Spatial variation in density of American black bears in northern Yellowstone National Park

The quality and availability of resources are known to influence spatial patterns of animal density. In Yellowstone National Park, relationships between the availability of resources and the distribution of grizzly bears (Ursus arctos) have been explored but have yet to be examined in American black bears (Ursus americanus). We conducted non-invasive genetic sampling during 2017–2018 (mid-May to mid-July) and applied spatially explicit capture-recapture models to estimate density of black bears and examine associations with landscape features. In both years, density estimates were higher in forested vegetation communities, which provide food resources and thermal and security cover preferred by black bears, compared with non-forested areas. In 2017, density also varied by sex, with female densities being higher than males. Based on our estimates, the northern range of Yellowstone National Park supports one of the highest densities of black bears (20 black bears/100 km²) in the northern Rocky Mountains (6–12 black bears/100 km² in other regions). Given these high densities, black bears could influence other wildlife populations more than previously thought, such as through displacement of sympatric predators from kills. Our study provides the first spatially explicit estimates of density for black bears within an ecosystem that contains the majority of North America's large mammal species. Our density estimates provide a baseline that can be used for future research and management decisions of black bears, including efforts to reduce human–bear conflicts.     

Factors associated with black bear density and implications for management

Wildlife density estimates are important to accurately formulate population management objectives and understand the relationship between habitat characteristics and a species’ abundance. Despite advances in density and abundance estimation methods, management of common game species continues to be challenged by a lack of reliable population estimates. In Washington, USA, statewide American black bear (Ursus americanus) abundance estimates are predicated on density estimates derived from research in the 1970s and are hypothesized to be a function of precipitation and vegetation, with higher densities in western Washington. To evaluate current black bear density and landscape relationships in Washington, we conducted a 4-year capture-recapture study in 2 areas of the North Cascade Mountains using 2 detection methods, non-invasive DNA collection and physical capture and deployment of global positioning system (GPS) collars. We integrated GPS telemetry from collared bears with spatial capture-recapture (SCR) data and created a SCR-resource selection model to estimate density as a function of spatial covariates and test the hypothesis that density is higher in areas with greater vegetative food resources. We captured and collared 118 bears 132 times and collected 7,863 hair samples at hair traps where we identified 537 bears from 1,237 detections via DNA. The most-supported model in the western North Cascades depicted a negative relationship between black bear density and an index of human development. We estimated bear density at 20.1 bears/100 km², but density varied from 13.5/100 km² to 27.8 bears/100 km² depending on degree of human development. The model best supported by the data in the eastern North Cascades estimated an average density of 19.2 bears/100 km², which was positively correlated with primary productivity, with resulting density estimates ranging from 7.1/100 km² to 33.6 bears/100 km². The hypothesis that greater precipitation and associated vegetative production in western Washington supports greater bear density compared to eastern Washington was not supported by our data. In western Washington, empirically derived average density estimates (including cubs) were nearly 50% lower than managers expected prior to our research. In eastern Washington average black bear density was predominantly as expected, but localized areas of high primary productivity supported greater than anticipated bear densities. Our findings underscore the importance that black bear density is not likely uniform and management risk may be increased if an average density is applied at too large a scale. Disparities between expected and empirically derived bear density illustrate the need for more rigorous monitoring to understand processes that affect population numbers throughout the jurisdiction, and suggest that management plans may need to be reevaluated to determine if current harvest strategies are achieving population objectives. © 2019 The Wildlife Society.     

Comparing clustered sampling designs for spatially explicit estimation of population density

Spatially explicit capture–recapture methods do not assume that animals have equal access to sampling devices (e.g., detectors), which allows for gaps in the sampling extent and nonuniform (e.g., clustered) sampling designs. However, the performance (i.e., relative root mean squared error [RRMSE], confidence interval coverage, relative bias and relative standard error) of clustered detector arrays has not been thoroughly evaluated. I used simulations to evaluate the performance of various detector and cluster spacings, cluster configurations (i.e., number of detectors arranged in a square grid), sampling extents and number of sampling occasions for estimating population density, the relationship between detection rate and distance to a detector from the animal's center of activity (σ) and base detection rates, using American black bears (Ursus americanus) as a case study. My simulations indicated that a wide range of detector configurations can provide reliable estimates if spacing between detectors in clusters is ≥1σ and ≤3σ. A number of cluster configurations and occasion lengths produced estimates that were unbiased, resulted in good spatial coverage, and were relatively precise. Moreover, increasing the duration of sampling, establishing large study areas, increasing detection rates and spacing clusters so that cross-cluster sampling of individuals can occur could help ameliorate deficiencies in the detector layout. These results have application for a wide array of species and sampling methods (e.g., DNA sampling, camera trapping, mark-resight and search-encounter) and suggest that clustered sampling can significantly reduce the effort necessary to provide reliable estimates of population density across large spatial extents that previously would have been infeasible with nonclustered sampling designs.     

Density and genetic structure of black bears in coastal South Carolina

The frequency of black bear (Ursus americanus) sightings, vehicle collisions, and nuisance incidents in the coastal region of South Carolina has increased over the past 4 decades. To develop the statewide Black Bear Management and Conservation Strategy, the South Carolina Department of Natural Resources needed reliable information for the coastal population. Because no such data were available, we initiated a study to determine population density and genetic structure of black bears. We selected 2 study areas that were representative of the major habitat types in the study region: Lewis Ocean Bay consisted primarily of Carolina Bays and pocosin habitats, whereas Carvers Bay was representative of extensive pine plantations commonly found in the region. We established hair snares on both study areas to obtain DNA from hair samples during 8 weekly sampling periods in 2008 and again in 2009. We used genotypes to obtain capture histories of sampled bears. We estimated density using spatially explicit capture–recapture (SECR) models and used information-theoretic procedures to fit parameters for capture heterogeneity and behavioral responses and to test if density and model parameters varied by year. Model-averaged density was 0.046 bears/km² (SE = 0.011) for Carvers Bay and 0.339 bears/km² (SE = 0.056) for Lewis Ocean Bay. Next, we sampled habitat covariates for all locations in the SECR sampling grid to derive spatially explicit estimates of density based on habitat characteristics. Addition of habitat covariates had substantial support, and accounted for differences in density between Carvers Bay and Lewis Ocean Bay; black bear density showed a negative association with the area of pine forests (4.5-km² scale) and a marginal, positive association with the area of pocosin habitat (0.3-km² scale). Bear density was not associated with pine forest at a smaller scale (0.3-km²), nor with major road density or an index of largest patch size. Predicted bear densities were low throughout the coastal region and only a few larger areas had high predicted densities, most of which were centered on public lands (e.g., Francis Marion National Forest, Lewis Ocean Bay). We sampled a third bear population in the Green Swamp area of North Carolina for genetic structure analyses and found no evidence of historic fragmentation among the 3 sampled populations. Neither did we find evidence of more recent barriers to gene exchange; with the exception of 1 recent migrant, Bayesian population assignment techniques identified only a single population cluster that incorporated all 3 sampled areas. Bears in the region may best be managed as 1 population. If the goal is to maintain or increase bear densities, demographic connectivity of high-density areas within the low-density landscape matrix is a key consideration and managers would need to mitigate potential impacts of planned highway expansions and anticipated development. Because the distribution of black bears in coastal South Carolina is not fully known, the regional map of potential black bear density can be used to identify focal areas for management and sites that should be surveyed for occupancy or where more intensive studies are needed. © 2012 The Wildlife Society.     

Genetic mark–recapture population estimation in black bears and issues of scale

Abundance estimates for black bears (Ursus americanus) are important for effective management. Recently, DNA technology has resulted in widespread use of noninvasive, genetic capture–mark–recapture (CMR) approaches to estimate populations. Few studies have compared the genetic CMR methods to other estimation methods. We used genetic CMR to estimate the bear population at 2 study sites in northern New Hampshire (Pittsburg and Milan) in 2 consecutive years. We compared these estimates to those derived from traditional methods used by the New Hampshire Fish and Game Department (NHFG) using hunter harvest and mortality data. Density estimates produced with genetic CMR methods were similar both years and were comparable to those derived from traditional methods. In 2006, the estimated number of bears in Pittsburg was 79 (95% CI = 60–98) corresponding to a density of 15–24 (95% CI) bears/100 km²; the 2007 estimate was 83 (95% CI = 67–99; density = 16–24 bears/100 km²). In 2006, the estimated number of bears in Milan was 95 (95% CI = 74–117; density = 16–25 bears/100 km²); the 2007 estimate was 96 (95% CI = 77–114; density = 17–25 bears/100 km²). We found that genetic CMR methods were able to identify demographic variation at a local scale, including a strongly skewed sex ratio (2 M:1 F) in the Milan population. Genetic CMR is a useful tool for wildlife managers to monitor populations of local concern, where abundance or demographic characteristics may deviate from regional estimates. Future monitoring of the Milan population with genetic CMR is recommended to determine if the sex ratio bias continues, possibly warranting a change in local harvest regimes. © 2011 The Wildlife Society.     

Dietary adjustability of grizzly bears and American black bears in Yellowstone National Park

Grizzly bears (Ursus arctos) and American black bears (U. americanus) are sympatric in much of Yellowstone National Park. Three primary bear foods, cutthroat trout (Oncorhynchus clarki), whitebark pine (Pinus albicaulis) nuts, and elk (Cervus elaphus), have declined in recent years. Because park managers and the public are concerned about the impact created by reductions in these foods, we quantified bear diets to determine how bears living near Yellowstone Lake are adjusting. We estimated diets using: 1) stable isotope and mercury analyses of hair samples collected from captured bears and from hair collection sites established along cutthroat trout spawning streams and 2) visits to recent locations occupied by bears wearing Global Positioning System collars to identify signs of feeding behavior and to collect scats for macroscopic identification of residues. Approximately 45 ± 22% ( ± SD) of the assimilated nitrogen consumed by male grizzly bears, 38 ± 20% by female grizzly bears, and 23 ± 7% by male and female black bears came from animal matter. These assimilated dietary proportions for female grizzly bears were the same as 10 years earlier in the Lake area and 30 years earlier in the Greater Yellowstone Ecosystem. However, the proportion of meat in the assimilated diet of male grizzly bears decreased over both time frames. The estimated biomass of cutthroat trout consumed by grizzly bears and black bears declined 70% and 95%, respectively, in the decade between 1997–2000 and 2007–2009. Grizzly bears killed an elk calf every 4.3 ± 2.7 days and black bears every 8.0 ± 4.0 days during June. Elk accounted for 84% of all ungulates consumed by both bear species. Whitebark pine nuts continue to be a primary food source for both grizzly bears and black bears when abundant, but are replaced by false-truffles (Rhizopogon spp.) in the diets of female grizzly bears and black bears when nut crops are minimal. Thus, both grizzly bears and black bears continue to adjust to changing resources, with larger grizzly bears continuing to occupy a more carnivorous niche than the smaller, more herbivorous black bear. © 2012 The Wildlife Society.     

Estimates of Abundance and Harvest Rates of Female Black Bears Across a Large Spatial Extent

American black bears (Ursus americanus) are an iconic wildlife species in the southern Appalachian highlands of the eastern United States and have increased in number and range since the early 1980s. Given an increasing number of human-bear conflicts in the region, many management agencies have liberalized harvest regulations to reduce bear populations to socially acceptable levels. Wildlife managers need reliable population data for assessing the effects of management actions for this high-profile species. Our goal was to use DNA extracted from hair collected at barbed-wire enclosures (i.e., hair traps) to identify individual bears and then use spatially explicit capture-recapture methods to estimate female black bear density, abundance, and harvest rate. We established 888 hair traps across 66,678 km² of the southern Appalachian highlands in Georgia, North Carolina, South Carolina, and Tennessee, USA, in 2017 and 2018, arranged in 174 clusters of 2–9 traps/cluster. We collected 9,113 hair samples from those sites over 6 weeks of sampling, of which 1,954 were successfully genotyped to 462 individual female bears. Our spatially explicit estimator included a percent forest covariate to explain inhomogeneous bear density across the region. Densities ranged up to 0.410 female bears/km² and regional abundance was 5,950 (95% CI = 4,988–7,098) female bears. Based on hunter kill data from 2016 to 2018, mean annual harvest rates for females were 12.7% in Georgia, 17.6% in North Carolina, 17.6% in South Carolina, and 22.8% in Tennessee. Our estimated harvest rates for most states approached or exceeded theoretical maximum sustainable levels, and population trend data (i.e., bait-station indices) indicated decreasing growth rates since about 2009. These data suggest that the increased harvest goals and poor hard mast production over a series of prior years reduced bear population abundance in many states. We were able to obtain reasonable population abundance and density estimates because of spatially explicit capture-recapture methods, cluster sampling, and a large spatial extent. Continued monitoring of bear populations (e.g., annual bait-station surveys and periodic population estimation using spatially explicit methods) by state jurisdictions would help to ensure that population trajectories are consistent with management goals. © 2021 The Wildlife Society.     

Sex-biased natal dispersal and inbreeding avoidance in American black bears as revealed by spatial genetic analyses

We tested the hypothesis that sex-biased natal dispersal reduces close inbreeding in American black bears, a solitary species that exhibits nearly complete male dispersal and female philopatry. Using microsatellite DNA and spatial data from reproductively mature bears (>or= 4 years old), we examined the spatial genetic structure of two distinct populations in New Mexico from 1993 to 2000. As predicted, relatedness (r) and the frequency of close relationships (parent-offspring or full siblings) decreased with distance among female dyads, but little change was observed among male or opposite-sex dyads. Neighbouring females were more closely related than neighbouring males. The potential for inbreeding was low. Most opposite-sex pairs that lived sufficiently close to facilitate mating were unrelated, and few were close relatives. We found no evidence that bears actively avoided inbreeding in their selection of mates from this nearby pool, as mean r and relationship frequencies did not differ between potential and actual mating pairs (determined by parentage analysis). These basic patterns were apparent in both study areas despite a nearly two-fold difference in density. However, the sex bias in dispersal was less pronounced in the lower-density area, based on proportions of bears with male and female relatives residing nearby. This result suggests that male bears may respond to reduced competition by decreasing their rate or distance of dispersal. Evidence supports the hypothesis that inbreeding avoidance is achieved by means of male-biased dispersal but also indicates that competition (for mates or resources) modifies dispersal patterns.     

Integrating video and genetic data to estimate annual age-structured apparent survival of American black bears

Camera or genetic data are increasingly used to estimate wildlife abundance and density. We integrated video camera data with genetic data over 7 years to estimate annual age-structured apparent survival of American black bears (Ursus americanus). We identified 70 individuals through meticulous scrutiny of 7531 video captures, cross-referenced with 721 genetic captures from hair samples concurrently collected from stations in view of cameras. We used the Cormack–Jolly–Seber model in Program Mark to estimate annual age-structured apparent survival for yearling males, yearling females, 2+ year-old males, and 2+ year-old females. We manually calculated cub survival. We compared parameter estimates based on combined video and genetic data with those based on only genetic data. Combining video and genetic data provided a means to test video-based identification accuracy, which was highest for females (97%–100%). Annual apparent survival was highest for yearling females (φ = 0.92, SE = 0.07), followed by 2+ year-old females (φ = 0.88, SE = 0.05), 2+ year-old males (φ = 0.84, SE = 0.06), and yearling males (φ = 0.80, SE = 0.14). Annual cub survival (φ = 0.86, SE = 0.07) was likely biased because we could not account for mortality that occurred in-den through early spring. Annual apparent survival and recapture probabilities derived from only genetic data were lower than those derived from combined video and genetic data. Our finding that noninvasive data can be used to estimate annual age-structured apparent survival of a species with relatively indistinct traits is broadly relevant to wildlife research and conservation.     

Learning to live with black bears: A psychological model of acceptance

The reappearance and recovery of large carnivores in human-dominated landscapes creates a need to understand how people will respond to the presence of these animals. We tested a psychological model of acceptance to determine what variables most influence people's acceptance for black bears (Ursus americanus) in an area with an emerging black bear population (Ohio, USA). We hypothesized that people's perceptions of risk and benefit related to bears would mediate the effect of trust (in wildlife management agencies) and personal control (over interactions with and management of wildlife) on acceptance for black bears. We used a mail-back survey of Ohio residents (n = 9,400; adjusted response rate = 35%) to assess the variables of interest and test the hypothesized model. Based on multiple criteria of model fit, the hypothesized model fit the data acceptably well. The model explained approximately 62% of the variance in acceptance, and perception of risk associated with black bears had the largest impact on the level of acceptance. As large carnivore populations expand and interactions with humans increase, our results will aid managers in designing outreach materials and communications aimed at promoting acceptance for large carnivores. Our model suggests that interventions raising an individual's social trust in the managing agency, or personal control can indirectly raise stakeholders' acceptance by reducing risk perception and increasing perception of benefit from carnivores. © 2012 The Wildlife Society.     

Building tolerance for bears: A communications experiment

The present study examined the feasibility of experimentally manipulating perceptions of benefit and control via communications to increase public acceptance of bears. We assigned subjects to either a pseudo-control (basic bear biology message) or 1 of 3 treatments adding a benefits message, a perceived control message, or combining messages about both benefits and perceived control. Within-subjects pre–post t-tests showed a significant increase in acceptance among those in the benefits and combined treatments. A between-subjects 1-way analysis of variance (ANOVA) showed a significant difference between the perceived control and combined treatments (where the perceived control message actually decreased acceptance). Our results highlight the importance of including information about benefits stemming from the presence of black bears, as adding this information tended to increase stakeholder acceptance of black bear populations. © 2013 The Wildlife Society.     

A harvest framework for a recovering American black bear population

Having reproducible and transparent science-based processes in wildlife management ensures the integrity of decision making. These processes are particularly important when establishing harvest frameworks, as guiding information in the peer-reviewed literature is limited. We provide an example using multiple data sets, whose products guided aspects of the development of a harvest framework for a population of recolonizing American black bears (Ursus americanus) in Missouri, USA. To characterize the spatial distribution of harvest, we used 10 years (2010–2019) of black bear global positioning system (GPS) location data and 30 years (1991–2020) of sightings data to assess spatial vulnerability to harvest as the intersection among information on bear occurrence, bear sightings, and hunter land-use tendencies (i.e., the avoidance of steep slopes, large distances from roads). We then used the spatial vulnerability assessment, information on the distribution of public and private lands, and easily discernable boundaries (i.e., major highways, rivers) to suggest boundaries for bear management zones. Additionally, to identify the timing of harvest that would limit female harvest bias, we assessed the temporal vulnerability of harvest using sex-based changes in average daily step lengths and monthly utilization distribution sizes during fall. Black bear occurrence and sighting propensity was greater in southwestern Missouri, and potential hunter land use appeared pervasive across the landscape given the lack of landscape features that would disincentivize use. Given the influence of black bear occurrence and sighting propensity, spatial harvest vulnerability diminished from southern and southeastern to central portions of Missouri, with areas north of the Missouri River not a part of the established black bear range. We consequently divided areas south of the Missouri River into 3 black bear management zones: a small southwestern zone with primarily private lands and high harvest vulnerability, a southeastern zone that encompassed considerable public lands and moderate amounts of vulnerability, and a central zone that was composed mainly of areas of low vulnerability. Temporally, males did not exhibit movement-based changes, but females became less active after the first week of October and used 63.9% less area through fall. Based on movements rates of males and females, a hunting season after the first week of October could reduce the likelihood of females being harvested. Harvests from the black bear harvest season in 2021 suggest that the proportion of bears harvested in each zone was similar in distribution to the proportion of permits allocated across zones with no harvest sex bias, which was aligned with agency goals. Animal movement and space use data products can guide harvest framework decision-making.     

Combining data from 43 standardized surveys to estimate densities of female American black bears by spatially explicit capture–recapture

Spatially explicit capture–recapture (SECR) models are gaining popularity for estimating densities of mammalian carnivores. They use spatially explicit encounter histories of individual animals to estimate a detection probability function described by two parameters: magnitude (g ₀), and spatial scale (σ). Carnivores exhibit heterogeneous detection probabilities and home range sizes, and exist at low densities, so g ₀ and σ likely vary, but field surveys often yield inadequate data to detect and model the variation. We sampled American black bears (Ursus americanus) on 43 study areas in ON, Canada, 2006–2009. We detected 713 animals 1810 times; however, study area-specific samples were sometimes small (6–34 individuals detected 13–93 times). We compared AIC _c values from SECR models fit to the complete data set to evaluate support for various forms of variation in g ₀ and σ, and to identify a parsimonious model for aggregating data among study areas to estimate detection parameters more precisely. Models that aggregated data within broad habitat classes and years were supported over those with study area-specific g ₀ and σ (ΔAIC _c  ≥ 30), and precision was enhanced. Several other forms of variation in g ₀ and σ, including individual heterogeneity, were also supported and affected density estimates. If study design cannot eliminate detection heterogeneity, it should ensure that samples are sufficient to detect and model it. Where this is not feasible, combing sparse data across multiple surveys could allow for improved inference.     

Spatial genetic structure and landscape connectivity in black bears: Investigating the significance of using different land cover datasets and classifications in landscape genetics analyses

Landscape genetic analyses allow detection of fine‐scale spatial genetic structure (SGS) and quantification of effects of landscape features on gene flow and connectivity. Typically, analyses require generation of resistance surfaces. These surfaces characteristically take the form of a grid with cells that are coded to represent the degree to which landscape or environmental features promote or inhibit animal movement. How accurately resistance surfaces predict association between the landscape and movement is determined in large part by (a) the landscape features used, (b) the resistance values assigned to features, and (c) how accurately resistance surfaces represent landscape permeability. Our objective was to evaluate the performance of resistance surfaces generated using two publicly available land cover datasets that varied in how accurately they represent the actual landscape. We genotyped 365 individuals from a large black bear population (Ursus americanus) in the Northern Lower Peninsula (NLP) of Michigan, USA at 12 microsatellite loci, and evaluated the relationship between gene flow and landscape features using two different land cover datasets. We investigated the relative importance of land cover classification and accuracy on landscape resistance model performance. We detected local spatial genetic structure in Michigan''s NLP black bears and found roads and land cover were significantly correlated with genetic distance. We observed similarities in model performance when different land cover datasets were used despite 21% dissimilarity in classification between the two land cover datasets. However, we did find the performance of land cover models to predict genetic distance was dependent on the way the land cover was defined. Models in which land cover was finely defined (i.e., eight land cover classes) outperformed models where land cover was defined more coarsely (i.e., habitat/non‐habitat or forest/non‐forest). Our results show that landscape genetic researchers should carefully consider how land cover classification changes inference in landscape genetic studies.