To ensure reproductive success, Canis species establish contiguous mosaics of territories in suitable habitats to partition space and defend limiting resources. Consequently, Canis species can exert strong effects on prey populations locally because of their year-round maintenance of territories. We assessed prey use by coyotes (Canis latrans) by sampling scats from within known territories in southeastern Alabama and the Savannah River area of Georgia and South Carolina. We accounted for the size and habitat composition of coyote home ranges to investigate the influence of space use, vegetation density, and habitat type on coyote diets. Coyote use of prey was influenced by a combination of mean monthly temperature, home range size, vegetation density, and hardwood forests. For example, coyote use of adult white-tailed deer (Odocoileus virginianus) was associated with cooler months and smaller home ranges, whereas use of rabbits (Sylvilagus spp.) was associated with cooler months, larger home ranges, and less vegetation density. Coyotes in our study relied primarily on nutritionally superior mammalian prey and supplemented their diet with fruit when available, as their use of mammalian prey did not appreciably decrease with increasing use of fruit. We suggest that differential use of prey by coyotes is influenced by habitat heterogeneity within their home ranges, and prey-switching behaviors may stabilize local interactions between coyotes and their food resources to permit stable year-round territories. Given that habitat composition affects coyote prey use, future studies should also incorporate effects of habitat composition on coyote distribution and abundance to further identify coyote influences on prey communities.

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Bait is often used to increase wildlife harvest susceptibility, enhance viewing opportunities, and survey wildlife populations. The effects of baiting depend on how bait influences space use and resource selection at multiple spatial scales. Although telemetry studies allow for inferences about resource selection within home ranges (third-order selection), they provide limited information about spatial variation in density, which is the result of second-order selection. Recent advances in spatial capture-recapture (SCR) techniques allow exploration of second- and third-order selection simultaneously using non-invasive methods such as camera traps. Our objectives were to describe how short-term baiting affects white-tailed deer (Odocoileus virginianus) behavior and distribution. We fit SCR models to camera data from baited and unbaited locations in southwestern Georgia to assess the effects of short-term baiting on second- and third-order selection of deer during summer and winter surveys. We found little evidence of second-order selection during late summer or early winter surveys when camera surveys using bait are typically conducted. However, we found evidence for third-order selection, indicating that resource selection within home ranges is affected. Concentrations in space use resulting from baiting may enhance disease transmission, change harvest susceptibility, and potentially bias the outcome of camera surveys using bait.

White‐tailed deer (Odocoileus virginianus) populations and deer hunter participation on federal public lands within the Appalachian Mountains of the southeastern United States have been declining over the last 30 years. Our study focused on Chattahoochee National Forest hunters in North Georgia, a region that has sustained a 64% decline in buck harvest success rates and 68% decline in hunter participation during 1979–2018. To better understand factors influencing satisfaction of remaining hunters, we sent mail questionnaires to 1,271 hunters in February 2019. We received 441 completed questionnaires for a 36% adjusted response rate. First, we used principal component analysis to identify 4 unique motivations for deer hunting: 1) escaping the daily routine and spending time outdoors, 2) harvesting deer for food, 3) socializing with hunting partners, and 4) harvesting trophy bucks. Second, we used ordinal logistic regression, which indicated that perception of a low deer population density was associated with lower levels of satisfaction. Perception of the right number of hunters on the landscape was associated with higher levels of satisfaction. In addition, greater importance ratings of harvesting trophy bucks were associated with lower satisfaction levels. Last, we applied revised importance‐performance analysis to 19 aspects of WMA deer hunting, which revealed that managers should focus on increasing opportunities for hunters to see deer and harvest bucks for the best chance at improving hunter satisfaction. Considering the 64% decline in harvest success rates between 1979 and 2018, the positive relationship between hunter satisfaction and perception of deer density, and hunter desires to see more deer and have more opportunities to harvest bucks, we recommend managing the deer population to increase numbers. Overall, our findings suggested that hunters and managers agree on the direction of deer management on North Georgia public lands for the near future. © 2021 The Wildlife Society.

White-tailed deer (Odocoileus virginianus) and hunters on 2 Wildlife Management Areas (WMAs) within the Chattahoochee National Forest of northern Georgia, USA, significantly declined in number from the 1980s to 2018. Managers were interested in understanding how they could manipulate hunter distribution according to deer management goals. To understand the spatial distribution of hunting pressure and factors driving hunter resource selection, we analyzed GPS tracking data from 58 deer hunters over the 2018-2019 and 2019-2020 hunting seasons. We evaluated hunter selection on 3 spatial scales relative to elevation, slope, and distance from roads, trails, wildlife openings, deciduous forest, mixed forest, and evergreen forest. We incorporated covariates into 6 binary logistic regression models, plus a null model, within a used versus available framework. First, we compared hunter locations to available locations generated within the 2 WMAs.Elevation and distance to deciduous forest had the greatest effect on hunter selection, where hunters selected for lower elevations and closer proximity to deciduous forest. Second, we compared individual hunting bout locations to available locations generated within a buffer around the hunter's starting location with a buffer radius equal to the maximum distance they travelled from their starting location. At the bout