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.

In savanna ecosystems, African elephants (Loxodonta africana) and large trees such as marula (Sclerocarya birreaand) and knobthorn (Acacia nigrescens) have ecological and human value; however, elephants have a large impact on favored trees, motivating the need for ecological conservation strategies. This study examined the perceptions of tourists and residents towards elephants, large trees, and other relevant factors for management purposes. In the Associated Private Nature Reserves, South Africa, a survey was distributed to tourists and residents to determine perceptions of elephants of different age classes, group sizes and sex, and toward savanna habitat impacted to varying degrees by elephants. Both interest groups had high attractiveness rankings for all elephant types. Undamaged tree types received high attractiveness rankings while damaged trees received lower ranks, revealing a conflict of interests.Undamaged trees and the elephant types that cause high amounts of impact to those trees are both liked. Respondents may not be associating attractiveness levels with levels of impact. Residents encouraged more intrusive elephant management methods than tourists. Environmental manipulation was found to be the most supported and balanced technique. This supports the use of meta-population management, which focuses primarily on the environment and the elephant population secondarily.

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