Bayesian integrated population modeling (IPM) using BUGS and JAGS

1 Dec 2014 - 11:45

Bayesian integrated population modeling (IPM) using BUGS and JAGS

Instructors: Michael Schaub & Marc Kéry, Swiss Ornithological Institute, Res Altwegg, University of Cape Town, Sarah J. Converse, USGS Patuxent Wildlife Research Center. Date: 19 to 23 October 2015 Venue: Kirstenbosch Research Centre, South African National Biodiversity Institute, Cape Town, South Africa Computers: Bring your own laptop with latest R and WinBUGS, JAGS or OpenBUGS Costs (provisional): 600 USD (reduced fees will apply to delegates from African countries)

Download application form: here


Integrated population models (IPM) represent the powerful combination, in a single Leslie-type of model, of different data sources that are informative about the dynamics of an animal population (Besbeas et al. 2002; Schaub et al. 2007). Typical IPMs combine one or more time-series of counts with another data set that is directly informative about survival probabilities, such as ring-recovery or capture-recapture. However, many other sources of demographic information may be envisioned instead of or in addition, including age-at-death data, occupancy or replicated point count data. Currently, for non-statisticians the only practical manner to develop and fit an IPM is using BUGS software (WinBUGS, OpenBUGS, JAGS). This intermediate-level course is a practical and hands-on introduction to developing and fitting integrated population models using BUGS software. It is based on the successful book by Kéry & Schaub, Bayesian Population Analysis using WinBUGS (Academic Press, 2012), a copy of which is included in the course fees. The course also provides a thorough introduction for ecologists and wildlife managers of a very wide variety of models fit using BUGS software and as documented in the BPA book. Contents include the following topics: Basic introduction Hierarchical models as an overarching theme of population modeling, including IPMs Bayesian analysis of hierarchical models Introduction to BUGS software in the context of generalised linear models (GLM) and traditional random-effects models Ingredients of IPMs State-space models Cormack-Jolly-Seber and ring-recovery models for estimating survival probabilities Multistate capture-recapture models for estimating survival and transition probabilities Site-occupancy models and binomial mixture models IPM Theory Various case studies which differ in complexity and in the data types that are combined In this intermediate-level workshop 3/4 of the time is spent on lecturing and 1/4 on solving exercises. No previous experience with program WinBUGS, or Bayesian statistics, is assumed. However, a good working knowledge of modern regression methods (ANOVA, ANCOVA, generalised linear models) and of program R and at least some basic knowledge about capture-recapture and/or occupancy models is required. This is a pre-announcement. We will circulate more detail and an application form in January 2015.