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.

No abstract

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.

No abstract

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.

Cougar (Puma concolor) populations are a challenge to estimate because of low densities and the difficulty marking and monitoring individuals. As a result, their management is often based on imperfect data. Current strategies rely on a source–sink concept, which tends to result in spatially clumped harvest within management zones that are typically approximately 10,000 km2. Agencies often implement quotas within these zones and designate management objectives to reduce or maintain cougar populations. We propose an approach for cougar management founded on their behavior and social organization, designed to maintain an older age structure that should promote population stability. To achieve these objectives, hunter harvest would be administered within zones approximately 1,000 km2 in size to distribute harvest more evenly across the landscape. We also propose replacing the term “quota” with “harvest threshold” because quotas often connote a harvest target or goal rather than a threshold not to exceed. In Washington, USA, where the source–sink concept is implemented, research shows that high harvest rates may not accomplish the intended population reduction objectives due to immigration, resulting in an altered population age structure and social organization. We recommend a harvest strategy based on a population growth rate of 14% and a resident adult density of 1.7 cougars/100 km2 that represent probable average values for western populations of cougars. Our proposal offers managers an opportunity to preserve behavioral and demographic attributes of cougar populations, provide recreational harvest, and accomplish a variety of management objectives. We believe this science‐based approach to cougar management is easy to implement, incurs few if any added costs, satisfies agency and stakeholder interests, assures professional credibility, and may be applied throughout their range in western North America. © 2013 The Wildlife Society.

Humans have dramatically altered ecosystem structure through landscape manipulation, often leaving refuge patches of suitable habitat for wildlife amidst inhospitable terrain. Large carnivores are especially vulnerable to such habitat modification because they tend to have low population densities and wide‐ranging movements necessitated by their food requirements. Cougars (Puma concolor), unlike many other large carnivores, have demonstrated an ability to exploit resources in fragmented and managed landscapes. The influence of increasing landscape development on cougar foraging behavior, however, has yet to be fully elucidated. Accordingly, we investigated variation in cougar use of three prey types (synanthropes, ungulates, and rodents) along a wildland–urban gradient in western Washington to determine how urbanization affects the foraging ecology of this apex predator. We predicted that cougar diets would comprise more synanthropic prey (e.g., prolific urban species) and fewer deer as a function of increasing residential development. Generalized linear mixed model results showed that the odds of cougar predation on synanthropic prey did increase with urbanization. The odds of ungulate predation, however, remained relatively consistent across the wildland–urban gradient despite cougar use of black‐tailed deer (Odocoileus hemionus columbianus) and elk (Cervus canadensis) increasing over time. These results suggest that cougar–ungulate predator–prey systems can persist in landscapes with substantial human presence. The odds of forest‐associated rodent (Castor sp., Aplodontia sp.) predation decreased with increasing development, suggesting that urbanization may coincide with more intensive beaver management near residences and thereby reduce beaver and mountain beaver presence in exurban landscapes in western Washington. Most cougars exhibited similar diets, but certain individuals deviated significantly from the population averages characterizing use of all three major prey categories. This variation suggests that cougar population responses to urbanization are unlikely to be uniform and that cases of human–cougar conflict may be linked to individual cats, rather than the population as a whole.

The application of species distribution models (SDMs) to areas outside of where a model was created allows informed decisions across large spatial scales, yet transferability remains a challenge in ecological modeling. We examined how regional variation in animal‐environment relationships influenced model transferability for Canada lynx (Lynx canadensis), with an additional conservation aim of modeling lynx habitat across the northwestern United States. Simultaneously, we explored the effect of sample size from GPS data on SDM model performance and transferability. We used data from three geographically distinct Canada lynx populations in Washington (n = 17 individuals), Montana (n = 66), and Wyoming (n = 10) from 1996 to 2015. We assessed regional variation in lynx‐environment relationships between these three populations using principal components analysis (PCA). We used ensemble modeling to develop SDMs for each population and all populations combined and assessed model prediction and transferability for each model scenario using withheld data and an extensive independent dataset (n = 650). Finally, we examined GPS data efficiency by testing models created with sample sizes of 5%–100% of the original datasets. PCA results indicated some differences in environmental characteristics between populations; models created from individual populations showed differential transferability based on the populations' similarity in PCA space. Despite population differences, a single model created from all populations performed as well, or better, than each individual population. Model performance was mostly insensitive to GPS sample size, with a plateau in predictive ability reached at ~30% of the total GPS dataset when initial sample size was large. Based on these results, we generated well‐validated spatial predictions of Canada lynx distribution across a large portion of the species' southern range, with precipitation and temperature the primary environmental predictors in the model. We also demonstrated substantial redundancy in our large GPS dataset, with predictive performance insensitive to sample sizes above 30% of the original.