On the Bayesian Estimation of a Closed Population Size in the Presence of Heterogeneity and Model Uncertainty

Ruth King, Stephen P. Brooks

Universities of St. Andrews and Cambridge


We consider the estimation of the size of a closed population, often of interest for wild animal populations, using a capture-recapture study. The estimate of the total population size can be very sensitive to the choice of model used to fit to the data. We consider a Bayesian approach, in which we consider all eight plausible models initially described by Otis et al. (1978) within a single framework, including models containing an individual heterogeneity component. We show how we are able to obtain a model-averaged estimate of the total population, incorporating both parameter and model uncertainty. To illustrate the methodology we initially perform a simulation study and analyse two datasets where the population size is known, before considering a real example relating to a population of dolphins based in North East Scotland.


Bayesian approach, Heterogeneity, Model-averaging, Population size, Reversible jump Markov chain Monte Carlo.