Spatially Explicit Maximum Likelihood Methods for Capture–Recapture Studies
University of St Andrews · University of Otago
Abstract
Live-trapping capture-recapture studies of animal populations with fixed trap locations inevitably have a spatial component: animals close to traps are more likely to be caught than those far away. This is not addressed in conventional closed-population estimates of abundance and without the spatial component, rigorous estimates of density cannot be obtained. We propose new, flexible capture-recapture models that use the capture locations to estimate animal locations and spatially referenced capture probability. The models are likelihood-based and hence allow use of Akaike's information criterion or other likelihood-based methods of model selection. Density is an explicit parameter, and the evaluation of its…
Citation impact
- FWCI
- 12.82
- Percentile
- 100%
- References
- 25
Authors
2Topics & keywords
- Mark and recapture
- Akaike information criterion
- Statistics
- Estimator
- Covariate
- Abundance estimation
- Model selection
- Mathematics