Skip to main content

Counting Sheep (Bayesian Methods to Account for Time-Dependent Covariates in Open-Population Capture-Recapture Models)

Date:
-
Location:
University of Kentucky, Whitehall Classroom Building room 102
Speaker(s) / Presenter(s):
Simon Bonner, University of British Columbia

 

Capture-recapture methods are widely used to monitor endangered wildlife populations. A requirement of simple capture-recapture models is that all individuals alive on one sampling occasion have the same probability of capture. While this assumption may be reasonable in small, isolated populations, there are many variables that might in uence an individual's catchability and estimates of survival rates or abundance will be biased if these differences are ignored. However, covariates of the capture probability which vary both between individuals and over time, like body mass, present a challenge in the analysis of capture-recapture data because 1) their values can only be measured for the individuals captured on each sampling occasion and 2) the unknown values are not missing at random and cannot be ignored. In this talk, I will present Bayesian methods to incorporate the effects of such covariates in the Cormack-Jolly-Seber and Jolly-Seber models (the two most common models for open-population capture-recapture data). My talk will begin with an introduction to capture-recapture methods and the problems associated with time-dependent covariates. I will then describe my method for including such covariates in the Cormack-Jolly-Seber model to estimate survival rates and how this method can be extended to the Jolly-Seber model to obtain estimates of abundance. I will illustrate my methods by application to data from the study of Soay sheep on the Isle of Hirta,Scotland, and conclude by discussing applications to more complicated models and comparisons with other approaches. 

Event Series: