List of Illustrations ix
List of Tables xi
Preface xvii
Chapter One: Introduction to the Handbook by Bryan F. J. Manly, Trent L. McDonald, and Steven C. Amstrup 1
1.1 Introduction 1
1.2 Overview of chapters 2 to 8 3
1.3 Maximum Likelihood with Capture-Recapture Methods 9
1.4 Model Selection Procedures 17
1.5 Notation 19
Chapter Two: Classical Closed-population Capture-Recapture Models by Anne Chao and Richard M. Huggins 22
2.1 Introduction 22
2.2 Structure of Capture-Recapture Experiments and Data 23
2.3 Early Models and Estimators 26
2.4 Limitations of Early Models and the Motivation for More General Models 34
2.5 Chapter Summary 35
Chapter Three: Classical Open-population Capture-Recapture Models by Kenneth H. Pollock and Russell Alpizar-Jara 36
3.1 Introduction 36
3.2 The Original Jolly-Seber Model 38
3.3 The Jolly-Seber Likelihood Components 44
3.4 Restrictions and Generalizations of the Jolly-Seber Model 45
3.5 Age-dependent Models 46
3.6 Goodness-of-Fit and Model Selection Issues 47
3.7 Examples 48
3.8 Conclusions 55
3.9 Chapter Summary 55
Chapter Four: Modern Closed-population Capture-Recapture Models by Anne Chao and Richard M. Huggins 58
4.1 Introduction 58
4.2 Discrete-time Models with Unequal Catchabilities 58
4.3 Continuous-time Models 78
4.4 Computing Considerations 85
4.5 Chapter Summary 86
Chapter Five: Modern Open-population Capture-Recapture Models by James D. Nichols 88
5.1 Introduction 88
5.2 Conditional Single-age Models 89
5.3 Conditional Multiple-age Models 102
5.4 Reverse-time Models 107
5.5 Unconditional Models 109
5.6 The Robust Design 116
5.7 Discussion 120
5.8 Chapter Summary 121
Chapter Six: Tag-recovery Models by John M. Hoenig, Kenneth H. Pollock, and William Hearn 124
6.1 Introduction 124
6.2 Assumptions of Brownie Models 128
6.3 Interpretation of the Tag-recovery Rate Parameter 128
6.4 Functional Linkage Between the Exploitation Rate and the Survival Rate 131
6.5 Instantaneous Rate Models for Estimating Harvest and Natural Mortality 131
6.6 Diagnostics and Tests of Assumptions 132
6.7 Preventing and Dealing with Failures of Assumptions 134
6.8 Chapter Summary 140
Chapter Seven: Joint Modeling of Tag-recovery and Live-resighting Data by Richard J. Barker 142
7.1 Introduction 142
7.2 Data Structure 144
7.3 Simple Models 145
7.4 More General Models 156
7.5 Model Fitting and Assessment 157
7.6 Tag Misreads and Tag Loss 161
7.7 Computing Considerations 161
7.8 Chapter Summary 163
Chapter Eight: Multistate Models by Carl J. Schwarz 165
8.1 Introduction 165
8.2 The Arnason-Schwarz Model 166
8.3 The Jolly-Seber Approach 177
8.4 Multisample Stratified Closed Populations 187
8.5 Multisample Stratified Open Populations 192
8.6 Chapter Summary 194
Chapter Nine: Examples by Trent L. McDonald, Steven C. Amstrup, Eric V. Regehr, and Bryan F. J. Manly 194
9.1 Introduction 196
9.2 Open-population Analyses of Data on the
European Dipper 198
9.3 The Huggins Closed-population Model Applied to the
European Dipper Data 231
9.4 Assessing Goodness-of-Fit 236
9.5 Horvitz-Thompson Open-population Size Estimates 241
9.6 A Multistate (Multistrata) Model 245
9.7 Polar Bears in the Southern Beaufort Sea 247
9.8 Dead Recoveries of Mallard Ducks 254
9.9 Chapter Summary 263
Chapter Ten: Capture-Recapture Methods in Practice by Bryan F. J. Manly, Steven C. Amstrup, and Trent L. McDonald 266
10.1 Introduction 266
10.2 Closed-population Models 266
10.3 Open-population Models 267
10.4 Tag-recovery Models 269
10.5 Other Models 270
10.6 Model Selection 271
10.7 Known Ages 272
Appendix 275
A.1 Capability Matrix for Common Capture-Recapture Software Packages 275
A.2 General and Contact Information for Common Capture-Recapture Software Packages Listed in Table A.1 277
References 281
Contributor's Notes 301
Index 303

Every day, biologists in parkas, raincoats, and rubber boots go into the field to capture and mark a variety of animal species. Back in the office, statisticians create analytical models for the field biologists' data. But many times, representatives of the two professions do not fully understand one another's roles. This book bridges this gap by helping biologists understand state-of-the-art statistical methods for analyzing capture-recapture data. In so doing, statisticians will also become more familiar with the design of field studies and with the real-life issues facing biologists.
Reliable outcomes of capture-recapture studies are vital to answering key ecological questions. Is the population increasing or decreasing? Do more or fewer animals have a particular characteristic? In answering these questions, biologists cannot hope to capture and mark entire populations. And frequently, the populations change unpredictably during a study. Thus, increasingly sophisticated models have been employed to convert data into answers to ecological questions. This book, by experts in capture-recapture analysis, introduces the most up-to-date methods for data analysis while explaining the theory behind those methods. Thorough, concise, and portable, it will be immensely useful to biologists, biometricians, and statisticians, students in both fields, and anyone else engaged in the capture-recapture process.

Steven C. Amstrup researches bears and their ecosystems. His interests include distribution and movement patterns as well as wildlife population dynamics. Trent L. McDonald is a statistician and project manager with Western EcoSystems Technology, Inc. and Adjunct Professor of Statistics at the University of Wyoming. Bryan F. J. Manly is the author of several books on the statistics of natural selection, multivariate analysis, resource selection by animals, research study designs, computer-intensive statistics, and environmental statistics.