The wildland-urban interface lies at the confluence of human-dominated and wild landscapes, creating a number of management and conservation challenges. Because wildlife ecology, behavior, and evolution at this interface are shaped by both natural and human phenomena, this requires greater understanding of how diverse factors affect ecosystem and population processes. We illustrate the challenge of understanding and managing a frequent and often undesired inhabitant of the wildland-urban landscape, the cougar (Puma concolor). In wildland and residential areas of western Washington State, USA, we captured and radiotracked 27 cougars to model space use and understand the role of landscape features in interactions (sightings, encounters, and depredations) between cougars and humans. Resource utilization functions (RUFs) identified cougar use of areas with features that were probably attractive to prey, influential on prey vulnerability, and associated with limited or no residential development. Early-successional forest (þ), conifer forest (þ), distance to road (À), residential density (À), and elevation (À) were significant positive and negative predictors of use for the population, whereas use of other landscape features was highly variable. Space use and movement rates in wildland and residential areas were similar because cougars used wildland-like forest patches, reserves, and corridors in residential portions of their home range. The population RUF was a good predictor of confirmed cougar interactions, with 72% of confirmed reports occurring in the 50% of the landscape predicted to be medium-high and high cougar use areas. We believe that there is a threshold residential density at which the level of development modifies the habitat but maintains enough wildland characteristics to encourage moderate levels of cougar use and maximize the probability of interaction. Wildlife managers trying to reduce interactions between cougars and people should incorporate information on spatial ecology and landscape characteristics to identify areas with the highest overlap of human and cougar use to focus management, education, and landscape planning. Resource utilization functions provide a proactive tool to guide these activities for improved coexistence with wildlife using both wildland and residential portions of the landscape.

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SUMMARYUnderstanding the resource needs of animals is critical to their management and conservation. Resource utilization functions (RUFs) provide a framework to investigate animal-resource relationships by characterizing variation in the amount of resource use. In this context a ‘resource’ is any aspect of a species' fundamental niche that can be mapped throughout the area of investigation (such as study area or home range). Extensive global positioning system (GPS) data from 17 cougars (Puma concolor) demonstrate the utility and potential challenges of estimating RUFs within the home range for far-ranging species. Ninety-nine per cent utilization distributions (UDs) estimated using bivariate plug in, univariate least-squares cross-validation and reference bandwidth selection methods were compared. Distance to water, per cent clear-cut and regenerating forest, and slope were used to estimate cougar RUFs. UDs derived from GPS data were more refined, and plug-in UDs were least similar to UDs derived from other bandwidths. RUFs were resilient to variation in the smoothing parameter, with all methods yielding coefficients that largely reflected observations of foraging ecology and behaviour. Cougars were individualistic, but use was generally positively associated with the presence of regenerating forest and inversely associated with steep slopes. Advances in technology allow for greater accuracy and resolution of the UD, but software improvements and spatially explicit information on animal behaviour are needed to better understand resource use.

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Estimates of cougar (Puma concolor) density are among the least available of any big game species in North America because of monetary and logistical challenges. Thus, wildlife managers identify cougar density estimates as a high priority need for population estimation, developing harvest guidelines, and evaluating management objectives. Cougar densities range from <1 to almost 7 cougars/100 km2; however, the magnitude of spatial and temporal variation associated with these estimates is difficult to assess because this range of densities could potentially be reported for any given population using different demographic, temporal, durational, and analytical approaches. We used long‐term global positioning system (GPS) data from collared cougars across 5 diverse study areas in Washington, USA, as the basis for calculating multiple annual independent‐aged (≥18 months) cougar densities, using consistent methods, and conducted a meta‐analysis to assist with statewide harvest guidelines. To generate specific harvest guidelines for unobserved populations at the management unit scale, we employed a Bayesian decision‐theoretic approach that minimizes statistical risk of failing to achieve a defined harvest rate. For the 16‐year field effort, we calculated 24 annual densities for independent‐aged cougars. Average annual densities ranged from 1.55 ± 0.44 (SD) cougars/100 km2 (n = 5 years) to 2.79 ± 0.35 cougars/100 km2 (n = 5 years) among the 5 study areas. Explicit delineation of the cougar population demonstrated that contribution to density can vary considerably by sex and age class. Application of a 12–16% harvest rate within the risk analysis framework yielded a potential annual harvest of 249 cougars over 91,000 km2 of cougar habitat in Washington. Given the importance of density for establishing harvest guidelines, and the degree of uncertainty in projecting derived densities to future years and unstudied management units, our approach may lessen the ambiguity of extrapolations and increase the longevity of research results. Our risk analysis can be used for a diverse array of species and management objectives and be incorporated into an adaptive management framework for minimizing management risk. Our recommendations can improve standardization in reporting and interpretation of cougar density comparisons and bring clarity to the sources of variability observed in cougar populations. © 2021 The Wildlife Society.