Using habitat suitability and landscape connectivity in the spatial prioritization of public outreach and management during carnivore recolonization

Factors influencing frequency and severity of human-American black bear conflicts in New York, USA

Free-ranging large carnivores are involved in human-wildlife conflicts which can result in economic costs. Understanding factors that lead to human-wildlife conflicts is important to mitigate these negative effects and facilitate human-carnivore coexistence. We used a human-American black bear (Ursus americanus) conflict database maintained by the New York State Department of Environmental Conservation to determine whether drought, conflicts within the Adirondack and Catskill Parks as compared to outside of these parks, mild severity (Class 3) conflicts early in the year (April-June), and bear harvest in the previous year (as an index of bear abundance), were associated with greater frequency of high or moderate severity (Class 1-2) conflicts later in the year (July-September) across New York, USA. During 2006-2019, we obtained 3,782 mild severity conflict records early in the year, and 1,042 high or moderate severity records later in the year. We found that a one standard deviation increase in the cumulative precipitation difference from mean early in the year (about 7.59 cm) coincided with a 20% decrease in conflicts, and that Wildlife Management Units (WMUs) within the parks were predicted to have 5.61 times as many high or moderate severity conflicts as WMUs outside the parks. We also found that a one standard deviation increase in the frequency of mild severity conflicts (equivalent to 5.68 conflicts) early in the year coincided with an increase in the frequency of high or moderate severity conflicts in a WMU later in the year by 49%, while a one standard deviation increase in the bear abundance index in the previous year (0.14 bears/10 km2) coincided with a 23% increase in high or moderate severity conflicts. To reduce the frequency and severity of conflicts to facilitate human-black bear coexistence, we recommend the following measures to be taken in place consistently and build over time in local communities: (i) further reducing black bear access to anthropogenic foods and other attractants, (ii) non-lethal measures including bear-resistant waste management, (iii) electric fencing, and (iv) modifying placement or configuration of field crops.

Assessing the spatial-temporal patterns of conflicts between humans and Asiatic black bears (Ursus thibetanus) around the Gaoligongshan Nature Reserve, China

Conflicts between humans and Asiatic black bears (Ursus thibetanus) are widespread in Asia and pose challenges to human-bear coexistence. Identifying effective mitigation measures requires a thorough understanding of human-bear conflicts (HBC). We assessed spatial-temporal patterns of HBC and their impact factors around the Baoshan Section of the Gaoligongshan Nature Reserve (GNNR) between 2012 and 2020. The results suggested that crop raiding by bears occurred most commonly, followed by beehive loss, livestock depredation, and human casualties. HBC hotspots occurred near the protected area where local people frequently encountered bears. The landscapes with lower elevation and human density were at higher risk of HBC. Furthermore, villages with more fragmented forests or less fragmented croplands were more vulnerable to HBC. The differences in agricultural structures contributed to the diverse composition of HBC between the two regions. In addition, crop raiding by bears decreased significantly, probably due to the changing landscape composition and configuration derived from human behaviors, yet livestock depredation and beehive loss increased. Our findings indicated the complex interrelationship between the environment, bears, and humans, which could guide the implementation of mitigation measures. We recommend multiple approaches based on a social-ecological system to mitigate HBC.

Distribution model transferability for a wide-ranging species, the Gray Wolf

Using existing data can be a reliable and cost-effective way to predict species distributions, and particularly useful for recovering or expanding species. We developed a current gray wolf (Canis lupus) distribution model for the western Great Lakes region, USA, and evaluated the spatial transferability of single-state models to the region. This study is the first assessment of transferability in a wide-ranging carnivore, as well as one of few developed for large spatial extents. We collected 3500 wolf locations from winter surveys in Minnesota (2017–2019), Wisconsin (2019–2020), and Michigan (2017–2020). We included 10 variables: proportion of natural cover, pastures, and crops; distance to natural cover, agriculture, developed land, and water; major and minor road density; and snowfall (1-km res.). We created a regional ensemble distribution by weight-averaging eight models based on their performance. We also developed single-state models, and estimated spatial transferability using two approaches: state cross-validation and extrapolation. We assessed performance by quantifying correlations, receiver operating characteristic curves (ROC), sensitivities, and two niche similarity indices. The regional area estimated to be most suitable for wolves during winter (threshold = maximum sensitivity/specificity) was 106,465 km² (MN = 48,083 km², WI = 27,757 km², MI = 30,625 km²) and correctly predicted 88% of wolf locations analyzed. Increasing natural cover and distance to crops were consistently important for determining regional and single-state wolf distribution. Extrapolation (vs. cross-validation) produced results with the greatest performance metrics, and were most similar to the regional model, yet good internal performance was unrelated to greater extrapolation performance. Factors influencing species distributions are scale-dependent and can vary across areas due to behavioral plasticity. When extending inferences beyond the current occurrence of individuals, assessing variation in ecology such as habitat selection, as well as methodological factors including model performance, will be critical to avoid poor scientific interpretations and develop effective conservation applications. In particular, accurate distribution models for recovering or recovered carnivores can be used to develop plans for habitat management, quantify potential of unoccupied habitat, assess connectivity modeling, and mitigate conflict, facilitating long-term species persistence.