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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Many wildlife species shift their diets to use novel resources in urban areas. The consequences of these shifts are not well known, and consumption of reliable-but low quality-anthropogenic food may present important trade-offs for wildlife health. This may be especially true for carnivorous species such as the American white ibis (), a nomadic wading bird which has been increasingly observed in urban parks in South Florida, USA. We tested the effects of anthropogenic provisioning on consumer nutrition (i.e. dietary protein), body condition and ectoparasite burdens along an urban gradient using stable isotope analysis, scaled mass index values and GPS transmitter data. Ibises that assimilated more provisioned food were captured at more urban sites, used more urban habitat, had lower mass-length residuals, lower ectoparasite scores, assimilated less 15N and had smaller dietary isotopic ellipses. Our results suggest that ibises in urban areas are heavily provisioned with anthropogenic food, which appears to offer a trade-off by providing low-quality, but easily accessible, calories that may not support high mass but may increase time available for anti-parasite behaviours such as preening. Understanding such trade-offs is important for investigating the effects of provisioning on infection risk and the conservation of wildlife in human-modified habitats.This article is part of the theme issue 'Anthropogenic resource subsidies and host-parasite dynamics in wildlife'.

Context Spatial variation in abundance is influenced by local-and landscape-level environmental variables, but modeling landscape effects is challenging because the spatial scales of the relationships are unknown. Current approaches involve buffering survey locations with polygons of various sizes and using model selection to identify the best scale. The buffering approach does not acknowledge that the influence of surrounding landscape features should diminish with distance, and it does not yield an estimate of the unknown scale parameters. Objectives The purpose of this paper is to present an approach that allows for statistical inference about the scales at which landscape variables affect abundance. Methods Our method uses smoothing kernels to average landscape variables around focal sites and uses maximum likelihood to estimate the scale parameters of the kernels and the effects of the smoothed variables on abundance. We assessed model performance using a simulation study and an avian point count dataset. ResultsThe simulation study demonstrated that estimators are unbiased and produce correct confidence interval coverage except in the rare case in which there is little spatial autocorrelation in the landscape variable. Canada warbler abundance was more highly correlated with site-level measures of NDVI than landscape-level NDVI, but the reverse was true for elevation. Canada warbler abundance was highest when elevation in the surrounding landscape, defined by an estimated Gaussian kernel, was between 1300 and 1400 m. Conclusions Our method provides a rigorous way of formally estimating the scales at which landscape variables affect abundance, and it can be embedded within most classes of statistical models.

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