Estimating cougar densities in northeast Oregon using conservation detection dogs

Abstract

Estimating densities of cougar (Puma concolor) is important for managing cougars and their prey but remains challenging because of cougar's elusive and solitary behavior. To evaluate a non-invasive, genetic capture–recapture method to estimate cougar population size and density, we surveyed a 220-km2 area using conservation detection dogs trained to locate scat over a 4-week sampling period in northeast Oregon. We collected 272 scat samples and conducted DNA analysis on 249 samples from which we determined individual identification from 73 samples that represented 21 cougars (9 males and 12 females). We evaluated 4 models to estimate cougar densities: Huggins closed population capture–recapture (Huggins), CAPWIRE, multiple detections with Poisson (MDP), and spatially explicit capture–recapture (SECR). Population estimates for cougars using our study area were 26 (95% CI = 22–35, 9 males and 17 females) from Huggins models, 24 (95% CI = 21–30, 9 males and 15 females) from CAPWIRE, and 27 (95% CI = 24–42, 9 males and 18 females) from the MDP model. We accounted for the edge effect in density estimates caused by individuals whose home ranges included only a portion of the survey grid by buffering the study area using the mean home range radius of 8 cougars equipped with global positioning system collars on or near the study area. We estimated densities of 4.6 cougars/100 km2 (95% CI = 3.8–8.3) for the Huggins model, 4.8 cougars/100 km2 (95% CI = 4.2–7.8) for the MDP model, 4.2 cougars/100 km2 (95% CI = 3.3–5.3) for the CAPWIRE model, and 5.0 cougars/100 km2 (95% CI = 3.2–7.7) for the SECR model. Our results suggested estimating cougar densities using scat detection dogs could be feasible at a broader scale with less effort than other methods currently being used. © 2014 The Wildlife Society.