We are using bobcats (Lynx rufus) as a model organism to examine how roads affect the abundance, distribution, and genetic structure of a wide-ranging carnivore. First, we compared the distribution of bobcat-vehicle collisions to road density and then estimated collision probabilities for specific landscapes using a moving window with road-specific traffic volume. Next, we obtained incidental observations of bobcats from the public, camera-trap detections, and locations of bobcats equipped with GPS collars to examine habitat selection. These data were used to generate a cost-surface map to investigate potential barrier effects of roads. Finally, we have begun an examination of genetic structure of bobcat populations in relation to major road networks. Distribution of vehicle-killed bobcats was correlated with road density, especially state and interstate highways. Collision models suggested that some regions may function as demographic sinks. Simulated movements in the context of the cost-surface map indicated that some major roads may be barriers. These patterns were supported by the genetic structure of bobcats. The sharpest divisions among genetically distinct demes occurred along natural barriers (mountains and large lakes) and in road-dense regions. In conclusion, our study has demonstrated the utility of using bobcats as a model organism to understand the variety of threats that roads pose to a wide-ranging species. Bobcats may also be useful as one of a group of focal species while developing approaches to maintain existing connectivity or mitigate the negative effects of roads.

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To understand large scale animal—habitat associations, biologists often rely on intensive home‐range based studies, where a large number of locations are obtained from relatively few individuals equipped with radio transmitters and then extrapolate patterns of habitat use to much larger areas. Alternatively, extensive methods (e.g. incidental observations) that provide few observations per individual can be effectively used to sample large areas. Both methods have advantages, limitations, and potential sources of bias. We used these different approaches in an effort to identify habitat features that may be important to expanding populations of bobcats Lynx rufus in New Hampshire, USA. Twelve adult bobcats with GPS‐equipped transmitters provided detailed summaries of movement patterns within a 2300‐km2 study area. We also solicited incidental observations from citizens throughout the state (24 200 km2). Using locations from both methods, we developed logistic models based on a comparison of home range composition to study area composition (second‐order habitat selection). We also explored an approach to reduce potential bias associated with incidental observations (overrepresentation of human population centers) by applying a weighing factor. The telemetry and uncorrected observation‐based models overlapped substantially with eight common covariates. The telemetry‐based model indicated that bobcats preferred areas with few roads, limited human development, high stream densities, and steep topography. In contrast, the adjusted (to reduce bias) observation‐based model indicated bobcats preferred areas with an abundance of roads and development with few streams and limited topographic variation. Because of these differences, we recommend caution when using sightings to model habitat associations unless biases associated with such information can be identified and overcome. Although public sightings had limited application for describing bobcat habitat, they were useful in documenting a recent range expansion and revealing novel prey use by bobcats.

The formal concept of wildlife stakeholder acceptance capacity (WSAC) in wildlife management is less than a generation old. The genesis of wildlife management in North America occurred during a time when populations of many wildlife species were low, their habitats were altered and degraded, and the human population was rapidly urbanizing. The focus of wildlife management was to restore wildlife populations and habitats. Once restored, wildlife managers strove to maintain populations at levels within biological carrying capacities (BCC) and provide benefits to a relatively narrow range of stakeholders. In recent years, cultural changes associated with a predominantly suburban society have led to conflicts with traditional wildlife management approaches and broadened the stakeholder base. Wildlife managers have had to consider the interests of a wider stakeholder base that supports a diversity of often conflicting expectations, while relying on traditional funding sources. For certain species, management for WSAC has taken priority over management for BCC. This scenario is particularly focused in the northeast United States where human population densities are some of the highest in the nation. We explore the current state of our knowledge of WSAC for certain species in the east, and review the tools being used for monitoring and assessment. We discuss adequacy of these approaches and offer suggestions for incorporating WSAC into wildlife management planning and operations. We consider the implications of WSAC to the future of wildlife management in North America.

Mesocarnivores play important ecological roles and are valued by diverse stakeholders. These species are often the focus of conservation efforts or are managed for sustainable harvest. Management actions require accurate population monitoring, but such monitoring is challenging because mesocarnivores are elusive and persist at low densities. We addressed this challenge by evaluating 2 monitoring methods (scent stations and motion-sensitive cameras) using multi-method modeling.We estimated occurrence probabilities and habitat relationships for 8 mesocarnivore species by fitting occupancy models to data collected at 75 sites from October to December 2021 across a 3,200-km 2 system in New Hampshire, USA. We assessed the relative estimated precision of the methodological approaches and their costs. We also evaluated tradeoffs in occurrence estimation and uncertainty among study designs by analyzing simulations run across various numbers of study sites and 2 study durations. Cameras cost roughly 10 times more than scent stations but strongly outperformed them in terms of species' detectability and parameter estimate precision. Multi-method models yielded the most precise estimates of occurrence probability and habitat relationships. Parameter estimates were on average twice as precise for camera and multi-method models compared to scent stations. Additionally, the estimated precision and direction (positive or negative) of habitat relationships varied with the method employed. Longer camera deployments, additional study sites, and multi-method approaches nearly always reduced uncertainty, but these