This text is written to provide a mathematically sound but accessible and engaging introduction to Bayesian inference specifically for environmental scientists, ecologists and wildlife biologists. It emphasizes the power and usefulness of Bayesian methods in an ecological context.

The advent of fast personal computers and easily available software has simplified the use of Bayesian and hierarchical models . One obstacle remains for ecologists and wildlife biologists, namely the near absence of Bayesian texts written specifically for them. The book includes many relevant examples, is supported by software and examples on a companion website and will become an essential grounding in this approach for students and research ecologists.

Key Features

Engagingly written text specifically designed to demystify a complex subject
Examples drawn from ecology and wildlife research
An essential grounding for graduate and research ecologists in the increasingly prevalent Bayesian approach to inference
Companion website with analytical software and examples
Leading authors with world-class reputations in ecology and biostatistics


Students and researchers in animal ecology, population ecology, wildlife management, conservation biology, and ecological and biological statistics.

Table of Contents

Chapter 1. Bayesian Inference Chapter 2. Probability Chapter 3. Statistical Inference Chapter 4. Posterior Calculations Chapter 5. Bayesian Prediction Chapter 6. Priors Chapter 7. Multimodel Inference Chapter 8. Hidden Data Models Chapter 9. Closed-Population Mark-Recapture Models Chapter 10. Latent Multinomials Chapter 11. Open Population Models Chapter 12. Individual Fitness Chapter 13. Autoregressive Smoothing


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© 2010
Academic Press
Print ISBN:
Electronic ISBN: