Selection of den sites and chronology of denning by black bears in the eastern Sierra Nevada and western Great Basin

Use of dens during winter is an important strategy for American black bears (Ursus americanus) for both energy conservation and reproduction; and occupancy of suitable den sites has implications for reproductive fitness. Denning strategies may change as a result of changing climatic conditions and habitat loss. Black bears occupy arid environments in the eastern Sierra Nevada and the western ranges of the Great Basin Ecosystem. Our objectives were to identify: (1) which physical characteristics of habitat influenced selection of den sites at multiple spatial scales and (2) which environmental factors influenced timing of entrance and exit of dens by females and males. We evaluated selection of den sites by black bears at three spatial scales (300, 1000, and 4000 m) from 2011 to 2022. Terrain ruggedness was important for selection of den sites at all spatial scales. Within a 300-m buffer from the den, bears selected den sites with rugged terrain, lower horizontal visibility, and greater canopy cover, resulting in more concealment and protection than that of the surrounding environment. Within 1000- and 4000-m buffers around each den, bears selected den sites with rugged terrain, northern aspects, and steep slopes. At the 4000-m scale, we observed interactions between sex with slope and distance to roads; females selected den sites on steeper slopes and closer to roads than did males. Females remained in the dens longer than males by entering earlier in the autumn and exiting later in the spring. Male bears exited their dens earlier with increasing consecutive days above freezing temperatures, but that relationship was weak for females. Knowing what characteristics are important for selection of den sites, and influence timing of denning, will be important for understanding how shifting climatic patterns will affect bears, particularly in arid environments that may be prone to wider fluctuations in climatic drivers of denning in the future.

Sampling methodology influences habitat suitability modeling for chiropteran species

Technological advances increase opportunities for novel wildlife survey methods. With increased detection methods, many organizations and agencies are creating habitat suitability models (HSMs) to identify critical habitats and prioritize conservation measures. However, multiple occurrence data types are used independently to create these HSMs with little understanding of how biases inherent to those data might impact HSM efficacy. We sought to understand how different data types can influence HSMs using three bat species (Lasiurus borealis, Lasiurus cinereus, and Perimyotis subflavus). We compared the overlap of models created from passive-only (acoustics), active-only (mist-netting and wind turbine mortalities), and combined occurrences to identify the effect of multiple data types and detection bias. For each species, the active-only models had the highest discriminatory ability to tell occurrence from background points and for two of the three species, active-only models preformed best at maximizing the discrimination between presence and absence values. By comparing the niche overlaps of HSMs between data types, we found a high amount of variation with no species having over 45% overlap between the models. Passive models showed more suitable habitat in agricultural lands, while active models showed higher suitability in forested land, reflecting sampling bias. Overall, our results emphasize the need to carefully consider the influences of detection and survey biases on modeling, especially when combining multiple data types or using single data types to inform management interventions. Biases from sampling, behavior at the time of detection, false positive rates, and species life history intertwine to create striking differences among models. The final model output should consider biases of each detection type, particularly when the goal is to inform management decisions, as one data type may support very different management strategies than another.

Mapping and modeling human-black bear interactions in the Catskills region of New York using resource selection probability functions

Black bears (Ursus americanus) are an iconic and common species throughout much of the United States and people regularly interact with these large predators without conflict. However, negative interactions between people and bears can manifest in conflicts that can hinder conservation efforts. Black bears are highly attracted to anthropogenic sources of food, and negative interactions with people are primarily a product of trash mismanagement. In the Catskills region of New York State, home to a large population of black bears, over 400 such conflicts are reported each year. While the New York Department of Environmental Conservation (DEC) has seen progress recently in educating residents of the region on how to reduce unwanted interactions with bears, they have had less success educating the 12 million tourists that visit the Catskills each year. Understanding where conflict may occur in the future, and the environmental and anthropogenic factors that precede it, may help guide management strategies to reduce these unwanted interactions. Therefore, we designed resource selection probability functions (RSPFs) to examine the relationship between human-black bear conflicts in the Catskills with a suite of landscape and anthropogenic data, using conflicts reported to the DEC across the state of New York in 2018-2019. We found that human-black bear conflicts were more likely to occur in the residential areas of the Catskills on the urban-wildland interface; areas with relatively higher human population densities, away from dense forest, and further from heavily urbanized areas. While future work is needed to continuously validate our model predictions, our results will provide the DEC and other conservation managers in the Catskills the ability to create more targeted plans for mitigating unwanted human-black bear interactions, and provide a better understanding of the mechanisms driving human-carnivore interactions at an urban-wildland interface more generally.