Abstract
This article is motivated by a series of data on a population of mouflons (Ovis gmelini) in the Caroux-Espinouse massif and focuses upon discriminating between competing biological hypotheses corresponding to the dependence of any or all of the population parameters upon either sex, location, or age. We show how we can analyze the data using a Bayesian approach, where we are able to take into account prior information obtained via a previous radio-tagging study. We consider the Amason-Schwarz model together with its submodels to describe the data. Efficiently exploring model space using reversible jump Markov chain Monte Carlo methodology, we are able to calculate model-averaged estimates of parameters of interest, which incorporate both parameter and model uncertainty. In addition, we quantitatively compare different biological hypotheses by calculating their corresponding posterior probabilities. In particular, we show that survival rates tend to remain constant with some evidence to suggest a slight senescent decline. We also provide evidence to suggest that movement around the habitat is largely the same for both sexes up until age 4, when the males appear to extend their migration range, venturing further from the main flock in search of better grazing.
Original language | English |
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Pages (from-to) | 486-513 |
Number of pages | 28 |
Journal | Journal of Agricultural, Biological and Environmental Statistics |
Volume | 8 |
Issue number | 4 |
DOIs | |
Publication status | Published - Dec 2003 |
Keywords
- Arnason-Schwarz
- Bayesian analysis
- capture-recapture
- Markov chain Monte Carlo
- model averaging
- model discrimination
- CAPTURE-RECAPTURE DATA
- CHAIN MONTE-CARLO
- RING-RECOVERY DATA
- MODEL SELECTION
- BAYESIAN-ANALYSIS
- OVIS-GMELINI
- MULTIPLE CAPTURE
- POPULATION
- PROBABILITIES
- UNCERTAINTY