Mark-recapture with occasion and individual effects: Abundance estimation through Bayesian model selection in a fixed dimensional parameter space |
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| Authors: | Email author" target="_blank">John?W?DurbanEmail author David?A?Elston |
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| Institution: | 1.National Research Council, hosted by the NOAA Fisheries,A laska Fisheries Science Center,Seattle;2.Biomathematics and Statistics Scotland,The Macaulay Institute,Aberdeen,UK |
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| Abstract: | We present a Bayesian mark-recapture method for explicitly communicating uncertainty about the size of a closed population
where capture probabilities vary across both individuals and sampling occasions. Heterogeneity is modeled hierarchically using
a continuous logistic-Normal model to specify the capture probabilities for both individuals that are captured on at least
one occasion and individuals that are never captured and so remain undetected. Inference about how many undetected individuals
to include in the model is accomplished through a Bayesian model selection procedure using MCMC, applied to a product space
of possible models for different numbers of undetected individuals. Setting the estimation problem in a fixed dimensional
parameter space enables the model selection procedure to be performed using the freely available WinBUGS software. The outcome
of inference is a full “posterior” probability distribution for the population size parameter. We demonstrate this method
through an example involving real mark-recapture data. |
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