Jacques, C.N., R.W. Klaver, T.C. Swearingen, E.D. Davis, C.R. Anderson, J.A. Jenks, C.S. DePerno, and R.D. Bluett. 2019. Estimating detection and density of bobcats with capture-mark-recapture data from camera traps. Wildlife Society Bulletin 43:256-264.
Abstract
Camera‐trapping data analyzed with spatially explicit capture–recapture (SCR) models can provide a rigorous method for estimating density of small populations of elusive carnivore species. We sought to develop and evaluate the efficacy of SCR models for estimating density of a presumed low‐density bobcat (Lynx rufus) population in fragmented landscapes of west‐central Illinois, USA. We analyzed camera‐trapping data from 49 camera stations in a 1,458‐km2 area deployed over a 77‐day period from 1 February to 18 April 2017. Mean operational time of cameras was 52 days (range =32–67 days). We captured 23 uniquely identifiable bobcats 113 times and recaptured these same individuals 90 times; 15 of 23 (65.2%) individuals were recaptured at ≥2 camera traps. Total number of bobcat capture events was 139, of which 26 (18.7%) were discarded from analyses because of poor image quality or capture of only a part of an animal in photographs. Of 113 capture events used in analyses, 106 (93.8%) and 7 (6.2%) were classified as positive and tentative identifications, respectively; agreement on tentative identifications of bobcats was high (71.4%) among 3 observers. We photographed bobcats at 36 of 49 (73.5%) camera stations, of which 34 stations were used in analyses. We estimated bobcat density at 1.40 individuals (range =1.00–2.02)/100 km2. Our modeled bobcat density estimates are considerably below previously reported densities (30.5 individuals/100 km2) within the state, and among the lowest yet recorded for the species. Nevertheless, use of remote cameras and SCR models was a viable technique for reliably estimating bobcat density across west‐central Illinois. Our research establishes ecological benchmarks for understanding potential effects of colonization, habitat fragmentation, and exploitation on future assessments of bobcat density using standardized methodologies that can be compared directly over time. Further application of SCR models that quantify specific costs of animal movements (i.e., least‐cost path models) while accounting for landscape connectivity has great utility and relevance for conservation and management of bobcat populations across fragmentedMidwestern landscapes.