Bayesian Population Analysis using WinBUGS

Dr. Marc Kéry is a senior scientist at the Swiss Ornithological Institute, a non-profit NGO with about 200 employees dedicated primarily to bird research, monitoring, and conservation. Marc was trained as a plant population ecologist at the universities of Basel and Zürich, Switzerland. After a 2-year postdoc at the (then) USGS Patuxent Wildlife Center in Laurel, USA, he moved into animal population ecology and during the last 25 years has worked at the interface between population ecology, biodiversity monitoring, wildlife management, and applied statistics. He has published more than 150 peer-reviewed journal articles and six textbooks on applied statistical modeling. He has taught more than 60 one-week workshops all over the world to biologists and wildlife managers about the concepts and practice of modern statistical analysis in their fields, something which goes together with his books, which target the same audiences.Dr. Michael Schaub is a senior scientist and head of the population biology research group at the Swiss Ornithological Institute, and a courtesy professor at the University of Bern, Switzerland.Michael was trained as an animal population ecologist at the universities of Basel and Zürich. After a 1-year postdoc at the Centre National de la Rechereche Scientifique (CNRS) in Montpellier, France, he jointed the Swiss Ornithological Institute. His research interests include population dynamics, capture-recapture models, integrated population models, and migratory birds. He has coauthored approximately 170 peer-reviewed journal publications and the two books on applied Bayesian modeling for ecologists and has taught about 30 week-long workshops all over the world.

• 1. Introduction2. Very brief introduction to Bayesian statistical modeling3. Introduction to the generalized linear model (GLM): The simplest model for count data4. Introduction to random effects: The conventional Poisson GLMM for count data5. State-space models6. Estimation of population size7. Estimation of survival probabilities using capture-recapture data8. Estimation of survival probabilities using mark-recovery data9. Multistate capture-recapture models10. Estimation of survival and recruitment using the Jolly-Seber model11. Integrated population models12. Metapopulation modeling of abundance using hierarchical Poisson regression13. Metapopulation modeling of species distributions using hierarchical logistic regression14. Concluding remarks