Resource selection of mule deer in a shrub‐steppe ecosystem: influence of woodland distribution and animal behavior

Impacts of management practices on habitat selection during juvenile mountain lion dispersal

Dispersal is a complex series of movements before an individual establishes a home range. Animals must travel and forage in unfamiliar landscapes that include anthropogenic risks such as road crossings, harvest, and urban landscapes. We compare dispersal behavior of juvenile mountain lions (Puma concolor) from two geographically distinct populations in California and Nevada, USA. These two sites are ecologically similar but have different management practices; hunting is permitted in Nevada, whereas mountain lions are protected in California. We used GPS-collar data and net-squared displacement analysis to identify three dispersal states: exploratory, departure, and transient home range. We then compared each dispersal state of the two mountain lion populations using an integrated step selection analysis (iSSA). The model included explanatory variables hypothesized to influence one or more dispersal states, including distance to forest, shrub, water, hay and crop, developed lands, and four-wheel drive roads, as well as elevation and terrain ruggedness. Results revealed consistent habitat selection between sites across most landscape variables, with one notable exception: anthropogenic covariates, including distance to developed land, distance to hay and crop, and distance to four-wheeled drive roads, were only statistically significant on modeled habitat selection during dispersal in the population subject to hunting (i.e., Nevada). Results suggest that hunting (pursuit with hounds resulting in harvest) and non-lethal pursuit (pursuit with hounds but no harvest allowed) increase avoidance of anthropogenic landscapes during dispersal for juvenile mountain lions. By comparing populations, we provided valuable insights into the role of management in shaping dispersal behavior.

Effects of large-scale gold mining on habitat use and selection by American pronghorn

Anthropogenic disturbances, including extraction of natural resources and development of alternative energy, are reducing and fragmenting habitat for wildlife across the globe. Effects of those disturbances have been explored by studying populations that migrate through oil and gas fields or alternative energy facilities. Extraction of minerals, including precious metals and lithium, is increasing rapidly in remote areas, which results in dramatically altered landscapes in areas of resident populations of wildlife. Our goal was to examine how a resident population of American pronghorn (Antilocapra americana) in the Great Basin ecosystem selected resources near a large-scale disturbance year around. We investigated how individuals selected resources around a large, open-pit gold mine. We classified levels of disturbance associated with the mine, and used a random forest model to select ecological covariates associated with habitat selection by pronghorn. We used resource selection functions to examine how disturbances affected habitat selection by pronghorn both annually and seasonally. Pronghorn strongly avoided areas of high disturbance, which included open pits, heap leach fields, rock disposal areas, and a tram. Pronghorn selected areas near roads, although selection was strongest about 2 km away. We observed relatively broad variation among individuals in selection of resources, and how they responded to the mine. The Great Basin is a mineral-rich area that continues to be exploited for natural resources, especially minerals. Sagebrush-dependent species, including pronghorn, that rely on this critical habitat were directly affected by that transformation of the landscape, which is likely to increase with expansion of the mine. As extraction of minerals from remote landscapes around the world continues to fragment habitats for wildlife, increasing our understanding of impacts of those changes on behaviors of wildlife before populations decline, may assist in the mitigation and minimization of negative impacts on mineral-rich landscapes and on wildlife populations.

Diel activity structures the occurrence of a mammal community in a human-dominated landscape

Anthropogenic developments alter the environment and resources available to wildlife communities. In response to these real or perceived threats from this development, species may adjust their spatial occurrence. Additionally, wildlife species may adjust when in diel time (24-h light-dark cycle) they occupy sites on the landscape to adapt to changing conditions. However, many wildlife studies only focus on where a species does and does not occur, ignoring how species may shift their diel activity at sites to mitigate threats. We used a multi-state diel occupancy modeling framework to investigate how a community of mammals (mesocarnivores, urban-adapted omnivores, and herbivore/small mammals) respond to differing levels of anthropogenic development and forest cover across two climatic seasons. We collected camera trap data at 240 survey locations across the summer and winter of 2021-2022. We modeled multi-state diel occupancy for 14 mammal species with extent of development/forest and season hypothesized to influence diel occupancy and season hypothesized to influence the probability of detection. We found that all species displayed heterogeneity in both diel occupancy and detection either by extent of development/forest and or season. Within the mesocarnivore species group, coyote and red fox were less sensitive to development and had higher occupancy probability at these sites in general but used them more during the night, while more sensitive mesocarnivores including fisher and bobcat occupied the day state only when there was increasing forest cover. Our results highlight the importance of incorporating diel activity in habitat modeling to better understand the relationship between a species and its landscape, particularly in a region that is vulnerable to increased anthropogenic pressure.

Dynamic winter weather moderates movement and resource selection of wild turkeys at high-latitude range limits

For wide-ranging species in temperate environments, populations at high-latitude range limits are subject to more extreme conditions, colder temperatures, and greater snow accumulation compared with their core range. As climate change progresses, these bounding pressures may become more moderate on average, while extreme weather occurs more frequently. Individuals can mitigate temporarily extreme conditions by changing daily activity budgets and exhibiting plasticity in resource selection, both of which facilitate existence at and expansion of high-latitude range boundaries. However, relatively little work has explored how animals moderate movement and vary resource selection with changing weather, and a general framework for such investigations is lacking. We applied hidden Markov models and step selection functions to GPS data from wintering wild turkeys (Meleagris gallopavo) near their northern range limit to identify how weather influenced transition among discrete movement states, as well as state-specific resource selection. We found that turkeys were more likely to spend time in a stationary state as wind chill temperatures decreased and snow depth increased. Both stationary and roosting turkeys selected conifer forests and avoided land covers associated with foraging, such as agriculture and residential areas, while shifting their strength of selection for these features during poor weather. In contrast, mobile turkeys showed relatively weak resource selection, with less response in selection coefficients during poor weather. Our findings illustrate that behavioral plasticity in response to weather was context dependent, but movement behaviors most associated with poor weather were also those in which resource selection was most plastic. Given our results, the potential for wild turkey range expansion will partly be determined by the availability of habitat that allows them to withstand periodic inclement weather. Combining hidden Markov models with step selection functions is broadly applicable for evaluating plasticity in animal behavior and dynamic resource selection in response to changing weather. We studied turkeys at northern range limits, but this approach is applicable for any system expected to experience significant changes in the coming decade, and may be particularly relevant to populations existing at range peripheries.

Permanent daylight saving time would reduce deer-vehicle collisions

Overlap between wildlife and human activity is key to causing wildlife-vehicle collisions, a globally pervasive and growing source of wildlife mortality.^1,2 Policies regarding clock time often involve abrupt seasonal shifts in human activity, potentially influencing rates of human-wildlife conflict. Here, we harness the biannual shift between standard and daylight saving time as a natural experiment to reveal how the timing of human activity influences deer-vehicle collisions. Based on 1,012,465 deer-vehicle collisions and 96 million hourly traffic observations across the United States, we show that collisions are 14 times more frequent 2 hours after sunset than before sunset, highlighting the importance of traffic during dark hours as a key determinant of deer-vehicle collision risk. The switch from daylight saving to standard time in autumn causes peak traffic volumes to shift from before sunset to after sunset, leading to a 16% spike in deer-vehicle collisions. By reducing traffic after dark, our model predicts that year-round daylight saving time would prevent 36,550 deer (Odocoileus sp.) deaths, 33 human deaths, 2,054 human injuries, and US$1.19 billion in collision costs annually. In contrast, permanent standard time is predicted to increase collisions by an even larger magnitude, incurring an additional US$2.39 billion in costs. By targeting the temporal dimension of wildlife-vehicle collisions, strategies such as year-round daylight saving time that reduce traffic during dark hours, especially during the breeding season of abundant ungulates, would yield substantial benefits for wildlife conservation and reduce the social and economic costs of deer-vehicle collisions.

Spatiotemporal patterns of male and female white-tailed deer on a hunted landscape

Resource selection in sexually dimorphic ungulates is at least partially explained by sex-specific resource requirements and risk aversion strategies. Females generally spend more time in areas with less risk and abundant, high-quality forage due to their smaller body size. However, demographically variable responses to risk are context dependent, and few have concurrently quantified male and female behavior within areas with the same resource base. We captured 111 (54 males, 57 females) adult white-tailed deer (Odocoileus virginianus) from 2009 to 2018 on a site in South Carolina, USA, where hunters were the primary source of adult mortality. We fit each deer with a GPS collar programmed to collect locations at 30-min intervals. Upon collar recovery, we analyzed the data to estimate sex- and time-specific selection for, and distance to, various cover types. While both sexes generally avoided risky areas (i.e., sites hunted more frequently) during the day, females (p = .41) were more likely than males (p = .16) to use risky areas containing abundant food resources during the day, where p = probability of selection. Our findings indicate that female white-tailed deer may be forced to utilize high risk areas during high risk periods due to their smaller body size and increased nutritional demands, whereas larger males are better able to forgo foraging opportunities during risky periods to mitigate risk; however, our study design left room for the possibility that our observations were driven by innate sex-specific patterns in white-tailed deer. Nonetheless, our study contributes information to the literature by describing sex-specific resource selection by diel period on a site where sexes shared the same resources and were presented with the same landscape of risk.