Handbook of Capture-Recapture Analysis

Capa
Steven C. Amstrup, Trent L. McDonald, Bryan F. J. Manly
Princeton University Press, 20 de nov de 2005 - 313 páginas

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.

 

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Conteúdo

Introduction to the Handbook
1
12 Overview of Chapters 2 to 8
3
13 Maximum Likelihood with CaptureRecapture Methods
9
14 Model Selection Procedures
17
15 Notation
19
Classical Closedpopulation CaptureRecapture Models
22
22 Structure of CaptureRecapture Experiments and Data
23
23 Early Models and Estimators
26
68 Chapter Summary
140
Joint Modeling of Tagrecovery and Liveresighting Data
142
72 Data Structure
144
73 Simple Models
145
74 More General Models
156
75 Model Fitting and Assessment
157
76 Tag Misreads and Tag Loss
161
78 Chapter Summary
163

24 Limitations of Early Models and the Motivation for More General Models
34
25 Chapter Summary
35
Classical Openpopulation CaptureRecapture Models
36
32 The Original JollySeber Model
38
33 The JollySeber Likelihood Components
44
34 Restrictions and Generalizations of the JollySeber Model
45
35 Agedependent Models
46
36 GoodnessofFit and Model Selection Issues
47
37 Examples
48
38 Conclusions
55
Modern Closedpopulation CaptureRecapture Models
58
43 Continuoustime Models
78
44 Computing Considerations
85
45 Chapter Summary
86
Modern Openpopulation CaptureRecapture Models
88
52 Conditional Singleage Models
89
53 Conditional Multipleage Models
102
54 Reversetime Models
107
55 Unconditional Models
109
56 The Robust Design
116
57 Discussion
120
58 Chapter Summary
121
Tagrecovery Models
124
62 Assumptions of Brownie Models
128
64 Functional Linkage Between the Exploitation Rate and the Survival Rate
131
66 Diagnostics and Tests of Assumptions
132
67 Preventing and Dealing with Failures of Assumptions
134
Multistate Models
165
82 The ArnasonSchwarz Model Introduction
166
83 The JollySeber Approach
177
84 Multisample Stratified Closed Populations
187
85 Multisample Stratified Open Populations
192
86 Chapter Summary
194
Examples
196
92 Openpopulation Analyses of Data on the European Dipper
198
93 The Huggins Closedpopulation Model Applied to the European Dipper Data
231
94 Assessing GoodnessofFit
236
95 HorvitzThompson Openpopulation Size Estimates
241
96 A Multistate Multistrata Model
245
97 Polar Bears in the Southern Beaufort Sea
247
98 Dead Recoveries of Mallard Ducks
254
99 Chapter Summary
263
CaptureRecapture Methods in Practice
266
103 Openpopulation Models
267
104 Tagrecovery Models
269
105 Other Models
270
106 Model Selection
271
107 Known Ages
272
Appendix
275
A2 General and Contact Information for Common CaptureRecapture Software Packages Listed in Table A1
277
References
281
Contributors Notes
301
Index
303
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Sobre o autor (2005)

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.

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