This comprehensive book, rich with applications, offers a quantitative framework for the analysis of the various capture-recapture models for open animal populations, while also addressing associated computational methods.

The state of our wildlife populations provides a litmus test for the state of our environment, especially in light of global warming and the increasing pollution of our land, seas, and air. In addition to monitoring our food resources such as fisheries, we need to protect endangered species from the effects of human activities (e.g. rhinos, whales, or encroachments on the habitat of orangutans). Pests must be be controlled, whether insects or viruses, and we need to cope with growing feral populations such as opossums, rabbits, and pigs.

Accordingly, we need to obtain information about a given population's dynamics, concerning e.g. mortality, birth, growth, breeding, sex, and migration, and determine whether the respective population is increasing , static, or declining. There are many methods for obtaining population information, but the most useful (and most work-intensive) is generically known as capture-recapture, where we mark or tag a representative sample of individuals from the population and follow that sample over time using recaptures, resightings, or dead recoveries. Marks can be natural, such as stripes, fin profiles, and even DNA; or artificial, such as spots on insects. Attached tags can, for example, be simple bands or streamers, or more sophisticated variants such as radio and sonic transmitters.

To estimate population parameters, sophisticated and complex mathematical models have been devised on the basis of recapture information and computer packages. This book addresses the analysis of such models. It is primarily intended for ecologists and wildlife managers who wish to apply the methods to the types of problems discussed above, though it will also benefit researchers and graduate students in ecology. Familiarity with basic statistical concepts is essential.

Provides a comprehensive description of capture-recapture models for open populations Begins with simple models and builds to more complex ones Explains how technological developments (GPS, genetic markers, computer software) can be effectively employed

Autorentext

George Seber is a retired Professor of Statistics at Auckland University, New Zealand, a Fellow of the Royal Society of New Zealand, and recipient of the Society's Hector Medal in Information Sciences. He is the author or coauthor of seventeen books on various branches of statistics. More recently, as a trained counselor/psychotherapist, he has written an extensive book on counseling for practitioners and a booklet on the dying and death of loved ones, as well as a book on religion and science. He has published research articles on a variety of statistical subjects.

Matthew Schofield is a Senior Lecturer of Statistics at the University of Otago, New Zealand. In 2017 he was the recipient of the Littlejohn Research Award, the premier research award of the New Zealand Statistical Association. He has published over twenty five research articles, many of which involve the development of capture-recapture methodology.

Inhalt
Preface.- 1 A Brief History of Capture-Recapture.- 2 Tagging methods and Tag Loss.- 3 Tag Returns from Dead Animals.- 4 Using Releases and Resightings.- 5 Mark-Recapture: Basic Models.- 6 Multiple Recaptures: Further Methods.- 7 Departures from Model Assumptions.- 8 Combined Data Models.- 9 Further Bayesian and Monte Carlo Recapture Methods.- 10 Log-Linear Models for Multiple Recaptures.- 11 Combining Open and Closed Models.- 12 Continuous Dead-Recovery Models.- 13 Multisite and StateSpace Models.- 14 Designing and Modeling Capture-Recapture Experiments.- 15 Statistical Computation.- 16 Where to Now?.- APPENDIX A Some General Results.- References.- Index.