Talk by Audrey Beliveau (DSAS Colloquium)

Visitng from Waterloo University

Title: Escaping the independence assumption in integrated population modeling

Abstract: Capture-recapture surveys are frequently used to study survival rates and population trends in animal populations. They consist of a series of occasions, on which animals are captured and released in the population. Individuals captured for the first time are marked with a unique identification number, while recaptured individuals have their identifier number recorded. Oftentimes, a single population is studied using additional types of surveys, e.g. visual count surveys or carcass recoveries. The integration of all the data in a single statistical analysis is a very exciting mechanism to fully exploit the potential of the data. This is typically achieved by approximating the full joint likelihood of the data as a product of likelihoods.

In this talk I introduce a new Bayesian modeling framework to integrate capture-recapture data with other sources of data in a fully explicit manner. This approach relies on the use of an appropriate set of latent variables that allows to formulate the full joint likelihood of the data. I will present new simulation study results that compare the new approach with the usual approach (product of likelihoods). The RMSE and credible intervals are typically smaller with the new approach, often considerably so, particularly when estimating fecundity rates. I will also illustrate the use of the methods on a dataset from a bats colony.