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Handbook of Capture-Recapture Analysis

Author Bryan J. Manly , Trent L. McDonald , Steven C. Amstrup
Release Date: 2010/12/01
ISBN: 9781400837717
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Book Description

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.

Table of Contents

  1. Cover
  2. Halftitle
  3. Title
  4. Copyright
  5. Contents
  6. List of Illustrations
  7. List of Tables
  8. Preface
  9. One Introduction to the Handbook Bryan F. J. Manly, Trent L. McDonald, and Steven C. Amstrup
    1. 1.1 Introduction
    2. 1.2 Overview of Chapters 2 to 8
    3. 1.3 Maximum Likelihood with Capture–Recapture Methods
    4. 1.4 Model Selection Procedures
    5. 1.5 Notation
  10. Two Classical Closed-population Capture–Recapture Models Anne Chao and Richard M. Huggins
    1. 2.1 Introduction
    2. 2.2 Structure of Capture–Recapture Experiments and Data
    3. 2.3 Early Models and Estimators
    4. 2.4 Limitations of Early Models and the Motivation for More General Models
    5. 2.5 Chapter Summary
  11. Three Classical Open-population Capture–Recapture Models Kenneth H. Pollock and Russell Alpizar-Jara
    1. 3.1 Introduction
    2. 3.2 The Original Jolly-Seber Model
    3. 3.3 The Jolly-Seber Likelihood Components
    4. 3.4 Restrictions and Generalizations of the Jolly-Seber Model
    5. 3.5 Age-dependent Models
    6. 3.6 Goodness-of-Fit and Model Selection Issues
    7. 3.7 Examples
    8. 3.8 Conclusions
    9. 3.9 Chapter Summary
  12. Four Modern Closed-population Capture–Recapture Models Anne Chao and Richard M. Huggins
    1. 4.1 Introduction
    2. 4.2 Discrete-time Models with Unequal Catchabilities
    3. 4.3 Continuous-time Models
    4. 4.4 Computing Considerations
    5. 4.5 Chapter Summary
  13. Five Modern Open-population Capture–Recapture Models James D. Nichols
    1. 5.1 Introduction
    2. 5.2 Conditional Single-age Models
    3. 5.3 Conditional Multiple-age Models
    4. 5.4 Reverse-time Models
    5. 5.5 Unconditional Models
    6. 5.6 The Robust Design
    7. 5.7 Discussion
    8. 5.8 Chapter Summary
  14. Six Tag-recovery Models John M. Hoenig, Kenneth H. Pollock, and William Hearn
    1. 6.1 Introduction
    2. 6.2 Assumptions of Brownie Models
    3. 6.3 Interpretation of the Tag-recovery Rate Parameter
    4. 6.4 Functional Linkage Between the Exploitation Rate and the Survival Rate
    5. 6.5 Instantaneous Rate Models for Estimating Harvest and Natural Mortality
    6. 6.6 Diagnostics and Tests of Assumptions
    7. 6.7 Preventing and Dealing with Failures of Assumptions
    8. 6.8 Chapter Summary
  15. Seven Joint Modeling of Tag-recovery and Live-resighting Data Richard J. Barker
    1. 7.1 Introduction
    2. 7.2 Data Structure
    3. 7.3 Simple Models
    4. 7.4 More General Models
    5. 7.5 Model Fitting and Assessment
    6. 7.6 Tag Misreads and Tag Loss
    7. 7.7 Computing Considerations
    8. 7.8 Chapter Summary
  16. Eight Multistate Models Carl J. Schwarz
    1. 8.1 Introduction
    2. 8.2 The Arnason-Schwarz Model
    3. 8.3 The Jolly-Seber Approach
    4. 8.4 Multisample Stratified Closed Populations
    5. 8.5 Multisample Stratified Open Populations
    6. 8.6 Chapter Summary
  17. Nine Examples Trent L. McDonald, Steven C. Amstrup, Eric V. Regehr, and Bryan F. J. Manly
    1. 9.1 Introduction
    2. 9.2 Open-population Analyses of Data on the European Dipper
    3. 9.3 The Huggins Closed-population Model Applied to the European Dipper Data
    4. 9.4 Assessing Goodness-of-Fit
    5. 9.5 Horvitz-Thompson Open-population Size Estimates
    6. 9.6 A Multistate (Multistrata) Model
    7. 9.7 Polar Bears in the Southern Beaufort Sea
    8. 9.8 Dead Recoveries of Mallard Ducks
    9. 9.9 Chapter Summary
  18. Ten Capture–Recapture Methods in Practice Bryan F. J. Manly, Steven C. Amstrup, and Trent L. McDonald
    1. 10.1 Introduction
    2. 10.2 Closed-population Models
    3. 10.3 Open-population Models
    4. 10.4 Tag-recovery Models
    5. 10.5 Other Models
    6. 10.6 Model Selection
    7. 10.7 Known Ages
  19. Appendix
    1. A.1 Capability Matrix for Common Capture–Recapture Software Packages
    2. A.2 General and Contact Information for Common Capture–Recapture Software Packages Listed in Table A.1
  20. References
  21. Contributor’s Notes
  22. Index
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