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A Bayesian capture-recapture population model with simultaneous estimation of heterogeneity
journal contribution
posted on 2023-05-16, 19:11 authored by Stephen CorkreyStephen Corkrey, Brooks, S, Lusseau, D, Parsons, K, Durban, JW, Hammond, PS, Thompson, PMWe develop a Bayesian capture-recapture model that provides estimates of abundance as well as time-varying and heterogeneous survival and capture probability distributions. The model uses a state-space approach by incorporating an underlying population model and an observation model, and here is applied to photo-identification data to estimate trends in the abundance and survival of a population of bottlenose dolphins (Tursiops truncatus) in northeast Scotland. Novel features of the model include simultaneous estimation of time-varying survival and capture probability distributions, estimation of heterogeneity effects for survival and capture, use of separate data to inflate the number of identified animals to the total abundance, and integration of separate observations of the same animals from right and left side photographs. A Bayesian approach using Markov chain Monte Carlo methods allows for uncertainty in measurement and parameters, and simulations confirm the model's validity.
History
Publication title
Journal of the American Statistical AssociationVolume
103Issue
483Pagination
948-960ISSN
0162-1459Department/School
Tasmanian Institute of Agriculture (TIA)Publisher
American Statistical AssociationPlace of publication
United StatesRights statement
Copyright 2008 American Statistical AssociationRepository Status
- Restricted