Handbook of Capture-Recapture Analysis

(Paperback)

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Description

Helps biologists understand state-of-the-art statistical methods for analyzing capture-recapture data. This book introduces the methods for data analysis while explaining the theory behind those methods. It is useful for biologists, biometricians, and statisticians, students in both fields, and anyone else engaged in the capture-recapture process.

Reviews

Winner of the 2007 Wildlife Publications Award in the Outstanding Edited Book Category, The Wildlife Society "This is a good book for anyone with a basic understanding of capture-recapture models who wants to develop their knowledge and apply these techniques to their own data. Exactly what a handbook should be!"--Laura Cowen, Quarterly Review of Biology "The editors have done an admirable job in trying to make complex capture-recapture models accessible to a greater range of field-based ecologists."--David Wilson, Austral Ecology "The capture, tagging, and subsequent recapture of animals, birds, and fish is the field biologists most important tool for enumerating and quantifying the status of wild populations. This mark-recapture data must be subjected to sophisticated statistical analyses back in the office, and there can be a disconnect between those who do the field work and those who do the analyses. This text, written by authors with expertise in the field and in the office, successfully bridges that gap. This handbook will be immediately useful to ecologists, biologists, and statisticians."--Northeastern Naturalist

Author Bio

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.