Density estimation in a wolverine population using spatial capture–recapture models |
| |
Authors: | J Andrew Royle Audrey J Magoun Beth Gardner Patrick Valkenburg Richard E Lowell |
| |
Institution: | 1. USGS Patuxent Wildlife Research Center, 12100 Beech Forest Road, Laurel, MD 20708, USA;2. Alaska Department of Fish and Game, P.O. Box 667, Petersburg, AK 99833, USA;3. Alaska Department of Fish and Game, P.O. Box 115526, Juneau, AK 99833, USA |
| |
Abstract: | Classical closed-population capture–recapture models do not accommodate the spatial information inherent in encounter history data obtained from camera-trapping studies. As a result, individual heterogeneity in encounter probability is induced, and it is not possible to estimate density objectively because trap arrays do not have a well-defined sample area. We applied newly-developed, capture–recapture models that accommodate the spatial attribute inherent in capture–recapture data to a population of wolverines (Gulo gulo) in Southeast Alaska in 2008. We used camera-trapping data collected from 37 cameras in a 2,140-km2 area of forested and open habitats largely enclosed by ocean and glacial icefields. We detected 21 unique individuals 115 times. Wolverines exhibited a strong positive trap response, with an increased tendency to revisit previously visited traps. Under the trap-response model, we estimated wolverine density at 9.7 individuals/1,000 km2 (95% Bayesian CI: 5.9–15.0). Our model provides a formal statistical framework for estimating density from wolverine camera-trapping studies that accounts for a behavioral response due to baited traps. Further, our model-based estimator does not have strict requirements about the spatial configuration of traps or length of trapping sessions, providing considerable operational flexibility in the development of field studies. © 2011 The Wildlife Society. |
| |
Keywords: | Bayesian capture–recapture density Gulo gulo motion-detection cameras spatial models wolverine |
|
|