A Long-Term Population Monitoring Approach for a Wide-Ranging Carnivore: Noninvasive Genetic Sampling of Gray Wolf Rendezvous Sites in Idaho, USA

摘要

Various monitoring methods have been developed for large carnivores, but not all are practical or sufficiently accurate for long-term monitoring over large spatial scales. From 2009 to 2010, we used a predictive habitat model to locate gray wolf rendezvous sites in 4 study areas in Idaho, USA and conducted noninvasive genetic sampling (NGS) of scat and hair found at the sites. We evaluated species and individual identification PCR success rates across the study areas, and estimated population size with a single-session population estimator using 2 different recapture-coding methods. We then compared NGS population estimates to estimates generated concurrently from telemetry data. We collected 1,937 scat and 166 hair samples and identified 193 unique individuals over 2 years. For fecal DNA samples, species identification success rates were consistently high (>92%) across areas. Individual identification success rates ranged from 78% to 80% in the drier study areas and dropped to 50% in the wettest study area. The degree of agreement between NGS- and telemetry-derived population estimates varied by recapture-coding method with considerable variability in 95% confidence intervals. Population estimates derived from NGS methods were most influenced by the average number of detections per individual. We demonstrate how changes in field effort and recapture-coding method can affect population estimates in a widely used single-session population estimation model. Our study highlights the need to further develop reliable population estimation tools for single-session NGS data, especially those with large differences in capture frequencies among individuals stemming from severe capture heterogeneity (i.e., overdispersion). (c) 2014 The Wildlife Society.