Abstract

Remote cameras have become a popular tool for monitoring wildlife. We used remote cameras to estimate bobcat (Lynx rufus) population abundance on the Utah Test and Training Range during two sample periods between 2015 and 2017. We used two statistical methods, closed capture mark-recapture (CMR) and mark-resight Poisson log-normal (PNE), to estimate bobcat abundance within the study area. We used the maximum mean distance moved method (MMDM) to calculate the effective sample area for estimating density. Additionally, we captured bobcats and estimated home range using minimum convex polygon (MCP) and kernel density estimation (KDE) methods. Bobcat abundance on the UTTR was 35-48 in 2017 and density was 11.95 bobcats/100 km2 using CMR and 16.69 bobcats/100 km2 using PNE. The North Range of the study area experienced a decline of 36-44 percent in density between sample periods. Density declines could be explained by natural predator prey cycles, by habituation to attractants or by an increase in home range area. We recommend that bobcat abundance and density be estimated regularly to establish population trends.To improve the management of bobcats on the Utah Test and Training Range (UTTR), we investigated bobcat (Lynx rufus) habitat use. We determined habitat use points by capturing bobcats in remote camera images. Use and random points were intersected with remotely sensed data in a geographic information system. Habitat variables were evaluated at the capture point scale and home range scale. Home range size was calculated using the mean maximum distance moved method. Scales and habitat variables were compared within generalized linear mixed-effects models. Our top model (AICc weight = 1) included a measure of terrain ruggedness, mean aspect, and land cover variables related to prey availability and human avoidance.

Degree

College and Department

Life Sciences; Plant and Wildlife Sciences

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