Trent L. McDonald – författare

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.

Literature on resource selection by animals is a maze of methodologies for data collection and interpretation. Field biologists need a guide through the labyrinth - this book aims to provide such a guide. It gives a clear and consistent framework for the study of how animals select their resources (food and habitat), by taking the reader through different types of study design. The authors have clearly identified the need to pull together the diffuse literature, and biologists should greatly improve their experimental design, methodology, and analysis with the information provided. A second edition, the text has been updated to include many developments. There is material on discrete choice models, the analysis of data from geographical information systems, compositional analysis, Mahalanobis distance methods, and neural networks and related approaches.