Bayesian analysis of Jolly-Seber type models; incorporating heterogeneity in arrival and departure

TL;DR

This paper introduces a Bayesian mixture model approach with reversible jump MCMC to analyze heterogeneity in arrival and departure processes in wildlife populations, demonstrated on migrating sandpipers.

Contribution

It extends existing stopover models by incorporating heterogeneity in arrival and behavior, providing a flexible Bayesian framework for ecological data analysis.

Findings

Revealed heterogeneity in sandpiper stopover durations.

Demonstrated the model's ability to identify different arrival groups.

Provided ecological insights into migration behavior.

Abstract

We propose the use of finite mixtures of continuous distributions in modelling the process by which new individuals, that arrive in groups, become part of a wildlife population. We demonstrate this approach using a data set of migrating semipalmated sandpipers (Calidris pussila) for which we extend existing stopover models to allow for individuals to have different behaviour in terms of their stopover duration at the site. We demonstrate the use of reversible jump MCMC methods to derive posterior distributions for the model parameters and the models, simultaneously. The algorithm moves between models with different numbers of arrival groups as well as between models with different numbers of behavioural groups. The approach is shown to provide new ecological insights about the stopover behaviour of semipalmated sandpipers but is generally applicable to any population in which animals arrive in groups and potentially exhibit heterogeneity in terms of one or more other processes.