Bayesian Methods for Ecology

The interest in using Bayesian methods in ecology is increasing, however many ecologists have difficulty with conducting the required analyses. McCarthy bridges that gap, using a clear and accessible style. The text also incorporates case studies to demonstrate mark-recapture analysis, development of population models and the use of subjective judgement. The advantages of Bayesian methods, are also described here, for example, the incorporation of any relevant prior information and the ability to assess the evidence in favour of competing hypotheses. Free software is available as well as an accompanying web-site containing the data files and WinBUGS codes. Bayesian Methods for Ecology will appeal to academic researchers, upper undergraduate and graduate students of Ecology.

1. Introduction; 2. Critiques of statistical methods; 3. Analysing averages and frequencies; 4. How good are the models?; 5. Regression and correlation; 6. Analysis of variance; Case studies; 7. Mark-recapture analysis; 8. Effects of marking frogs; 9. Population dynamics; 10. Subjective priors; 11. Conclusion; Appendix A. A tutorial for running WinBUGS; Appendix B. Probability distributions; Appendix C. MCMC algorithms.

Statistical analysis of data is fundamentally important in ecology but most ecologists have difficulty with conducting analyses. McCarthy describes how to use Bayesian methods to analyse a wide range of data and models in ecology. This accessible text will appeal to academic researchers, upper undergraduate and graduate students of Ecology.

Michael A. McCarthy is Senior Ecologist at the Royal Botanical Gardens, Melbourne and Senior Fellow in the School of Botany at the University of Melbourne.