Handbook of Capture-Recapture Analysis

Steven C. Amstrup, Trent L. McDonald, Bryan F. J. Manly, Steven Amstrup, Trent McDonald, Bryan Manly

• Publisher: Princeton University Press
• Year: 2010
• ISBN:
  9781400837717
• Topic: Biowissenschaften
• Subtopic: Zoologie

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.

Index

age, 272–73

age 0 cohort models, 105–6

age-dependent models, 46–47

age-specific breeding models, 106–7

conditional multiple-age models, 102–7

conditional single-age models, 89–102

Agresti, A., 71–72

Akaike, H., 18, 92, 98

Akaike’s information criterion (AIC), 18, 47–48, 60, 72, 102, 229

Arnason-Schwarz model, 171

closed-population models, 267

conditional single-age models, 92, 98

Cormack-Jolly-Seber model, 53, 224, 236, 240, 268

covariates, 224

goodness-of-fit, 271–72

multistate models, 165

polar bears, 249

quasi, 99–100, 236, 249

reduced-parameter models, 92

tag-recovery models, 127, 139, 163

weighting of, 100

Alexander, H. M., 72

Alho, J. M., 72, 111

Allen, D. M., 130

Alpizar-Jara, Russell, 5–6, 36–57, 267–68, 301

Alt, G. L., 161

American alligator, 48–51

Amstrup, Steven C., 1–21, 301

model examples, 196–264

open-population models, 111

practical methods, 266–73

Andersen, P. K., 85

Anderson, D. R., 8, 18, 171, 254

closed-population models, 79, 84

open-population models, 92, 98–100

tag-recovery models, 131–32, 145

Arnason, A. N., 8, 198

multistate models, 166, 183, 192

open-population models, 38, 43–44, 109, 111–12

Arnason-Schwarz model, 187–88, 195

AIC, 171

Bayesian methods, 171

breeder recruitment, 175, 177

Canadian geese, 166–67, 172–76

contingency test for, 170

Cormack-Jolly-Seber model, 167–71, 175

data collection, 167–69

dead recoveries, 175

experimental protocol of, 167–69

goodness-of-fi...