On the Bayesian estimation of a closed population size in the presence of heterogeneity and model uncertainty.
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, Wildlife Monographs 62, 1-135) 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 analyze two datasets where the population size is known, before considering a real example relating to a population of dolphins off northeast Scotland.
School of Mathematics and Statistics, University of St. Andrews, North Haugh, St. Andrews, Fife KY16 9SS, U.K.
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R
King
The Statistical Laboratory, University of Cambridge, Cambridge, CB3 0WB, U.K.
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SP
Brooks
D000465:Algorithms; D000818:Animals; D001499:Bayes Theorem; D001699:Biometry / Q000379:methods*; D016208:Databases, Factual / Q000706:statistics & numerical data; D004289:Dolphins; D015233:Models, Statistical; D011156:Population Density; D011817:Rabbits