© Marcel Burkhardt
Bayesian population analysis using WinBUGS is a gentle introduction to the analysis of distribution, abundance and population dynamics of animals and plants using the flexible Bayesian software WinBUGS (or, alternatively, programs OpenBUGS or JAGS, for both of which all code should work as well). The book contains a comprehensive collection of richly commented worked examples, such as generalized linear mixed models (GLMMs), state-space models, Cormack-Jolly-Seber models, ring-recovery models, multistate models, Jolly-Seber models, integrated population models, as well as Binomial mixture and site-occupancy models. It will be of interest to quantitative scientists working in the fields of population ecology, conservation biology, evolutionary biology, population management, disease ecology, fisheries or wildlife biology. The text is ideal for self-study and for an advanced graduate-level course.
Marc Kéry and Michael Schaub are population ecologists with the Swiss Ornithological Institute. Together, they have authored over 120 peer-reviewed journal articles on a wide range of topics, including the analysis of large-scale monitoring programs, demographic population analyses, experimental design for animal and plant surveys, and the population ecology of rare species, as well Introduction to WinBUGS for Ecologists (Academic Press, 2010).
2. Brief introduction to Bayesian statistical modeling
3. Introduction to the generalized linear model (GLM): The simplest model for count data
4. Introduction to random effects: Conventional Poisson GLMM for count data.
5. State-space models for population counts
6. Estimation of the size of a closed population from capture-recapture data
7. Estimation of survival from capture-recapture data using the Cormack-Jolly-Seber (CJS) model
8. Estimation of survival using mark-recovery data
9. Estimation of survival and movement from capture-recapture data using multistate models
10. Estimation of survival, recruitment and population size from capture-recapture data using the Jolly-Seber (JS) model
11. Estimation of demographic rates, population size and projection matrices from multiple data types using integrated population models
12. Estimation of abundance from counts in metapopulation designs using the binomial mixture model
13. Estimation of occurrence and species distribution from detection/nondetection data in metapopulation designs using site-occupancy models
14. Concluding remarks
Appendix 1: A list of WinBUGS tricks
Appendix 2: Some further useful multistate capture-recapture models
Web appendix 1: Utility functions
Web appendix 2: Code to simulate data for the integrated population model
This webpage contains supplementary documents to the book and workshop announcements