Open population maximum likelihood spatial capture-recapture

Abstract

Open population capture-recapture models are widely used to estimate population demographics and abundance over time. Bayesian methods exist to incorporate open population modelling with spatial capture-recapture, allowing for estimation ofthe effective area sampled and population density. Here, open population spatial capture-recapture, both Cormack-Jolly-Seber and Jolly-Seber models, is formulated as a hidden Markov model, allowing inference by maximum likelihood. The method is applied to a twelve-year survey of male jaguars (Panthera onca) in the Cockscomb Wildlife Sanctuary Basin, Belize, to estimate the apparent survival and population abundance over time. The hidden Markov model approach is compared with Bayesian data augmentation, demonstrating it to be substantially more efficient. A simulation study shows maximum likelihood inference to be negligibly biased for small sample sizes and recapture rates.