Fencing amplifies individual differences in movement with implications on survival for two migratory ungulates.

Fences have recently been recognized as one of the most prominent linear infrastructures on earth. As animals traverse fenced landscapes, they adjust movement behaviours to optimize resource access while minimizing energetic costs of coping with fences. Examining individual responses is key for connecting localized fence effects with population dynamics. We investigated the multi-scale effects of fencing on animal movements, space use and survival of 61 pronghorn and 96 mule deer on a gradient of fence density in Wyoming, USA. Taking advantage of the recently developed Barrier Behaviour Analysis, we classified individual movement responses upon encountering fences (i.e. barrier behaviours). We adopted the reaction norm framework to jointly quantify individual plasticity and behavioural types of barrier behaviours, as well as behaviour syndromes between barrier behaviours and animal space use. We also assessed whether barrier behaviours affect individual survival. Our results highlighted a high-level individual plasticity encompassing differences in the degree and direction of barrier behaviours for both pronghorn and mule deer. Additionally, these individual differences were greater at higher fence densities. For mule deer, fence density determined the correlation between barrier behaviours and space use and was negatively associated with individual survival. However, these relationships were not statistically significant for pronghorn. By integrating approaches from movement ecology and behavioural ecology with the emerging field of fence ecology, this study provides new evidence that an extraordinarily widespread linear infrastructure uniquely impacts animals at the individual level. Managing landscape for lower fence densities may help prevent irreversible behavioural shifts for wide-ranging animals in fenced landscapes.

Attracting Diverse Students to Field Experiences Requires Adequate Pay, Flexibility, and Inclusion.

Access to field experiences can increase participation of diverse groups in the environmental and natural resources (ENR) workforce. Despite a growing interest among the ENR community to attract and retain diverse students, minimal data exist on what factors undergraduate students prioritize when applying for field experiences. Using a nationwide survey of US undergraduate ENR students, we show that attracting most students to field experiences-especially racial or ethnic minority students-will require pay above minimum wage. However, the concurrent landscape of pay in ENR fell short of meeting many students' pay needs. Aside from pay, ENR students valued training in technical field skills and analytical or research skills, working with their desired study species or taxa, and working near school or family. Additional barriers beyond limited pay included incompatible schedules and noninclusive work environments. Our findings provide important insights for attracting a diverse workforce to this critical stage in career advancement for students in ENR.

Context dependency of top-down, bottom-up and density-dependent influences on cheetah demography.

Research on drivers of demographic rates has mostly focused on top predators and their prey, and comparatively less research has considered the drivers of mesopredator demography. Of those limited studies, most focused on top-down effects of apex predators on mesopredator population dynamics, whereas studies investigating alternative mechanisms are less common. In this study, we tested hypotheses related to top-down, bottom-up and density-dependent regulation of demographic rates in an imperilled mesopredator, the cheetah (Acinonyx jubatus). We used a 25-year dataset of lion density, cheetah density and prey density from the Mun-Ya-Wana Conservancy in South Africa and assessed the effects of top-down, bottom-up and density-dependent drivers on cheetah survival and reproduction. In contrast to the top-down and bottom-up predictions, both adult and juvenile cheetahs experienced the lowest survival during months with high prey densities and low lion densities. We observed support only for a density-dependent response in juvenile cheetahs, where they had a higher probability of reaching independence during times with low cheetah density and low prey density. We did not identify any strong drivers of litter size. Collectively, our results indicate that high apex predator abundance might not always have negative effects on mesopredator populations, and suggest that context dependency in top-down, bottom-up and density-dependent factors may regulate demographic rates of cheetahs and other mesopredators. Our results highlight the complexities of population-level drivers of cheetah demographic rates and the importance of considering multiple hypotheses of mesopredator population regulation.

White-tailed deer detection rates increase when coyotes are present.

Predator species can indirectly affect prey species through the cost of anti-predator behavior responses, which may involve shifts in occupancy, space use, or movement. Quantifying the various strategies implemented by prey species to avoid adverse interactions with predators can lead to a better understanding of potential population-level repercussions. Therefore, the purpose of this study was to examine predator-prey interactions by quantifying the effect of predator species presence on detection rates of prey species, using coyotes (Canis latrans) and white-tailed deer (Odocoileus virginianus) in Central Appalachian forests of the eastern United States as a model predator-prey system. To test two competing hypotheses related to interspecific interactions, we modeled species detections from 319 camera traps with a two-species occupancy model that incorporated a continuous-time detection process. We found that white-tailed deer occupancy was independent of coyote occupancy, but white-tailed deer were more frequently detectable and had greater detection intensity at sites where coyotes were present, regardless of vegetation-related covariates. In addition, white-tailed deer detection rates at sites with coyotes were highest when presumed forage availability was relatively low. These findings suggest that white-tailed deer may be exhibiting an active avoidance behavioral response to predators by increasing movement rates when coyotes are present in an area, perhaps due to reactive evasive maneuvers and/or proactive attempts to reduce adverse encounters with them. Concurrently, coyotes could be occupying sites with higher white-tailed deer densities. Because white-tailed deer did not exhibit significant shifts in daily activity patterns based on coyote occupancy, we further suggest that white-tailed deer in our study system generally do not use temporal partitioning as their primary strategy for avoiding encounters with coyotes. Overall, our study implements a recently developed analytical approach for modeling multi-species occupancy from camera traps and provides novel ecological insight into the complex relationships between predator and prey species.

Incorporating human dimensions is associated with better wildlife translocation outcomes.

Wildlife translocations are increasingly used to combat declining biodiversity worldwide. Successful translocation often hinges on coexistence between humans and wildlife, yet not all translocation efforts explicitly include human dimensions (e.g., economic incentives, education programs, and conflict reduction assistance). To evaluate the prevalence and associated outcomes of including human dimensions as objectives when planning translocations, we analyze 305 case studies from the IUCN's Global Re-Introduction Perspectives Series. We find that fewer than half of all projects included human dimension objectives (42%), but that projects including human dimension objectives were associated with improved wildlife population outcomes (i.e., higher probability of survival, reproduction, or population growth). Translocation efforts were more likely to include human dimension objectives if they involved mammals, species with a history of local human conflict, and local stakeholders. Our findings underscore the importance of incorporating objectives related to human dimensions in translocation planning efforts to improve conservation success.

Caution is warranted when using animal space-use and movement to infer behavioral states.

BACKGROUND: Identifying the behavioral state for wild animals that can't be directly observed is of growing interest to the ecological community. Advances in telemetry technology and statistical methodologies allow researchers to use space-use and movement metrics to infer the underlying, latent, behavioral state of an animal without direct observations. For example, researchers studying ungulate ecology have started using these methods to quantify behaviors related to mating strategies. However, little work has been done to determine if assumed behaviors inferred from movement and space-use patterns correspond to actual behaviors of individuals. METHODS: Using a dataset with male and female white-tailed deer location data, we evaluated the ability of these two methods to correctly identify male-female interaction events (MFIEs). We identified MFIEs using the proximity of their locations in space as indicators of when mating could have occurred. We then tested the ability of utilization distributions (UDs) and hidden Markov models (HMMs) rendered with single sex location data to identify these events. RESULTS: For white-tailed deer, male and female space-use and movement behavior did not vary consistently when with a potential mate. There was no evidence that a probability contour threshold based on UD volume applied to an individual's UD could be used to identify MFIEs. Additionally, HMMs were unable to identify MFIEs, as single MFIEs were often split across multiple states and the primary state of each MFIE was not consistent across events. CONCLUSIONS: Caution is warranted when interpreting behavioral insights rendered from statistical models applied to location data, particularly when there is no form of validation data. For these models to detect latent behaviors, the individual needs to exhibit a consistently different type of space-use and movement when engaged in the behavior. Unvalidated assumptions about that relationship may lead to incorrect inference about mating strategies or other behaviors.

Habitat complexity and lifetime predation risk influence mesopredator survival in a multi-predator system.

Variability in habitat selection can lead to differences in fitness; however limited research exists on how habitat selection of mid-ranking predators can influence population-level processes in multi-predator systems. For mid-ranking, or mesopredators, differences in habitat use might have strong demographic effects because mesopredators need to simultaneously avoid apex predators and acquire prey. We studied spatially-explicit survival of cheetahs (Acinonyx jubatus) in the Mun-Ya-Wana Conservancy, South Africa, to test hypotheses related to spatial influences of predation risk, prey availability, and vegetation complexity, on mesopredator survival. For each monitored cheetah, we estimated lion encounter risk, prey density, and vegetation complexity within their home range, on short-term (seasonal) and long-term (lifetime) scales and estimated survival based on these covariates. Survival was lowest for adult cheetahs and cubs in areas with high vegetation complexity on both seasonal and lifetime scales. Additionally, cub survival was negatively related to the long-term risk of encountering a lion. We suggest that complex habitats are only beneficial to mesopredators when they are able to effectively find and hunt prey, and show that spatial drivers of survival for mesopredators can vary temporally. Collectively, our research illustrates that individual variation in mesopredator habitat use can scale-up and have population-level effects.