabbit, porcupine, and golden eagle, each comprised less than 1 percent of the total victims. The lone golden eagle was killed apparently as it attempted to scavenge from a pumakilled deer. Other pumas were puma food on rare occasions (2 percent). Although small numbers of cattle, including newborn calves, often were in puma home ranges along the western edge of our study area, we did not find any cattle killed by pumas during the ten years of research. Nor did ranchers in that area report any puma-killed livestock. Pumas sometimes killed animals but did not consume them, including fourteen other pumas, four gray foxes, one coyote, and one long-eared owl. Biologists in Montana concluded that pumas protected food caches by killing but not

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PHOTO 26. Desert mule deer were the most important prey to pumas on the San Andres Mountains.

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Table 16-1. Prey killed by pumas on the San Andres Mountains, New Mexico, 1985–1995.a,b Species Desert mule deer Desert bighorn sheep Pronghorn Oryx Puma Coyote Striped skunk Badger Ringtail Leporids Porcupine Golden eagle

No. recorded

Percent

479 10 5 3 13 3 3 1 1 1 5 1

91.2 1.9 1.0 0.6 2.0 0.6 0.6 0.2 0.2 0.2 1.0 0.2

aPuma

prey included puma kills and probable puma kills. addition to these animals, pumas also killed but did not eat fourteen other pumas, four gray foxes, one coyote, and one long-eared owl. bIn

eating coyotes (Boyd and O’Gara 1985). Similarly, while studying resource use by pumas, bobcats, and coyotes in the central Idaho wilderness, Koehler and Hornocker (1991) explained that pumas defended or usurped food caches by killing but not eating bobcats and coyotes. As we discussed previously, pumas were killed during intraspecies competition for food and mates. We suspect that the gray foxes and the coyote were killed as a result of interspecies competition for food. We know from evidence of tracks and feces at caches that these carnivores occasionally scavenged from puma kills. We even watched a lone coyote usurp a large mule deer buck that had just been killed by a radio-collared subadult female puma. Another explanation is that bobcats, coyotes, and foxes are potential predators of small puma cubs; hence, female pumas that kill those enemies enhance their own reproductive success. We believe that bobcats and coyotes are capable of killing puma cubs that are smaller than they are, and coyotes could certainly gang up on cubs (e.g., this happened to six-month-old cub M137). Gray foxes could probably kill newborns. On two occasions we observed gray foxes lounging on rocks within about 20 m of puma nurseries with suckling cubs. Cubs this small could be vulnerable to fox predation when their mother departed to forage. Killing enemies to reduce competition for food

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and to protect offspring would seem to be adaptive pursuits for pumas. The long-eared owl pillaged from its ground perch and left dead on the sand was killed by a cub that may have simply found the bird to be an irresistible stimulus to the hunt. Prey items in puma fecal samples and stomachs we collected from the San Andres Mountains complemented the cadaver tallies (Table 16-2). Elmer’s (1997) analysis of 832 fecal samples and four stomachs had a more accurate representation of puma diet because it detected a greater variety of small prey. Naturally, field searches for puma-killed prey bias against small prey items because they are often completely consumed by pumas; hence, evidence of their demise is rarely if ever detected. Desert mule deer was the most important prey (85.6 percent), while other ungulates, including pronghorn, desert bighorn, oryx, and javelina, each comprised less than 1 percent. Rodents were the second most important class of food (5.5 percent), with porcupines comprising the bulk (3.2 percent). Jackrabbits and hares (i.e., Leporids) came in third (4.2 percent). Puma hair was in 2 percent of the samples, but it was impossible to distinguish if hair was ingested during cannibalism or grooming. Perhaps the most curious prey item, found in one stomach, was the ornate box turtle (Terrapene ornata). These small land turtles are most vulnerable in the peak of their activity from mid-July through August as they take advantage of the rainy season in their quest for food. Vegetation occurred in 20 percent of the sample and was composed principally of grass but included some piñon nuts, juniper twigs, and other woody plant parts. Although some vegetation was probably ingested accidentally when it adhered to prey tissues, pumas sometimes graze sparingly on green grass for reasons that are not known. We speculate the grass may act as an emetic to help expel hair or as roughage that hastens expulsion of gut parasites. Again, complementing the results of our count of prey cadavers, no remains of livestock were found in the puma feces or stomachs. We used Elmer’s (1997) puma diet results to estimate the relative percentage that each prey species contributed to the total biomass consumed and the relative number of prey animals killed by pumas on the San Andres Mountains. This helped to illuminate the importance of each prey type. To accomplish this, we applied a correction factor developed by Ackerman (1982) in his research on the diet and energetics of pumas in south-central Utah. While conducting feeding trials on captive pumas, Ackerman found there was a positive relationship between the number of field-collectible feces and the consumption of small prey [i.e., feces / kg = 1.98 + 0.035 ¥ estimated prey weight (kg)]. This means that per unit mass of the prey animal, larger prey would result in fewer collectible feces than would small prey animals. This phenomenon occurs because large prey are composed of proportionately more highly digestible protein-rich flesh,

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Table 16-2. Prey items identified by hair and bone remains in 832 puma fecal samples and four stomachs collected from the San Andres Mountains, New Mexico, during 1985–1995 (adapted from Elmer 1997). Species Desert mule deer Rodents Leporids Puma Badger Unidentified birds Pronghorn Skunk Desert bighorn sheep Oryx Box turtle Coyote Javelina Ringtail Vegetation

Frequency

Percent frequency

716 46 35 17 16 6 6 6 5 3 1 1 1 1 167

85.6 5.5 4.2 2.0 1.9 0.7 0.7 0.7 0.6 0.4 0.1 0.1 0.1 0.1 20.0

but small prey are composed of relatively larger proportions of bones, hide, and hair, which are more likely to pass through the digestive tract (Floyd et al. 1978). Hence, Ackerman’s correction factor would give a more-accurate estimate of the relative biomass that each prey species contributed to puma diet. We used only those prey items that comprised more than 0.5 percent of the diet by frequency of occurrence and applied the correction factor to those prey that weighed more than 1 kg; for smaller prey, we used their estimated average weight (Ackerman 1982). Desert mule deer comprised 92.4 percent of the biomass consumed by pumas (Table 16-3). Cadavers, fecal and stomach analyses, and relative biomass and number of each prey species consumed clearly indicated that energetic and nutritional demands of pumas on the San Andres Mountains were strongly linked to deer. Other ungulates were relatively minor contributors. Low availability and vulnerability of desert bighorn sheep, pronghorn, and oryx calves rendered these animals as sporadic victims of puma opportunism and, consequently, of relatively little importance to the overall nutritional and energy needs of pumas.

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Table 16-3. Puma prey utilization based on 832 puma fecal samples and four stomachs collected from the San Andres Mountains, New Mexico, during 1985–1995.

Preya Mule deer Leporids Porcupine Badger Squirrels Pronghorn Desert bighorn

Percent Estimated frequency weight (kg)b (A) (B) 85.6 4.2 3.2 1.9 1.3 0.7 0.6

44.0 1.3 5.0 7.0 0.3 40.0 53.0

Correction Relative Relative number factor biomass individuals (kg/feces)c consumed (%)d consumed (%)e (C) (D) (E) 3.52 2.03 2.16 2.22 0.30 3.38 3.84

92.4 2.6 2.1 1.3 0.1 0.7 0.7

41.4 39.4 8.3 3.8 6.5 0.4 0.2

aPrey

that comprised more than 0.5 percent of diet by frequency of occurrence in Elmer (1997). weights: Mule deer—assumed 27 percent were fawns that averaged 15 kg and 73 percent were one year or older that averaged 55 kg (masses of fawns from Anderson 1981; masses of adults from deer captured on San Andres Mountains in this study). Leporids—assumed 50 percent were jack rabbits and 50 percent were cottontail. Squirrels—assumed composition of 33.3 percent each of rock squirrels, white-tailed antelope squirrels, and New Mexico ground squirrels. Masses of leporids, porcupines, badgers, and ground squirrels from the Southwest Biological Museum, Albuquerque, New Mexico. Pronghorn masses from White Sands Missile Range records. Desert bighorn sheep— assumed 20 percent were lambs that averaged 29 kg and 80 percent were one year or older that averaged 59 kg (masses from Krausman et al. 1999). cC = 1.98 + 0.035 ¥ B (from Ackerman 1982:19). dD = (A ¥ C) / S (A ¥ C) ¥ 100. eE = (D 4 B) / S (D 4 B) ¥ 100. bEstimated

Small prey items, rabbits and hares in particular, were probably seized opportunistically to help pumas endure periods between deer kills. Possibly young pumas, including large cubs and independent subadults, had better success at killing small prey relative to killing ungulates and thus may have been responsible for the bulk of those prey in feces, but we have no supporting empirical data. We documented sixteen cases of pumas scavenging twelve mule deer, one desert bighorn sheep, and one oryx that died of nonpredation causes. Two deer were each used by two pumas at different times. The ungulates were scavenged from one to twenty-nine days after death. Pumas scavenged about 9 percent of the total number of ungulates that we found dead from nonpredation causes (i.e., deer, sheep, oryx, and javelina that died natural deaths plus accidental

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deaths resulting from unintended captures in our snares; Logan et al. 1999). Scavenging was done by thirteen male and three female pumas. All of the males were territorial adults. One of the female pumas was a subadult and two were adults that were not raising cubs. In Alberta, biologists found four carcasses of adult female moose scavenged by three adult female pumas and one adult male puma (Ross and Jalkotzy 1996). The motivation for an individual puma to scavenge a particular carcass may depend upon immediate circumstances, such as risk of harm to self or offspring from other dangerous predators (e.g., pumas, wolves, bears, coyotes), degree of hunger, and ease of killing live prey. Sometimes when a puma came to scavenge, cadaver tissues were fresh, such as if the animal had been dead for less than one day. But sometimes the tissues were putrid and laden with maggots and flies. Consumption of scavenged animals ranged from as little as 1–2 kg to almost complete consumption of edible parts. The pumas sometimes handled the carcasses just like prey they killed— dragging them to concealing vegetation, consuming vital organs first (i.e., heart, lungs, liver), eviscerating stomachs and intestines, covering remains with ground debris between meals, and scraping (males only) around feeding sites. These handling characteristics probably increased the number of ungulate carcasses that we included in the “probable puma kill” category. Scavenging by pumas on wild prey is an oddity in the literature (Anderson 1983), thus contributing to the conventional wisdom that pumas almost exclusively eat prey that they have killed. We certainly found a higher incidence of puma scavengers than any other studies, but we cannot reliably claim that this behavior occurred more frequently in the desert than in other environments. Our field policy of periodically checking on the status of carcasses (to be able to better characterize decomposition) while en route to other field activities may have simply enabled us to observe scavenging more often than did other biologists. Clearly, pumas on the San Andres Mountains were highly dependent upon mule deer for food. As we studied effects of puma predation on the mule deer population, we learned that the dynamics of the puma and deer populations in this relatively simple desert ecosystem were tightly linked.

LP > >

KX

1. Pumas are opportunistic predators, capable of killing prey in a wide range of sizes, from rabbits to moose. Prey size and competition with other predators may have influenced the evolution of puma size on a latitudinal gradient (i.e., puma size increases with latitude). 2. Desert mule deer were the most important prey to pumas on the San Andres Mountains, comprising about 91 percent of puma-killed animals we

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found, about 86 percent of the diet as measured by frequency of occurrence in feces and stomachs, and about 92 percent of total biomass consumed. Other important prey included leporids and rodents. Other ungulates, including desert bighorn sheep, pronghorn, and the exotic oryx, comprised a minuscule amount of the puma’s diet. 3. Pumas, particularly males, scavenged about 9 percent of cadavers of animals that died of nonpredation causes. Pumas handled scavenged carcasses as they would kills.

Chapter 17

Pumas and Desert Mule Deer

Mule deer were the most numerous large prey animals for pumas on the San Andres Mountains. Deer inhabited the mountains because food and water were relatively abundant there. In contrast, deer were rare or locally nonexistent in the comparatively desolate basins adjacent to the mountains. Not surprisingly, pumas were distributed principally on the mountains where prey were most abundant and vulnerable (recall Fig. 4-1). In that habitat, ample structural cover—furnished by shrubs, trees, tall grass, broken terrain, rock outcrops, and boulders—rendered advantages to the solitary, stalking, and ambush hunting style of the puma (Logan and Irwin 1985, Laing and Lindzey 1991).

Hypotheses, Predictions, and Terms Our research hypothesis was that puma predation was the strongest proximate limiting factor affecting deer population growth rates. A limiting factor is any factor that causes changes in production or loss of animals and hence contributes to population limitation (i.e., the upper limit that a population can reach in an environment; Caughley and Sinclair 1994:114). Factors such as predation, disease, and food supply are all limiting factors and can all operate on a population simultaneously. The distinction comes in determining which of these limiting factors most likely sets the upper limit of the prey population. If puma predation is the primary proximate limiting factor for the deer population, then two predictions must hold: (1) puma predation must be the most important proximate cause of mortality that affects deer population growth rates, and (2) experimental removal of pumas from the Treatment Area should 311

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be associated with an increase in deer survival rates, which are linked to a reduction in puma predation rates. We tested these predictions by quantifying puma predation behavior (i.e., diet, predation rates) and measuring the relationships of puma density and predation rates to deer population parameters. Puma predation rates on radio-collared deer were particularly informative because they came the closest to measuring the total response of puma predation, which is the product of the numerical response (i.e., changes in predator numbers with prey density) and the functional response (i.e., variation in the number of prey consumed per predator as prey density changes) (Holling 1959, Pech et al. 1992, Caughley and Sinclair 1994, Messier 1995). This was our most direct way of estimating the proportion of the breeding-age deer killed by pumas (Marshall and Boutin 1999). Finally, we tested the self-limiting hypothesis developed by Seidensticker et al. (1973), which postulates that pumas evolved a social system to limit their population so that they do not overexploit their prey. The drought that struck the San Andres Mountains during our research provided us with a natural experimental setting in which to test this hypothesis. If the pumas fit the hypothesis, we would expect them to respond to a severe deer population decline by exhibiting slowed population growth or a decline in density to the extent that they did not hasten the deer population decline.

Characteristics of Dead Deer We found 540 dead desert mule deer during 1985–1995. Pumas killed 89 percent (n = 479) while 11 percent (n = 61) died of other causes. Fawns comprised 22 percent (n = 107) of the total number of deer killed by pumas; 71 percent of those were six months or younger (Table 17-1). When we excluded the radiocollared deer from the total (n = 77 during 1986–1995) and included only those deer killed by pumas that we found by chance during our field work (n = 402), then fawns comprised 26.6 percent of the sample of deer killed by pumas. Because pumas almost completely consumed fawns, we suspect that fawns were somewhat underrepresented in the kill sample. Also, because fawns were almost completely devoured, we could not ascertain the gender of sixty-seven fawns. Of those we could identify, there were fifteen bucks and twenty-five does. The ratio was not different from a hypothetical 1:1 sex ratio at birth [1]. The sample of sixty-one deer that died of causes not related to puma predation (Table 17-1) was too small to make any meaningful comparisons with puma-killed deer. Furthermore, because we documented puma kills throughout the year and the sex and age population composition counts of deer were limited to winter or fall, we could not reliably test if pumas selected among sex and age groups of deer.

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Slide @318%

PHOTO 27. A mule deer buck killed and eaten by a puma.

Nonetheless, it was clear that puma predation was the most important single proximate cause of death in desert mule deer on the San Andres Mountains, which supported our first prediction.

Fates of Radio-Collared Deer Fates of radio-collared deer further emphasized the importance of puma predation as a proximate limiting factor. We monitored 175 radio-collared deer (ninety-one bucks, eighty-four does) that were one year or older for 153,137 deer-days (74,067 buck-days, 79,070 doe-days) during biological years 1987–1988 to 1993–1994 to quantify annual survival and agent-specific mortality rates. Each year we monitored twenty-eight to fifty-three bucks and twenty-seven to fifty does. Because of the ruggedness of the mountains, we sometimes lost radio contact with deer for days or weeks at a time. So once per month we extended one of our weekly telemetry flights to locate radio-collared pumas to also recontact “lost” deer. Hence, the number of days that lapsed after a deer’s death until we could examine the carcass varied widely, averaging 19 ± 12 days (range = 3–61, median = 18). Pumas killed about sixty-two of the deer (35.4 percent), including thirty-five bucks and twenty-seven does. Radio-col-

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lared pumas were implicated in at least thirty-nine (63 percent) of those deaths. Twenty-nine (16.6 percent) other radio-collared deer, including eighteen bucks and eleven does, died of causes that showed no evidence of puma predation. We lumped all such deaths into a category called “other causes,” because we frequently could not ascertain specific agents of death. Still, we could tell that none of the deer was likely killed by pumas. In most cases, we could not determine the proximate causes of death due to advanced tissue autolysis, but coyotes apparently killed four of the deer (i.e., 13.8 percent of deaths from “other causes,” 4.4 percent of all deaths). Radio-collared bucks that died averaged 6.1 ± 2.3 years of age, which was very similar to the average of 6.7 ± 2.1 years for deceased does [2]. Because we did not sample the age distribution of the living deer one or more years old, we could not interpret how the age distribution of dead deer compared with survivors. We estimated survival rates and agent-specific mortality rates for radio-collared deer using Micromort software (Heisey and Fuller 1985a), the same technique that we used to compute survival rates for radio-collared pumas. Survival rates of bucks and does one or more years old fluctuated relatively little during biological years 1987–1988 to 1991–1992. During those years survival rates were relatively high. Buck survival rates ranged from about 0.81 to 0.90 and doe survival rates ranged from about 0.83 to 0.92. But survival rates for both sexes declined substantially during the final two full years that we quantified deer survival rates (Table 17-2); survival rates for bucks and does were about 0.62 and 0.75, respectively. The years 1992–1993 to 1993–1994 included two of the three years of severe growing-season drought on the San Andres Mountains. During the seven-year span, bucks tended to have lower survival rates than does, but only rates in 1990–1991 were significantly different (Table 17-2) [3]. We projected deer survival rates for 1994–1995, even though our research ended in March 1995, to see if the declining trend continued. We did this letting Micro mort compute the daily survival rates for radio-collared bucks and does (n = 14 each sex) that we monitored during the 238 days in the interval and assumed that those rates would hold constant throughout the year (i.e., bucks = 0.99825022365, does = 0.99926552365). The resulting survival rates for bucks (0.53) and does (0.76) suggested that survival rates for deer one or more years old would stay low during the third year of drought. Puma predation rates on radio-collared bucks and does fluctuated during the seven-year span (Table 17-3). During the first five years, predation rates on bucks ranged from about 0.06 to 0.19 and predation rates on does ranged from about 0.04 to 0.12. Then, during the drought years, puma predation rates on the deer increased substantially to about 0.28–0.30 on bucks and 0.23–0.25 for does. Bucks and does were about equally susceptible to puma predation during

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Table 17-2. Survival rates of radio-collared desert mule deer, San Andres Mountains, New Mexico, 1987–1995.a Biological 1987–88 1988–89 1989–90 1990–91 1991–92 1992–93 1993–94 1994–95d

Yearb

Deer-days

Bucks Rate

6748 10434 10199 13626 14103 11326 7631 2286

0.90 0.81 0.81 0.81c 0.86 0.62 0.62 0.53

95% C.L.

Deer-days

Does Rate

0.77–1.0 0.69–0.96 0.68–0.96 0.70–0.94 0.76–0.97 0.48–0.79 0.46–0.83

9014 11483 14075 12879 12901 11243 7475 2723

0.89 0.88 0.83 0.92c 0.84 0.75 0.75 0.76

95% C.L. 0.77–1.0 0.78–1.0 0.73–0.95 0.83–1.0 0.74–0.97 0.62–0.90 0.59–0.94

aSurvival rates and 95 percent C.L. (Confidence Limits) were computed using Micromort software (Heisey and Fuller 1985a,b). bBiological years spanned August–July each year. In years 1987–1988 to 1993–1994, twenty-eight to fifty-three bucks and twenty-seven to fifty does were monitored. cSurvival rates for bucks and does were significantly different (Z = 1.476, P = 0.07). dThe 1994–1995 year extended only from August to March due to termination of the study. In that period, fourteen bucks and fourteen does were monitored. Annual survival rates for bucks and does were projected from daily survival rates computed for the 238 days the deer were monitored in the interval; in other words, bucks = 0.99825022365 ; does = 0.99926552365.

the seven-year span; only in 1990–1991 were puma predation rates significantly different [4]. There appeared to be a strong interaction between growing-season (July through September) droughts and puma predation rates on deer one or more years old. Again, we asked ourselves if the trend of increased puma predation rates would hold during 1994–1995. We used the daily survival rates and daily puma predation rates (i.e., bucks = 0.00174978, does = 0.00073448) computed using the program Micromort to estimate puma predation rates for the entire interval (see Heisey and Fuller 1985a and Table 17-3). Results suggested that high puma predation rates on bucks (0.47) and does (0.24) would continue with the drought. Death rate from “other causes” also varied for both sexes (Table 17-3). Rates for bucks ranged from 0 to 0.13, while rates for does ranged from 0 to 0.08. During the seven-year span, bucks appeared to be somewhat more susceptible to “other causes” of mortality than does [5]. Rates of death from “other causes” did not increase during the drought years, unlike puma predation rates. To the contrary, rates tended to decline for both sexes. In the last year of our study, 1994–1995, none of the radio-collared deer died of “other causes.”

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FIGURE 17-1. Rates of survival, puma predation, and death from other causes for radio-collared mule deer, San Andres Mountains, New Mexico.

Putting all these rates together—survival, puma predation, and death f rom “other causes”—suggests that puma predation and “other causes” of m o rtality trade off in re l a t i ve importance to survival of deer one or more years old (Fig. 17-1). An inverse relationship emerged between rates of puma p redation and death from “other causes,” which was stronger for does than for bucks [6]. No t a b l y, during the drought years, puma predation on bucks and does increased mark e d l y, while deaths from “other causes” waned. This suggested that puma predation on deer was partially compensatory; that is, puma predation substituted for “other causes” of mortality in some instances. We would expect the degree of compensatory mortality via puma pre d a t i o n to increase during drought years because more deer would likely suffer fro m malnutrition. Our data on condition of deer killed by pumas was too limited to test this

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idea; nevertheless, it showed that puma predation is partially compensatory. During the study, we were able to examine femur marrow in 106 deer one or more years old (fifty-six bucks, forty-six does, four undetermined sex) that were killed by pumas 0.5–16 days ( x– = 5.1 ± 4.1, median = 4.0) before we inspected their remains. This sample comprised 28 percent of the total number of deer (n = 372) one or more years old that we found killed by pumas during our study. Of the sample, seventy-four had marrow that was white and pink in color, with a firm consistency like candlestick wax. These characteristics suggested that the deer were probably not metabolizing fat in the long bones to meet energy demands, and thus they could have been in good nutritional condition. Another thirty-two deer (sixteen bucks, thirteen does, three undetermined sex) had marrow that was colored red, pink, yellow, amber, or orange and had the consistency of gelatin. Characteristics of the femur marrow in this latter group indicated that fat depletion had reached extreme levels in the long bones, the last fat reserves available for energy metabolism. This condition suggested the animals were in extremely poor condition and were probably dying (Mech and DelGuidice 1985). Hence, it appeared that at least 30 percent of the puma predation on this sample of 106 deer one or more years old was compensatory mortality. Still, survival rates appeared to respond to reduction in puma numbers on the Treatment Area, suggesting that some puma predation was also partially additive. An increase in buck survival in 1991–1992 corresponded with the lowest number of pumas and is correlated with a reduction in puma predation. Similarly, an increase in doe survival in 1990–1991 coincided with the removal of pumas and a decline in puma predation. These dynamics satisfied our second prediction—that removal of pumas should result in increased deer survival. It appeared to us, as we carefully inspected the carcasses of many of the deer, that some were in sound health prior to being killed by a puma. Pumas are large powerful predators, perfectly capable of bringing down even the healthiest deer if they can position themselves close to the prey for the critical final attack. Pumas can accomplish this with an undetected stalk. Or deer, regardless of their state of health, may place themselves in mortal danger simply by moving to a puma waiting to ambush. Another way we examined the effect of puma predation on deer was by pooling the radio-collared bucks and does together to compute deer survival rates and agent-specific mortality rates (Table 17-4). In doing this, we were treating all the radio-collared deer as sentinels to puma predation (i.e., major prey items susceptible to puma predation). We postulated that deer survival rates were strongly related to puma predation. A linear model was unequivocal; about 90 percent of the variation in deer survival rates was explained by puma predation rates [7]. This would further support our first prediction, because we would

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Table 17-4. Survival rates and agent-specific mortality rates of radio-collared deer (bucks and does pooled), San Andres Mountains, New Mexico, 1987–1994.a Rates Biological Year 1987–88 1988–89 1989–90 1990–91 1991–92 1992–93 1993–94

Survival

95% C.L.

Puma predation

95% C.L.

Other causes

95% C.L.

0.89 0.85 0.82 0.86 0.85 0.68 0.68

0.80–0.99 0.76–0.94 0.74–0.91 0.79–0.94 0.78–0.93 0.58–0.79 0.56–0.82

0.07 0.09 0.08 0.12 0.06 0.25 0.28

0.0–0.14 0.02–0.16 0.02–0.14 0.04–0.19 0.01–0.12 0.16–0.35 0.16–0.40

0.04 0.06 0.10 0.03 0.09 0.07 0.04

0.0–0.10 0.0–0.12 0.03–0.16 0.0–0.06 0.03–0.15 0.01–0.12 0.0–0.09

aSurvival

rates and agent-specific mortality rates with 95 percent C.L. (Confidence Limits) were computed using Micromort software (Heisey and Fuller 1985b).

expect variation in survival rates of breeding-age deer to relate to deer population growth rates. Even if puma predation is the primary proximate limiting factor, a deer population can still grow if reproduction outpaces mortality. In fact, this phenomenon has been documented. In the central Idaho wilderness, mule deer and elk increased in numbers even though they were primary prey (70 percent aggregate frequency in feces) for a puma population similar in density to the puma population on the San Andres Mountains (Hornocker 1970, Seidensticker et al. 1973). As we have mentioned previously, the Idaho biologists hypothesized that pumas in that environment evolved a social system that limited their densities below a level set by absolute numbers of deer and elk (Seidensticker et al. 1973). A population of mule deer in southern Utah increased even though it was the mainstay (81 percent of biomass consumed) for a low-density puma population that was about one-third the density of the Idaho population (Ackerman 1982, Lindzey et al. 1994). Biologists there explained that the pumas may have been behaving in accordance with the hypothesis offered by the Idaho researchers, or that the deer population did not increase enough to cause a numerical response in the puma population (Lindzey et al. 1994). And in the Northern Yellowstone Ecosystem, where a puma population was increasing, puma “predation was neither a major source of mortality nor a significant factor limiting the numbers or growth rates of elk and mule deer populations.” There, pumas “removed about

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2–3% of elk and 3–5% of mule deer each year” (Murphy et al. 1998b:27). Biologists there explained that open, nonforested habitats used by elk and deer, and migration of deer away from puma habitats in winter, provided those ungulates with spatial and temporal refuge from puma predation (Murphy et al. 1998b). Our next aim was to assess the influence of puma predation on deer population growth on the San Andres Mountains.

Mule Deer Population Dynamics We modeled the deer population so we could associate changes in deer population parameters with puma population size and predation rates. The model was a relatively simple deterministic, discrete time model that simulated the dynamics of the deer population on the Treatment Area, where most data-gathering procedures for deer population parameters were focused. By deterministic, we mean that population parameters put into a mathematical equation determine the estimated change in the deer population. And by discrete time, we mean the model is applied in annual units (i.e., the biological year, August through July) beginning with the deer birth pulse. This approach did not require us to know what the deer population size actually was for the purpose of estimating deer population dynamics during the study. Instead, we were able to calculate the finite rate of increase each year (l = Nt + 1 / Nt), where l > 1 means the deer population increased, and l < 1 means the population declined. Then by multiplying the annual ls to the projected deer population size the previous year, starting with one thousand deer in the first year, we could simulate the trajectory of the deer population. The basic model was Nt + 1 = B (sb ) + D (sd ) + [AD (fa ) + YD (fy ) - Fd ] Nt = the base population of 1,000 deer one year or older at the beginning of the biological year (August through July). Nt + 1 = deer population size at the end of the biological year. It reflects the change in the 1,000 deer base population (i.e., 1,000 + births – deaths). B = estimated number of bucks (one year or older) in the base population. D = estimated number of does (one year or older) in the base population. AD = the number of does two years or older. YD = the number of yearling does. fa = fetal rate of does two years or older. fy = fetal rate for yearling does. sb = survival rate for bucks.

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sd = survival rate for does. Fd = the number of fawns that died. Although most of the model parameters were gathered in surveys conducted on the San Andres Mountains (Table 17-5), we had to rely on some estimates from other desert mule deer populations that were studied by the New Mexico Department of Game and Fish in other parts of southern New Mexico. Furthermore, because we did not know how some parameters might vary during drought conditions, we varied some of the parameters ourselves. Consequently, we developed six different population simulations, or models (i.e., six models numbered 1 to 6, Table 17-6), to simulate the dynamics of the deer population on the Treatment Area. Model parameters, their origins and variations, and our assumptions are described in detail in Appendix 4. Results from the deer population model were parsimonious with our perceptions of deer population dynamics through direct observation. All six models indicated that the deer population increased during the first five years (1987–1988 to 1991–1992), relatively rapidly at first, then gradually. But during the last three years (1992–1993 to 1994–1995) the deer population declined rapidly (Table 17-7). Models 1 and 3 and models 5 and 6 produced the same estimates of l each year when l was rounded off to three significant figures; this indicated that the slight decline in yearling doe fetal rate (0.9–0.81) had virtually no effect on the model simulations. Consequently, we decided to depict the range of deer population dynamics by using simulations from models 1, 2, 4, and 6 (Fig. 17-2). Not surprisingly, the two parameters that affected the dynamics of simulations the most were fawn production and survival rates of deer one or more years old. If the number of surviving fawns exceeded the number of deaths in deer one or more years old, then the population increased; if it did not, the population declined. By extension then, the role that pumas played in these dynamics clearly depended upon predation rates on deer.

Puma Predation and Mule Deer Population Growth How did puma predation impact growth patterns of the deer population? Considering that deer population trends and growth rates were quite similar among models 1, 2, 4, and 6, we chose the two models representing the most pessimistic (model 2) and optimistic (model 6) simulations of the deer population to test for the influence of puma predation. Our premise—puma predation suppressed deer population growth—was tested by regressing annual deer population growth rates of models 2 and 6 (i.e., l, Table 17-7) on corresponding annual puma predation rates on radio-collared deer (Table 17-4). Recall that we

Table 17-7. Finite rates of increase (l) estimated by modeling the desert mule deer population on the San Andres Mountains, New Mexico, 1987–1995. Biological Model 1 Year la 1987–88 1988–89 1989–90 1990–91 1991–92 1992–93 1993–94 1994–95 aModels bModels

1.13 1.18 1.05 1.06 1.06 0.91 0.86 0.70

Model 2 l

Model 3 la

Model 4 l

Model 5 lb

Model 6 lb

1.13 1.18 1.05 1.06 1.06 0.84 0.77 0.70

1.13 1.18 1.05 1.06 1.06 0.91 0.86 0.70

1.17 1.18 1.05 1.06 1.06 0.84 0.77 0.70

1.17 1.18 1.05 1.06 1.06 0.91 0.86 0.70

1.17 1.18 1.05 1.06 1.06 0.91 0.86 0.70

1 and 3 produced the same l each year when l was rounded off to three significant figures. 5 and 6 produced the same l each year when l was rounded off to three significant figures.

FIGURE 17-2. Desert mule deer population trend on the San Andres Mountains, New Mexico.

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FIGURE 17-3. Relationship of deer population growth rates (lambda) to puma predation rates on radio-collared deer (bucks and does combined), San Andres Mountains, New Mexico.

considered puma predation rates on radio-collared deer to represent the total response of puma predation (i.e., the product of the numerical response and the functional response). In this specific case, it was the total response on the reproducing segment of the deer population. The test suggested that puma predation rates had a negative relationship to deer population trends and explained 87 percent and 79 percent of the variation in deer population growth rates for models 2 and 6, respectively [8] (Fig. 17-3). This meant that puma predation suppressed deer population growth, thus satisfying our first prediction. The linear model [8] suggested that the mule deer population increased when puma predation rates were less than 0.14 and less than 0.17 for deer models 2 and 6, respectively. Another way of looking at conditions favorable for deer population increase was by a univariate model that used deer survival rates to account for all mortality factors in aggregate. Our model suggested that the deer population grew when deer survival rates exceeded 0.80 and 0.77 for deer models 2 and 6, respectively [9]. Deer death rates from “other causes” were uninformative in explaining deer population growth rates [10]. Deer population growth was also influenced by fawn production. A linear model showed a strong positive relationship between ls of deer models 2 and 6 and corresponding fawn:doe ratios [11] (Fig. 17-4). This explained 80 percent

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and 92 percent of the variation in deer population growth rates generated by models 2 and 6, respectively. Furthermore, this model [11] predicted, given the environmental conditions during our re s e a rch, that the deer population increased when winter fawn counts exceeded about thirty-nine and thirty-seven fawns per 100 does for deer models 2 and 6, respectively. Below those ratios, the deer population declined. Consequently, two key proximate factors strongly influenced growth rates of the desert mule deer population: puma predation and fawn production. A multiple regression model using puma predation rate and fawns per 100 does as independent variables suggests that those two factors were strong determinants of deer population growth rates, explaining 94 percent of the variation in ls from deer models 2 and 6 [12]. All this made sense because puma predation directly removed animals from the deer population while fawn production added to it. To identify the independent variable with the greatest incremental predictive power, we sequentially examined partial correlation coefficients. The partial correlation coefficient measures the strength of the relationship between the dependent variable (i.e., in this case l) and a single predictor variables (e.g., puma predation rate) when the effects of other predictor variables (e.g., fawns / 100 does) in the model are held constant (Hair et al. 1995). Puma predation had a stronger influence than fawn production on deer population growth rates generated by deer model 2, but for model 6, fawn production was slightly more

FIGURE 17-4. Relationship of deer population growth rates (lambda) to fawn production, San Andres Mountains, New Mexico.

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important than puma predation [12]. If puma predation also altered the number of fawns that survived, then puma predation was the strongest proximate limiting factor affecting deer population growth rates. Other than the proportion of fawns in the puma-kill sample (i.e., about 27 percent), we had no direct empirical data on kill rate of fawns. So, we assessed this indirectly. We postulated that puma predation altered fawn numbers and tested this with a measure of association between fawn counts and puma numbers. The test indicated a negative correlation between the ratio of fawns per 100 does counted in winter deer population surveys (Table 17-5) and adult puma density in January in the Treatment Area (see Chapter 10, Table 10-2) [13]. The sample of puma-killed deer had already established that pumas were eating fawns, and now we had an indirect deduction that fawn numbers were substantially altered by puma predation. Moreover, there was a negative correlation between the ratio of fawns per 100 does and puma predation rates on radio-collared deer one or more years old [14]. In other words, more fawns in the population meant that puma predation rates on older deer would diminish; fewer fawns meant greater predation pressure on older deer. This was a mechanism that explained why puma predation rates in radio-collared deer did not exhibit an increasing trend during the first puma population increase phase in the Treatment Area from 1987–1988 to 1989–1990 (Fig. 17-5). This all made sense in light of other puma research demonstrating the

FPO @ 75%

FIGURE 17-5. Relationship of adult puma numbers to predation rates on radio-collared deer (bucks and does combined), San Andres Mountains, New Mexico.

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importance of deer fawns and other juvenile hoofed prey to pumas. Biologists in the central Idaho wilderness (Hornocker 1970) and southern Utah (Hemker 1982) found that pumas killed fawns in greater proportions than their occurrence within the population. In addition, female pumas selected fawns on the east slope of California’s Sierra Nevada. There, puma mothers (the segment of the population with the greatest energy demands, Ackerman 1982) selected fawns less than four months old (Pierce et al. 2000a). A preference for fawns should not be surprising; on average, they are probably considerably easier to stalk and kill than adult deer. Probably for the same reason, pumas also selected elk calves in central Idaho (Hornocker 1970). In Yellowstone National Park, pumas selected elk calves above all other classes of prey (Murphy et al. 1998b). Similarly, along the east slope of the Rocky Mountains in southwestern Alberta, pumas selected calf moose over yearlings and adults, and male pumas appeared to prefer moose calves even to other species of prey, including mule deer, elk, bighorn sheep, and white-tailed deer (Ross and Jalkotzy 1996). Pumas relying on feral horses as fodder for part of the year in California and Nevada selected foals almost exclusively (Turner et al. 1992). From this we inferred what seemed obvious: fawns were critical for puma food and deer population growth. When fawn production was high, the fawn segment of the population probably absorbed a critical level of the puma predation, in essence diverting predation pressure away from the older, reproducing segment of the deer population. And there were enough fawns left over to outpace mortality in the deer population as a whole. Thus, the deer population grew. However, during the drought years, fewer fawns were produced and survived, probably because of a combination of lower birth rates, viability, and predation. Hence, during the drought, the brunt of puma predation fell on older deer. Productivity and survival of mule deer fawns has been shown to be strongly affected by habitat conditions. Mule deer does on “severely depleted” summer range in central Utah were found to have lower ovulation rates, lower fetal rates, and fawns with lower masses than does on “good summer range” in southern Idaho (Julander et al. 1961). On a desert range in central Arizona, researchers found an interaction between fawn survival, forage conditions they linked to rainfall patterns, and predation from a host of predators, including pumas, coyotes, and black bears (Smith and LeCount 1979). In our Chihuahua Desert study area, where the fawning period coincides with the summer monsoon season, mule deer does are dependent upon late-summer rains to produce highnutrient and high-energy foods they need for lactation. In the closely related black-tailed deer, does in peak lactation and with single fawns increased their food intake by 35 percent, while does with twins increased theirs by 70 percent

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(Sadleir 1982). Mule deer does also have considerably higher water requirements during late pregnancy and lactation (Short 1981); they may need to consume more than 5 liters of free water per day (Hervert and Krausman 1986). Does try to partially meet these requirements by seeking out habitats with better forage characteristics and water sources (Hervert and Krausman 1986, Ordway and Krausman 1986). We also expect the increase in herbaceous ground vegetation (i.e., grasses, tall forbs) to more effectively hide fawns from predators (Teer et al. 1991). Once fawns are weaned, high-quality foods are needed for maintenance and growth (Bronson 1989), and to give them the energy, strength, and agility to better evade predators. Drought in three consecutive growing seasons on the San Andres Mountains must have been strenuous on deer. Ecological carrying capacity (i.e., the natural limit of a population set by resources in the environment, Caughley and Sinclair 1994:117) for deer was low in that period of our research. Drought not only depleted deer foods, but also caused some perennial springs to go dry. In the first year of drought, fawns were probably most affected, followed by mothers. Fawns are more vulnerable than adults to water deprivation because their greater relative metabolic rate and smaller body size increase their water demands (Short 1981, Hervert and Krausman 1986). Due to the strain of pregnancy and lactation, we would expect does entering winter in poor condition to have lower fertility rates and to produce smaller, more-vulnerable fawns the following summer. Lower fertility rates and lower fawn survival probably contributed to the decline in fawn production in subsequent years. We would expect the intensity of the effects of weather and food on deer reproduction and survival to depend on the size of the deer population relative to ecological carrying capacity (Picton 1984). Mule deer also abandon home ranges where traditional water sources go dry to search for other water sources (Hervert and Krausman 1986). Not only does this behavior impose abnormally high energy costs, but we believe it also makes deer more vulnerable to puma predation as they explore unfamiliar surroundings. In addition, deer normally concentrated around free water during the hot, dry part of the year (normally April through June) on our study area. If these effects actually occurred, increasing the susceptibility of deer to physiological stress, then we hypothesize that compensatory mortality from puma predation increased during the drought. In other words, a larger proportion of the deer that pumas killed would have died anyway, particularly fawns (see Bartmann et al. 1992, Singer et al. 1997). In addition, the hot, dry ambient environment and deer concentrations probably interacted to boost puma predation rates. Deer carcasses decompose rapidly under those conditions—in about two or three days. Deer concentrating around water sources could make it easier for pumas to kill another deer, compressing time spans between kills. Dynamics such as these

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could enhance food acquisition for pumas, thus increasing fertility rates and cub survival, at least in the short term, and thereby contribute to a delay in the decline of the puma population itself.

Some Behavioral Interactions between Deer and Pumas Information on how prey respond behaviorally to the presence of pumas has been limited to Hornocker’s (1970:35) observations in central Idaho. “The mere presence of a [puma] or family of [pumas] in a locality or watershed does not appear to alarm game animals. When a kill is made, however, the reaction is striking. Deer and elk immediately leave the area, cross to the far side, and in some instances leave to enter a different drainage. This behavior, observed without exception, acts to distribute game animals.” On the San Andres Mountains, we could not detect if deer abandoned locales because pumas killed prey there. However, we made several observations indicating that some deer did not move away from areas where pumas killed prey. As we crept upon a puma family to count cubs, we disturbed seven deer, some from their day beds, within 100 m of F45 and her three two-month-old cubs as they ate a buck that F45 killed that day. Another time, we watched at least eight deer trotting through an area about 100 m from a buck that had been killed by F183 but had been usurped by a lone coyote. The deer passed within about 170–250 m from the two predators. In another case, we disturbed twelve deer when they were about 60 m from a snare site where two pumas consorted. F61 was caught in a snare, and M46 stayed beside her until we approached within 50 m. F61 had killed two ten-yearold does at the spring within a twenty-four-hour span and had cached the carcasses about 27 m apart. One deer was cached under juniper trees where we snared F61 and the other lay partially covered with leaves and sticks (pawed over it by the puma) at the edge of a small spring-fed pool of water. The male puma left the area while we chemically immobilized the female to tag her. After we finished, we left the still-groggy puma to recover in shade of juniper trees about 25 m up slope from the water. At this time the twelve deer we had disturbed earlier walked down to the pool in single file to drink! This latter instance occurred in July, near the peak of hot, dry weather, and suggests that water stress aggravates vulnerability of deer to puma predation. Observations we made in the summer drought of 1994 exhibited how pumas exploited prey that came to water sources. In the month of June, female puma F149 killed at least seven deer within a 60-m radius of perennial Dugout Spring, located 1.9 airline km from the nursery where she gave birth to three male cubs on 1 June. These deer included four does that were two to eight years old (x– = 6 ± 2.7 years) and three young does ten to eleven months old. Consump-

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tion of the carcasses varied from about 40 up to 100 percent of edible tissues. The carcass of one of the short yearlings was abandoned after only three days, probably because it was putrid. F149 frequently used this nearest water source to her nursery, driven there by the high water requirements of lactation and the extreme hot, dry ambient environment. This environment also concentrated deer around the spring, magnifying their vulnerability to F149. But puma predation was not the only cause of death at Dugout Spring that June: two other deer, a four-year-old buck and a seven-year-old doe, apparently lay down and died 8–11 m from the water. Rapid tissue autolysis prevented a determination of exact causes of death, but we surmised that the deer deaths were related to extreme weather conditions and malnutrition. The same summer, territorial male M36 occasionally hunted around Buckhorn windmill, which trickled water into a small earthen impoundment. Among dense willow baccharis and cattails, he killed five ungulates within a span of about fourteen days, including three mule deer does that were four to six years old ( x– = 4.7 ± 1.2 years), one fawn buck (probably an offspring of one of the does), and one yearling pronghorn buck. He also killed a coyote that apparently came to scavenge one of his kills. M36’s consumption of the carcasses varied from about 10 to 90 percent of edible tissues. Rapid decomposition of the carcasses in the dry heat and the concentrated available prey probably contributed to this extraordinarily high kill rate.

Did Puma Predation Limit the Deer Population? Puma predation did not—by itself—stop the deer population from increasing on the San Andres Mountains. Deer model simulations, which we emphasize were consistent with our field observations, indicated that the deer population increased in the face of an increasing puma population during biological years 1987–1988 to 1990–1991 (Fig. 17-2). The deer population continued to grow through 1991–1992 as the puma population on the Treatment Area was suppressed by our experimental removal. Clearly, although predation by pumas was slowing the rate of increase in the deer population (i.e., it was the major proximate limiting factor), it was not stopping growth. Thus, in that span of time, puma predation did not limit the deer population. In the absence of drought, we would have expected the deer population to continue growing until densitydependent effects from intraspecies competition for food regulated it or until the puma population grew to a level to limit it through predation. But in this relatively unstable desert environment, drought drastically changed the dynamics between pumas and deer. It triggered a threshold response due to a combination of lower fawn production (i.e., via lower birth and survival rates) and

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substantially greater predation on breeding-age deer. From 1992–1993 through 1994–1995, the deer population declined sharply. Puma predation was the single most important proximate cause of mortality that accelerated the decline. However, puma predation cannot be said to have limited the deer population (i.e., set its upper limit), because the deer population probably would have declined during the drought even without pumas on the scene. It was the food supply for the deer that ultimately limited the deer population, while pumas were the major proximate cause of death driving the deer population downward.

Did Pumas Limit Their Own Density and Not Harm Their Food Supply? We concluded that pumas on the San Andres Mountains did not limit their population below a level set by the prey as Seidensticker et al. (1973) hypothesized for pumas in the Idaho wilderness. Instead, the large-mammal community suffered destabilizing effects of drought and puma predation. During the deer decline phase (i.e., 1992–1993 to 1994–1995), puma predation rates were inversely density dependent (i.e., depensatory), meaning that pumas were killing a larger proportion of deer as the deer population declined (Caughley and Sinclair 1994:15–16, Messier 1995). Furthermore, the puma population was increasing as the deer population was declining. Thus, the puma population exhibited a lag—a delayed numerical change in the puma population in response to the decline of its food base (Fig. 17-6). This type of lag has been exhibited in other tightly linked predator-prey systems such as wolves and moose on Isle Royale National Park (McLaren and Peterson 1994) and coyotes, lynx, and snowshoe hares in southwest Yukon (O’Donoghue et al. 1998). Not only did puma predation expedite the deer decline on the San Andres Mountains, but also we expected it to deepen and protract the low phase in deer numbers, at least until the puma population declined as well. In a variable environment like the desert, where the periodicity and amplitude of prey declines would be impossible to anticipate, it is difficult for us to imagine how pumas could evolve a social system to limit their population density below the level set by the prey. Independently, researchers studying pumas and mule deer in Round Valley on the east slope of the Sierra Nevada in California also concluded that pumas did not conform to the self-limiting hypothesis (Pierce et al. 2000b). Their study focused on a relatively small area of about 90 km2 where deer and pumas concentrated during the winter period extending from November through April. In winters 1992–1997, the biologists studied the spatial and temporal distributions of ten radio-collared adult pumas along with the spatial and tempo-

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FIGURE 17-6. Mule deer and puma population trends on the San Andres Mountains, New Mexico.

ral distributions of live radio-collared mule deer and sites where 112 radio-collared deer were killed by pumas. During the study, the estimated deer population increased from about 1,344 in 1993 to 1,913 in 1997. Conversely, the number of adult radio-collared pumas with winter distributions on the area declined from about six in the winter season 1992–1993 to three in 1996–1997. The biologists intimated there was a general decline in the puma population in the area due to deaths of adults, but data on puma population dynamics and exact mechanisms causing population decline were not stated. Such information might have explained why the puma population did not increase along with the deer population as would be expected in theory. Nevertheless, because the biologists found that the distribution of deer killed by individual pumas could be explained by the distribution of live deer alone, instead of by the partitioning of prey via territorial and mutual avoidance behavior (i.e., pumas did not sequester prey by defending it or excluding other pumas from prey-rich areas), and because puma distributions overlapped principally in areas where deer were more abundant, they inferred that pumas are “most likely limited by prey availability and not territoriality” (Pierce et al. 2000b). They also suggested that the corresponding seasonal migrations of the deer and pumas from low-elevation winter ranges to high-elevation summer ranges “decreased the likelihood that

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social interactions or a stable land-tenure system could have been regulating the population” (Pierce et al. 2000b, also see Pierce et al. 1999).

Cases of Pumas and Other Carnivores Limiting Prey Populations Evidence that puma predation limits prey populations has accumulated in recent years and suggests that pumas may not have limited their densities below a level set by the food supply in other areas. In the Montgomery Pass Wild Horse Territory along the California and Nevada border, biologists found that pumas limited the feral horse population by preying on foals, particularly those less than three months old. Over 80 percent of foal mortality was attributed to puma predation. Mule deer were also a staple for the pumas. These deer migrated into the wild horse territory each winter from the Sierra Nevada. Biologists believed that pumas switched seasonally between the two main prey species, utilizing mule deer during the winter and foals during May to October (Turner et al. 1992). This ability to switch to another prey probably magnified the depressive effect of puma predation on the horse population because the puma population was probably maintained at a higher level than it would have achieved if horses were the only food source year-round. A pronghorn population in central Arizona was limited by puma predation. The pronghorns were vulnerable to puma predation because they inhabited rugged, brushy terrain favored by stalking pumas (see Logan and Irwin 1985). Puma predation accounted for about 75 percent of deaths to adult doe pronghorns. Moreover, doe mortality from puma predation alone exceeded effective recruitment of female progeny (Ockenfels 1994). In the Great Basin Desert of Nevada sits a small 15-km2 basin where pumas were the main proximate mortality factor that reduced a porcupine population from more than eighty animals to fewer than five animals in only three years (i.e., a 94 percent reduction). In that environment, pumas depended principally upon mule deer for food. However, the mule deer population declined precipitously over a seven-year period, 1987–1993, apparently as a result of a persistent drought. It was during the latter two years of that period that puma predation on porcupines increased dramatically (i.e., eleven of fourteen deaths the first year, eleven of sixteen deaths the second year), driving the population to near extinction (Sweitzer et al. 1997). This case paralleled the effect that puma predation had on the small, isolated desert bighorn sheep population on the San Andres Mountains (see Chapter 18). Carnivores with which pumas evolved during the Holocene are also capable of limiting prey populations. Wolves limited moose populations in interior

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Alaska (Gasaway et al. 1983), Pukaskwa National Park, Ontario (Bergerud et al. 1983), and Isle Royale National Park Michigan (McLaren and Peterson 1994). Also, wolf predation caused declines in caribou populations in British Columbia (Bergerud and Elliot 1986, Seip 1992). Coyote predation limited a whitetailed deer population in Texas (Teer et al. 1991). There is also evidence that black bear predation limited a moose population in Saskatchewan (Stewart et al. 1985), and together grizzly and wolf predation limited a moose population in Yukon (Larsen et al. 1989). In the Glacier National Park area of northern Montana and southern British Columbia, predation by a host of predators, especially pumas and wolves, limited the white-tailed deer and elk populations (Kunkel and Pletscher 1999). In that rugged, densely vegetated landscape pumas and wolves mostly killed similar types of prey in similar spatial and temporal distributions. The predator-caused decline in deer and elk populations, seizing of puma kills by wolves, and direct killing of pumas by wolves suggested that those two carnivores engaged in exploitative and interference competition for food (Kunkel et al. 1999). Particularly in ecosystems where pumas compete with other carnivores for the same prey, it is difficult for us to conceive that pumas would evolve a social system to limit their own density below the level set by the prey unless their competitors do too.

What Limits the Puma Population? We hypothesize that the puma population on the San Andres Mountains was ultimately limited by food. The amount of prey actually vulnerable to the stalking and ambush hunting style of pumas is influenced by habitat characteristics. Habitat continuity, physiographic and vegetative structure, and food abundance and distribution all affect what prey species are present and their distribution, abundance, and vulnerability (Hornocker 1970, Seidensticker et al. 1973, Logan and Irwin 1985, Laing and Lindzey 1991, Murphy et al. 1998b, this study). Because of the strong link between pumas and deer, we expected the puma population to decline after the deer decline. No alternative prey was available in high-enough biomass to buffer the effects of the deer decline. Unable to switch to another food source, pumas could not sustain their relatively high population density. Our research tenure did not witness a puma decline, but there were portending signs: the adult puma population in the Treatment Area declined slightly by January 1995, and during the drought years the rate of population increase in the Reference Area declined. One to two years after we left the San Andres Mountains, two wildlife biologists—Mara Weisenberger (U.S. Fish and Wildlife Service, San Andres National Wildlife Refuge) and Dave Holderman (U.S. Army White Sands Missile Range, Environmental Services)—

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supported our prediction. Their field searches suggested that the puma population declined. Locales that traditionally held puma scrapes, or where puma tracks were predictably found, were now barren. We speculate there was a fouryear span from the first biological year of the deer population decline (1992–1993) to the first year that the puma population apparently declined (1995–1996). If puma density is ultimately limited by food, then we would expect a significant correlation between puma density or biomass and vulnerable prey biomass in areas where pumas and prey are protected from population-altering human exploitation. So far, such data on pumas are not available to test this hypothesis. However, support for this premise exists in literature on other large carnivores. The ecological equivalent of the puma in the Eastern Hemisphere is the leopard. Leopards and pumas are similar in body size and behavior, and they use a similar wide range of habitats and prey (see Bailey 1993). While analyzing data from African leopard populations in eleven sub-Saharan conservation areas, Stander et al. (1997) found a significant correlation between leopard biomass and available biomass of prey weighing 15–60 kg (r 2 = 0.72, P < 0.01). Leopard densities varied widely from 0.5 to 24 cats per 100 km2. The highest reported densities from four populations (i.e., 11–24 / 100 km2) were about two to five times that of the highest puma densities in North America (see Chapter 10, Table 10-7). Likewise for wolves, which can compete with pumas where the two carnivores are sympatric, Fuller (1989:20–21) examined the relationship of wolf density to ungulate density in twenty-five areas in North America and found that “average wolf densities are clearly correlated with biomass of ungulates” (r 2 = 0.72, P < 0.001).

How Would a Puma Population Respond to a Prey Crash? Other carnivores give insights into how pumas might respond to a severely diminished prey base. Wolves, coyotes, bobcats, lynx, and African lions exhibited lower body condition, reduced reproductive output, reduced survival, and reduced recruitment following prey population declines (Schaller 1972, Bertram 1973, Brand et al. 1976, Mech 1977a, Todd et al. 1981, Todd and Keith 1983, Parker et al. 1983, Knick 1990, Boertje and Stephenson 1992, Poole 1994, Mowat et al. 1996, O’Donoghue et al. 1997). We would expect pumas, particularly cubs, to have lower survival. Cubs would be especially vulnerable because mothers would have to hunt for longer periods, thus leaving cubs more exposed to predation, including cannibalism. Longer time spans between feedings of milk or meat would increase their risk of starvation, akin to African lion cubs during periods of prey shortages (Packer et al. 1988). Pumas would need to

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expend more energy to hunt increasingly scarce prey; thus, their physical condition would deteriorate. Some mothers might abandon cubs, as do cheetahs that have difficulty securing food (Caro 1994). In addition, we expect females to have lower pregnancy and birth rates. Some in particularly poor condition might fail to reproduce altogether, like lynx in a snowshoe hare decline (O’Donoghue et al. 1997). As intraspecies or interspecies competition for food increased, we would expect greater emigration rates in subadult females. At the extreme stage of prey shortage, pumas might increase their use of space in search of better hunting grounds, as bobcats do during a lagomorph decline (Knick 1990). Some might even become nomadic, as lynx do during hare declines (Ward and Krebs 1985, O’Donoghue et al. 1997). This activity might also increase antagonistic encounters with other pumas and carnivores, which may compete directly for prey or carrion. Pumas might also shift their diet toward smaller prey animals that may be carriers of lethal diseases such as plague, which killed adult female F68 in April 1995. Some pumas would simply starve to death (Shaw 1980, T. Ruth personal communication regarding starving pumas in northern Montana following prey decline). Starvation was the leading cause of death among adult and subadult female leopards in South Africa. But it also claimed some adult and subadult males (Bailey 1993). Apparently, the leopards had difficulty capturing prey during the dry season because of the lack of stalking cover. Bailey (1993) indicated that food-stressed leopards could become severely emaciated in one to three months. For pumas, lower birth and survival rates should result in population decline with the potential for population collapse if food shortage persisted. But before the puma population got to that point, it could threaten small populations of prey with local extinction—the main lesson of our next chapter.

LP > >

KX

1. Pumas killed 89 percent of 540 dead deer we found; 11 percent died of other causes. Fawns comprised about 27 percent of puma-killed deer we found by chance, but there was probably a negative bias to finding fawns. 2. Out of 175 radio-collared deer one year and older, pumas killed about 35 percent, while about 17 percent died of other causes. Survival rates for radio-collared deer fluctuated little during biological years 1987–1988 to 1991–1992 but declined substantially during 1992–1993 to 1994–1995 when effects of drought were prevalent. During drought years, puma predation rates also increased substantially. There appeared to be an inverse relationship between rates of puma predation and death from other causes, suggesting that puma predation is partially compensatory. A positive response of deer survival rates to puma reduction suggested that puma pre-

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3.

4. 5.

6.

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dation is also partially additive. Deer survival rates were strongly related to puma predation rates. Results from a deterministic, discrete time model showed that the deer population increased during biological years 1987–1988 to 1991–1992 but declined rapidly during 1992–1993 to 1994–1995. The deer population dynamics were consistent with our field observations. Two key proximate factors—fawn production and puma predation— strongly influenced deer population growth. Deer population limitation was determined by the interaction of puma predation, the strongest proximate cause of mortality, and deer habitat condition, as influenced by weather, which affected fawn production and survival and adult deer health and vulnerability to predation. Pumas did not adjust their population downward as the deer population crashed. Instead, puma numbers increased or remained high as the deer population declined, thus exhibiting a lag. Puma predation hastened the deer decline. Consequently, we concluded that the self-limiting hypothesis did not explain how pumas on the San Andres Mountains related to their prey base. We hypothesized that the puma population is ultimately limited by food.

LN N5LN5)L 1. Male:female sex ratio for fifteen buck and twenty-five doe fawns killed by pumas did not differ from 1:1. Chi-square test: c2 = 2.50, 1 d.f., P > 0.10. 2. Ages of radio-collared bucks that died were not different from ages of radiocollared does that died during the seven biological years 1987–1988 to 1993–1994. Two-sample t-test: t = –1.351, d.f. = 88, P = 0.18. 3. Tests for differences between buck and doe surv i val rates. Z test: 1990–1991, Z = 1.476, P = 0.07. All other years, Z = 0.128–1.229, P = 0.11– 0.45. 4. Tests for differences in puma predation rates on bucks and does. Z test: 1990–1991, Z = 2.499, P = 0.006; all other years, Z = 0.399–0.825, P = 0.21– 0.35. 5. Tests for differences in rates of death from “other causes” for bucks and does. Z test: years 1987–1988, 1988–1989, 1990–1991, 1992–1993, 1993–1994, Z = 1.330–2.133, P = 0.02–0.09; years 1989–1990, 1991–1992, Z = 0.282–0.802, P = 0.21–0.39. 6. Test for association between rates of puma predation and death from “other causes” on bucks and does. Spearman correlation coefficients: bucks rs = –0.50, P = 0.29; does rs = –0.71, P = 0.10. 7. Test for a linear relationship between survival rates of radio-collared deer

340

8.

9.

10.

11.

12.

13.

14.

PART IV. PUMA–PREY RELATIONSHIPS

(bucks and does pooled) and puma predation rates. Linear regression: deer survival rate = 0.9281 – 0.9129 (predation rate), P = 0.001, r2 = 0.90. Test for a linear relationship between deer model 2 ls and puma predation rates. Linear regression: l = 1.2232 – 1.5498 (predation rate), P = 0.002, r2 = 0.87. Test for a linear relationship between deer model 6 ls and puma predation rates. Linear regression: l = 1.2013 – 1.1780 (predation rate), P = 0.007, r2 = 0.79. Linear regression of deer model 2 l on survival rates of radio-collared deer (bucks and does one or more years old combined): l = – 0.3000 + 1.6323 (deer survival rate), P = 0.001, r2 = 0.89. Linear regression of deer model 6 l on survival rates of radio-collared deer (bucks and does one or more years old combined): l = 0.0177 + 1.2728 (deer survival rate), P = 0.003, r2 = 0.86. Test for a linear relationship between deer model 2 ls and deer death rates from “other causes.” Linear regression: l = 0.9803 + 0.5300 (death rate from “other causes”), P = 0.84, r2 = 0.009. Test for a linear relationship between deer model 6 ls and death rates from “other causes.” Linear regression: l = 1.0402 + 0.0200 (death rate from “other causes”), P = 0.99, r2 = 0.00002. Test for a linear relationship between deer model 2 ls and fawns per 100 does. Linear re g ression: l = 0.5692 + 0.0111 (fawns per 100 does), P = 0.003, r2 = 0.80. Test for linear relationship between deer model 6 ls and fawns per 100 does. Linear regression: l = 0.6002 + 0.0109 (fawns per 100 does), P = 0.0002, r2 = 0.92. Multiple regression models on ls for deer models 2 and 6: model 2 l = 0.8837 – 1.0652 (predation rate) + 0.0067 (fawns per 100 does), P = 0.004, r2 = 0.94. Partial correlation coefficients: puma predation, r = –0.86, P = 0.03; fawns per 100 does, r = 0.71, P = 0.11. Model 6 l = 0.8837 – 1.0652 (predation rate) + 0.0067 (fawns per 100 does), P = 0.004, r2 = 0.94. Partial correlation coefficients: puma predation, r = –0.77, P = 0.07; fawns per 100 does, r = 0.83, P = 0.04. Test for association between fawns per 100 does and adult puma density in January in the Treatment Area, 1988–1994. Spearman correlation coefficient (1-tailed test): rs = –0.72, P = 0.05. Test for association between fawns per 100 does and puma predation rates on radio-collared deer (bucks and does pooled). Spearman correlation coefficient (1-tailed test): rs = –0.68, P = 0.06.

Chapter 18

Pumas and Desert Bighorn Sheep

Pumas on the San Andres Mountains used desert bighorn sheep for food only sparingly (i.e., 2 percent of puma kills, 0.6 percent frequency in puma fecal samples and stomachs). Nevertheless, we needed to assess the impact that puma predation had on the prospect of recovery of this endangered ungulate population. Because this sheep population eventually went extinct, it serves as a case history on extinction of mammal populations, and bighorn sheep populations in particular (see Berger 1990, 1999, Krausman et al. 1996, Wehausen 1999). Therefore, we provide the historical context of desert bighorn sheep distribution in southern New Mexico and factors known to have and suspected of having influenced sheep population fluctuations.

Hypothesis and Predictions We hypothesized that puma predation was the strongest proximate limiting factor affecting the sheep population. Hence, we predicted that (1) puma predation must be the most important proximate cause of mortality affecting sheep population growth, and (2) experimental removal of pumas in the Treatment Area should cause an increase in sheep survival rates that was linked to a reduction in puma predation rates. These predictions were tested primarily by quantifying puma predation rates on radio-collared sheep relative to other limiting factors and measuring the relationship of puma density to puma predation rates. In addition, we examined how puma predation rates on radio-collared sheep related to puma predation rates on radio-collared mule deer and the abundance of deer fawns. 341

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Pre-history, History, and Threats Events leading to the fate of the sheep population on the San Andres Mountains began long before we arrived to conduct our research. Historically, there were at least sixteen desert mountain ranges in southern New Mexico that supported populations of desert bighorn sheep (Sandoval 1979a). Those populations, existing on mountain ranges separated by desert basins of various expanses, probably formed a metapopulation. The San Andres Mountains, estimated to provide about 710 km2 of suitable sheep habitat (Dunn 1994), may have had the largest subpopulation of sheep, at least in the past one hundred years. Actually, there were also sheep in the Organ Mountains, which were connected to the south end of the San Andres Mountains (Sandoval 1979b). And there may have been sheep in the Oscura Mountains, about 10 km northeast of the north end of the San Andres Mountains. Prehistorically, it is possible that this mountain chain supported a larger, more dispersed, and more persistent sheep population than in historical times. Over millennia, dispersing sheep probably moved across desert basins (i.e., matrix habitat) between mountain ranges in southern New Mexico, albeit infrequently. Rams, especially, experience wanderlust during the breeding season and are capable of straight-line distance travels of over 50 km (Krausman et al. 1999). Although ewes tend to be much more sedentary, some of them could have moved long distances during relatively cool, wet climatic periods when food and water, and hence sheep populations, might have had greater distribution and abundance. The most recent cooler, wetter ambient condition in the southern New Mexico was probably the “little ice age,” which lasted roughly from about 1600 to 1900 (Neilson 1986). Evidence of others goes much farther back. Water levels in playa lakes, as inferred from temporal distributions and abundances of aquatic, grassland, and desert scrub animals found on Howell’s Ridge in southwestern New Mexico, suggest that much longer wet periods occurred about 700 to 1,700 years ago, 2,500 to 3,300 years ago, and from 5,000 years ago to the Pleistocene (Van Devender 1995). Sheep immigrating into other subpopulations would have augmented populations numerically and genetically. Immigrating sheep may have even rescued some subpopulations from extinction and recolonized some habitat patches where sheep had disappeared. Climate change was not the only factor that might have affected metapopulation dynamics—so would modern human developments. European immigrants to southern New Mexico during the 1800s and 1900s brought new threats to the desert bighorn sheep metapopulation. Introduced livestock, particularly sheep and goats, competed with wild sheep for food and introduced diseases that could kill desert sheep (e.g., pneumonia, chronic sinusitis, scabies; Bunch et al. 1999). Overgrazing by livestock may have transformed

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grass-covered slopes to tree- and shrub-studded ones, diminishing habitat quality for sheep by reducing their ability to detect predators but enhancing food for deer and cover for stalking predators (also see Berger and Wehausen 1991, Neilson 1986, Van Devender 1995). Settlers sometimes killed wild sheep for food (Buechner 1960, Valdez and Krausman 1999). The construction of fences to manage livestock movements as well as to delineate highway and railroad rightsof-way probably eliminated the already intermittent movements of sheep between the mountain ranges. Most patches of sheep habitat became permanently isolated from one another. Thus, extant sheep populations became increasingly vulnerable to detrimental effects that befall small isolated populations. Sheep in the Organ Mountains lingered as late as 1910. In the Guadalupe Mountains, representing the eastern-most extent of sheep in New Mexico, sheep disappeared about the late 1940s (Sandoval 1979b). By the time we started our research in 1985, only four wild desert bighorn sheep populations remained in New Mexico, all together adding up to fewer than 150 animals (Elenowitz 1987). In an environment where climate and weather fluctuations already create a tenuous hold on life, human disruptions to the metapopulation dynamics and changes in sheep population health and in plant and animal communities probably heightened extinction risks to sheep populations. Historical accounts say sheep on the San Andres Mountains were “rare” in 1902 and 1903 (J. A. Gaut, Biological Survey, cited in Sandoval 1979b). The first official attempt to census the population was undertaken in 1942 by staff of the newly designated San Andres National Wildlife Refuge; a minimum of thirty-one sheep were counted. Through 1950 the population increased to at least 140 sheep. But from 1951 to 1953 the population plummeted again to about fifty-three sheep. According to Lang (1956) the decline was caused by a combination of factors: severe drought, overpopulation of deer, overgrazing by domestic livestock, and disturbances by deer hunters. During the next fourteen years, the sheep population increased gradually, reaching an all-time estimated high of 270 sheep in 1967. The population high justified regulated sport-hunting seasons for rams with at least three-quarter-curl horns. However, the 1967 estimate was contested by Welch (1969), who thought it too high and that an estimate of 150–200 sheep was more realistic. Apparently, a rethinking of the crude population estimates was being undertaken at the time, because a 1968 estimate of 250 sheep was also disputed by Augsburger (1970) and later modified by Sandoval (1979b) to about 160 sheep. The first intensive study of the desert bighorn sheep was conducted by Sandoval (1979b). He employed a combination of helicopter and ground surveys in 1975 and 1976 to estimate there were 200 ± 18 sheep. The sheep population again declined during the years 1978–1979. Sheep

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hunting was halted. In November 1979 there were an estimated eighty sheep (Sandoval 1980). The decline was attributed to a widespread epizootic of scabies (Lange et al. 1980). This disease, caused by a mite (Psoroptes spp.), produces clinical signs on the sheep that include trunk alopecia (i.e., hair loss); intense itching; protein exudation; mucopurulent effusion from and severe folding of the pinnae (i.e., external ears); ear canals occluded with fleshy plugs; purulent inflammation of the outer ear; destruction of the tympanic membrane (i.e., ear drum); ataxia; and weakness (Sandoval 1979a, Sandoval 1980, Lange et al. 1980, Lange 1982, Clark and Jessup 1990). Scabies may also cause hearing loss (Norrix et al. 1995), hypothermia, and suppression of the immune system (Clark and Jessup 1990). Besides scabies, some of the sheep captured in 1979 had antibodies against contagious ecthyma, and 28 percent of them had clinical signs of this disease. Contagious ecthyma is a viral disease that causes scabby lesions on the mouth, eyelids, forelegs, and udders. It can lead to secondary blindness, lameness, and impaired feeding, which contribute to emaciation and death. Lambs are particularly susceptible to starvation (Lance 1982). Sandoval (1980) thought that scabies could have acted as a predisposing factor to contagious ecthyma, and that the large-scale die-off could have been due to both diseases. Physiological effects of these diseases, if not causing death directly, could predispose sheep to death from a variety of other causes, including bacterial infections, accidental falls from precipices, and predation. The origin of the scabies mites in this wild sheep population has been a mystery, but Sandoval (1980) suggested that domestic sheep and goats introduced on the San Andres Mountains during the early 1900s may have passed them to the desert bighorn sheep. He associated other scabies-caused bighorn sheep population declines that occurred in California, Colorado, Oregon, and Wyoming with the introduction of domestic sheep. Furthermore, there is evidence that the desert mule deer act as an alternate host for the mites. We found four mule deer killed by pumas that were infested with psoroptic mites. The New Mexico Department of Game and Fish and the U.S. Fish and Wildlife Service sampled at least 151 deer from the San Andres Mountains during 1989–1993; twentysix had mites in their ears (Boyce 1994). Study of morphological characters of mites in the sympatric sheep and deer populations on the San Andres Mountains suggested that the mites are not host specific and that they may represent a single interbreeding population (Boyce et al. 1990). Unfortunately, the extent to which deer may transmit mites to sheep or vice versa has not been adequately tested (Clark and Jessup 1992). In November 1979, a sheep rescue effort was made by the U.S. Fish and Wildlife Se rvice, the New Mexico Department of Game and Fish, and the U.S. Army at White Sands Missile Range. Forty-nine sheep we re captured

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using a helicopter, net-gun, and drug-filled darts so they could be treated (Sandoval 1980). T h i rt y - f i veof the sheep surv i ved capture and treatments. Of those, seven we re kept in captivity at New Mexico State Un i versity in Las Cruces for study of the transmission and control of psoroptic mites. The remaining twenty-eight sheep we re transported to the New Mexico De p a rtment of Game and Fish desert bighorn sheep breeding facility at Red Ro c k , where they remained for thirteen months. T h e re, some of the sheep died of blue-tongue viral pneumonia and contagious ecthyma. Only twe l ve surv i v i n g sheep we re returned to the San Andres Mountains in January 1981. At that time, the entire sheep population was estimated to be about forty animals (Hoban 1990). In a short span of about forty years, the sheep population on the San Andres Mountains had fluctuated to lows less than or equal to fifty animals three times. Biologists studying demographics of bighorn sheep in Wyoming, Montana, and South Dakota have estimated that sheep populations with no effective immigration (i.e., gene flow) need to have more than 150 total individuals to avoid short-term (i.e., generational time) loss of genetic variability (Fitzsimmons and Buskirk 1992). Population bottlenecks of the San Andres Mountains sheep population provided conditions for erosion of genetic variation through inbreeding (i.e., mating between close relatives) and genetic drift (i.e., changes in allele frequency in a small population caused by random sampling of gametes to form zygotes). There is evidence that this may have occurred. Researchers compared genetic variation in five major histocompatibility complex loci (tightly linked loci involved in the immune response) and three microsatellite loci among desert bighorn sheep from the San Andres Mountains and from eleven populations in the Mojave Desert and Peninsular Ranges in Nevada and California. They found that San Andres sheep exhibited the lowest heterozygosity (i.e., genetic variation where there are different alleles at more than one locus) (Boyce et al. 1996). Similar research, this time using ten highly variable microsatellite loci, found that sheep from the San Andres Mountains had lower genetic variation than ten other desert bighorn sheep populations in Arizona and California (Gutiérrez-Espeleta et al. 1998). Yet, these patterns of low genetic variation could also result from a very small number of sheep founding the population. Effects of lower genetic variation in the San Andres sheep are unknown and would be very difficult to measure. Theoretically, increased expression of deleterious alleles could suppress individual reproductive performance, viability of young, resistance to parasites and diseases, and the ability to adapt to a changing environment. Cumulative effects could result in lower population growth rates, which in turn could retard the ability of the population to rebound from population declines. A resulting small population could then be at greater risk

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to extinction from unpredictable environmental events that destabilize the population (Lacy 1997).

Sheep Population Characteristics during Our Research As we explained in Chapter 4, survey techniques to count sheep on the San A n d res Mountains varied in kind and intensity. These methods pro d u c e d minimum counts of sheep ranging from twenty-two to thirt y - s e ven (Table 18-1). Population estimates seemed to reflect survey techniques, as longer s e a rch time and the use of a helicopter resulted in a greater number of sheep observations. Even considering that biologists probably missed a few lone sheep or small bands during surveys, the sheep population on the San A n d res Mountains probably ranged from thirty to forty animals during 1986–1994.

Table 18-1. Desert bighorn sheep observed in surveys conducted on the San Andres Mountains, New Mexico, 1986–1994. Adults

Yearlings

Year

Rams

Ewes

Rams

Ewes

1986a 1987a 1988a 1989a 1990b 1991c 1992d 1993e 1994a

9 9 10 10 7 3 6 7 12

15 13 11 15 9 10 13 11 12

3 3 3 3

2 3 5 2 3 1

2

Lambs Unk. Sex Rams 4 3 3

3 5

2 2

Ewes

2

3 5 2 3 1

5

2

Unk. Sex Total 1 1 6 2 5 8

36 37 34 34 22 22 31 30 34

aNumbers for 1986–1989 and 1994 were obtained from ground-based observations and radiotelemetry data gathered year-round (San Andres National Wildlife Refuge files). bNumbers for 1990 were from ground-based observations and radiotelemetry data gathered during December and known mortalities that occurred during the rest of the year (San Andres National Wildlife Refuge files). cNumbers for 1991 were from ground-based observations and radiotelemetry data gathered during 31 August–10 September (New Mexico Department of Game and Fish files). dNumbers for 1992 were from ground-based observations and radiotelemetry data gathered during May–December (San Andres National Wildlife Refuge files). eNumbers for 1993 were from a helicopter survey conducted on 20–21 November (New Mexico Department of Game and Fish files).

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The surveys also provided data on herd composition. Based on the sheep classified by gender during surveys, lambs apparently were born at an equal sex ratio (17 males:16 females). This ratio held into the yearling age class (19 males:18 females). But in the adult age class, there generally were fewer males than females, with the ratio of adult rams to adult ewes ranging from 0.30:1 to 1:1 and averaged 0.67:1 (Table 18-1). Tendency toward fewer adult rams was probably because of proportionately greater mortality (see below). The ratio of lambs to adult ewes ranged from 0.27:1 to 0.69:1 and averaged 0.51 ± 0.16:1. The ratio of yearlings to adult ewes ranged from 0.17:1 to 0.73:1 and averaged 0.39 ± 0.19:1. On average, the ratio of lambs to adult ewes during the 1986–1994 surveys was quite similar to the average lamb:ewe ratio (x– = 0.50 ± 0.21) this sheep population exhibited during its initial documented growth phase during 1941–1952 when the population increased from a low of about twenty-seven sheep to an estimated 112 sheep. And it was similar to the average lamb:ewe ratio ( x– = 0.54 ± 0.17) from population surveys conducted during 1965–1976 when sheep population estimates were their historical highest, ranging from 182 to 270 sheep (Sandoval 1979b:13). During those times, lamb production was high enough to offset mortality and to spur population growth. But the difference during our research was that mortality of sheep apparently matched or outpaced reproduction.

Fates of Radio-Collared Sheep We and U.S. Fish and Wildlife Service biologists monitored a total of forty-three radio-collared sheep (sixteen rams, twenty-seven ewes) from August 1985 to March 1995 to detect puma predation and characteristics of the sheep that died. The number of radio-collared sheep monitored each year comprised 36–83 percent of the number of adults and yearlings observed during annual surveys during 1986–1994 (Fig. 18-1). We detected twenty-six radio-collared sheep that died. With the help of agency biologists who concentrated on the fates of these sheep, we were able to get to sheep that died in an average of 7 ± 7 days after death (range = 0–30, median = 5). Pumas killed ten radio-collared sheep, including four rams (x– age = 1.7 ± 1.5, range = 0.8–four years) and six ewes (x– age = 8 ± 4.9, range = 3–16 years). Six of these sheep had clinical scabies, with infestations ranging in severity from relatively minor scaly lesions on the flanks to both ear canals completely occluded with scabs. A six-year-old ewe had no scabies lesions, but she was clearly emaciated prior to being killed by a puma. Her femur marrow was pink and gelatinous in consistency, indicating that fat depletion had reached extreme levels in the long bones, the last fat stores available for energy metabolism. This

FPO @ 82%

FIGURE 18-1. Number of adult and yearling desert bighorn sheep observed in annual surveys and radio-collared during each year, San Andres Mountains, New Mexico.

Slide @318%

PHOTO 28. A desert bighorn ewe killed and eaten by a puma.

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Slide @171% PHOTO 29. A yearling desert bighorn ram with ear canals occluded with scabs. This ram was killed and eaten by puma M3.

condition suggests that the animal was in extremely poor condition and was probably dying (Mech and DelGuidice 1985). We estimated that about 30 percent of puma-caused deaths in the radio-collared desert bighorn sheep was compensatory mortality (i.e., the same percentage we found for mule deer one or more years old). Besides the emaciated ewe mentioned previously, there were two ewes killed by male puma M23 in January and March 1989 that were twelve and sixteen years old, respectively. Chances were that these two ewes would not have survived another year. They were as old or older than a twelve-year-old ewe and two rams that were thirteen and fourteen years old when they apparently lay down or fell in their tracks and died from age-related ailments. Sixteen other radio-collared sheep, including eight rams (x– age = 7.2 ± 4.0, range = 4–14 years) and eight ewes (x– = 5.6 ± 3.4, range = 3–12 years) died from other causes. Natural causes of death included falls from cliffs (three rams, two ewes), aging (two rams, one ewe), scabies (two rams, one ewe), undetermined diseases (one ewe), and breached birth (one ewe). Two ewes died of undetermined natural causes. One ram died from a capture accident when he tumbled

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over a cliff after getting caught in a net. One of the rams that apparently died of scabies was scavenged by male puma M7. We also discovered an uncollared yearling ewe that died of undetermined causes not related to puma predation. When we found it, a coyote was scavenging the carcass as it lay partially submerged in a spring-fed pool. Ten of the sixteen radio-collared sheep that died of other causes had clinical scabies. The mildest case consisted of scabby lesions on one leg. Severest cases apparently caused death. One six-year-old ram had hemorrhaging and suppurative lesions over 40 percent of its body and was extremely emaciated. Another six-year-old ram had scabby lesions over 75 percent of its body and suppurative lesions over about 40 percent of its body. At the death site of the latter ram, we found where he had been scratching himself against rocks protruding out of a steep slope, leaving bloody scabs and hair on the rock. Furthermore, we suggest that if scabies causes bacterial infections that impair the inner ear, which is also vital for equilibrium, then scabies may contribute to deaths from accidental falls (19 percent of all deaths, 29 percent of deaths from other causes). Three of the five sheep that fell to their deaths had ear canals blocked by scabs. In all, clinical scabies was found in 62 percent of the dead radio-collared sheep (i.e., puma kills plus sheep that died of other causes), indicating that scabies was still at epizootic proportions in the sheep population during our research.

Survival Rates and Agent-Specific Mortality We used twenty-six radio-collared adult sheep (eleven rams, fifteen ewes) that lived in the Treatment Area to quantify annual survival rates and agent-specific mortality rates during biological years 1987–1988 to 1993–1994 to correspond with our puma population estimates and mule deer survival and agent-specific mortality rates in that area. We monitored those sheep for 22,240 days (7,380 ram-days, 14,860 ewe-days). These sheep lived in the Treatment Area. Two other radio-collared adult ewes lived exclusively in the Reference Area from the time they were originally captured in November 1989 through the end of our study in March 1995. We did not include them in our analyses of annual survival and agent-specific mortality rates because they did not live in the Treatment Area, where we experimentally removed pumas. Annual survival rates for six to nine adult ewes monitored per year ranged from 0.63 to 1.0 (x– = 0.89 ± 0.16) (Table 18-2). We had too few rams each year (one–seven / year) to estimate their survival rates, but we lumped them with ewes to boost the sample of radio-collared sheep available each year to estimate adult sheep survival rates and agent-specific mortality rates. With rams included, annual survival rates of adult sheep ranged from 0.58 to 1.0 (x– = 0.84 ± 0.17). Aside from the small number

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Table 18-2. Survival rates of radio-collared desert bighorn sheep, San Andres Mountains, New Mexico, 1987–1994.a Biological yearb

Sheep-days

Ewes Rate

1987–88 1988–89 1989–90 1990–91 1991–92 1992–93 1993–94

2,192 2,200 2,234 2,190 2,196 1,573 2,275

0.85 0.72 1.0 1.0 1.0 0.63 1.0

95% C.L. 0.62–1.0 0.45–1.0 1.0–1.0 1.0–1.0 1.0–1.0 0.33–1.0 1.0–1.0

Ewes plus ramsc Sheep-days Rate 95% C.L. 3,656 3,405 3,838 3,627 2,928 1,659 3,127

0.90 0.58 1.0 0.90 0.88 0.64 1.0

0.74–1.0 0.37–0.94 1.0–1.0 0.74–1.0 0.69–1.0 0.35–1.0 1.0–1.0

aSurvival rates and 95 percent C.L. (Confidence Limits) were computed using Micromort software (Heisey and Fuller 1985b). bBiological years spanned August–July each year. cIn years 1987–1988 to 1993–1994, one to seven rams and six to nine ewes were monitored.

of adult rams we could monitor, rams still showed a tendency to die at higher rates than ewes. Of the total of thirteen adult rams we monitored during 1985–1995, 69 percent of them died, as opposed to 41 percent of the twentyseven radio-collared adult ewes we monitored in the same time span. This may explain the observed tendency toward fewer adult rams than adult ewes in the population. Trying to estimate yearling and lamb survival rates was even more tenuous, given their smaller numbers and variation in the surveys. We estimated survival rates of yearling sheep by calculating a finite rate of survival (number of yearlings surviving to two years old / number monitored) for a total of ten radio-collared yearlings that we monitored from 1985 to 1994. Of those, three rams were killed by pumas, resulting in a survival rate of 0.70. Although we could not be certain that all yearlings counted in one year were the same individuals counted as lambs in previous years, we calculated a rough finite rate of lamb survival by dividing the number of yearlings observed in surveys during 1987–1994 by the number of lambs observed in previous years from 1986 to 1993. We assumed the difference represented the number of lambs that died. The resulting finite lamb survival was 0.77. By multiplying these rates by the total number of lambs observed during 1986–1994 (i.e., 56 lambs ¥ 0.77 ¥ 0.70) we estimated that roughly thirty offspring would have survived to two years old. By recalculating

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annual survival rates of adult rams and ewes (combined) for annual periods (January through December) 1986–1994 (using Micromort software) to correspond with the survey data, we estimated that about thirty-four adult sheep died (i.e., S (1 – annual survival rate x number of adult sheep counted / year)) [1]. Hence, in the observed sheep numbers there was roughly a net loss of four sheep during the nine-year period. Consequently, we concluded that the desert bighorn sheep population on the San Andres Mountains during our research was static and vulnerable at a very low number of about thirty to forty animals. It is important to stress that during 1987–1988 to 1991–1992, when environmental conditions were favorable enough to stimulate a mule deer population increase, the sheep population apparently did not respond similarly. During this period the puma population throughout the entire study area was also increasing from a biological low point; it was again experimentally reduced in the Treatment Area in 1990–1991. Part of the reason the sheep population could not respond effectively to favorable environmental conditions was the natural propensity of ewes to produce only one lamb per year, unlike mule deer, which can produce twins. Twinning has not yet been observed in wild desert bighorn sheep and has very rarely been seen even in captive animals (Krausman et al. 1999). This probably stymied the potential for reproduction to outpace realized mortality. Puma predation and death from other causes on radio-collared adult sheep was highly sporadic (Table 18-3). During biological years 1987–1988 to 1993–1994, four sheep were killed by pumas, including one ram and two ewes killed by male puma M23 from 1 January to 11 March 1989. In those years, six radio-collared adult sheep (two rams, four ewes) died of other causes. The general pattern was that more adult sheep died from “other causes” than from puma predation—the opposite pattern from what we documented for desert mule deer. We removed M23 from the study area (he was translocated to northern New Mexico) to honor our agreement with cooperators to remove any pumas that killed more than one of the endangered sheep. He was the only puma in our ten-year study to demonstrate an affinity for killing sheep. It is probable that if he had stayed on the San Andres Mountains he would have killed more sheep. After we removed M23, only one other radio-collared sheep was killed by a puma; this occurred in August 1990 (Fig. 18-2). Puma predation rates on radiocollared sheep (i.e., ewes and rams combined) were apparently entirely independent of the number of adult pumas on the Treatment Area, puma predation rates on radio-collared mule deer (i.e., bucks and does combined), and the relative abundance of highly vulnerable deer fawns (i.e., as indexed by fawns / 100 does) [2]. With so few sheep relative to the number of deer and other alternate prey, all the pumas, except for maybe M23, apparently did not purposely hunt them. Instead, we think pumas killed sheep that they encountered by sheer

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FIGURE 18-2. Rates of surv i val, puma predation, and deaths from other causes for radiocollared desert bighorn sheep, San Andres Mountains, New Mexico.

chance, probably while they were actually hunting the more-abundant deer that also lived in sheep habitat. We periodically observed deer, and sometimes found remains of deer killed by pumas, in some of the most rugged terrain used by sheep.

Did Puma Predation Limit the Sheep Population? We concluded that puma predation was a strong limiting factor to this remnant desert bighorn sheep population, because puma predation was the single most identifiable cause of death. But puma predation rates were not related to puma density. Sporadic puma predation by itself apparently did not stop the sheep population from growing during our research tenure. More sheep actually died from other causes, at least half of which were probably aggravated by disease. All mortality factors rendered the sheep population unstable, particularly in the midst of drought and a rapidly declining mule deer population—the puma’s chief prey. How long would the deer satisfy the energy demands of an increasing puma population without escalating jeopardy to the sheep?

Finale of the Sheep Population Dynamics between pumas and sheep changed markedly after our research ended. Biologists Mara Weisenberger and Gary Montoya for the San Andres

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National Wildlife Refuge continued monitoring the remaining, aging radio-collared sheep. In 1996, seven of nine sheep (78 percent) with working radio collars died. New Mexico Department of Game and Fish biologists radio-collared a ram in April 1997, bringing the number of collared sheep available for monitoring to three. But in 1997, two more sheep died. Hence, in the span of only nineteen months, from February 1996 to August 1997, nine radio-collared adult sheep died, including two rams and seven ewes. Pumas killed one ram and five ewes (x– age = 8.8 ± 2.0, range = 6–11 years), while one ram and two ewes died of “other causes” (x– age = 12.0 ± 3.0, range = 9–15 years). Two of these deaths could not be determined, but a twelve-year-old ewe fell from a precipice. This decline seemed to have left only one eight-year-old radio-collared ewe. We surmised that the greater puma predation rates on the radio-collared sheep were indeed linked to the crash in the mule deer population, which by 1996 must have been close to its nadir. Pumas probably were having to hunt their home ranges intensively to find large prey. They could accomplish this by hunting more often and traversing more habitat. In the process, we suspect they increased encounter rates, and thus predation rates, on sheep and drove the small population downward. Biologists could not find other non-radio-collared sheep, probably indicating that attrition had occurred in them as well. This notion was supported in December 1996 when biologists with the U.S. Fish and Wildlife Service, New Mexico Department of Game and Fish, and White Sands Missile Range partnered to conduct a survey using three helicopters, each one assigned to canvass about one-third of the San Andres Mountains. No sheep were seen in fifteen hours of survey time. In December 1997 another helicopter survey of the mountains was launched. Only one sheep was seen in five hours, the last radio-collared ewe. U.S. Fish and Wildlife biologists conducted subsequent ground searches and used cameras to monitor three springs that sheep were known to use; no more sheep were found. With only one remaining ewe, the desert bighorn sheep population on the San Andres Mountains was biologically extinct. The major proximate mechanism responsible for the extinction, as indicated by fates of radio-collared sheep, was puma predation. We believe a combination of factors, both human and nonhuman, ultimately brought about the biological extinction of the sheep on the San Andres Mountains. Climatic and human-induced impacts resulting in isolation (i.e., disintegration of the regional metapopulation), disease (i.e., possible introduction of scabies), and the possible attendant loss of genetic variation from three population bottlenecks resulted in a small unstable sheep population at the brink of extinction. A naturally low reproductive rate could not offset deaths. Finally, drought and attendant puma predation caused extinction of the population.

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Pumas and Other Sheep Populations Puma predation is a substantial mortality factor in other bighorn sheep populations in North America. It is a major factor threatening the persistence of a federally endangered sheep population in the desert Peninsular Ranges of Southern California. When the sheep population was listed as endangered in 1998, there were about 330 yearling and adult animals. Biologists studying the fates of 113 (sixteen rams, ninety-seven ewes) radio-collared adult sheep during 1992–1998 found that pumas killed forty-two of sixty-one (69 percent) of the sheep that died. On an annual basis, the puma predation rate tended to be four times the rate from non-predation mortality. The mean annual survival rate of 0.79 was low relative to other bighorn sheep populations in southeastern California (greater than or equal to 0.91), northwestern Arizona (greater than or equal to 0.86), and four populations in the Mojave Desert (greater than or equal to 0.85) (Hayes et al. 2000). It was also lower than the mean annual survival rate of 0.84 that we found for the desert bighorn sheep on the San Andres Mountains. Biologists did not assess to what extent puma predation was compensatory or additive. Still, they concluded that if high puma predation continues on adult sheep, the population probably will not grow. In the Mojave Desert of California, a tiny population of about a dozen bighorn sheep experienced substantial variation in puma predation. During 1989–1992, annual survival rates for ewes averaged about 0.62, with all mortality due to puma predation. However, during the following three years there was no puma predation and the sheep population increased by 15 percent per year (Wehausen 1996). While studying pumas and bighorn sheep in southwestern Alberta from 1985 to 1994, biologists found that puma predation was highly variable, ranging from 0 to 57 percent of winter (i.e., December through March) mortality in a sheep population that numbered between 112 and 158 animals. Of twentynine sheep killed by pumas, thirteen were lambs and sixteen were one year or older. Pumas selected lambs. Apparently 29 percent of lambs, 44 percent of ewes, and 50 percent of rams killed by pumas exhibited anatomical or behavioral abnormalities, which may have predisposed them to predation. Not all pumas on the study area killed sheep equally. Of five radio-collared female pumas monitored intensively, two never killed sheep, one killed only one sheep, one killed five sheep, and another killed seventeen sheep. This last puma killed 8.7 percent (n = 11) of the early-winter sheep population and 26.1 percent (n = 6) of the lambs in winter 1993–1994. The biologists believed that this high predation triggered a decline in the sheep population that continued into 1995 and 1996. The puma was monitored with radiotelemetry for more than ten years,

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and the biologists believe she learned to kill sheep in her later life (Ross et al. 1997). This situation in Alberta, like our experience with M23, indicates that individual pumas can cause serious mortality in small sheep populations.

LP > >

KX

1. Desert bighorn sheep on the San Andres Mountains during 1985–1995 comprised a remnant population of only about thirty to forty animals. The population probably was once part of a regional metapopulation in southern New Mexico. Since the beginning of the twentieth century, the sheep population has had a history of wide fluctuations from about fifty to two hundred animals, including three demographic bottlenecks of fifty or fewer animals. Human activity and development in southern New Mexico probably contributed to the decline of desert bighorn sheep regionally and to the extinction risk for sheep on the San Andres Mountains in particular. 2. Puma predation was the single-most identifiable cause of mortality in radiocollared sheep, claiming 23 percent of sheep monitored. Puma predation on sheep was sporadic. Pumas seemed to kill sheep opportunistically, probably while they were actually seeking deer. We estimated that about 30 percent of puma predation was compensatory. There was no association between puma predation rates on radio-collared sheep and the number of adult pumas, puma predation rates on radio-collared deer, or fawn productivity. More sheep died from other causes, comprising 37 percent of sheep we monitored. Total mortality approximately matched reproduction; hence, the sheep population was static during our research. 3. Scabies, which was responsible for the sheep population crash during 1978–1979, was still an epizootic during our research. Clinical scabies occurred in 62 percent of all radio-collared sheep that died. Scabies probably predisposed sheep to a variety of mortality causes, including predation, falls from cliffs, malnutrition, and disease. 4. Small population size, predation, high incidence of disease, and drought rendered the sheep population highly unstable and vulnerable. By 1997, the sheep population was biologically extinct due to intensified puma predation following a crash in the deer population.

LN N5LN5)L 1. Combined annual survival rates for radio-collared adult (two years or older) desert bighorn rams (n = 13) and ewes (n = 21) monitored for 30,188 radiodays from 1986 to 1994: 1986 = 0.81, 1987 = 0.74, 1988 = 0.71, 1989 = 0.73, 1990 = 0.91, 1991 = 1.0, 1992 = 0.64, 1993 = 1.0, 1994 = 0.90 (x– = 0.83 ± 0.13).

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2. Test for association using Spearman correlation coefficients between puma predation rates on radio-collared adult sheep and the following parameters in the seven-year span: numbers of adult pumas on the Treatment Area, rs = –0.13; puma predation rates on radio-collared adult deer, rs = 0.13; fawns/100 does, rs = 0.30. All P > 0.50.

Chapter 19

Synthesis: Pumas and Weather Modulate Large-Mammal Population Dynamics on the San Andres Mountains

Puma predation was the most important proximate cause of mortality affecting desert mule deer and desert bighorn sheep on the San Andres Mountains. The effect that pumas had on these native ungulate populations was linked to unpredictable weather events (specifically, an unusual wet period followed by drought) and attendant effects on herbivore foods, free water, and probably security cover. These dynamics appeared to be a classic case of biotic (i.e., puma predation, plants, population size, disease) and abiotic (i.e., weather) forces interacting to influence the nature of population, community, and ecosystem processes (Matson and Hunter 1992, Post et al. 1999). Both predation and weather were destabilizing forces. An unusually wet weather pattern created an environment favoring production of an ample food supply and cover that enabled the deer population to grow relatively rapidly, even with puma predation slowing it down. Ample deer in the environment probably reduced puma predation on sheep. We believe the subsequent drought, in combination with herbivory, stressed plants and desiccated water sources. This effectively constricted food supply and cover, thus reducing deer fertility rates and fawn security. At the same time, the puma population was increasing. This triggered a predation threshold response; pumas continued killing the less359

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abundant fawns while increasing predation pressure on the now more vulnerable reproduction-aged deer. Increased puma predation rates on the growtharrested deer population hastened the deer population decline, driving it to lower numbers, at least in the short term, than it might have attained without puma predation. This exposed the sheep to greater puma predation. Although we were unable to observe the fate of puma population directly, after a lag it apparently declined in response to its dwindling prey base. What might happen next undoubtedly depends on whether drought persists, or if it is replaced with a relatively normal or wet weather regime. These dynamics pertain to an ongoing debate regarding the influence that apex predators and plants exert on ecosystems (see Matson and Hunter 1992, Hunter and Price 1992, Power 1992, Strong 1992, Menge 1992, McLaren and Peterson 1994, Post et al. 1999, Terborgh et al. 1999). If predators have primacy on system dynamics then there is top-down control. According to this scenario, animals at the top of the food chain are food limited, and at successively lower trophic levels animals are alternatively predator, then food limited (Power 1992). So if pumas exerted top-down control on the San Andres Mountains, the puma population would be limited by food, chiefly deer; puma predation would limit the deer population; and plants would be limited by food (e.g., water, soil nutrients). But if primary producers (i.e., plants) have primacy, the system is controlled from the bottom up. This scenario holds that animals at each trophic level are food limited (Power 1992). Thus, food would limit the plants, which would limit deer, which would limit pumas. One way of sensing the relative strengths of top-down and bottom-up control is to consider what might happen if the top and bottom trophic levels were removed from the San Andres Mountains ecosystem. Absence of pumas would have profound effects. We would expect the deer population to grow at a faster rate and to higher numbers before it would be limited by food. Thereafter, it might decline at a slower rate, but in the process it might impose longer-lasting negative impacts to food sources due to intensified and protracted overbrowsing. Furthermore, because deer and sheep distributions overlap substantially and the diet of those two ungulates overlap by more than 70 percent (Sandoval 1979b), exploitation competition between deer and sheep would be expected to increase. Hence, the ability of a small sheep population to grow would depend upon its competitive interactions with deer and upon the quantity and quality of food available. Puma predation, by dampening the growth rate of the deer population, may lower exploitation competition between deer and sheep. Hence, puma predation plays a crucial role, modulating the numbers of the most abundant ungulate (i.e., deer) and its attendant effects on food plants and other herbivores. We view the puma’s impacts on ecosystem dynamics as dis-

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Slide @318%

PHOTO 30. The puma is a keystone species in wild desert ecosystems, and it can serve as an umbrella species in conservation efforts.

proportionately large relative to its numbers or biomass in the ecosystem, thus qualifying the puma as a keystone species (Meffe and Carrol 1997). Now take away the plants and what happens? The system collapses. Clearly, it is the desert plants that have primacy in the food web, capturing most of the energy (from the sun) needed to sustain the large-mammal community on the San Andres Mountains. Primary productivity affects health, reproductive performance, and hence population growth of ungulates and small alternate prey (e.g., rabbits, hares, rodents), which together enable ungulate populations to endure predation. In turn, population levels of prey determine the population level of the puma (see Power 1992). Just during the twentieth century, severe droughts occurred at least six times in southern New Mexico: 1908–1913, 1934–1935, 1951–1956, 1963–1965, 1971, and 1976 (Neilson 1986), with each interposed with relatively wet periods. Clearly, weather (a subset of the regional climate) is an unpredictable natural perturbation, whether it produces wet cycles or drought. It can destabilize the system by acting directly on plants; thus, it modifies relative strengths of top-down and bottom-up forces within a relatively short time scale (i.e., within one year). On the San Andres Mountains, top-down and bottom-up forces interacted simultaneously and were modified by weather to shape large-mammal commu-

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nity dynamics. The ecosystem is much too complicated to describe its control as a simple dichotomy—top-down or bottom-up. Instead, it is much more important to understand that the desert ecosystem is naturally variable and to understand how biotic and abiotic factors influence its dynamics. Likely, these dynamics have been operating for the life of the Chihuahuan Desert—about four thousand years (Van Devender and Toolin 1983). Considering them in this context is essential for developing management and conservation strategies for pumas, prey, and habitat, particularly in a milieu of unprecedented human pressure.

P a rt V

Pumas and People

Chapter 20

Conservation and Management of Wild Pumas

Conservation is a confluence of our ethical obligation to protect nature and our understanding of how nature works. Consequently, conservation is laden with human values. Still, when people conserve species or ecosystems, then biological diversity is perpetuated through genetic variation in species and populations, variation in communities and ecosystems, and the interactions among life forms. In addition, biological diversity provides opportunities for adaptation to future environments. Humans benefit in the long term. Our security is in healthful environments that persistently support a diversity of life, including big mammals on the same trophic level as us. Over millions of years of evolution, such environments nurtured and sustained humans; they ignited our spirit and imagination and fostered a will to explore and discover. Humans now dominate practically eve ry livable terrestrial enviro n m e n t on Earth; thus, it is up to us to care for our celestial home. Will we re s o l ve to conserve environments that sustain us and a resplendent array of other large mammals, including big, free-ranging carnivo res? Or will we decide to l i ve in a world impoverished of those beasts? In the next one hundred years, the human legacy on Earth will be defined. Humans can have a legacy of wisdom and self-restraint, curbing our genetic propensity to maximize our own re p ro d u c t i ve success and attendant appetite for re s o u rces so that a myriad of life forms, including big predators, may persist in intact wild ecosystems. This could be one of our greatest virtues, in league with treating all humans with respect and dignity. Or will we prove we we re not wise enough, 365

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and that in humanity’s glutting of Earth we continued to drive life to extinction? We hope, this book will help people to understand what pumas require to thrive and what their role is in nature. In previous chapters, we established several reasons why the puma is a model keystone species on which to design landscape-level conservation strategies: (1) pumas strongly influence energy flow in ecosystems; (2) they are a potent selective force on prey animals; (3) they modulate prey populations; thus (4) they indirectly affect herbivory on plant communities; (5) they influence competitive interactions between herbivores; and (6) their persisting populations are dependent on expansive wild landscapes. Moreover, the puma is an umbrella species, because conservation strategies benefiting pumas also benefit an array of other life forms living in intact ecosystems. The time for developing and implementing conservation plans is now, while pumas still exist in viable populations and there still are sizable wild lands. Conservation strategies should consider the needs of people as well as the ecology and evolution of pumas. In the United States, humans have devastated big obligate carnivores. We compete with carnivores for both living space and animals that provide us food, fiber, and revenue, whether they be livestock or big game. Furthermore, we have a natural fear of big carnivores. Because of their size, strength, weaponry, and diet, they can easily overwhelm us, and even eat us. Those instances were probably more common in our prehistoric past; today, they are extraordinary. Our tendency has been to make our surroundings safe from such beasts. Jaguars ranged from southern Louisiana to Southern California as late as the 1800s. Today, jaguars are rare visitors to southern Arizona and southwestern New Mexico, probably having dispersed from what may be a relict population in Sonora Mexico. Throughout their range, jaguars are listed as endangered by the U.S. Department of Interior (USDI) (Valdez 2000). Wolves ranged the length and breadth of the Unites States into the 1800s, but now they too are on the endangered species list. Due to federal protection and recent reintroductions, their numbers have been increasing, particularly since the 1980s. In 1995, about 1,700 to 2,000 wolves lived in northern Minnesota, but only 100 to 120 lived in small breeding populations in Wisconsin, Michigan, Montana, and possibly Washington (Ballard and Gipson 2000). In 1999, the Greater Yellowstone Ecosystem had about 120 wolves, and central Idaho wild lands had about 145 wolves (U.S. Fish and Wildlife Service et al. 1999). Forested mountains and wilderness along the borders of Arizona and New Mexico had less than twenty Mexican wolves in early 2000 (U.S. Fish and Wildlife Service 2000). About the same time, coastal North Carolina was home to about ninety-five wild red wolves (Hackney 2000).

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Of the big flesh-eaters, only the puma exists today in viable populations across the western United States. But that is about half of its historical range in this country. As we discussed in Chapter 2, regulations on killing pumas in western states since 1965 allowed puma populations to recover from historical lows. Today, self-sustaining puma populations occur in at least twelve western states— Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Texas, Utah, Washington, and Wyoming. Because pumas live at very low densities and are highly cryptic, wildlife biologists and managers can never really know how many pumas may live in suitable habitats within these states. Still, wildlife agencies for seven states have volunteered educated guesses at the number of pumas, which added up to at least 21,400 animals in the late 1990s (Logan and Sweanor 2000). Assuming that the other five states had about 2,000 pumas each, then the number rises to about 31,400 wild pumas in the western United States. Sprinkle those pumas among the mountains and foothills of the West and one can fathom how sparsely these animals are actually distributed. In the eastern United States, there is reliable evidence of only one breeding population, that of the endangered Florida panther, which numbered about eighty animals in 1990 (Maehr et al. 1991). In Canada, pumas thrive in Alberta and British Columbia, where their numbers have been guessed at about 700 and 2,500, respectively (Logan and Sweanor 2000). Regardless of where wild pumas exist today, they all face the same major threats to their continued existence, and those are human made.

Threats to Pumas There are two major threats to self-sustaining puma populations—habitat loss and overkill. In this section we discuss these threats, and then follow with a section on what people can do to alleviate them.

Habitat Loss Habitat loss due to human development is the greatest single threat to puma conservation. Anyone who has flown in an airplane over the western United States, or crisscrossed it by car, knows human presence is ubiquitous. Burgeoning cities, towns, and industrial complexes link to one another by highways and railways like a gigantic web of humanity laid over the land, and most sizeable gentle areas that remain are used for agricultural fields and pasture. Anyone who has lived in the West in the past twenty years has seen the rapidity with which urbanization gobbles up wildlife habitat. Foothills and mountain slopes that bore no permanent human habitation back then are now dotted with houses or invaded by urban sprawl. Millions of us know what puma habitat looks like after

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it has been usurped, perforated, and fragmented for human use. If you live in, or have traveled through, the eastern front of the Rocky Mountains between Colorado Springs and Fort Collins, Colorado, or the Sandia Mountains east of Albuquerque and the Sangre de Cristo Mountains north of Santa Fe, New Mexico, or the Coast and Peninsular Ranges in Southern California, you have seen the lasting structures we have built that destroy puma habitat and disrupt puma movements. Today, the eleven western states where pumas range (excluding Texas) comprise the fastest-growing region in the United States. From 1990 to 1998, the human population in the region grew by about 15 percent (U.S. Census Bureau statistics 1999). By the year 2025, there will be about 25 million more people living in those western states, with an additional seven million people living in Texas (U.S. Census Bureau projections 1999). There are more people living in puma habitat today than ever before, and the influx continues. Greater human development contributes to smaller, more fragmented puma populations, increasing their risk of extinction and concomitantly increasing chances for potentially dangerous interactions between pumas and people. Remember Fig. 9-1 in Chapter 9? Imagine an ever-expanding web of humanity as cities, suburbs, and roads advance on the landscape. From civilized centers, more people venture out to recreate in the outdoors. Now think of pumas living in the mountains and those subadult pumas dispersing in random directions. It is not hard to see that as human developments and activity increase so will the risk that pumas will encounter humans. Extreme human development continues to threaten puma extinction from almost all of its historical range in the eastern United States. Natural recolonization, either from the isolated Florida population or from pumas in the West, appears to be stifled by widespread habitat loss, habitat fragmentation, and human presence even though ample prey (e.g., white-tailed deer, wild hog, turkey, raccoons) seems to exist. In the East, outside of Florida, there is scant evidence that individual pumas have tried to wrest an unfettered existence in recent years. In the 1990s, the Eastern Cougar Foundation (a group of naturalists, conservationists, and scientists dedicated to finding and conserving pumas in the East) documented only nine confirmed cases of pumas, with one each in New Brunswick, Ontario, Maine, Maryland, Massachusetts, Missouri, North Carolina, Vermont, and West Virginia. Confirmations were based on one carcass, two video tapes, bile salts extracted from feces in one case, hair identified in feces in two cases, DNA extracted from feces in one case, visual observation and hair in one case, and plaster casts of tracks in one case (Eastern Cougar Foundation 2000). Origins of these pumas were unknown; they may have been wild pumas,

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captive pumas that were released or escaped into the wild, or captive pumas out on a stroll in the woods with their owners (see McBride et al. 1993). Pumas in Florida attest to the perils of living in a heavily peopled landscape. Collisions with vehicles were second only to intraspecies strife as a major cause of mortality (Maehr 1997a). Isolation of the Florida panther due to habitat destruction for urban, agricultural, and industrial developments to the north has limited the population to only about eighty animals, making it susceptible to extinction due to some catastrophe (e.g., global warming and attendant flooding) or demographic decline due to effects of inbreeding depression or genetic drift. Prospects of expanding the population northward by direct human intervention appear bleak. In 1988, seven wild pumas caught in west Texas were released into northern Florida to study the feasibility of translocating pumas to help recover the species there. These animals spent only 10 to 293 days in the wild. Two of them were killed by people and a third was found floating in a river. Not surprisingly, one puma was grazed by a car, since the seven pumas crossed roads about 2,612 times during their movements (i.e., approximately 2.7 crossings / puma-day). In addition, when human hunters took to the woods to pursue deer, hogs, and turkeys, pumas with established home ranges were dislodged, wandered, and entered urban areas and livestock operations where they killed goats and exotic ungulates. This necessitated the early removal of the remaining introduced pumas from the wild (Belden and Hagedorn 1993). A second effort was made in 1993. This time nineteen Texas pumas, comprising both wild-caught and captive animals, were released into northern Florida. These pumas were in the wild for 46 to 492 days. Although fifteen of the pumas seemed to establish home ranges, only five (26 percent) remained in the wild through the end of the study. Five died from human causes, including collisions with vehicles (two), illegal shooting (two), and a neck snare (one). Five were removed for killing domestic calves and exotic Sika deer (Cervus nippon). Four other pumas (21 percent) were removed for a variety of reasons: landowner complaints (one), public safety (one), a cub abandoned by its mother (one), and an extreme excursion into Georgia where the animal was out of reach of the research team. This last animal had also previously been wounded with an arrow and might have died if not for medical treatment. In addition, of four cubs born in the northern Florida release area to introduced females, two died from human causes (collision with vehicle, capture accident), and one was removed with its mother for killing Sika deer (Belden and McCowan 1996). At the other end of the continent, conditions can be just as grim. In the Santa Ana Mountains in Southern California, a population of roughly twentyfive to forty pumas living in about 2,070 km2 of habitat was practically sur-

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rounded by urbanization, except for two tiny, tenuous corridors that allowed limited puma movement to other mountain ranges. Major impediments to movements in those corridors were eight-lane and six-lane freeways (Beier 1995). Immigration was so restricted that females in the population lacked a breeding male for about one full year (Padley 1990, Beier and Barrett 1993). Vehicle strikes were the single-most important cause of death, killing ten of thirty-one pumas that died during a five-year study. Another five pumas died at the hands of humans: one was illegally killed, one was shot by police, and three were killed to stop depredation on livestock (Beier and Barrett 1993). The biologist that studied the population concluded that unless connectivity is maintained to allow pumas to move freely between habitat patches in that region, the puma population in the Santa Ana Mountains will probably go extinct (Beier 1993, Beier 1996). In the Southwest, most of the biologically richest habitat and linkages—the river bottomlands—have changed forever. Look at a map of New Mexico and find the Rio Grande—its headwaters spilling out of Colorado, flowing south through the middle of the state, and to the western boundary of Texas. In 1583, Spanish explorer Antonio Espejo described the bosque along the Rio Grande in about the middle of New Mexico as being four leagues (i.e., about 19 km) wide in places (Bolton 1916). Bottomland woods growing along the shifting, sandy, gravelly course of the Rio Grande provided an almost-continuous corridor shaded by cottonwood (Populus fremontii), willow (Salix spp.), and walnut (Juglans major) trees, interspersed here and there by marshes. Compared to the adjacent upper desert basin, the bottomland was lush with prey, water, and cover, providing a secure link for pumas moving long distances north and south and serving as a lucrative temporary stopover for pumas moving east and west. The bosque probably supported its own resident puma population. Pumas could have preyed on the same animals that Native Americans living along the river relied upon—deer and turkeys. We suspect too that it was a vital habitat for jaguars, linking populations in New Mexico, Texas, and Mexico. That artery is gone now—severely fragmented or completely transformed. Most of the bosque has been chopped down and the floodplain channeled to make room for crops, pastures, cities, towns, and highways. Local protection and restoration projects, such as those of the U.S. Fish and Wildlife Service at Bosque del Apache and Sevilleta National Wildlife Refuges in the center of the state, help to maintain east-west links for contemporary dispersing pumas and a few individuals that use strands of extant bosque and the desert uplands as their home. Our own research documented habitat fragmentation on desert mountains. U.S. Highway 70 divides the San Andres Mountains and the Organ Mountains at San Augustin Pass—once a narrow, natural link of mountainous terrain about

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5 km wide. This stretch became a more treacherous filter to pumas moving north and south along the mountain chain when the highway was expanded from four to six lanes in 1993. Prior to expansion, at least seven of our radiocollared pumas successfully crossed the highway, including four dispersing male subadults, one adult male, and one subadult female that frequently traveled back and forth between our study area and the Organ Mountains, and one adult male that occasionally explored south of the highway. After expansion, the only documented puma crossings were of one tagged adult male and one unmarked subadult male that were both struck and killed by vehicles. None of our five radio-collared adult pumas with home ranges abutting the widened highway dared cross it. The wider highway and the greater volume and speed of traffic it carried probably discouraged pumas from moving between the San Andres and Organ Mountains and reduced survival of those that tried. If the linkage is completely severed, pumas could eventually go extinct in the Organ Mountains, particularly because female immigration from habitat patches across the vast desert basins to the east and west would probably be extremely rare (Sweanor et al. 2000). As human development expands along the Rio Grande floodplain and the western edge of the Sacramento Mountains, natural movements of dispersing pumas across southern New Mexico will dwindle. Across the Southwest, where human impacts affect puma movements in this way, puma subpopulations, particularly the small ones, will become less resilient. If extinction of subpopulations accelerates, entire metapopulations will unravel.

Puma Overkill Overkilling pumas threatens their conservation because it increases risks of extinction, especially to small populations. It can also destabilize regional populations and metapopulations. Overkill results from a variety of factors, including sport-hunting, illegal killing, accidents, and predator control. Hunting pumas is also associated with illegal killing and unintended mortality, such as orphaning of cubs and infanticide. Overkilling segments of puma populations has other risks we cannot fully comprehend because human selection is different than natural selection. Humans are the major cause of death in most puma populations today, except for populations protected from sport-hunting and control and those occupying the most remote, unpeopled habitats. In such places, the most common cause of death, and hence selection, is from other pumas (see Chapter 8). Sport-hunters are the major known cause of death of pumas in most Western states. In 1996 alone, hunters in Arizona, Colorado, Idaho, Montana, Nevada, Oregon, Utah, Washington, and Wyoming reported that they killed a total of 3,003 pumas (see Logan and Sweanor 2000: Table 17-1). Hunting seasons gen-

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erally span the winter months when snow cover easily exposes puma tracks to hunters. Ordinarily, trained dogs are released to trail pumas by scent in their tracks. In the desert Southwest where continuous snow cover is rare, hunters depend on dogs to hunt for puma scent. Odds of dogs successfully trailing pumas on snow are very high compared to trailing pumas on bare ground. Once the dogs catch up to the puma, the cat uses a strategy that it probably evolved to successfully evade predation from wolves and coyotes. It climbs a tree or promontory to get out of reach. This strategy must have worked successfully on wild canids; a puma need only wait for its nemesis to leave, climb down from the perch, and be on its way. But with human hunters, pumas are captive game. For trophy hunters, the puma’s death is practically assured. Humans caused 50 to 100 percent of puma deaths in study populations subjected to sport-hunting in Alberta, Idaho, Montana, and Wyoming (Ross and Jalkotzy 1992, Hornocker 1970, Murphy 1983a, Logan et al. 1986, respectively). Similarly, humans caused 57 to 92 percent of deaths in study populations in Arizona and along the New Mexico and Texas border where populations were subjected to heavy killing to protect livestock (Cunningham et al. 1995, Smith et al. 1986). Humans were also the main cause of death in populations in Arizona, British Columbia, and Colorado that were protected from sport-hunting for research purposes. In those populations, mortalities resulted from illegal killing inside, and legal killing outside, study area boundaries (Shaw 1977, Spreadbury et al. 1996, Anderson et al. 1992). Even in California and Florida, where pumas were protected from hunting statewide but where habitats were severely fragmented by human developments, vehicle collisions were an important cause of puma deaths (Beier and Barrett 1993, Maehr 1997a). Trends in population size could only be ascertained for two studies: the Alberta population increased slightly over nine years, and the Idaho population declined slightly in eight years. In the rest of the populations, human-caused mortalities would not have had a numerical effect on population dynamics only if all of the deaths were compensatory (i.e., if those deaths substituted for other natural mortality factors), which is probably not likely. Our research (see Chapter 10), as well as puma research in Utah (Lindzey et al. 1988, 1992), indicates that human off-take is not fully compensated for. In Alberta, a depressed puma population recovered after a reduction in sport-hunting pressure, suggesting that the killing was additive mortality (Ross and Jalkotzy 1992). Generally, uncertainty about effects of human off-take pervades puma management. Puma-hunting management in most western states is a far cry from science. Except in rare, intensively studied populations, wildlife managers generally do not have reliable population estimates on which to figure allowable harvest. Normally they depend upon bag limits, quotas, and hunting-season length to

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limit off-take, and hope the harvest does not overwhelm the population’s ability to absorb the pressure. Some western biologists have perceived general increases in puma populations since the early 1980s because there has been an upward trend in the number of pumas killed by hunters each year. And hunters have yet to complain about a “shortage” of pumas. Hence, agencies have had the propensity to liberalize puma hunting by extending hunting seasons and increasing kill quotas (see Logan and Sweanor 2000). Increasing puma harvest could be a reflection of more hunters searching for pumas each year. For example, during thirteen hunting seasons in New Mexico (i.e., 1984–1985 to 1996–1997), the number of puma-hunting permits issued per annum increased from 443 to 980 (121 percent), and the number of pumas reported killed per annum (reporting is mandatory in New Mexico) increased from 79 to 168 (113 percent) (Fig. 201). We found a strong linear relationship between these variables. The number of permits issued explained 80 percent of the variation in the puma harvest [1]. Similarly in Montana, the number of puma licenses sold explained 82 percent of the variation in the harvest from 1971 to 1990 (Aune 1991). Puma-hunting management in most western states appears to follow what we call a “sledgehammer approach.” In this approach, hunting off-take is progressively liberalized until population declines affect hunters to the extent that crude population indices based on harvest data—the number, sex, and spatial distribution of pumas killed, hunter success rates, and hunter testimony—sug-

FIGURE 20-1. Trends in number of puma-hunting permits issued and number of pumas killed by hunters in New Mexico.

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gest that the puma population has declined. When that happens, presumably human off-take has “hammered” the population into a decline phase, the amplitude of which managers cannot fully ascertain. If decline is apparent, then managers may decide that people have overkilled the puma population and correct the course by backing off on hunting pressure. The main reason for this approach is the lack of reliable, inexpensive techniques that managers can apply at the landscape level to track puma population dynamics relative to the management prescriptions. Because pumas live at low population densities in complex habitats and are highly secretive, managers cannot fly around in airplanes and helicopters to count pumas and estimate their numbers like they do to survey more visible big game, like deer, elk, or pronghorn. But, harvest data can be disconnected from what may be occurring with the puma population in the wild. The sex structure of harvested pumas does not reflect the living population. It is biased because hunters traditionally seek big males as trophies. Spatial distribution of hunter kills may change from year to year as hunters pursue cats in different areas weather patterns affect hunter success, previously hunted areas have been overharvested, or traffic from hunters is perceived to be unbearable. In some extremely heavily hunted puma populations, hunters are in such high competition with one another that they assail snow-covered ridges and canyons at night with four-wheel-drive rigs and snowmobiles looking for puma tracks with spotlights so that when legal hunting hours arrive with morning, they will be the first ones to release their dogs on the puma’s trail. Furthermore, managers do not comprehend how technology may enhance hunter success. Since we began studying pumas in the West in the early 1980s, puma hunters have increased their use of snowmobiles and all-terrain vehicles to search more habitat more thoroughly, radiotelemetry to track their dogs on puma trails more efficiently, and two-way radios and wireless phones to coordinate efforts between hunters. To what extent these tools mask downtrends in puma populations is entirely unknown. Some hunters may be reluctant to report that they may be causing declines in puma populations because that might bring tightening restrictions. For outfitters and guides that may earn $3,000 per puma hunt, the incentive to exploit the puma population is high. In addition to pumas killed legally by sport-hunters, there is also “collateral damage” that is sometimes illegal, sometimes accidental, and which is almost impossible for wildlife law enforcement officers and managers to quantify. Puma hunters we have met over the years have told us disastrous stories of incidents occurring in the bush: hunting dogs track a mother puma to a nursery and maul kittens to death (also see Roberson 1984); a hunter mistakenly judges the sex or size of a puma in the tree, kills it, then abandons the carcass to pursue another, bigger trophy. Hunters sometimes kill female pumas legally and unknowingly

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cause the orphaning of cubs. Cubs orphaned when they are less than nine months old usually die, and older cubs stand less of a chance of surviving. A few states have sanctioned “pursuit seasons” where hunters are allowed to chase pumas with their dogs but not kill them. But this may not be the presumed benign activity it was thought to be. Roberson (1984) discussed some of the abuses in “pursuit seasons,” which include mauling of cubs by dogs, purposeful wounding of pumas to restrict their movements so they could be found again during the kill season, and illegal killing of trophy pumas. There is also the possibility that repeated harassment of individual pumas by hunters for entertainment or to train their dogs may cause deleterious physiological effects (Harlow et al. 1992). We suspect that as hunting pressure on puma populations increases, so do “collateral damage” and the degree of uncertainty concerning the effects of human exploitation on puma populations. Although most states that allow puma hunting attempt to protect mothers by outlawing the killing of females with cubs at their sides (Logan and Sweanor 2000), this does not prevent their killing. Puma mothers are susceptible to harvest when they are not accompanied by their cubs. Research in Wyoming showed that during the winter hunting season, mothers were away from their cubs about 50 percent of the time that researchers with dogs encountered them (Logan 1983). More so, researchers studying pumas in Utah found that cub tracks were found with their mothers only 25 percent of the time; they concluded that 75 percent of mothers would not be recognized by hunters (Barnhurst and Lindzey 1989). In addition, we observed that distended teats and mammary glands are not a reliable clue for hunters. They are visible in mothers only during about the first two months after cubs are born and not necessarily right after cubs have suckled, which empties the tissues. Since as many as three out of four adult females may be raising cubs each year, it is possible that roughly 38–56 percent of adult females killed by hunters each year are mothers with dependent cubs. Further, there are at least three “beliefs” about pumas from which some western wildlife managers operate that could spawn results contradictory to management objectives. These could lead to erroneous conjecture about local puma density and thus to overkill of pumas or their prey. One assumption, that male pumas disperse long distances and show up in marginal habitat areas because all the surrounding puma habitat is “saturated” with pumas, we now know is false. Male puma dispersal is obligatory; they will even move through habitat with a suppressed population. Long-distance dispersal in male pumas probably evolved to avoid inbreeding and carries them through all kinds of terrain that may be prime or marginal habitat, even nonhabitat (see Chapter 13). Another false assumption is that male pumas fight over territory because the habitat is “satu-

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rated.” Thus stories heard from hunters about fighting pumas, as well as observed battle scars on hides from harvested cats, reinforce the notion that the puma habitat is full. We realize now that male pumas fight to compete for access to mates and that the rate of fighting can be independent of puma density (see Chapter 8). Finally, some managers believe that since pumas limit their own populations below the level set by the prey, management of human harvest of prey populations does not necessarily have to consider effects of puma predation. Pumas will readjust their populations accordingly. However, now we understand that pumas can limit or hasten a decline in a prey population. Thus, puma predation along with sport-hunting could reduce prey populations. Puma populations will likely decline after a lag period, which could be a few years after a decline in the prey base (see Chapter 17). Furthermore, additive mortality on prey populations imposed by sport-hunting could exacerbate declines in both prey and puma populations. Suppressing local puma populations may be a desired management objective. Wildlife managers may be pressed to reduce puma numbers in areas where encounters threaten the safety of humans and their pets (see Aune 1991, Halfpenny et al. 1991, Torres et al. 1996). Puma attacks on humans are relatively rare. However, the rate of puma attacks has increased since 1970. Between 1890 and 1996 about fifteen people were killed and about fifty-nine people were injured during sixty-six attack incidents in the United States and Canada combined. From 1970 to 1996, ten people were killed and forty-five injured in forty-nine attacks (Torres 1997). Two interacting reasons for the increase are that pumas generally expanded in numbers and distribution during that period, while numbers and distribution of humans living and recreating in puma habitats exploded (Aune 1991, Torres et al. 1996). Managers may also prescribe puma control programs to quell chronic depredation on livestock. For example, state-sanctioned puma control to protect domestic sheep has been operating in the Guadalupe Mountains in southeastern New Mexico since 1985. In addition, puma control may be deemed necessary to help recover endangered ungulate populations. For instance, in 1999 a puma bounty hunting program and extremely high harvest quotas were prescribed for southwestern New Mexico by the New Mexico Department of Game and Fish because puma predation was identified as the principal proximate cause of death in the state-endangered desert bighorn sheep. Because reduction programs create local population sinks, wildlife managers need to monitor their region-wide effects. In addition, these programs probably reduce the number of dispersing pumas available to augment other subpopulations. Hence, depending upon the number, size, and distribution of population sinks, attendant overkill could threaten the resilience of a population or metapopulation.

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Another source of uncertainty is that human-caused death is a different selection process than natural selection. Large-scale hunting of pumas by humans, especially for sport and population control, has influenced puma populations for only about the past two hundred years—about 0.05 percent of the time since extant puma lineages emerged. Humans generally kill the very individuals that nature would have selected to propagate the species—big males and females. Based on the life history and behavioral strategies that pumas apparently evolved (see Parts 2 and 3), the most successful pumas should include large, robust males and reproductively successful females. Trophy hunters seek the biggest males; hence, they remove individuals that are likely the most fit. Big males possess adaptive traits along with their large size, which allow them to successfully survive in the environment, compete with other males for mates, and father thriving young that inherit their “good genes.” Furthermore, the killing of territorial males by hunters may increase infanticide of cubs by new immigrant males. This reduces reproductive success of males that won the competition to breed, and it reduces the reproductive success of females. If big males cannot be found, then hunters may kill big females instead, the very ones that are probably most reproductively successful in North American environments. Larger females are probably better able to protect their offspring against marauding male pumas and other predators and to exploit a greater variety of large prey to more efficiently feed their young. What is the genetic, and thus the adaptive, cost of humans changing the selection process for pumas? We presume that killing individuals that natural selection would have otherwise chosen to survive and reproduce will tend to reduce fitness. Researchers investigating genetic variability in bighorn sheep, a species with a breeding system having characteristics similar to that of pumas (i.e., polygynous, sexual selection), have illuminated one possible mechanism for decline in fitness. Large-horned rams, which have breeding superiority, were more heterozygous than small-horned rams. They concluded that harvesting large-horned rams could reduce genetic variability and thus contribute to loss in fitness in bighorn sheep (Fitzsimmons et al. 1995). Because natural selection produced the traits that allowed pumas to persist today, we believe that natural selection processes should proceed at least in some large wild areas (see “Zone Management” in this chapter). Doing so may help conserve biological diversity and the resilience of puma populations.

Alleviating Threats It is relatively easy to complain about the factors that threaten puma conservation. Devising solutions is much more difficult and risky. But if, as a society,

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people decide to conserve self-sustaining puma populations and their wild environments, then it is going to require an informed and involved public.

Habitat Conservation Pumas require huge, wild, connected landscapes to support even minimum selfsustaining populations. Flourishing habitats have sufficient persistent prey sources and a complex terrain and vegetative structure that provides cover for stalking, security, and nurseries (see Logan and Irwin 1985, Laing and Lindzey 1991, Logan and Sweanor 2000). The wild landscape has to be big enough to accommodate breeding adults during their daily movements to hunt for food, seek mates, and avoid other pumas or predators, and it must provide for any needed seasonal habitats and movements of migrating pumas and prey. The landscape also has to have sufficient connectivity to accommodate natural dispersal patterns of puma progeny. As we discussed in Chapter 10, a minimum habitat area of 1,000–2,200 km2 is needed to sustain a nonmigratory puma population with a greater than 98 percent probability of persisting for one hundred years (Beier 1993), and that area needs to be linked to other puma-occupied habitats. Puma populations in smaller habitat patches without immigration have relatively high extinction risks. For example, twelve of one hundred simulated puma populations went extinct over a one-hundred-year period for habitat areas of 270 km2, the size of the Organ Mountains (Sweanor et al. 2000). Without immigration, small populations cannot be augmented numerically and thus are subject to greater risks of extinction from demographic and environmental uncertainty and natural catastrophes. Demographic uncertainty is risk resulting from random events on survival and reproduction of individuals. Environmental uncertainty refers to chance events like changes in weather, food supply, competitors, predators, or disease (Meffe and Carroll 1997:217). Natural catastrophes could be hurricanes, extensive wildfires, extensive human developments, and global warming. Furthermore, without gene flow from immigrants, inbreeding and genetic drift may erode genetic variability, viability, and reproductive vitality. Pumas could lose the ability to adapt to altered environmental conditions (Chepko-Sade et al. 1987, Gilpin 1987, Lande 1988, Saccheri et al. 1998). Clearly, immigration is essential for numeric and genetic augmentation in populations, especially small ones. In North America, pumas depend primarily upon large prey such as whitetailed deer, mule deer, elk, moose, peccary, and bighorn sheep. Yet they augment their diet with a variety of small prey such as rabbits and rodents. In highly variable environments like the desert Southwest, wildlife managers (i.e., professionals trained in wildlife sciences and government-appointed secretaries, directors, commissioners, and board members responsible for overseeing wildlife manage-

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ment agencies) should recognize that prey populations may fluctuate dramatically with changes in weather and climate. As we have pointed out, pumas are intrinsic participants to predator-prey dynamics in ecosystems. Their numbers are ultimately limited by their own food supply. During stress periods such as drought (or severe winters in more northern climes), pumas can hasten a decline in their prey, and, after a lag, the puma population must also decline. This will occur especially where alternate sources of prey are not available to sustain the puma population. Resilience of the puma population is tied to the ability of the main prey population to recover from a severe downturn. In stress periods, managers should monitor big-game populations more closely, because they may need to adopt more conservative harvest prescriptions to prevent even steeper declines in the puma prey base. Remember, human hunters are in competition with pumas for prey animals (also see Murphy et al. 1999). Yet, most human hunters today are extrinsic predators to an ecosystem. Unlike pumas, humans generally come from outside of ecosystems in which they hunt, and then haul their kill back out (except in subsistence situations). Furthermore, humans are not totally dependent on hunting success to survive and reproduce. Hunter selection may also counter natural selection, since healthy game are typically killed for food or trophies, and high-tech weapons (i.e., firearms, telescope sights, compound bows) make it more likely that animals are killed that might otherwise survive and reproduce. Hence, human offtake is probably mainly additive mortality that can reduce a population further if it is already suppressed by adverse habitat conditions (e.g., drought, severe winters, and attendant loss of food) and predation. Puma habitat conservation should be a combination of protecting habitat patches and the landscape linkages that join them. In the Southwest, where puma habitat comprises mountains separated by broad desert basins, this strategy is crucial to puma conservation. Here, pumas may exist in a metapopulation where long-term survival of puma subpopulations is dependent on the movement of pumas between habitat patches (see Chapter 10; Sweanor et al. 2000). Dispersing pumas augment subpopulations by moving through habitat and wild land or rural matrix. In this structure, the relatively resource-barren basins (i.e., matrix) and even the small habitat patches, such as the Fra Cristobal and Caballo Mountains, which are within puma dispersal distance, facilitate numeric and gene flow to more distant and substantial habitats such as the Black Range and Gila Wilderness. Female dispersers that do not reach the more distant patches disperse to closer patches and reproduce. Then their progeny disperse to other patches. For male pumas, wild land matrix, wild land corridors, and habitat patches are essential pathways for their much-longer dispersals. Although it may take a few generations, an individual puma’s genes can flow

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across the breadth and length of the basin and range physiography of New Mexico, where habitat patches and their tenant puma populations function as stepping stones along the way (Sweanor et al. 2000). In huge, contiguous habitat blocks, like Rocky Mountain masses, the same thing occurs, except dispersing pumas are almost always moving through habitat. Throughout the first 99.95 percent of puma evolutionary history, pumas could disperse from their natal areas in random directions with relatively little human interference, colonizing habitats, and developing interbreeding subpopulations. They evolved into an outbred species. It is these characteristics that made the puma such a resilient carnivore in changing environments. In the West, if self-sustaining, interconnected puma populations are to persist as they do today, then wildlife managers need to immediately identify, map, and conserve present puma habitat and landscape linkages. Already state and federal wildlife agencies have baseline information to begin the mapping process. There is statewide information on distributions of pumas, puma harvest, depredation incidents, and puma-human encounters to help identify occupied puma range and potential landscape linkages. Wildlife agencies can also tap into the expertise of their own local biologists, landowners, hunters, and naturalists regarding puma activity. And they can rely on the intuition of puma biologists who have studied behavior, habitat use, and movement patterns to help them identify potential links. Where critical questions arise regarding whether or not pumas actually move through segments of wild lands, there is no better source than the pumas themselves. Just as we learned from our research, radiocollared pumas provide detailed information on habitats and links that they use: subadults trace dispersal patterns that can eventually take them to other subpopulations, and adults delineate migration routes. Computerized geographic information systems are available for creating databases and maps from all of this information to assist wildlife managers in formulating conservation strategies for puma habitat at local and regional landscape scales. If pumas are to thrive in the East, there will also need to be an increased human tolerance toward this carnivore, and robust public support for habitat protection, habitat restoration, and modification of many of the human-built impediments to puma movements. There will need to be public or private funds generated to compensate people for puma predation on privately owned animals. Wildlife agencies will need to maintain well-trained, rapid-response capture teams to react to emergency situations to safeguard humans, private property, and pumas. Puma habitat and wild-land linkages are a patchwork of public and private lands. Protecting and managing them will require partnerships at all organizational levels of our society—federal, state, county, and municipal governments,

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private organizations, and individuals. Public domain, which includes national forests, Bureau of Land Management lands, national parks, national monuments, national wildlife refuges, federal lands under the authority of U.S. Department of Defense, state parks, and state wildlife management areas, are the foundational habitats that sustain puma population in most of the West, principally because those lands have the least human development. Rural and undeveloped private lands (e.g., farms and ranches) furnish vital needs too, particularly those that function as movement and migration corridors for pumas and their ungulate prey. However, in Texas, most of the puma habitat is composed of privately owned land. In southern Florida, the healthiest and most productive Florida panthers primarily inhabit private lands (Maehr 1990b). Protection of puma habitat on public domain can already be supported through current rules and laws that govern wildlife conservation. On multiple-use public domain lands, extraction of resources such as timber and minerals should be planned to minimize negative impacts on pumas and their ungulate prey, particularly in critical areas where activities on adjacent unprotected lands have destroyed or fragmented previously existing habitat or linkages. Ha b i t a t improvements can also be made, for instance by prescribing controlled burns to benefit ungulate prey. Outdoor recreational structures and facilities (e.g., campgrounds, roads, trails) could be designed to reduce risks of puma encounters and habituation to human activities (Ruth 1991, Murphy et al. 1999). On the other hand, local habitat modifications could be used to deter puma use of major human activity areas and to minimize predation on endangered animals (e.g., cutting or prescribed fire to reduce shrub cover that attracts herbivores and provides stalking cover for pumas). Private lands can be a problem, particularly where owners are not obligated to protect habitat for large carnivores, either because they harbor personal animus toward predators or because other land uses, such as residential, agricultural, or industrial development, yield greater monetary returns. In those cases, land stewardship programs with alternate incentives should be developed for landowners to compensate them for habitat protection. Government or private organizations could purchase land or lease easements and designate them for wildlife use. Substantial tax breaks on capital gains could be given to landowners that sell land for the preservation of wildlife habitat. For current landowners already dedicated to wildlife conservation, relief from inheritance taxes could sustain that legacy in their families. Otherwise, heirs may opt to sell wild and rural lands to opulent developers to offset paying high taxes. Controls will be needed in some regions to prevent urban developments from invading critical wildlife habitats. Support for conservation-oriented government programs requires strong public support to push through needed legislative action or ref-

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erenda. If the public at large believes that puma habitat and wild land linkages should be protected, then the public should share the costs of protecting those lands. The same can be said for restoring linkages that enhance the persistence of puma populations. An advantage is that restoration efforts aid other large animals as well. Florida panthers benefited directly from wildlife underpasses and fencing developed along a 64-km stretch of Interstate 75 to reduce collisions with wildlife. Underpasses allowed resident panthers to link parts of their home ranges and prevented the highway from becoming a population sink. Other mammals also used the underpasses, including bobcats, raccoons, black bears, white-tailed deer, and alligators (Alligator mississippiensis) (Foster and Humphrey 1995). Pumas used wildlife crossing stru c t u res in Banff National Park, Canada, where their home ranges were bisected by the Trans Canada Highway (Gloyne 1999). Some of those same stru c t u reswere also used by elk, deer, and wolves (Clevenger and Waltho 2000). In southern New Mexico, highway underpasses would pro bably reestablish a secure link between the San Andres and Organ Mountains. Those stru c t u res are expensive to build and thus re q u i re substantial public support to justify the expenditures. Designing them into highway development or improvement plans from the outset would reduce the long-term costs, both in money and to wildlife populations. In terms of dollars, it would be more expensive to go back to U.S. Highway 70 at San Augustin Pass, rip out the highway at strategic locations defined by habitat features and animal movement patterns, and install wildlife underpasses. Still, they may be needed to restore safe travel for mammals moving between the San Andres and Organ Mountains. Across the West today, there are puma habitats and wild-land linkages that have been destroyed and degraded; yet, there is still ample habitat in the public and private domain to support thriving puma populations. Now it is up to wildlife managers to inventory the remaining puma habitat and landscape linkages. It is the responsibility of the caring public to see to it that this is done. Habitat and linkages can only become part of the working structure for puma conservation if they are mapped and people can conceptualize their worth. Then wildlife professionals and interested citizens can look for and quantify the threats relative to human developments and devise strategies and enact programs for their conservation. Pumas and a myriad of other wildlife species will benefit and so will the quality of life for humans with strong obligations toward conserving wildlife, intact ecosystems, and biological diversity. In addition, habitats and linkages that benefit pumas will enhance chances for successful restoration of other big carnivores, such as gray wolves in the Rocky Mountains and Mexican wolves and jaguars in the Southwest.

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Preventing Unnecessary Overkill Ultimately, social values determine whether or not managers and scientists are allowed to manipulate puma populations to achieve management objectives or to test research hypotheses. Killing individual nuisance pumas that threaten humans and livestock is understandable, because they directly affect people’s individual well-being, and possibly their survival. But controlling puma populations to save endangered species or to boost ungulate populations to improve recreational hunting opportunities agitates controversy. Before proposing puma control for those reasons, we believe wildlife managers should ask themselves at least these basic questions: (1) Is puma predation the most important limiting factor suppressing the ungulate population? (2) Where is the ungulate population relative to the ecological carrying capacity of the habitat? If the population were above carrying capacity, it would be expected to decline even with puma control. If it were substantially below carrying capacity, then the ungulate population may increase, provided puma predation is mostly additive mortality. (3) To what extent is puma predation compensatory or additive? (4) Is puma control to save a small population of animals contributing to conservation of biological diversity? (5) In the case of endangered species restoration (e.g., bighorn sheep), to what extent would numerical augmentation of the imperiled population offset predation? (6) Are there other options? In addition, there are questions that managers should ask themselves about assessing the effectiveness of control actions: (1) How much do I need to reduce the puma population to attain the objective? (2) How will I know when I get there? (3) How long do I need to suppress the puma population? (4) How will the creation of a population sink affect other adjacent puma populations? Information on effects of puma control programs is scant, but answers to some of these questions could be attained from onsite research. That is why we strongly urge that puma control programs be carried out as experiments that test a priori hypotheses and include treatment and reference areas. To know what impact human off-take is having on pumas, wildlife managers must monitor puma populations in their habitat. Unfortunately, managers lack monitoring techniques with known accuracy, precision, and bias. A puma population estimator involving sampling puma tracks on snow from a helicopter has been tested but found to be very imprecise (Van Sickle and Lindzey 1991). Besides, almost continuous snow cover is needed, which is rare in most of the Southwest, and can be exceptional even in northern latitudes with chronic high winds and variable snowfall. Counting puma track on roads in southern Utah was found unreliable because of the poor relationship between puma density and track-finding frequency (Van Dyke et al. 1986, Van Sickle and Lindzey 1992). Biologists studying the utility of puma track surveys in Arizona found

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that track surveys probably will not detect small population fluctuations but may be useful in detecting 30 to 50 percent changes if 30 to 190 transects, each 8 km long, are established in dry washes. They estimated that 700 transects would be needed to detect a 10 percent decrease in a puma population and that the expense for such efforts would be prohibitive (Beier and Cunningham 1996). Thus, it appears that puma populations would fluctuate substantially before wildlife managers could measure the trend with any skill (i.e., the “sledgehammer” effect). Another method tries to identify individual pumas by measurements of their tracks in the field. It has discriminated individuals in specific research situations, but to do so the technique requires measurements of a large number of tracks from the same individual walking on similar substrates, conditions difficult to achieve in the field (Smallwood and Fitzhugh 1993, Grigione et al. 1999). To our knowledge, this method has not been applied at the landscape level. Obviously, there is a need to refine all these track indices to reflect puma abundance. Other promising, noninvasive techniques for estimating population size involve genotyping individual animals from tissue samples. Ernest et al. (2000) has genotyped individual pumas by their feces in California. Similar techniques were used to estimate population size in coyotes in the same state (Kohn et al. 1999). Techniques recently developed for lynx (McDaniel et al. 2000) and grizzly bears (Mowat and Strobeck 2000), using DNA from hair roots that have been snagged at bait stations in conjunction with mark-recapture analysis, could be modified to estimate puma population size. These methods should someday be applied to an intensively studied puma population to test their usefulness as indices to abundance. In the meantime, managers should assess puma population trends with a suite of indices, including track counts, harvest data (i.e., catch per unit effort), depredation complaint frequency (Torres et al. 1996), and testimonials from reliable people that routinely contemplate puma abundance in habitat. Until better monitoring tools are operational, we advise that puma sport-hunting prescriptions have conservative harvests of male pumas and protections for female pumas, regardless of whether or not they are raising cubs.

Adaptive Management—Involving People What can be done to provide for long-term puma conservation and the needs of people? Earlier in this chapter, we emphasized the need to appeal to people’s sense of responsibility, to conserve puma habitat, and to protect against puma overkill. Dealing with those, however, will be successful only inasmuch as people’s values toward land, animals, and other resources are acknowledged. Hence, an adaptive, landscape-level management approach that derives from reliable ecological information and public input is a defensible solution. Such an

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approach requires that wildlife professionals have reliable management tools and support from an informed, caring public. ZONE MANAGEMENT

Zone management was the adaptive management approach we proposed for pumas in New Mexico (Logan and Sweanor 1998). This involved partitioning the state into zones with different management objectives for puma populations in them as determined by wildlife managers and public stakeholders (Fig. 20-2). Management in each zone should be approached as an experiment, with its own objective(s), hypotheses, and prescriptions. But because wildlife managers cannot afford to monitor all zones, a monitoring program should be established, at least in select zones of each category. Managers can thus gauge their success in meeting objectives and adjust management prescriptions accordingly. Quotas should limit the annual puma kill in zones that allow population control and sport-hunting. Quotas would be estimated by agency biologists as the number necessary to achieve population objectives. Rates of puma population increase

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FIGURE 20-2. A hypothetical zone-management approach for pumas in New Mexico.

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estimated in this study could be used as reference points for calculating first quotas from initial population estimates. We developed three zone categories: Control Zone, Hunting Zone, and Refuge Zone. Control Zones allow for experimental puma population reduction in localized areas where it has been deemed necessary to substantially suppress puma numbers to protect human safety, private property (i.e., livestock, pets), and endangered species (e.g., desert bighorn sheep). Puma control could be accomplished by heavy sport-hunting pressure or killing by government agents. Regardless of the quota, individual pumas involved in human safety or depredation incidences could still be killed. Hunting Zones allow for sustained sportharvest with the objective of maintaining puma population stability (i.e., preventing decline). All females should be protected with lower quotas than those put on males, and all cubs should be protected. Light hunting could be allowed in areas used to link Hunting Zones and Refuge Zones. Refuge Zones would not allow human off-take, except individual pumas that threaten human safety and private property. Refuge Zones would function as robust biological savings accounts that contribute to puma population resilience (Weaver et al. 1996) by countering management-related mistakes that are probably going to occur from time to time in human-impacted populations (McCullough 1996). Refuges also allow natural selection to act on pumas. Puma genotypes in refuges can emigrate and become breeding members in other exploited populations. Our empirical data on puma demographics suggests that Refuge Zones should be at least as large as the San Andres Mountains chain, about 3,000 km2, and should be connected to other habitat patches via landscape linkages (see Chapter 10, Sweanor et al. 2000). Refuge Zones also function as reference areas against which managers can compare puma population dynamics in Control and Hunting Zones. For the state of New Mexico, we recommended that there be at least two Refuge Zones—one in the north and one in the south (Fig. 20-2). Applying this approach, or any other, requires that wildlife managers obtain available information on puma numbers and distribution in the state. They should map out potential puma subpopulations that are sources, sinks, and vulnerable to extinction because of small size or poor connectivity. Known and potential landscape linkages should also be mapped. Then, with consent from substantial stakeholders, they should proceed with developing management objectives for zones and with mapping them. The number and juxtaposition of Control, Hunting, and Refuge Zones should be decided carefully to assure that management in one zone does not jeopardize the management of an adjacent zone. Especially, boundaries of a Control Zone should not adjoin boundaries of a Refuge Zone because pumas killed in the Control Zone could have home ranges that overlap the Refuge

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Zone. In other words, the border between the Control and Refuge Zones could act as a sink for the Refuge Zone puma population (Woodroffe and Ginsberg 1998). This may have occurred when New Mexico wildlife managers put puma zone management into operation in fall 1999. Most of southwestern New Mexico was made a Control Zone (principally to protect desert bighorn sheep), with the eastern boundary abutting the San Andres Mountains chain, which was made a Refuge Zone. Managers considered the western boundary of White Sands Missile Range (which consists of a cattle fence) to be a reasonable demarcation between the two zones. Yet, hunters can kill pumas on about 93 km2 of habitat on the western edge of the San Andres chain. Thus, killing pumas on the Control Zone side would actually exploit the Refuge Zone puma population because, based on our research, most of the adult pumas ranging in those 93 km2 have home ranges that overlap the Refuge Zone. This problem could be easily rectified by moving the Refuge Zone boundary west to the north-to-south railroad line that bisects the Jornada del Muerto, a basin that clearly separates patches of puma habitat and thus the puma subpopulations. Still, progeny dispersing from Refuge Zones would be expected to have substantially lower survival rates if they immediately entered a Control Zone. Likewise, Control Zones could reduce immigration into Refuge Zones. Areas between Control and Refuge Zones could be buffered by conservatively harvested Hunting Zones. In the Southwest, desert basins along Refuge Zone boundaries could serve as natural buffers. Clearly, monitoring the impacts of people on puma populations in zones will be needed to assess and modify zone boundaries and zone management prescriptions. Puma off-take, whether to sustain the population for sport-hunting or to depress it for control, should be gauged relative to the rate at which the population tends to increase (Caughley and Sinclair 1994). We suggest that the observed rates of increase for our January population estimator (which coincided with most puma hunting seasons in the West) could be used as initial reference points (see Table 10-8), provided two conditions are met: (1) wildlife managers have a reliable estimate of puma numbers, and (2) the puma population is increasing. We recommend using the rates of increase for adults in the Reference Area as a guide, because they covered seven years (1989–1995) in which puma carrying capacity fluctuated. Rates of increase in those conditions may be reasonable averages with which to start. If the objective is to harvest a population to provide sport-hunting opportunity, then we recommend an initial harvest rate of less than 8 percent of adult males. Female pumas should be protected as a safety valve against overkill for two main reasons: (1) error in puma population estimates are generally not known, and (2) population monitoring methods can be very imprecise and may only detect 30–50 percent

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changes in puma numbers. A nominal female quota is desirable to legalize the killing of females that are mistaken as males by hunters and individual females encountered in the field by chance but which provide no opportunity for sex determination before hunters kill them. Thus hunters would report those females to be tallied by wildlife officials without fear of legal reprisal. With a quota on males and a smaller subquota on females, a Hunting Zone would be closed when either the male or female quota was reached. By virtue of the disproportionate quotas allotted to each sex, hunters are compelled to carefully choose males. In Hunting Zones, we discourage harvesting a puma population at the maximum rate of increase for the adult population (e.g., 11 percent), because the margin for error is small. The puma population would be harvested at the brink of population collapse. Furthermore, environmental perturbations, such as drought and prey declines, could cause a decline in the puma population growth rate. This scenario is particularly realistic for the relatively variable puma habitat in the Southwest. In such instances, the population may decline without harvest. During puma population decline, off-take, particularly at high rates, would probably accelerate population decline. On the other hand, if the objective is to reduce a puma population, then the adult puma population should be harvested at a rate exceeding the rate of increase (e.g., greater than 11 percent); both males and females should be removed. And based on our results from the Treatment Area it may be necessary for off-take to exceed 28 percent of the adult population to cause a decline. But managers should be sensitive to the possibility that extended off-take at such high rates may cause local extirpation of pumas. The major problem wildlife managers have with developing a harvest strategy is that they seldom (i.e., only in populations subjected to intensive research) if ever (i.e., all other cases) have reliable estimates of puma numbers in any region of interest. Zone management is an adaptive approach that addresses an array of puma management issues—from population control to protection— through public input, experimentation, population monitoring, and refuges that buffer management mistakes. But zone management is not a panacea; there are other approaches wildlife professionals and the public should pursue to aid puma management and conservation. RESEARCH

Research is needed in manifold areas. Whenever possible, a priori hypotheses should be tested and empirical data gathered in a manner for inclusion into models (e.g., population models, habitat models). Biologists should attempt to identify key patterns to develop theory about natural phenomena, steer man-

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agement and conservation strategies, and guide future research. Below, we propose urgent research needs. • As mentioned previously, there is a need for accurate, precise, and relatively inexpensive methods of monitoring puma population trends in habitat. Wildlife managers require such tools to gauge impacts of population management (i.e., sport-hunting, control) environmental perturbations (e.g., drought, prey fluctuations, habitat loss), and disease outbreaks. • Puma habitat use should be studied to help wildlife managers identify habitat and landscape linkages. This type of information is essential for designing nature re s e rves intended to accommodate pumas and other large carnivo res and for land managers assessing how human developments, resource extraction (e.g., logging, mining), and habitat modification (e.g., prescribed burning) may degrade or enhance puma habitat. It will also help to highlight are a s of potential puma-human encounter and could be used in designing trail systems and campgrounds in parks and wildlands that minimize encounters. It may also help managers plan habitat alterations that discourage puma use of c e rtain areas to reduce risk to endangered species, livestock, pets, and humans. • Puma behavior in peopled landscapes, such as housing developments and heavily used recreation areas, needs to be investigated to understand to what extent pumas may avoid or tolerate human activity. Likewise, we could learn what kinds of human behaviors or habitat modifications may attract or repel pumas. Databases on puma-human encounters should be maintained to divine patterns in encounters and to identify hot spots and trends. • Long-term research should address puma population dynamics, particularly how human off-take, prey fluctuations, and habitat loss affect them. • The genetic structure of regional puma populations or metapopulations need to be deciphered so that we can understand gene flow and how human modifications to habitat and landscape linkages may affect it. • Relationships of pumas to their prey need to be studied, particularly where puma predation may threaten endangered animals, such as desert bighorn s h e e p. It is also important to understand to what extent puma predation limits or regulates prey populations (see Caughley and Sinclair 1994:110–130) and to determine the importance of prey switching in multi-prey systems. These are especially important for ungulates that humans also impact t h rough hunting and habitat modification. Such information is fundamental for scientific management of puma and ungulate populations. Studies of pumas and ungulates will probably have to be at least twenty years in duration to include the full range of population fluctuation (i.e., increase, peak,

390

•

•

•

•

•

PART V. PUMAS AND PEOPLE

decline, low) of both predator and prey. As we learned ourselves, ten ye a r s was barely long enough to see drastic fluctuations in the deer population and not long enough to see the numerical response of the puma population to the deer population crash. Mo re ove r, we we re not on hand to document the biological extinction of the desert bighorn sheep. Experimental re m oval of prey or pumas could be used to test hypotheses about how puma predation affects p rey and vice versa. Additional research on translocated pumas should be done to learn more about their behavior and survival. This could be done in concert with removal experiments in puma-prey interaction studies. Removal of pumas from treatment areas does not have to be lethal for all individuals. After all, the cats are killing natural prey. Serious consideration and planning should be given to the translocation of select pumas following guidelines suggested by Ruth et al. (1998) and Belden and McCowan (1996). Those guidelines should be improved with additional research findings. Competition between pumas and other carnivores needs to be studied. Current research projects on pumas, wolves, and coyotes in the Northern Yellowstone Ecosystem, pumas and wolves in the central Idaho wilderness, and pumas and jaguars in Mexico should provide vital information on effects those carnivores have on ungulate populations as well as how they influence one another. Once Mexican wolves are well established in the Southwest, similar research should be done there too. Furthermore, the extent to which humans compete with carnivores should be assessed along with our impacts on prey populations. Aversive conditioning of pumas should be tested, such as using trained dogs to drive pumas away from humans and our focal activity areas, such as homes and campsites. Karelian bear dogs have been used in recent years to shepherd bears from human activity areas in national parks and forests (Hunt 2000). Perhaps an alternate breed would be the Rhodesian ridgeback, which was originally used to hunt African lions. Such guard animals may be a realistic option for people who live or recreate in puma habitat to minimize dangerous encounters and the need to kill pumas. Similarly, research should be done on protecting livestock from pumas using guard animals. Guard dogs (e.g., Akbash, Anatolian, Komondor) reduced coyote predation on domestic sheep and reliance of producers on lethal predator control (Andelt 1992, 1999). Human dimensions should be studied to better understand people’s beliefs, values, and preferences regarding pumas. For example, a 1999 study in Utah indicated that the use of predator control actions to protect game populations had only moderate support, and the use of sport-hunting to control black

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bears and pumas, the use of dogs to hunt bears and pumas, and the use of bear baiting were not supported by the majority of Utahans (Teel 1999). Understanding people’s values and perspectives toward wildlife is fundamental to a wildlife agency’s effectiveness in responding to public expectations, developing management prescriptions, and directing education. EDUCATION

As an extension of research, education is basic to our understanding of nature and to developing conservation strategies. Wildlife professionals need to be informed about puma ecology so they can formulate realistic policies and prescriptions that stand the greatest chance of success. The public needs to be informed about pumas because knowledge helps mold their beliefs and values and encourages realistic expectations from wildlife managers. Public workshops and other media (e.g., printed, television, radio) are particularly important in regions where the odds are greatest for puma-human conflicts. In recent years, agencies in puma-range states have actively informed people about pumas, and they need to continue these efforts. Moreover, it should be the responsibility of people living and recreating in puma habitat to inform themselves by gleaning information in libraries and by tapping the knowledge of wildlife experts. People should contact their state’s wildlife management agency if they have questions. Practically every Western state has produced a brochure about pumas in the Living With Wildlife series that contains a brief summary of biological information about pumas and tips on how people should behave if they live or recreate in puma habitat. A useful pocket book is Torres’ (1997) Mountain Lion Alert. It is filled with basic facts and good advice about pumas. People spending time in puma habitat should read it; parents should read it to their children. Some communities even organize their own workshops and produce informational material. A good example is Sandia Mountain Bearwatch, composed of citizens living in the Sandia Mountains east of Albuquerque, which informs people in New Mexico about wildlife in the mountains, ways to minimize detrimental impacts to animals and chances of dangerous encounters with bears and pumas, and how they should behave if they meet these animals. Bearwatch accomplishes this through consulting with wildlife professionals, researching published references, distributing their own written materials, and organizing neighborhood workshops. Research scientists also have an obligation to inform the public. Most often, they are the ones who have studied certain species or ecosystems to the extent that they have earned the status of “expert.” Scientists need to distill the oftencomplicated information into a format that most people can understand. What good is it to wildlife conservation if research results are only written in techni-

392

PART V. PUMAS AND PEOPLE

cal jargon and concepts acceptable to scientific journals, but wildlife managers and the public cannot fathom the messages? RESPONSIVE MANAGEMENT

As the human population expands into rural and wild landscapes the likelihood that pumas will encounter people will increase. This is true where humans usurp habitat from resident pumas for dwellings and supporting developments (e.g., roads, utilities), and where human growth intercepts dispersing pumas. To deal with those hapless pumas, wildlife management agencies need to support individuals or teams trained in the rapid and safe capture and control of pumas. Rapid-response agents can minimize the potential for attacks on humans and domestic animals. At the same time, agents could save some individual pumas by translocating them to remote puma habitat that they may have been seeking in the first place. Morever, one of the most important responsibilities of agency managers is to be in touch with the public’s values and expectations regarding puma management and conservation. A procession of twenty-two ballot measures in eleven states during 1980–2000 to increase protection of furbearers, wolves, black bears, and pumas (Minnis 1998) should be a strong signal to wildlife managers that influential stakeholders want carnivores protected from methods of killing that they believe are inhumane, unsporting, and immoral, and that they are willing to circumvent wildlife agency operations to accomplish their objectives. To protect pumas, California voters decided to ban puma sport-hunting throughout the state in 1990, and they defeated a ballot initiative to reinstate puma hunting in 1996. Oregon voters banned the use of dogs to hunt pumas in 1994, and Washington voters did the same in 1996 (Logan and Sweanor 1998). By abolishing sport-hunting or restricting methods of hunting, these measures limited options that wildlife managers could use for puma population management. Therefore, if wildlife managers want to retain influence in the management and conservation of pumas, they need to be responsive to stakeholders’ values. Otherwise, their management authority could be frustrated. CONSERVATION FUNDING

All wildlife conservation and management activities require funding. Hiring and training personnel, devising and implementing management plans, holding public meetings, conducting research, enforcing laws, monitoring populations, producing education material, and purchasing and maintaining habitat and equipment all require money. Conservation activities for endangered Florida panthers receive the bulk of funding from the U.S. Fish and Wildlife Service’s administration of the Endangered Species Act and the state of Florida’s own

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nongame wildlife trust funds. However, conservation and management of the thousands of pumas living in the West is dependent principally upon funds generated from the sale of hunting licenses and excise taxes on sporting arms and ammunition (via the Federal Aid in Wildlife Restoration Act). In the Proceedings of The Fifth Mountain Lion Workshop (Padley 1996b), wildlife agencies in four Western states (Nevada, Utah, Washington, and Wyoming) reported the amounts of money they spent on puma management. These ranged from $30,000 to $203,000 per year and averaged $114,500. The largest amount spent was for the state of Wyoming, which is required by law to pay for loss of private property caused by puma predation. Three other Western states (Colorado, Idaho, Utah) also reimburse property owners for losses due to puma depredation, which can easily exceed $100,000 per year. Other states did not distinguish expenditures for puma management in their budgets, which means puma management activities were paid for through other agency programs (e.g., law enforcement, game surveys, research, and information and education). A sobering lament we have heard from wildlife managers over the years is that their budgets do not adequately provide for scientific management of puma populations, needed research, or habitat protection. Clearly, monies generated from hunters alone are not enough to pay for puma management and conservation programs in the West. So all people concerned for puma conservation and science-based management, whether they hunt or not, should be doing what they can to support agencies charged with those responsibilities. One idea for a revenue-generating program is for states to support a species conservation certificate that citizens can buy voluntarily, the cost of which could be commensurate to the price of a hunting license or big game tag. For example, Western resident puma hunters presently pay on average $20 for a license and $37 for a tag if they kill a puma. (However, about half of the states do not require a separate tag.) It seems reasonable that nonhunters could pay $20–$40 for something like a Big Mammal Conservation Certificate, with all proceeds earmarked for conservation activities that benefit animals such as pumas, bears, wolves, deer, elk, javelina, and bighorn sheep. Enhanced funding for big mammals that require huge expanses of wild and rural lands would help to conserve, along with pumas, a diversity of other wild creatures. Hunters could buy the certificates too. The cost would be about the price for tickets to a movie or dinner at a restaurant for a family of four. The number of hunters purchasing puma hunting licenses in the mid-1990s numbered six hundred to fourteen hundred in most western states. Certainly, thousands more of the nonhunting public in each state could be encouraged to donate directly to big-mammal conservation programs. Regardless of whether people hunt, those with the monetary means to contribute to conservation should do so. After all, just by living—using space,

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food, and fiber—all people contribute to degradation of habitat and landscape linkages that populations of big mammals require to endure. In addition, public support of ballot initiatives and legislation that might generate substantial public funding for wildlife habitat and conservation activities should be explored and tailored to fit the political, economic, and cultural characteristics of each state. For example, in 1990 Californians passed the California Wildlife Protection Act, which requires that the state spend more than $30 million dollars per year until year 2020 on wildlife habitat protection, of which $10 million must be spent to benefit puma and deer populations. Another idea that has successfully generated substantial funds for conservation is the sale of specialty automobile license plates, such as Florida’s Conserve Wildlife plate. Obviously, some states may already have programs that citizens can finance. There are also conservation opportunities in the private sector. For example, The Nature Conservancy protects large tracts of wildlands and works cooperatively with rural landowners to conserve wildlife habitat. ENGAGED CITIZENSHIP

There is nothing more important in conservation than a caring, engaged citizenry. People interested in puma conservation should get involved. Learn about pumas. Get out in their habitat and contemplate what it is like for them to make a living there. Appreciate their wild environment. Find out how agencies charged with wildlife and natural resource management in your state try to conserve self-sustaining puma populations, their habitat, and other big mammals. If you support, are dissatisfied with, or have better ideas about how things should be done, then become part of the decision-making processes. Use the avenues that government agencies establish for your involvement. Contact elected and appointed officials responsible for overseeing wildlife and resource management agencies. Contact local, regional, and state agency personnel and let them know what you think. Attend the game commission or wildlife board meetings (whatever they’re called in your state) to participate in policy-making processes. Likewise, let federal land stewards know your opinions; they are responsible for vast puma habitat in the West. Vote for government representatives that you think would do the best job in environmental and conservation issues. Make sure that government appointees to wildlife management commissions or boards have a sound understanding in biology and ecology. If there is one thing we have learned in all our years of involvement with wildlife conservation, it is that generally nothing substantial ever happens without public support. The bigger and the more organized the public participation is, the better. Agencies crave public direction on highly volatile wildlife issues. Informed, caring citizens spur conservation initiatives to benefit big carnivores such as pumas

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and the myriad other species that live in their habitats and landscape linkages. Among the many enterprises in which people can invest portions of their intellect, energy, and wealth, that of conserving biological diversity through the keystone and umbrella services of pumas and other big mammals can be one of the most noble.

LP > >

KX

1. Major threats to pumas, and all big carnivores, are habitat loss and overkill. 2. To conserve self-sustaining puma populations indefinitely, it is essential to conserve as much remaining puma habitat and landscape linkages as possible. In addition, degraded habitat and linkages should be restored where possible. 3. An adaptive management approach, such as zone management, could be developed in puma-range states to provide an array of puma management options, including sustained sport-hunting, experimental control of populations if deemed necessary, and puma refuges. Puma population management actions should be designed as experiments. 4. Research on pumas that would benefit their management and conservation include population monitoring techniques, habitat use patterns, behavior, population dynamics, genetics, relationships with prey, translocation, relationships with other carnivores, aversive conditioning, protecting livestock, and human dimensions. 5. Educating people, especially those living in puma range, is one of the most important activities for conservation. It needs to be pursued at both public and private levels. 6. Rapid-response management teams need to be maintained as the human population expands into puma habitat. 7. Additional funding needs to be developed for conservation programs. Funds generated from sport-hunters are not enough. All citizens who care about wildlife conservation and can afford to donate should do so. 8. Citizens who care about wildlife conservation should be active in the public and political arenas, especially in support of conservation programs benefiting keystone and umbrella species that would also benefit myriad other wildlife species.

LN N5LN5) 1. Test for a linear relationship between number of pumas harvested per annum and number of puma permits issued per annum in New Mexico: Puma harvest = 36.124 + 0.104 (number of puma permits), r2 = 0.80, P < 0.0001.

Chapter 21

Epilogue

Puma concolor and Homo sapiens share a common history. As Earthlings, we have spun around this universe for about the past 390,000 years. When technologically advanced humans arrived in North America, pumas were here. Although they may have gone extinct with the mega-mammals in the late Pleistocene, pumas flourished again from a small number of founders that moved north from South America (Culver et al. 2000). Thus, the extant North American puma lineage has been here about as long as humans have. Over eons we trod the same country, hunted the same prey, and in essential instances of life, even killed and ate each other. Our basic endeavors in life were the same: acquire food, find a mate, keep our offspring safe. Humans dominated. We spread throughout the puma’s range and degraded or totally usurped their habitats. Puma distribution is now about one-half of what it was less than two hundred years ago. Where we did not displace them, we killed them out until the only extant populations thrived in remote rugged mountains of the West or in the forests and swamps of south Florida. Finally, in the mid-1960s (about three puma-lifetimes ago) we cultivated an ethical obligation to protect pumas. Once again they rebounded. Each time pumas endured the ravages of shifting climate, variable environments, and human exploitation, they did so because they had plenty of habitat in which to take refuge and enough genetic variability to adapt. Now as our human population expands, we continue to threaten their existence by destroying more habitat, fragmenting populations into ever-smaller units, and eroding their genetic ability to adapt. As long as humans dominate the Earth, the puma’s existence is entirely in our hands. 397

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We hope this book contributes to puma conservation and all that it means— intact wild ecosystems, landscape linkages, constrained human exploitation. We went to the mountains to study pumas up close, spending a substantial portion of our own lives to glean a real understanding of the animal and its environment. We canvassed the data, looked for patterns, and made comparisons to other reliable research on pumas and other carnivores. We probed research from extra disciplines, including paleontology and genetics, to better understand how pumas evolved. We tested previous scientific ideas about pumas and developed others. Scientists coming after us should test our ideas, add to the reliable ones, discard the undependable ones, and, in the process, enhance knowledge about pumas and their relationship to humans. Prospects for conservation should also benefit as long as scientific interpretations are conveyed in a manner most people can understand. We have not been entirely successfully at that here, because this book was meant to be a scientific treatise. Yet we hope the ideas will be understood well enough by other writers and speakers that wish to impart our messages to interested publics—those assorted stakeholders that will most determine conservation efforts that could favor pumas and a broad diversity of life forms. For ourselves, some of most treasured moments of our lives will be the times we hiked the canyons and ridges of the San Andres Mountains, experiencing their sublime wildness, following the tracks of pumas, trying to decipher how they made a living and how they affected that desert ecosystem. In rare dazzling moments, we watched pumas eye to eye. Through it all we were keenly aware of our fortune—experiencing one of the wildest large carnivores on one of the wildest remaining landscapes on Earth. That was exhilarating—and sometimes frightening! We can only wonder if our prehistoric ancestors were equally enchanted by pumas, other big carnivores, and wild lands. Perhaps that is the root of a conservation ethic today—and one that is adaptive. The wonder we have for wildlife and wild places probably has a genetic origin connecting our intellectual and emotional justifications for nurturing our natural environment. Humans have prospered greatly from biologically rich, clean environments. Our spirit to explore and survive in wild environments probably directly affected the evolution of our supreme intelligence. We believe that humans still need expansive wild places with big scary mammals that challenge us. By conserving those life forms in their wild environments, we benefit our own survival. If we accomplish that, then we will prove that we have earned our self-given name—sapi ens—the wise.

Appendix 1

Morphological Measurements of Pumas At Least 3.5 Months Old on the San Andres Mountains, New Mexico, 1985–1995

400

Appendix 1. Morphological Measurements of Pumas At Least 3.5 Months Old

Appendix 1. Morphological Measurements of Pumas At Least 3.5 Months Old

401

402

Appendix 1. Morphological Measurements of Pumas At Least 3.5 Months Old

Appendix 1. Morphological Measurements of Pumas At Least 3.5 Months Old

403

404

Appendix 1. Morphological Measurements of Pumas At Least 3.5 Months Old

Appendix 1. Morphological Measurements of Pumas At Least 3.5 Months Old

405

406

Appendix 1. Morphological Measurements of Pumas At Least 3.5 Months Old

Appendix 1. Morphological Measurements of Pumas At Least 3.5 Months Old

407

408

Appendix 1. Morphological Measurements of Pumas At Least 3.5 Months Old

Appendix 1. Morphological Measurements of Pumas At Least 3.5 Months Old

409

410

Appendix 1. Morphological Measurements of Pumas At Least 3.5 Months Old

Appendix 1. Morphological Measurements of Pumas At Least 3.5 Months Old

411

412

Appendix 1. Morphological Measurements of Pumas At Least 3.5 Months Old

Appendix 2

Reproductive Chronology of Mated Pairs of Pumas on the San Andres Mountains, New Mexico, 1987–1994

Mated pairs and estimated ages a Female Age (mo.)

Male

Age (mo.)

F15

43

M14

71

18–19 Feb. 1987

15 May 1987

87

3

F6

49

M7

50

1 Mar. 1987

31 May 1987

92

2

F21

38

M3

61

14 Jun. 1987

10 Sep. 1987

89

4

F4

81

M22

27

3 Aug. 1987

1 Nov. 1987

91

3

27 Mar. 1988 and 1 Apr. 1988

85g

2

F27e

38

M20

75

3–6 Jan. 1988

Approximate birth date c

Estimated gestation Litter period (days) d size

Dates pairs consorted b

90g

F37

62

M7

61

8 Feb. 1988

7 May 1988

90

3

F41

20

M38 or M36

45 46

19–21 Jun. 1988 26 Jun. 1988

14 Sep. 1988

88 81g

3

F15

61

M19

60

14 Aug. 1988

24 Nov. 1988

103

2

F37

78

M7

77

18 Jun. 1989

8 Sep. 1989

83

3

F57

70

M5

105

23 Jul. 1989

21 Oct. 1989

91

4

F65

21

M19

80

3 Dec. 1989

13 Mar. 1990

97

2

F41

34

M46

35

16 Dec. 1989

14 Mar. 1990

89

3

F27f

63

M53

40

11 Feb. 1990

7 Apr. 1990

56g

3

F47

38

M88

22

25–28 May 1990

24 Aug. 1990

92

3

F21

88

M3

110

5–7 Jul. 1991

4 Oct. 1991

92

4 (continues) 413

414

Appendix 2. Reproductive Chronology of Mated Pairs of Pumas

Mated pairs and estimated ages a Female Age (mo.)

Male

Age (mo.)

Dates pairs consorted b

Approximate birth date c

Estimated gestation Litter period (days) d size

F47

52

M3 or M88

110 36

25–26 Jul. 1991 27–29 Jul. 1991

25 Oct. 1991

93 91g

4

F28

52

M38 or M5

88 135

6 Jan. 1992 8 Jan. 1992

1 Apr. 1992

87 85g

3

F149

20

M5

141

25 Apr. 1992

25 Jul. 1992

92

4

F107

20

M88

45

25 Apr. 1992

25 Jul. 1992

92

4

F68

32

M29 or M36

56 94

12–21 Jun. 1992 14 Jun. 1992

8 Sep. 1992

89 87g

3

F47

65

M88

49

9–11 Aug. 1992

6 Nov. 1992

90

3

F45

70

M52

67

23 Aug. 1992

19 Nov. 1992

89

2

F21

106

M88

55

26 Feb. 1993

5 May 1993

89

4

F47

71

M88

55

25–28 Feb. 1993

26 May 1993

91

3

F90

32

M38

103

28 Mar. 1993

3 Jun. 1993

98

3

F126

44

M46

77

27 Jun. 1993

27 Sep. 1993

93

3

F107

38

M88

67

12 Feb. 1994

19 May 1994

97

3

F103

38

M173

41

27 Feb. 1994

31 May 1994

94

3

F149

37

M3

142

27 Feb. 1994

31 May 1994

94

3

F91

44

M46

86

12 Mar. 1994

5 Jun. 1994

86

3

F184

33

M138

48

23 Apr. 1994

28 Jul. 1994

97

4

F45

91

M151

60

22 May 1994

20 Aug. 1994

91

1h

F47

88

M193

37

24 Jul. 1994

22 Oct. 1994

91

2i

aAges

for the pumas are at the time the pair consorted. We estimated ages based on dental characteristics described in Ashman et al. (1983) and dental characteristics and appearance of known-age pumas in our own study. bWe recorded pumas consorting when their radiotelemetry locations overlapped and when we visually observed them together. cApproximate birth dates were determined from radiotelemetry data on mothers and by back-aging cubs. dGestation periods were estimated by including the first date that mated pairs were observed and by counting to the approximate birth date. Mean gestation period = 91.5 ± 4.0 days, n = 31. eBoth cubs produced by F27 were stillborn. fF27 aborted three fetuses on 7 April 1990, three days after she was recaptured. F27 died on 9 April 1990 due to capture-induced trauma. gThese estimated gestation periods were not used in calculation of the mean gestation period. hOnly one cub was visually observed with F45; it was sighted at four months and again at 6.5 months of age. F45’s litter may have been larger, and cubs may have died during the four-month interval before we saw the first cub. iWe visually observed F47’s two cubs at the birth nursery on 17 November 1994, near the end of our study. We could not subsequently capture, examine, and mark the cubs because F47’s radio collar quit working.

Appendix 3

Methods and Estimates of Annual Home Range Size for Pumas on the San Andres Mountains, New Mexico

To assess if our sample size was adequate to depict a puma’s annual home range size, we randomly chose an annual period from each of six study animals (three males, three females), systematically deleted locations to maintain a balanced monthly representation, and then graphed the area of each resulting home range (based on the 90 percent minimum convex polygon and 90 percent adaptive kernel) relative to the number of locations. The initial number of locations for each individual ranged from forty-five to fifty-one. Based on the minimum convex polygon, an average of thirty locations was needed to reach 90 percent of the final home range size. Results were more difficult to interpret using the adaptive kernel estimator, because home range size often fluctuated widely with each additional location and showed a general declining trend after an initial increase. An average of thirty-seven locations was required before the percent change (negative or positive) in home range size decreased to less than 10 percent. The declining trend in home range size with increasing sample size may be a result of better performance of the adaptive kernel model as more locations are obtained; smaller sample sizes have been found to lead to larger overestimates of home range size (Seaman and Powell 1996). When running CALHOME software, grid cell size was set at 50 ¥ 50. For the adaptive kernel, we let CALHOME calculate the optimum bandwidth (or smoothing parameter) for each data set, and then re-ran each data set using an 80 percent bandwidth. This was done because a smaller bandwidth may result 415

416

Appendix 3. Methods and Estimates of Annual Home Range Size for Pumas

in a better fit of the data (lowest least-squares cross-validation or LSCV score) when an animal uses two or more separate core areas (Kie et al. 1994). The bandwidth that produced the lowest LSCV score was used to determine home range size unless the 90 percent utilization distribution was broken into a greater number of polygons.

FIGURE A3-1. Home range sizes of pumas M5 (indicated in black) and F45 (in gray) plotted against the number of locations used to determine their size. Diamonds denote the number of locations after which home range size increased or decreased by 10 percent or less. Solid lines represent home ranges based on the 90 percent adaptive kernel, and dotted lines represent home ranges based on the 90 percent minimum convex polygon.

Table A3-1. Annual home range size (mean ± SD) for twenty-four adult male and thirty adult female pumas on the San Andres Mountains, New Mexico, 1986–1994. Home range estimate (km2)

Puma no.

na

x– no. locationsb

1c 3 5 7

3 8 6 4

42.7 44.8 42.7 45.8

Adaptive kernel 90%

60%

Males 226.2 ± 46.2 127.5 ± 25.9 180.8 ± 59.5 71.3 ± 40.6 186.4 ± 63.3 53.2 ± 20.1 183.3 ± 75.9 63.9 ± 40.2

Minimum convex polygon 100%

90%

218.5 ± 16.9 173.3 ± 51.4 162.7 ± 48.1 170.4 ± 94.7

155.5 ± 10.7 117.3 ± 43.2 118.5 ± 40.4 121.2 ± 72.4

Appendix 3. Methods and Estimates of Annual Home Range Size for Pumas

417

Home range estimate (km2) Adaptive kernel

Puma no.

na

x– no. locationsb

18 19 20d 22 29 36 38 46 49 52 53d 73 88 124 138 151 161 173 193 210 x– of x–

4 3 1 1 1 6 6 4 2 6 3 1 3 1 2 2 1 2 1 1 24

43.8 44.7 32.0 46.0 42.0 43.0 43.5 46.2 46.5 40.0 39.3 39.0 47.0 44.0 46.5 41.5 41.0 46.0 46.0 43.0 43.2

336.4 ± 225.9 144.3 ± 126.4 192.4 ± 20.6 68.0 ± 2.6 305.5 117.8 153.4 40.0 126.1 54.7 222.6 ± 74.0 70.6 248.8 ± 71.7 104.9 ± 17.3 229.6 ± 97.2 72.8 ± 39.7 113.2 ± 5.4 43.0 ± 5.3 104.4 ± 19.5 43.6 ± 16.8 245.8 ± 115.1 59.2 ± 19.3 177.8 74.2 174.1 ± 40.6 67.8 ± 13.7 81.4 24.8 249.6 ± 93.4 79.6 ± 17.3 271.2 ± 77.4 71.3 ± 26.0 259.7 42.7 132.8 ± 8.2 61.2 ± 7.4 59.3 16.8 180.0 ± 70.8 70.7 193.4 ± 69.6 68.5 ± 30.3

2 4 6 15 21 27 28 31 37 41 45 47 54 57 58

1 2 2 5 3 2 3 1 3 3 6 6 3 3 2

35.0 40.5 40.0 44.6 45.0 43.5 45.7 46.0 44.0 45.0 43.8 47.8 44.3 44.3 48.0

139.8 37.2 ± 2.1 116.0 ± 11.4 58.9 ± 14.2 63.6 ± 23.1 60.1 ± 13.7 89.9 ± 46.5 72.8 113.8 ± 15.2 48.5 ± 16.0 37.8 ± 11.4 33.9 ± 11.0 63.9 ± 36.5 46.7 ± 11.2 67.8 ± 32.6

90%

60%

Females 43.9 10.4 ± 1.2 40.4 ± 5.0 19.0 ± 8.5 23.3 ± 9.1 14.6 ± 1.6 30.0 ± 8.9 21.6 40.6 ± 18.1 23.0 ± 4.0 11.4 ± 2.9 11.4 ± 5.7 20.1 ± 11.6 17.9 ± 5.3 14.0 ± 2.0

Minimum convex polygon 100%

90%

367.8 ± 247.3 185.1 ± 11.7 320.6 142.1 108.9 245.5 ± 144.6 242.9 ± 51.9 213.5 ± 40.6 96.1 ± 5.2 104.7 ± 25.6 232.3 ± 52.3 139.2 171.4 ± 25.2 85.0 268.9 ± 23.5 271.4 ± 66.3 202.0 122.4 ± 3.5 75.2 194.6 188.1 ± 74.8

209.0 ± 125.7 125.1 ± 5.3 272.9 92.0 83.3 133.1 ± 32.6 163.4 ± 36.0 155.8 ± 38.3 61.0 ± 4.7 68.5 ± 17.7 171.7 ± 48.6 124.2 123.1 ± 23.4 66.1 163.2 ± 39.2 168.8 ± 14.8 150.8 90.2 ± 6.3 53.0 128.4 129.8 ± 50.3

121.5 39.2 ± 3.0 96.8 ± 0.1 58.9 ± 14.8 73.7 ± 9.6 79.9 ± 1.3 89.8 ± 47.2 71.3 90.9 ± 2.0 55.3 ± 17.7 38.0 ± 8.5 42.1 ± 13.1 62.7 ± 32.1 50.7 ± 4.0 92.2 ± 32.0

73.6 22.2 ± 7.1 60.4 ± 9.3 37.5 ± 11.8 46.7 ± 19.8 33.1 ± 3.4 59.1 ± 24.7 49.3 59.9 ± 8.2 38.0 ± 9.8 27.1 ± 6.8 24.2 ± 9.0 40.2 ± 18.2 33.4 ± 9.7 41.6 ± 21.6 (continues)

418

Appendix 3. Methods and Estimates of Annual Home Range Size for Pumas

Table A3-1. Continued Home range estimate (km2) –

Adaptive kernel

Minimum convex polygon

Puma no.

na

x no. locationsb

90%

60%

100%

90%

65 68 86 87 89 90 91 103 107 126 128 130 147 149 184 x– of x–

3 1 1 2 1 2 3 2 1 2 1 1 2 2 2 30

41.7 47.0 44.0 41.5 43.0 44.0 44.7 49.5 47.0 41.0 44.0 44.0 39.0 43.5 45.5 43.9

61.4 ± 26.4 30.1 92.8 107.8 ± 30.4 45.7 64.0 ± 5.6 45.5 ± 14.4 54.3 ± 0.7 67.6 80.7 ± 2.1 47.0 66.2 150.2 ± 194.0 61.4 ± 20.9 71.3 ± 35.4 69.9 ± 30.1

18.1 ± 3.3 8.8 28.0 34.9 ± 19.1 16.4 26.9 ± 1.1 19.5 ± 6.8 28.2 ± 5.0 19.4 26.4 ± 12.7 21.3 21.2 35.0 ± 43.5 21.0 ± 13.4 19.3 ± 14.0 22.9 ± 9.1

58.8 ± 21.3 25.7 117.7 106.8 ± 39.1 43.0 65.6 ± 0.5 55.4 ± 10.7 66.6 ± 20.2 72.2 74.2 ± 10.0 46.8 78.2 154.5 ± 201.0 48.0 ± 19.0 75.8 ± 43.2 71.7 ± 28.3

36.2 ± 11.5 16.1 57.8 71.0 ± 19.4 28.4 42.4 ± 2.5 34.2 ± 8.2 40.4 ± 2.1 52.3 43.2 ± 12.2 33.6 43.0 109.8 ± 143.3 33.0 ± 18.7 48.9 ± 30.2 44.6 ± 18.5

an = the number of years (1 January through 31 December) for which annual home range size was calculated. Annual home ranges were calculated only for pumas that were radio-monitored for ten months or more of a given twelve-month period. b The average number of locations obtained each year. Weekly aerial locations were augmented with ground locations as long as all locations were more than three days apart. cM1’s home range included area south of the study area (Organ Mountains) from 1986 to 1988; during those three years 19.5, 32.1, and 55.9 percent of his locations were outside the study area. dM1, M20, and M53 shifted their home range activities outside the study area over time. Only those years when they spent time in the study area are reported here.

Appendix 4

A Deterministic, Discrete Time Model That Simulated Mule Deer Population Dynamics in the Treatment Area, San Andres Mountains, New Mexico, 1987–1995

See Chapter 17 for its application. The basic deer model: Nt + 1 = B (sb) + D (sd) + [AD (fa) + YD (fy) – Fd ] Most model parameters were from surveys conducted on the San Andres Mountains. However, we had to rely on some estimates from other desert mule deer populations that were studied by the New Mexico Department of Game and Fish in other parts of southern New Mexico. We varied some of the parameters ourselves to simulate variation during drought conditions. Consequently, we developed six different population simulations, or models (i.e., six models numbered 1 to 6), to simulate the dynamics of the deer population on the Treatment Area (see Chapter 17 for details). Model parameters, their origins and variations, and our assumptions are described below. 419

420

Appendix 4. Simulated Mule Deer Population Dynamics in the Treatment Area

Nt = deer population size at the beginning of the deer biological year, which starts with the peak of the fawning season in August (births actually occurred from mid-July through September). Nt is the annual base population size assumed to be a representative population of 1,000 deer one year or older. Nt + 1 = deer population size at the end of the biological year. It reflects the change in the base population of 1,000 deer (i.e., 1,000 + births – deaths). B = estimated number of bucks (one year or older) in the base population. We assumed it was proportional to the buck:doe ratio estimated from the annual deer population composition count (Table 17-5). Models 4, 5, and 6 assume the buck:doe ratio in year 1 was biased high, and thus they use an estimated correction (Table 17-6). D = estimated number of does (one year or older) in the base population. We assumed it was proportional to the buck:doe ratio estimated from the annual deer population composition count (Table 17-5). Models 4, 5, and 6 attempt to correct for a potential bias in year 1 (see parameter B above). AD = the number of does two years or older. We estimated AD by subtracting the estimated number of yearling does from the total number of does in the base population. YD = the number of yearling does. We assumed they bred at 1.5 years old and gave birth at two years old. The proportion of yearling does in the doe population was estimated after an initial iteration of the model where all does in year 1 were assumed to be two years or older. Then the average proportion of yearling does (estimated from the number of fawns and does surviving to Nt + 1) during all subsequent years was used to estimate the proportion of yearling does in year 1. fa = fetal rate of does two years or older. We assumed it to be equal to the average of 1.15 fetuses per doe for twenty-seven adult does sampled on the Treatment Area in April 1990, and the average of 1.10 fetuses per doe for thirty adult does sampled on the Treatment Area in April 1991 (New Mexico Department of Game and Fish unpublished data). Fetal rates were estimated during the last trimester of pregnancy using the rectal abdominal palpation method (Hulet 1972, Humphreys and Elenowitz 1988). This method tends to underestimate the true fetal rate by 6–12 percent (Humphreys and Elenowitz 1988); hence, fetal rates we used were probably slightly conservative. We used fetal rates of 1.15 for the first three years and 1.10 for the last five years (Table 17-6). We assumed the sex ratio for deer births to be 1:1. fy = fetal rate for yearling does. We assumed it to be equal to the average of 0.90 fetuses per doe for thirty-three yearlings sampled (Humphreys and Elenowitz 1988:24) in the Guadalupe Mountains, New Mexico (about 160 km eastsoutheast of our Treatment Area). For models 1, 2, 4, and 5, we used 0.90 for

Appendix 4. Simulated Mule Deer Population Dynamics in the Treatment Area

421

years 1–3; additionally, for years 4–8, we assumed fy was equal to the average of 0.81 for fifteen yearlings sampled (Humphreys and Elenowitz 1988:24) on the MacGregor Range, New Mexico (about 75 km east-southeast of our Treatment Area). For models 3 and 6, we assumed fetal rates for yearling does were equal to 0.90 for all years (Table 17-6). sb = survival rate for bucks. We assumed it to be equivalent to the survival rate of radio-collared bucks (Table 17-2). sd = survival rate for does. We assumed it to be equivalent to the survival rate of radio-collared does (Table 17-2). Fd = number of fawns that died. We estimated it by subtracting the number of fawns that survived to the annual deer population composition counts from the estimated number of fawns born [i.e., fawns born = AD (fa) + YD (fy)] minus an additional percentage loss. Temple (1981) found that 90 percent of the total mortality for forty radio-collared fawns on Fort Bayard, New Mexico (about 150 km west of our Treatment Area), occurred during the first fortynine days of life, and 10 percent occurred during the rest of the year. For the model, we assumed two fawn mortality schedules: (1) ninety percent of the total fawn mortality occurred before the winter composition counts and 10 percent occurred between the composition counts and the end of the biological year; (2) eighty percent and 20 percent of the fawn mortality occurred during the two previously defined periods. We used schedule 2 in two of the models (Table 17-6) to account for potential increased fawn mortality during drought conditions (i.e., schedule 2 increased the estimated fawn mortality by 10 percent). The sex ratio of fawns that died in the population was assumed to be 1:1.

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About the Authors

KENNETH LOGAN and LINDA SWEANOR met on a bighorn sheep study in the North Absaroka Wilderness of Wyoming in 1983. They married in 1985, and have been studying pumas ever since. Kenneth has a B.S. in Range and Wildlife Management from Texas A&I University, an M.S. in Zoology and Physiology from the University of Wyoming, and a Ph.D. in Wildlife Sciences from the University of Idaho. Linda earned a B.S. in Wildlife Biology and Zoology from Colorado State University and an M.S. in Wildlife Sciences from the University of Idaho. As ecologists with the Hornocker Wildlife Institute, they directed field research on pumas, mule deer, and desert bighorn sheep in the Chihuahua Desert from 1985 to 1995 and thereafter developed New Mexico’s puma management plan by working with the public and other wildlife professionals. Presently, Kenneth and Linda are scientists with the University of California at Davis, School of Veterinary Medicine, Wildlife Health Center. They are studying interactions of pumas with mule deer, bighorn sheep, and humans in southern California. Their passion is raising their son Oren.

Index

Abrey, N., 293 Accidents as cause of puma deaths, 129, 137–38 Ackerman, B. B., 89, 138, 173, 189, 196, 198, 305, 306, 320, 329 Adams, D. B., 10 Adaptability of puma, 15 Adaptive kernel method to estimate home range, 189, 190, 249 Adaptive management, 384–95, 395 conservation funding, 392–94 education, 391–92 engaged citizenship, 394–95 research, 388–91 responsive management, 392 zone management, 385–88 Adult pumas: age structure, 77–80 defined, 64 home range, see Home range for adult pumas mortality and survival of: human-caused, 115–16 natural, 127–39, 143 sex ratios of, 73–75, 292 Aerial telemetry, 190 African Leopard, The (Bailey), xxiv Age of pumas: dental characteristics to determine, 47–49 eye color and, 50 Age structure of puma population, 75–81 Akinson, Holly, 287 Alberta, Canada, puma study in, see Jalkotzy, Martin; Ross, Ian Alkon, P. U., 55

Andelt, W. F., 390 Anderson, Allen E., 7, 8, 18, 126, 128, 136, 149, 152, 153, 223, 267, 269, 274, 372 Anderson, E. M., 10, 12, 13, 90, 101, 219 Anderson, W. D., 20, 36, 42, 80, 308 Apache, 34 Arcese, P., 275 Armadillo, 302 Armitrage, K. B., 102 Arvas, Thomas, xxiv Ashman, David, 7, 8, 48, 70, 90 Augsburger, J. G., 343 Aune, K. E., 302, 373, 376 Avoidance of other pumas, 267, 282–83, 286, 288, 290 by females to reduce infanticide, 140, 141, 283 Badger, 303 Bailey, Ted, xxiv, 102, 140, 198, 219, 272, 274, 275, 293, 294, 297, 337, 338 Ballard, W. B., 366 Barnhurst, D., 42, 269, 375 Barone, M. A., 103, 109, 243 Barrett, R. H., 74, 119, 128, 136, 240, 275, 302, 370, 372 Bartmann, R. M., 330 Beasom, S. L., 52 Beckett, P. H., 33, 34 Beier, P., 74, 119, 128, 136, 147, 149, 151, 178, 239, 240, 244, 275, 297, 302, 370, 372, 378, 384 Belden, R. C., 8, 168, 197, 369, 390 Berger, J., 343 Bergerud, A. T., 335 451

452

Index

Bertram, C. R., 337 Biological diversity, 365 Birth-interval home range, 192–95 Birth intervals of pumas, 87, 92–93, 110 Black bears, 14, 32–33 Bobcats, 202, 219, 304, 337, 338 Boellstorff, D. E., 105 Boertje, R. D., 337 Bolton, H. E., 370 Bonney, R. C., 89 Boutin, S., 313 Boyce, W. M., 84, 136, 344, 345 Boyd, D., 304 Boykin, K. G., 27 Brahmachary, R. L., 275 Branch, L. C., 302 Brand, C. J., 337 Brashares, J. S., 275 Breeding, see Reproduction of pumas Breternitz, C. D., 33, 34, 35 British Columbia puma study, see Spreadbury, B. R. Bronson, F. H., 89, 90, 95, 96, 109, 330 Brown, D. E., 16, 27 Brown, J. L., 285 Buechner, H. K., 343 Bunch, T. D., 342 Bureau of Land Management (BLM), 23 Burney, D. A., 12, 13 Burt, W. H., 189, 285 Buskirk, S. W., 198, 345 Caddick, G. B., 86, 103, 120 CALHOME software, 189, 413 California Wildlife Protection Act, 394 Calow, P., 71 Canadian lynx, 202, 219 Cannibalism, 120, 222, 305 Caro, T. M., 183, 244, 245, 275, 294, 296, 338 Carroll, C. R., 176, 361, 378 Catching pumas, 42–51 Caterwaul, 271–72 Caughley, G., 85, 169, 311, 313, 330, 333, 386, 389 Cheek rubbing as form of chemical communication, 275 Cheetahs, 9, 293 chemical communication among, 275 coalitions formed by, 295–97

response to prey crash, 338 social organization of, 183 transient behavior in, 244 Chemical communication, 273–76, 277, 283, 284 Chepko-Sade, B. D., 153, 178, 378 Chihuahua Desert, 14, 29 Clapperton, B. K., 275 Clark, P. J., 255, 256 Clark, R., 344 Clevenger, A. P., 382 Climate of research area, 27–29, 168 large-mammal population dynamics and, 359–62, 379 Clouded leopards, 297 Clutton-Brock, T. H., 72, 104, 110, 184 Coccidiodmycosis, 245 Coe Clough, N., 118 Colorado puma study, see Anderson, Allen E. Communication among pumas, 269–76, 277 chemical, 273–76, 277, 283, 284 vocalizations, 269–72, 277 Conservation and management of wild pumas, 365–98 alleviating threats, 377–95 adaptive management, 384–95 habitat conservation, 378–82 preventing unnecessary overklil, 383–84 funding for conservation, 392–94 threats to pumas: habitat loss, 367–71 puma overkill, 371–77 Conservation Biology, 145 Contagious ecthyma, 344, 345 Converse, L. J., 275 Coulson, J. C., 97 Cox, J. A., 8 Coyotes, 32, 121, 302, 303, 304, 333, 337 Crawshaw, P. G., 198, 295 Crow, J. F., 178 Cryptorchidism, 108–109, 134, 243 Cubs, puma: age structure of the population, 75–77 birth weights, 20 capturing nursling, 47–48, 49 color of coats, 20 defined, 64

Index infanticide, see Infanticide mass, gender and, 71–72 mortality and survival of: human-caused, 115–16 of matrilineal mothers, 101, 125–26 natural, 117–22 mother’s defense of, 141 orphaned, 121–22, 124, 371, 375 parental investment, 96, 111, 268–69 sex structure of, 69–72 vocalizations, 270–71 Culver, M., 10, 11, 17, 179, 242, 243 Cunningham, S. C., 129, 136, 176, 302, 372, 384 Daniel, W. W., 59 Definitions: adults, 64 cubs, 64 deterministic, 321 discrete time, 321 dispersers, 64, 145 duration of transient behavior, 231 emigrants, 65, 145 fidelity to home range, 211 functional response, 313 home range, 64, 185, 189 immigrants, 65, 145 independent home range, 231 limiting factor, 311 natal home range, 231 numerical response, 313 philopatric, 65, 145, 231 recruits, 65, 145 residents, 64 site attachment, 231 spatiotemporal relationships, 257 subadult home range, 231 subadults, 64 total response, 313 transient home range, 231, 244 DelGuidice, G. D., 319, 349 Density of puma population, 160–69, 179–80 comparison of San Andres Mountain pumas with other populations, 166–68 habitat and, 168–69

453

home range size of adult pumas and, 204–10 female response to changes in puma density, 206–208 male response to changes in puma density, 208–10 self-limiting hypothesis and, 210–11 prey density and, 168 Dental characteristics, 21, 48–50 DeRose, M. A., 243 Description of puma, 18–21 body size, 18–19, 21 claws and feet, 19 color, 19–20 sex organs, 21 teeth, 21 Desert bighorn sheep, 14, 15, 30, 35, 302 diseases affecting, 344–45, 347, 349, 350, 355, 357 as endangered species, 31 extinction on San Andres Mountains, 354–55, 357 history of New Mexico, prior to San Andres Mountains puma study, 342–46, 357 monitoring radio-collared, 51, 53–54, 57 fates of, 347–50 mortality of, 58, 347–50, 357 survival rates and agent-specific mortality, 350–54 pumas and, 302, 305, 307, 341–62 hypothesis and predictions, 341 other populations outside New Mexico, 356–57 predation, 341, 347, 349, 352–54, 355, 357, 359–62, 378 puma control and survival of, 36–37, 341 statistics, 357–58 summary, 357 surveys of population characteristics, 346–47 weather and population dynamics of, 359–62 Desert mule deer, 14, 15, 30, 31, 35, 88, 302, 307, 311–40, 378 characteristics of dead, 313–14 definitions, 311–13

454

Index

Desert mule deer (continued) deterministic, discrete time model that simulated population dynamics of, on Treatment Area, 419–21 hunting by humans, 31 mortality and survival rates, 58, 314–21, 339 pumas and, 311–40, 355 behavioral interactions, 331–32 limit on the deer population, 332–33 mule deer population dynamics, 321–31, 339, 359–62 partially compensatory nature of puma predation of, 318–19 predation and mule deer population growth, 322–31, 339 as primary source of food, 176, 302, 303, 305, 306, 308–309 research hypotheses and predictions, 311–13, 319–20 self-limiting hypothesis and, 333–35, 339 statistics, 339–40, 419–21 summary, 338–39 radio-collared, 49, 51–53, 57 fates of, 314–21, 338 weather and population dynamics of, 359–62 Diet of pumas, 301–309 patterns of pumas and prey, 301–302 prey size and puma body size, 301–302, 308 on the San Andres Mountains, 302–308 scavenging, 307–308, 309 summary, 308–309 see also Prey of pumas Direct interactions between pumas, 259–69 for breeding activity, 259–60, 265, 267 between family members, 268–69 independent pumas, associations between: female-female, 264–65 male-female, 265–67 male-male, 260–64 for intraspecies strife, 260–63, 265, 267 statistics, 278–79 summary, 277 Disease:

desert bighorn sheep and, 344–45, 347, 349, 350, 355, 357 puma mortality and, 120–21, 129, 136–37 Dispersers, puma, 148–53, 154–55, 375 defined, 64, 145 population density and, 152–53 subadult: females, 233–36, 240–43, 245–46 frustrated, 239–40 hypotheses to explain, 240–43, 246 males, 236–39, 240–43, 246, 283 timing of dispersal, 148–49 Dobson, F. S., 153, 240 Dogs used to catch puma, 42 Doyel, D. E., 33, 34, 35 Drugs, immobilizing, 47, 48 Dunn, W. C., 342 Duration of transient behavior defined, 231 Dwarf mongoose, 275 Ear tags, 50 Eastern Cougar Foundation, 368 Eaton, R. L., 72 Education as conservation strategy, 391–92 Ehret, G., 270 Eidenbach, P. L., 26, 34, 35, 36 Eisenberg, J. F., 14 Elam, D. R., 178 Elenowitz, A., 52, 343, 420 Elk, 302, 335, 378 Elliot, J. P., 335 Elmer, Mike, 58, 305 Emigration, 153, 155, 176 defined, 65, 145 Emlen, J. T., Jr., 184, 285, 286 Endangered species, 366 Endangered Species Act of 1973, 15, 392 Engaged citizenship, puma conservation and, 394–95 Erlinge, S., 184 Ermines, 293 Erwin, D. H., 14 Etkin, W., 285–86 Evans, Dr. Wain, xxiii, xxiv, 36 Evans, F. C., 255, 256 Evolutionary ecology, 6 Ewer, R. F., 17, 124 Eye color, age and, 50

Index Fecundity rates of pumas, 85–86, 110 Fidelity, adult puma home range, see Home range for adult pumas, fidelity Fidelity Index, 212, 213–14, 215 Findley, J. S., 16 Fisher, Amy, 49 Fitness of adult female pumas, factors associated with, 140–41 Fitness of adult male pumas, factors associated with, 141–42 Fitzhugh, E. L., 384 Fitzsimmons, N. N., 345, 377 Floater, see Transient home range Florida panthers, 7, 295, 369, 372 cryptorchidism among, 109 direct interaction between, 267 dispersal by, 149 as endangered species, 15, 367, 392–93 habitat loss, 369, 372 habitat preservation, 382 home range shifts, 219, 224 inbreeding in, 103, 243 intraspecies strife among, 136, 369 litter size, 86 longevity of, 80 male philopatry, 239 mortality/survival rates: of cubs, 119–20 reproduction of, 90–91, 95 transient behavior in, 244 Floyd, T. J., 306 Foster, M. L., 382 Frank, D. H., 198 Franklin, W. L., 302 Freeman, S., 6, 10, 84, 96, 97 Fuller, T. K., 127, 128, 168, 315, 316, 317, 320, 337 Fulwyler, Major General Niles, xxiv Functional response, defined, 313 Funding for puma conservation, 392–94 Garrott, R. A., 189, 213 Gasaway, W. C., 335 Gashwiler, J. S., 138 Gaut, J. A., 343 Geist, V., 14, 53 Geographic distribution and status of puma, 15–16 Gestation period, puma, 91, 110

455

Gilpin, M. E., 178, 378 Ginsberg, J. R., 212 Gipson, P. S., 366 Gittleman, J. L., 198 Gloyne, C., 382 Golden eagle, 303 Goldman, E. A., 17 Gonyea, W. J., 19 Goodrich, J. M., 198 Gorman, M. L., 273, 275, 276 Grafen, A., 97 Gray fox, 32, 304 Gray wolves, 14, 382 Gregg, C. T., 136 Grigione, M. M., 384 Grizzly bears, 14, 16, 33, 384 Guanaco, 302 Gutiérrez-Espeleta, G. A., 345 Habitat, puma, 336, 389 conservation of, 378–82 home range size and, 197–98 loss of, as threat, 367–71 population density and, 168–69 Hackney, R., 366 Hagedorn, B. W., 369 Hailey, M. P., 110 Hair, J. F., 327 Halfpenny, J. C., 376 Halpin, Z. T., 153 Hand capture of cubs, 48, 51 Hares, 302, 306, 333, 338 Harlow, H. J., 375 Harris, A. H., 13 Harvey, P. H., 14, 198 Hast, M. H., 269 Hawley, J. W., 26 Hayne, D. W., 189 Hedrick, P. W., 103, 243 Heisey, D. M., 127, 128, 315, 316, 317, 320 Hembrillo Base Camp, 40 Hemker, T. P., 98, 119, 149, 168, 195, 201, 204, 273, 287, 329 Hemmer, H., 17 Hemming, J. E., 53 Herron, J. C., 6, 10, 84, 96, 97 Hertel, F., 12 Hervert, J. J., 330

456

Index

Heske, E. J., 198 Hiraiwa-Hasegawa, M., 72 Hoban, P. A., 35, 345 Hoffmeister, D. F., 16 Holderman, Dave, 336 Holling, C. S., 313 Holocene epoch, 12, 29 Home range: for adult pumas, see Home range for adult pumas defined, 64, 185, 189 methods and estimates of annual size of, on San Andres Mountains, 413–16 scent markings and, 275 for subadults, see Home range for subadult pumas Home range for adult pumas, 189–229, 282, 284 annual, 191–92 birth-interval, 192–95 comparison of San Andres Mountain pumas to other populations, 201 delineating the, 189–91 energy demands and, 195–98 factors influencing size of, 195–201 energy demands, 195–98 gender, 198–201, 282 prey abundance, and puma density, 201–11 fidelity, 211–25, 283–84 benefits of fidelity and the twostrategies hypothesis, 223–25 defined, 211 distances between mean locations method, 213, 214–16 Fidelity Index, 212, 213–14, 215 home range shifts in pumas, 216–22 homing by translocated pumas, 222–23 methods of determining, 212–16 self-limiting hypothesis and, 225 lifetime, 195 old males, 245 range size, prey abundance, and puma density, 201–11 seasonal, 191–92 statistics, 227–29 summary, 225–27 Home range for subadult pumas, 231–46

definitions, 231 dispersal: by females, 233–36, 240–43, 245–46 frustrated, 239–40 hypotheses to explain, 240–43, 246 by males, 236–39, 240–43, 246 philopatry in females, 232–33, 235–36, 245 statistics, 246 summary, 245–46 transient behavior, 244–245, 246, 283 Hopkins, R. A., 74, 80, 201, 219, 221–22, 224, 274, 275 Hornocker, Maurice, xxiii–xxv, 6–7, 21, 42, 63, 86, 136, 138, 152, 175, 183, 245, 286, 294, 304, 320, 329, 336, 372 self-limiting hypothesis and, 184–85, 284 Hornocker Wildlife Institute, xxiii–xxiv Horses, feral, 335 Humphrey, S. R., 382 Humphreys, D., 52, 420 Hunt, C., 390 Hunt, R. M., 9 Hunter, M. D., 359, 360 Hunting and predator control, 115–16, 164–65, 176–77 government sanctioned, 16, 36–37, 376 management of puma hunting, problems with, 373–76 natural selection process, effects on, 377, 379 overkill as threat to pumas, 371–77 preventing unnecessary overkill, 383–84 prohibition of, 16, 37, 176, 367 tenure of territorial males affected by, 142 Iason, G. R., 72 Idaho puma study, see Seidensticker, J. C. Immigrants, puma, 153, 154, 155, 159 defined, 65, 145 Inbreeding, 102–103 avoidance of, 240, 243, 246, 283 Independence of puma progeny, 146–48, 154 timing of, resumption of breeding behavior in mothers and, 147–48

Index Independent home range defined, 231 Infanticide, 120, 140, 142, 266–67, 371 avoidance of other pumas by mothers to reduce threat of, 140, 141 Interactions between pumas: communication, see Communication among pumas direct, see Direct interactions between pumas spacial relationships, see Spatial relationships statistics, 277–79 summary, 276–77 Intraspecies strife, 287–88, 375–76 as cause of adult puma mortality, 129–36, 139–42, 143, 239 direct interactions for, 260–63, 265, 267 Iriarte, J. A., 21, 301, 302 Irwin, L. L., 168, 197, 273, 335, 336, 378 Jackrabbits, 303, 306 Jackson, P., 16, 17 Jaguars, 14, 16, 32, 102, 365, 370, 382 comparison of social structures of pumas and, 294, 295, 297, 298 home range size for, 198, 295 scent markings, 274, 295 size of, 18 Jalkotzy, Martin, 7, 63, 70, 77, 86, 90, 95, 98, 101, 119, 136, 138, 142, 147, 149, 153, 166, 167, 168, 174, 185, 195, 204, 224, 242, 286, 308, 329, 372 James, W. H., 72 Javelina, 30, 305, 307 Jennrich, R. I., 189 Jessup, D., 344 Jiménez, J. A., 243 Johnson, W. E., 9, 10 Jornada Experimental Range, 28, 35 Julander, O., 329 Kaufmann, J. H., 286 Keith, L. B., 337 Keystone species, pumas as, 365 Kie, J. G., 189, 190 Kimura, M., 178 Knick, S. T., 337, 338 Koch, James, xxiv Koehler, G. M., 304

457

Koepfli, K., 177 Kohn, M. H., 384 Kottlowski, F. E., 26, 27 Kovacs, K. M., 105 Krackow, S., 72 Krausman P. R., 330, 342, 343, 352 Krebs, C. J., 65, 202, 338 Kruuk, H., 273 Kruuk, L. E. B., 72 Kunkel, K., 335 Kurtén, B., 10, 12, 13, 18, 301 Lack, D., 84, 378 Lacy, R. C., 178, 346 Laing, S. P., 101, 159, 168, 197, 222, 336, 378 Lair, H., 191 Lance, W. R., 344 Lande, R., 378 Land tenure system, 185, 186, 285, 286, 287 Lang, E. M., 343 Lange, R. E., 344 Larsen, D. G., 335 Laumbach, K., 34 Le Boeuf, B. J., 104, 110 LeCount, 329 Lenti Boero, D., 275 Leopards, 102, 338 chemical communications among, 274, 275 comparison of social structure of pumas and, 294, 297, 298 home ranges, 198, 219, 294 prey biomass and population densities, 168, 337 vocalizations, 272 Leyhausen, P., 17, 183, 270, 275, 294 Lidicker, W. Z., 153 Limiting factors: defined, 311 puma predation as primary proximate, for desert mule deer population, 311–13, 314 of San Andres Mountains puma population, 336–37 Lindstedt, S. L., 198 Lindzey, Fred, 7, 8, 63, 74, 86, 90, 95, 101, 128, 138, 159, 167, 168, 174, 175, 186, 197, 222, 269, 320, 336, 372, 375, 378, 383

458

Index

Linneaus, 16 Lions, African, 102, 109, 337 chemical communication among, 275 coalitions formed by, 295–97 home range size and prey abundance, 202 inbreeding, 243 social organization of, 183 transient behavior in, 244 Litter size, 83–84, 86–87, 110 Litvaitis, J. A., 202 Logan, Kenneth A., xxiv, xxvii–xxxi, 15, 42, 43, 45, 47, 65, 70, 74, 86, 90, 98, 106, 149, 152, 167, 168, 197, 245, 273, 302, 308, 335, 336, 367, 371, 372, 373, 375, 378, 385, 392 Long-eared owl, 305 Lopez-Gonzalez, C. A., 16, 70, 101, 119 Lorenz, K., 292 Lott, D. F., 198, 292 Lynxes, American, 293, 333, 337, 384 response to prey crash, 338 McBride, R. T., 136 McCowan, J. W., 390 McCullough, D. R., 385 McDaniel, G. W., 384 Macdonald, D. W., 184, 201 McDougal, C. W., 87, 109, 142 Mace, G. M., 285 McLaren, B. E., 333, 335, 360 Maehr, D., 8, 80, 91, 95, 120, 149, 219, 222, 224, 244, 267, 269, 297, 367, 372, 381 Maehr, D. S., 72, 74, 86, 103, 136 Marshall, L. G., 11, 313 Martin, L. D., 14 Mass, puma: of adult male, 109–10, 142 home range size and, 198 of cubs, gender and, 71–72 morphological measurements of puma 3.5 months or older on San Andres Mountains, 399–412 prey size and puma body size, 301–302, 308 Mating, see Reproduction of pumas Matrilines, puma, 99–101, 233, 282, 290, 297 longevity of, 102

survival rate of cubs with matrilineal mothers, 101, 125–26 Matson, P. A., 359, 360 Mayr, E., 6 Mech, L. D., 319, 337, 349 Meffe, G. K., 176, 361, 378 Mehrer, C. F., 124 Menge, B. A., 360 Messier, F., 168, 313, 333 Metapopulation dynamics, 175–79, 180 Micromort survival analysis software, 127, 128–29, 162, 316, 352 Minimum convex polygon (MCP) method to estimate home range, 189–90, 231, 249 Minnis, D. L., 392 Minta, S., 198 Mitani, J. C., 110 Montoya, Gary, 354–55 Moore, C. T., 72 Moose, 302, 333, 378 Morgan, B., 36 Morphological measurements of puma 3.5 months or older on San Andres Mountains, 399–412 Morris, D. W., 240 Mortality of desert bighorn sheep, see Desert bighorn sheep, mortality of Mortality of desert mule deer, see Desert mule deer, mortality and survival rates Mortality/survival of puma, 115–44 human-caused, 115–16, 142 investigation methods, 58–59 male/female, 120, 122, 126, 127–28, 143 natural, 117–45 of adults, 127–39, 143 of cubs, 117–22, 142–43 of subadults, 122–27, 143 reasons pumas kill other pumas, 139–42, 143 statistics, 143–44 summary, 142–43 Mowat, G., 337, 384 Mule deer, desert, see Desert mule deer Müller-Schwarze, D., 273 Muñoz, D., 36 Murphy, Ke r ry, 7, 97, 104, 105, 107, 109, 293, 301, 321, 336, 372, 379, 381

Index Museum of Southwestern Biology, 37 Natal home range, defined, 231 National Cancer Institute,Laboratory of Genetic Diversity, 50 Neal, D. L., 166, 201, 274 Nearest-neighbor analysis, 254–56 Neilson, R. P., 342, 343, 361 Nevada Department of Wildlife, 7 Nevada puma study, see Ashman, David New Mexico Department of Agriculture, Veterinary Diagnostic Service, 58, 136 New Mexico Department of Game and Fish, xxiv, 16, 31, 32, 36, 37, 49, 52, 53, 232, 322, 344, 345, 355, 376, 420 Noble, G. K., 285 Nomadic behavior, see Transient home range Norrix, L. W., 344 Northern Yellowstone Ecosystem, study of pumas in, see Murphy, Kerry Noss, R. F., 178 Nottingham, B. G., 274, 294, 295 Nowak, R. M., 15, 16, 17 Nowell, K., 16, 17 Numerical response, defined, 313 Nuñez, R. B., 295 Nunn, C. L., 72 Nunney, L., 178 O’Brien, S. J., 8, 9, 10, 103, 243 Ockenfels, R. A., 335 O’Donoghue, M., 333, 337, 338 Odors, chemical communication through, see Chemical communication O’Gara, B., 304 Ordway, L. L., 330 Organ Mountains, 26, 27, 37, 178, 370–71, 378, 382 desert bighorn sheep in, 342, 343 Orians, G. H., 285 Ornate box turtle, 305 Orphaned cubs, 121–22, 124, 371, 375 Oryx, 31–32, 303, 305, 307 Oscura Mountains, 36–37, 342 Owen-Smith, N., 13, 285 Packer, C., 21, 104, 109, 140, 243, 266, 294, 296, 297, 337

459

Padley, W. D., 265, 272, 393 Palanza, P. S., 275 Parental investment in offspring, 96, 111 Parker, G. R., 337 Paw petroglyph, 33 Peccary, 14, 302, 378 Pech, R. P., 313 Pecon-Slattery, J., 9, 10 Pederson, J., 31 Pereira, M. E., 72 Perrins, C. M., 84 Peters, G., 269–70, 271, 272 Peterson, R. O., 333, 335, 360 Peterson Method, 65 Philopatric lions, 297 Philopatric pumas, 148–53, 154 defined, 65, 145, 231 subadult females, 232–33, 235–36 Phylogeny of pumas, 9–15 Physiography and geology of study area, 26–27 Picton, H. D., 330 Pierce, B. M., 88, 168, 186, 211, 223, 290, 329, 333, 334, 335 Pitelka, F. A., 285 Pleistocene, 12–14 mass extinction of mammals during, 11–12, 13–14, 301 Pollock, K. H., 126, 128 Poole, K. G., 337 Population of pumas, study area: age structure, 75–81 census of, methods for, 65–68, 80 density of, see Density of puma population experimentally removing pumas, 157–60, 179, 222–23, 390 growth rates, 169–75, 180 limiting factor for, 336–37 metapopulation dynamics, 175–79, 180 observed, 51 self-limiting hypothesis, see Self-limiting hypothesis sex structure, 69–75, 80–81, 292 structure of, 69–81, 159 Porcupine, 303 Post, E., 360 Powell, R. A., 190 Power, M. E., 360, 361 Precipitation in study area, 26–27

460

Index

Prey biomass (prey density), 168 dispersal and, 241–43 home range size and, 202–204 Prey of pumas: animals killed but not consumed, 303–304 cases of puma and other carnivores limiting prey populations, 335–36 densities of, see Prey biomass (prey density) diet, 301–309 patterns of pumas and prey, 301–302 prey size and puma body size, 301–302, 308 on the San Andres Mountains, 302–308 scavenging, 307–308, 309 summary, 308–309 method of attack, 21 response to prey crash, 337–38 see also Desert mule deer; specific prey, e.g. Desert bighorn sheep Price, P. W., 360 Prides, forming of, 296–97 Pronghorns, 30, 302–303, 305 Protection of puma, legal, 15, 16 Puberty of pumas, first litters and, 93–96, 110–11 Puma concolor, 10 Pusey, A. E., 140, 243, 266, 294, 296 Quigley, H. B., 295 Rabinowitz, A. R., 274, 294, 295 Raccoon, 302 Radiotelemetry, 45, 50 study aided by, 51, 54–57 Rail, C. D., 136, 137 Randall, J. A., 275 Ranging behavior, see Home range Rasas, O. A. E., 275 Rattlesnake bites, 138 Read, A. F., 14 Recruits, puma, 154, 155 after experimentally removing pumas from Treatment Area, 159 defined, 65, 145 Reiter, J., 104, 110 Reproduction of pumas, 83–113, 281

birth intervals, 87, 92–93, 110 chemical communication and, 275–76, 284 direct interactions for breeding, 259–60, 265, 267 dispersal and competition for mates, 240–41 fecundity rates, 85–86, 110 fidelity, 105 gestation, 91, 110 litter size, 83–84, 86–87, 110 mating, 91–92 natality, 83–87, 110 parental investment, 96, 111, 268–69 as polyestrous, 89, 90 polygynous, 74, 105 promiscuity, 74, 105, 140–41 puberty and first litters, 93–96, 110–11 reproductive chronology of mated pairs on San Andres Mountains, 413–14 reproductive success, 96–110, 111 females, 98–103, 111 males, 103–10, 111 scent marking and, 275 statistics, 111–13 summary, 110–11 timing of births, 88–91, 110 two-strategies hypothesis, see Twostrategies hypothesis Reproductive success of pumas, 96–110, 111 females, 98–103, 111 males, 103–10, 111 Research area, see San Andres Mountains, New Mexico, as puma study area Research hypotheses and predictions, 63–64 Research on pumas, future needs for, 388–91 Research team, 23 Residents defined, 64 Responsive management, 392 Ricklefs, R. E., 69, 160 Ringtail, 303 Roamer, see Transient home range Roberson, J., 374, 375 Robinette, W. L., 53, 70, 72, 138 Rodents, 302, 378 Roelke, M. E., 8, 103, 243 Roff, D. A., 243 Ross, Ian, 7, 15, 63, 70, 77, 80, 86, 90, 95,

Index 98, 101, 119, 136, 138, 142, 147, 149, 153, 166, 167, 168, 174, 185, 195, 204, 224, 242, 286, 308, 329, 357, 372 Roth, J. A., 118 Rubenstein, D. I., 281 Russell, D. E., 10 Ruth, T. K., 47, 98, 106, 107, 139, 141, 157, 338, 381, 390 Saccheri, I., 178, 243, 378 Sadleir, R. M., 330 Saiz, R. B., 31–32 Sale, M., 34 Salman, David, xxiv Saltz, D., 55 San Andrecito Camp, 39–40, 41 San Andres Mountain National Wildlife Refuge, 35 San Andres Mountains, New Mexico, as puma study area, 23–26 catching wild pumas, 42–51 climate, 27–29, 168, 359–62, 379 counting pumas, 65–68 fauna of, 30–33 flora of, 29–30 human use, history of, 33–36 life afield, 39–42 map, 24 physiography and geology of, 26–27 puma exploitation, history of, 36–37 reasons for choosing, 23–26 Reference Area (RA), 26 research hypotheses and predictions, 63–64 terms for pumas, 64–65 Treatment Area (TA), 26 experimentally removing pumas from, 157–60, 179, 222–23, 390 see also specific aspects of puma behavior San Andres Wildlife Refuge, 343, 354–55 Sandell, M., 183, 184, 198, 201, 202, 203, 244, 292–93, 293 Sandoval, A. V., 35, 36, 342, 343, 344, 345, 347 SAS Institute, Inc., 59 Saunders, G. C., 118 Savage, D. E., 10 Scabies, 344, 347, 349, 350, 355, 357 Scent markers, 273–76, 284, 295

461

Schaller, G. B., 183, 198, 244, 245, 270, 275, 294, 296, 337 Schenk, A., 105 Schmidt, J. L., 219 Schoener, T. W., 191 Scow, K., 270 Scrapes as form of chemical communication, 273–76, 284 Seaman, D. E., 190 Seidensticker, J. C., 7, 63, 64, 70, 74, 104, 146–47, 152, 159, 167, 168, 175, 183, 186, 201, 204, 219, 245, 267, 273, 274, 275, 289, 320, 336 home range fidelity and, 223 self-limiting hypothesis and, 184–85, 210, 211, 284–85, 286, 287, 313, 333 Seip, D. R., 335 Self-limiting hypothesis, 183, 184–87, 284–88, 333–35, 376 land tenure and, 285 San Andres study and, 186–87, 210–11, 225, 286–88, 293, 298, 313, 333, 339 territoriality and, 285–86 Septicemic plague (Yersinia pestis), 136–37 Sex organs of pumas, 21 Sex structure: of desert bighorn sheep, 347 of puma population, 69–75, 80–81, 292 Sexual selection, 109 Shaffer, M., 178 Shaw, H. G., 42, 74, 338, 372 Shields, W. M., 177, 243 Short, H. L., 330 Sibly, R. M., 71 Sierra Oscura Mountains, 26 Sinclair, A. R. E., 240, 311, 313, 330, 333, 386, 389 Sinclair, D. F., 88, 255 Singer, F. J., 330 Site attachment defined, 231 Sitton, L. W., 274 Slade, N. A., 191 Smallwood, K. S., 384 Smith, C. R., 31–32 Smith, Frank, xxiv, 42, 57, 149 Smith, J. L. D., 87, 102, 109, 142, 198, 222, 224, 274, 275, 276, 295 Smith, R. H., 329 Smith, R. L., 105

462

Index

Smith, T. E., 274, 372 Snares, foothold, 43–47, 50–51, 115 vocalization of snared pumas, 270 Snow leopards, 102, 297 Snowshoe hares, 333, 338 Social organization of pumas, 7 adaptive significance of, 281–98 communication, see Communication among pumas comparison with other big cats, 294–97, 298 direct interactions between pumas, see Direct interactions between pumas self-limiting hypothesis and, see Selflimiting hypothesis social structure of desert pumas, 281–84 female structure, 282–83 male structure, 283–84 spatial relationships, see Spatial relationships two-strategies hypothesis and, see Twostrategies hypothesis Source-sink metapopulation structure, 177–78, 180 Spatial relationships of pumas, 247–56, 284, 286, 292 home range overlap indices, 249–54 nearest-neighbor analysis, 254–56 spatiotemporal relationships, 257–59, 275 statistics, 277–78 summary, 276–77 Spreadbury, B. R., 70, 86, 90, 136, 167, 185, 204, 222, 234, 245, 274, 372 SSPS, Inc., 59 Stander, P. E., 168, 198, 203, 294, 337 Starvation, 120–21 Statistics, study, 395 age structure, 81 body mass, 21 desert bighorn sheep, 357–58 desert mule deer, 339–40, 419–21 home range for adult pumas, 227–29, 413–16 home range for subadult pumas, 246 interactions between pumas, 277–79 morphological measurements, 399–412 mortality/survival, 143–44

overview of analytical and statistical methods, 59 sex structure, 81 Stearns, S. C., 6, 71, 96 Stenseth, N. C., 153 Stephenson, R. O., 337 Stoddart, D. M., 273 Striped skunk, 302, 303 Strobeck, C., 384 Strong, D. R., 360 Stuart, A. J., 12, 13 Studies of pumas, synopsis of previous, 6–8 Subadults, puma: age structure of the population, 75–77 defined, 64 home range of, see Home range for subadult pumas mortality and survival of: human-caused, 115–16 natural, 122–27, 143 sex ratio of, 73 Sunquist, M. E., 198, 222, 224, 294, 295 Survival of puma, see Mortality/survival of puma Sweanor, Linda L., xxvii–xxxi, 15, 44, 56, 145, 152, 153, 175, 178, 191, 192, 212, 219, 240, 271, 283, 302, 367, 371, 373, 378, 379, 380, 385, 392 Sweitzer, R. A., 335 Swihart, R. K., 191 Taber, 302 Tagging, 50 Tattooing, 49 Taxonomy, puma, 16–17 Taylor, D., 36 Taylor, M. E., 293 Teel, T. L., 391 Teer, J. G., 330, 335 Teeth of pumas, 21, 48–50 Temperature in study area, 28–29 Templeton, A. R., 177 Terborgh, J., 360 Territoriality, 285–86, 287, 293 Thomas, C. S., 97 Thorne, E. T., 136, 137 Thrapp, D. L., 34 Tigers, 109, 142

Index chemical communication among, 274, 275 comparison of social structure of pumas and, 294, 297, 298 home range, 295 fidelity, 224, 295 size, 198 scent markings, 274, 295 Todd, A. W., 337 Toolin, L. J., 362 Torres, S. G., 302, 376, 384 Total response defined, 313 Transient home range, 244–45, 246, 282, 283 defined, 231, 244 Translocation of pumas, experimental, 157–60, 179, 390 homing by translocated pumas, 222–23 Trapping, 42–43, 116 Trivers, R., 6, 70, 72, 96, 109, 183, 198 Trowbridge, B. J., 276 Turner, F. B., 189, 329 Turner, J. W., 335 Two-strategies hypothesis, 183–84, 288–93, 297–98 female strategy, 288–90 home range fidelity and, 223–25 male strategy, 290–93 U.S. Census Bureau, 368 U.S. Department of Interior, 366 U.S. Fish and Wildlife Service, 36, 52, 53, 54, 344, 355, 366, 370, 392 U.S. Forest Service, 35 Utah puma study, see Lindzey, Fred Valdez, R, 343, 366 Van Ballenberghe, V., 169 Van Devender, T. R., 342, 343, 362 Van Orsdol, K. G., 202 Van Sickle, W. D., 383 Van Valkenburgh, B., 10, 11, 12 Vaughan, T. A., 9 Vincent, A., 96 Vocalizations, puma, 269–72, 277, 283 caterwaul, 271–72

463

cubs, 270–71 yowl and raspy ouch, 272 Waid, D. D., 200 Wallen, S., 274 Waltho, N., 382 Ward, R. M. B., 202, 338 Waser, P. M., 292 Wayne, R. K., 177 Weather, see Climate of research area Webb, S. D., 10 Weckerly, F. W., 109 Wehausen, J. D., 343, 356 Weisenberger, Mara, 336, 354–55 Welch, R. D., 343 Wemmer, C., 270 Werdelin, L., 9 White, G. C., 189, 213 White Sands Missile Range, xxiv, 23, 24, 31, 32, 35, 37, 344, 355 White Sands National Monument, 35 White-tailed deer, 14, 302, 335, 378 Wildt, D. E., 243 Wiley, R. H., 292 Willard, D. E., 72 Williams, J. S., 136 Wilson, E. O., 285 Windy season in study area, 29 Wolf, M., 243 Wolff, R., 275 Wolves, 16, 32, 33, 333, 335, 366, 382 prey biomass and population densities of, 168, 337 Wood, J. P., Jr., 33, 36 Woodroffe, R., 96 Worton, B. J., 189, 190 Wozencraft, W. C., 16, 17, 270, 271 Wrangham, R. W., 183, 184, 281, 295 Wyoming puma study, see Logan, Kenneth A. Yersinia pestis, 136–37 Young, S. P., 15, 16, 20, 179 Young, T. P., 212 Zar, J. H., 59 Zone management, 385–88

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CHARLES C. SAVITT President, Center for Resource Economics/Island Press

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SUSAN E. SECHLER Director of Global Programs, The Rockefeller Foundation PETER R. STEIN Managing Partner, The Lyme Timber Company RICHARD TRUDELL Executive Director, American Indian Resources Institute WREN WIRTH President, The Winslow Foundation