Bayesian Population Analysis using WinBUGS: A Hierarchical Perspective

Bayesian statistics has exploded into biology and its sub-disciplines, such as ecology, over the past decade. The free software program WinBUGS, and its open-source sister OpenBugs, is currently the only flexible and general-purpose program available with which the average ecologist can conduct standard and non-standard Bayesian statistics.

Comprehensive and richly commented examples illustrate a wide range of models that are most relevant to the research of a modern population ecologistAll WinBUGS/OpenBUGS analyses are completely integrated in software RIncludes complete documentation of all R and WinBUGS code required to conduct analyses and shows all the necessary steps from having the data in a text file out of Excel to interpreting and processing the output from WinBUGS in R

1. Introduction

2. Very 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: The conventional Poisson GLMM for count data

5. State-space models

6. Estimation of population size

7. Estimation of survival probabilities using capture-recapture data

8. Estimation of survival probabilities using mark-recovery data

9. Multistate capture-recapture models

10. Estimation of survival and recruitment using the Jolly-Seber model

11. Integrated population models

12. Metapopulation modeling of abundance using hierarchical Poisson regression

13. Metapopulation modeling of species distributions using hierarchical logistic regression

14. Concluding remarks