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.     

Estimating population size and density of a low-density population of black bears in Rocky Mountain National Park, Colorado

Rocky Mountain National Park (RMNP) is home to a low-density black bear (Ursus americanus) population that exists at >2,400?m with a very limited growing season. A previous study (1984–1991) found bear densities among the lowest reported (1.37–1.52 bears/100?km²). Because of concerns of viability of this small population, we assessed population size and density of black bears from 2003 to 2006 to determine the current status of RMNP’s bear population. We used three approaches to estimate population size and density: (1) minimum number known, (2) occupancy modeling, and (3) catch per unit effort (CPUE). We used information from capture and remote-triggered cameras, as well as visitor information, to derive a minimum known population estimate of 20–24 individuals and a median density estimate of 1.35 bears/100?km². Bear occupancy was estimated at 0.46 (SE?=?0.11), with occupancy positively influenced by lodgepole pine stands, non-vegetated areas, and patch density but negatively influenced by mixed conifer stands. We combined the occupancy estimate with mean home-range size and overlap for bears in RMNP to derive a density estimate of 1.44 bears/100?km². We also related CPUE to density estimates for eight low-density black bear populations to estimate density in RMNP; this estimate (1.03 bears/100?km²) was comparable to the occupancy estimate and suggests that this approach may be useful for future population monitoring. The use of corroborative techniques for assessing population size of a low-density black bear population was effective and should be considered for similar low-density wildlife populations.     

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.     

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.     

Predator densities and white-tailed deer fawn survival

Predation is the dominant source of mortality for white-tailed deer (Odocoileus virginianus) <6 months old throughout North America. Yet, few white-tailed deer fawn survival studies have occurred in areas with 4 predator species or have considered concurrent densities of deer and predator species. We monitored survival and cause-specific mortality from birth to 6 months for 100 neonatal fawns during 2013–2015 in the Upper Peninsula of Michigan, USA, while simultaneously estimating population densities of deer, American black bear (Ursus americanus), coyote (Canis latrans), bobcat (Lynx rufus), and gray wolf (Canis lupus). We estimated fawn predation risk in response to sex, birth mass, and date of birth. Six-month fawn survival pooled among years was 36%, and fawn mortality risk was not related to birth mass, date of birth, or sex. Estimated mean annual deer and predator densities were 334 fawns/100 km², 25.9 black bear/100 km², 23.8 coyotes/100 km², 3.8 bobcat/100 km², and 2.8 wolves/100 km². Despite lower estimated per-individual kill rates, coyotes and black bears were the leading sources of fawn mortality because they had greater densities relative to bobcats and wolves. Our results indicate that the presence of more predator species in a system is not entirely additive in its effect on fawn survival. © The Wildlife Society, 2019     

Integrating sign surveys and telemetry data for estimating brown bear (Ursus arctos) density in the Romanian Carpathians

Accurate population size estimates are important information for sustainable wildlife management. The Romanian Carpathians harbor the largest brown bear (Ursus arctos) population in Europe, yet current management relies on estimates of density that lack statistical oversight and ignore uncertainty deriving from track surveys. In this study, we investigate an alternative approach to estimate brown bear density using sign surveys along transects within a novel integration of occupancy models and home range methods. We performed repeated surveys along 2‐km segments of forest roads during three distinct seasons: spring 2011, fall‐winter 2011, and spring 2012, within three game management units and a Natura 2000 site. We estimated bears abundances along transects using the number of unique tracks observed per survey occasion via N‐mixture hierarchical models, which account for imperfect detection. To obtain brown bear densities, we combined these abundances with the effective sampling area of the transects, that is, estimated as a function of the median (± bootstrapped SE) of the core home range (5.58 ± 1.08 km²) based on telemetry data from 17 bears tracked for 1‐month periods overlapping our surveys windows. Our analyses yielded average brown bear densities (and 95% confidence intervals) for the three seasons of: 11.5 (7.8–15.3), 11.3 (7.4–15.2), and 12.4 (8.6–16.3) individuals/100 km². Across game management units, mean densities ranged between 7.5 and 14.8 individuals/100 km². Our method incorporates multiple sources of uncertainty (e.g., effective sampling area, imperfect detection) to estimate brown bear density, but the inference fundamentally relies on unmarked individuals only. While useful as a temporary approach to monitor brown bears, we urge implementing DNA capture–recapture methods regionally to inform brown bear management and recommend increasing resources for GPS collars to improve estimates of effective sampling area.     

Noninvasive Estimation of Black Bear Abundance Incorporating Genotyping Errors and Harvested Bear

ABSTRACT Estimating black bear (Ursus americanus) population size is a difficult but important requirement when justifying harvest quotas and managing populations. Advancements in genetic techniques provide a means to identify individual bears using DNA contained in tissue and hair samples, thereby permitting estimates of population abundance based on established mark-capture-recapture methodology. We expand on previous noninvasive population-estimation work by geographically extending sampling areas (36,848 km²) to include the entire Northern Lower Peninsula (NLP) of Michigan, USA. We selected sampling locations randomly within biologically relevant bear habitat and used barbed wire hair snares to collect hair samples. Unlike previous noninvasive studies, we used tissue samples from harvested bears as an additional sampling occasion to increase recapture probabilities. We developed subsampling protocols to account for both spatial and temporal variance in sample distribution and variation in sample quality using recently published quality control protocols using 5 microsatellite loci. We quantified genotyping errors using samples from harvested bears and estimated abundance using statistical models that accounted for genotyping error. We estimated the population of yearling and adult black bears in the NLP to be 1,882 bears (95% CI = 1,389-2,551 bears). The derived population estimate with a 15% coefficient of variation was used by wildlife managers to examine the sustainability of harvest over a large geographic area.     

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.     

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.     

Unraveling the mystery of the glacier bear: Genetic population structure of black bears (Ursus americanus) within the range of a rare pelage type

Glacier bears are a rare grey color morph of American black bear (Ursus americanus) found only in northern Southeast Alaska and a small portion of western Canada. We examine contemporary genetic population structure of black bears within the geographic extent of glacier bears and explore how this structure relates to pelage color and landscape features of a recently glaciated and highly fragmented landscape. We used existing radiocollar data to quantify black bear home‐range size within the geographic range of glacier bears. The mean home‐range size of female black bears in the study area was 13 km² (n = 11), whereas the home range of a single male was 86.9 km². We genotyped 284 bears using 21 microsatellites extracted from noninvasively collected hair as well as tissue samples from harvested bears. We found ten populations of black bears in the study area, including several new populations not previously identified, divided largely by geographic features such as glaciers and marine fjords. Glacier bears were assigned to four populations found on the north and east side of Lynn Canal and the north and west side of Glacier Bay with a curious absence in the nonglaciated peninsula between. Lack of genetic relatedness and geographic continuity between black bear populations containing glacier bears suggest a possible unsampled population or an association with ice fields. Further investigation is needed to determine the genetic basis and the adaptive and evolutionary significance of the glacier bear color morph to help focus black bear conservation management to maximize and preserve genetic diversity.     

Brown Bear Density and Estimated Harvest Rates in Northwestern Alaska

Human-caused mortality in general, and unregulated hunting in particular, have been implicated in reductions in brown bear (Ursus arctos) populations throughout much of their range. In northwestern Alaska, USA, bear densities have not been assessed in 20 years while harvest regulations have been liberalized, raising concerns that broad undetected population declines might occur. We used a modified mark-resight approach to estimate brown bear density during 2005–2018 in 4 subareas throughout the region. We also summarized harvest information for each subarea and used our survey results to estimate harvest rates. We estimated densities for independent bears assuming constant or heterogeneous probabilities of detection and occurrence. We present the results of the constant model for more direct comparison with past work and the heterogeneity model results to provide estimates of density that are less likely to be negatively biased. Using the constant model, we estimated the density of independent bears was 17.0, 49.2, 24.9, and 19.4/1,000 km² on portions of the Seward Peninsula, the lower Noatak River, the upper Noatak River, and Gates of the Arctic National Park and Preserve, respectively. These estimates are broadly similar to those from past work in interior and northwestern Alaska, with the exception of the lower Noatak River subarea where our estimates are the highest reported for a bear population in northern Alaska. We estimated that the harvest rate on the Seward Peninsula was approximately 5.2% or 7.7% on average, depending upon the model used. In the remaining areas, we estimated annual harvest rates were <2.5%, well within sustainability guidelines from past work. Overall, our results suggest that brown bear densities are similar or somewhat higher than in the past in much of northwestern Alaska and that current harvest rates are sustainable in most areas, except perhaps the Seward Peninsula. Ongoing survey work will be useful for further evaluating the assumptions of the modified mark-resight survey approach, assessing population trajectory, and determining the effect of harvest on brown bear populations. © 2021 The Wildlife Society.     

Grizzly Bear Density in Glacier National Park,Montana

Abstract: We present the first rigorous estimate of grizzly bear (Ursus arctos) population density and distribution in and around Glacier National Park (GNP), Montana, USA. We used genetic analysis to identify individual bears from hair samples collected via 2 concurrent sampling methods: 1) systematically distributed, baited, barbed-wire hair traps and 2) unbaited bear rub trees found along trails. We used Huggins closed mixture models in Program MARK to estimate total population size and developed a method to account for heterogeneity caused by unequal access to rub trees. We corrected our estimate for lack of geographic closure using a new method that utilizes information from radiocollared bears and the distribution of bears captured with DNA sampling. Adjusted for closure, the average number of grizzly bears in our study area was 240.7 (95% CI = 202–303) in 1998 and 240.6 (95% CI = 205–304) in 2000. Average grizzly bear density was 30 bears/1,000 km², with 2.4 times more bears detected per hair trap inside than outside GNP. We provide baseline information important for managing one of the few remaining populations of grizzlies in the contiguous United States.     

Population density of primates in a large fragment of the Brazilian Atlantic rainforest

We performed a line transect survey (352.4 km) of primates in the Serra de Paranapiacaba, at one of the largest relatively undisturbed fragments of the Atlantic rainforest of Southeastern Brazil (ca. 1400 km²), in August 1998. The brown capuchin, Cebus apella nigritus, was the most common species found in the area (20 groups, density estimate: 5.31 ± 2.05 individuals per km², mean ± SE). Nine groups of the brown howler monkey, Alouatta guariba clamitans, and eight of the woolly spider monkey, Brachyteles arachnoides arachnoides, were also recorded, with preliminary density estimates of 0.79 ± 0.40 and 2.33 ± 1.37 individuals per km², respectively. Density estimates for these species in other fragments of Atlantic rainforest are reviewed, showing that densities in Paranapiacaba are among the lowest reported. It is suggested that the higher densities reported for isolated populations in small forest patches (<50 km²) is related to the absence of main primate predators, the density compensation phenomenon and the ecological plasticity of some primate species. In contrast, local extinction in many small patches is probably related to hunting pressure. Given the important primate populations found in the Paranapiacaba fragment, conservation strategies for the studied species should give priority to effective protection of the largest remnant fragments from illegal hunting and deforestation, rather than translocation of individuals or captive breeding programs to introduce monkeys in small forest fragments vulnerable to hunting and of uncertain future.     

Range and local population densities of brown bear Ursus arctos in Slovenia

Solid understanding of species’ range and local population densities is important for successful wildlife management and research. Specific behavioral and ecological characteristics make brown bear Ursus arctos a difficult species to study. We present a map of range and local population densities of brown bears in Slovenia, made with the use of a new approach similar to voting classifications based on a combination of four datasets: Global Positioning System telemetry data, records of bear removals, systematic and opportunistic direct observations and signs of bear presence, and noninvasive genetic samples. Results indicate that the majority of bears in Slovenia live in Dinaric Mountains in the southern part of the country where local bear population densities exceed 40 bears/100 km². This is one of the highest population densities reported so far for this species worldwide. Population densities decrease towards the north (Alpine region) and are very low along the border with Italy and Austria where almost no females are present. This explains slow past and present expansion of this transboundary bear population into the Alps and should be considered in future bear re-colonization management strategies. Results also showed that data from observations and removals overestimate bear population densities at low values, while mortality and genetic data overestimate population densities in areas with more people. Nevertheless, all data types appeared useful for describing the general bear distribution patterns. Similar approach could be applied to studies of other charismatic or game species, for which several types of data are often available.     

Evaluation of Bear Rub Surveys to Monitor Grizzly Bear Population Trends

Abstract: Wildlife managers need reliable estimates of population size, trend, and distribution to make informed decisions about how to recover at-risk populations, yet obtaining these estimates is costly and often imprecise. The grizzly bear (Ursus arctos) population in northwestern Montana, USA, has been managed for recovery since being listed under the United States Endangered Species Act in 1975, yet no rigorous data were available to evaluate the program's success. We used encounter data from 379 grizzly bears identified through bear rub surveys to parameterize a series of Pradel model simulations in Program MARK to assess the ability of noninvasive genetic sampling to estimate population growth rates. We evaluated model performance in terms of 1) power to detect gender-specific and population-wide declines in population abundance, 2) precision and relative bias of growth rate estimates, and 3) sampling effort required to achieve 80% power to detect a decline within 10 years. Simulations indicated that ecosystem-wide, annual bear rub surveys would exceed 80% power to detect a 3% annual decline within 6 years. Robust-design models with 2 simulated surveys per year provided precise and unbiased annual estimates of trend, abundance, and apparent survival. Designs incorporating one survey per year require less sampling effort but only yield trend and apparent survival estimates. Our results suggest that systematic, annual bear rub surveys may provide a viable complement or alternative to telemetry-based methods for monitoring trends in grizzly bear populations.     

Mark–recapture using tetracycline and genetics reveal record-high bear density

We used tetracycline biomarking, augmented with genetic methods to estimate the size of an American black bear (Ursus americanus) population on an island in Southeast Alaska. We marked 132 and 189 bears that consumed remote, tetracycline-laced baits in 2 different years, respectively, and observed 39 marks in 692 bone samples subsequently collected from hunters. We genetically analyzed hair samples from bait sites to determine the sex of marked bears, facilitating derivation of sex-specific population estimates. We obtained harvest samples from beyond the study area to correct for emigration. We estimated a density of 155 independent bears/100 km², which is equivalent to the highest recorded for this species. This high density appears to be maintained by abundant, accessible natural food. Our population estimate (approx. 1,000 bears) could be used as a baseline and to set hunting quotas. The refined biomarking method for abundance estimation is a useful alternative where physical captures or DNA-based estimates are precluded by cost or logistics. © 2011 The Wildlife Society.     

Long-Term Evaluation of Cougar Density and Application of Risk Analysis for Harvest Management

Estimates of cougar (Puma concolor) density are among the least available of any big game species in North America because of monetary and logistical challenges. Thus, wildlife managers identify cougar density estimates as a high priority need for population estimation, developing harvest guidelines, and evaluating management objectives. Cougar densities range from <1 to almost 7 cougars/100 km²; however, the magnitude of spatial and temporal variation associated with these estimates is difficult to assess because this range of densities could potentially be reported for any given population using different demographic, temporal, durational, and analytical approaches. We used long-term global positioning system (GPS) data from collared cougars across 5 diverse study areas in Washington, USA, as the basis for calculating multiple annual independent-aged (≥18 months) cougar densities, using consistent methods, and conducted a meta-analysis to assist with statewide harvest guidelines. To generate specific harvest guidelines for unobserved populations at the management unit scale, we employed a Bayesian decision-theoretic approach that minimizes statistical risk of failing to achieve a defined harvest rate. For the 16-year field effort, we calculated 24 annual densities for independent-aged cougars. Average annual densities ranged from 1.55 ± 0.44 (SD) cougars/100 km² (n = 5 years) to 2.79 ± 0.35 cougars/100 km² (n = 5 years) among the 5 study areas. Explicit delineation of the cougar population demonstrated that contribution to density can vary considerably by sex and age class. Application of a 12–16% harvest rate within the risk analysis framework yielded a potential annual harvest of 249 cougars over 91,000 km² of cougar habitat in Washington. Given the importance of density for establishing harvest guidelines, and the degree of uncertainty in projecting derived densities to future years and unstudied management units, our approach may lessen the ambiguity of extrapolations and increase the longevity of research results. Our risk analysis can be used for a diverse array of species and management objectives and be incorporated into an adaptive management framework for minimizing management risk. Our recommendations can improve standardization in reporting and interpretation of cougar density comparisons and bring clarity to the sources of variability observed in cougar populations. © 2021 The Wildlife Society.     

Pattern of space use by female black bears in the White River National Wildlife Refuge,Arkansas, USA

The manner in which space is used by animals may influence several aspects of biology, including the pattern of resource use and intra-specific competition. We monitored 16 radio-collared female black bears (Ursus americanus) for 9,216 radio days during 1993–1995 in the White River National Wildlife Refuge (WRNWR), Arkansas, U.S.A. to investigate space use patterns. Annual home ranges (95% convex polygon) ranged from 2.10 to 11.34 km² with a mean (± SD) size of 4.90 (± 2.09) km² (n = 16). Largest home ranges were occupied by 2 females with yearlings during one year of study. Home ranges among neighbouring bears overlapped considerably. Although bears maintained larger home ranges during summer, the size of home range did not differ among seasons (P > 0.50). Our estimates of home range size for female black bears were smaller than those obtained in a study of the same population during 1979–1982. Because the size of the bear population at WRNWR was substantially smaller (about 130 bears) during 1979–1982 compared to the present population of ≥348 bears, these results suggested that population density and size of female black bear home ranges may be negatively correlated. Conservation implications of density-dependent space use pattern are also discussed.     

The Abundance and Distribution of Wolverines in British Columbia,Canada

ABSTRACT The abundance and distribution of carnivores and their habitat are key information needed for status assessment, conservation planning, population management, and assessment of the effects of human development on their habitat and populations. We developed a habitat quality rating system, using existing wolverine (Gulo gulo) distribution, wolverine food, ecosystem mapping, and human development data. We used this and empirically derived estimates of wolverine density to predict wolverine distribution and abundance at a provincial scale. Density estimates for wolverines in high-quality habitat averaged 6.2 wolverines/1,000 km² (95% CI = 4.2–9.5). We predicted mean densities ranging from 0.3/1,000 km² in rare-quality habitat to 4.1/1,000 km² in moderate-quality habitat. Our predicted population estimate for wolverines in British Columbia was 3,530 (95% CI = 2,700-4,760). We predicted highest densities of wolverines in interior mountainous regions, moderate densities in interior plateau and boreal forest regions, and low densities in mainland coastal regions and drier interior plateaus. We predicted that wolverines would be rare on Vancouver Island, along the outer mainland coast, and in the dry interior forests, and absent from the Queen Charlotte Islands, interior grassland environments, and areas of intensive urban development.     

Testing the precision and sensitivity of density estimates obtained with a camera‐trap method revealed limitations and opportunities

The use of camera traps in ecology helps affordably address questions about the distribution and density of cryptic and mobile species. The random encounter model (REM) is a camera‐trap method that has been developed to estimate population densities using unmarked individuals. However, few studies have evaluated its reliability in the field, especially considering that this method relies on parameters obtained from collared animals (i.e., average speed, in km/h), which can be difficult to acquire at low cost and effort. Our objectives were to (1) assess the reliability of this camera‐trap method and (2) evaluate the influence of parameters coming from different populations on density estimates. We estimated a reference density of black bears (Ursus americanus) in Forillon National Park (Québec, Canada) using a spatial capture–recapture estimator based on hair‐snag stations. We calculated average speed using telemetry data acquired from four different bear populations located outside our study area and estimated densities using the REM. The reference density, determined with a Bayesian spatial capture–recapture model, was 2.87 individuals/10km² [95% CI: 2.41–3.45], which was slightly lower (although not significatively different) than the different densities estimated using REM (ranging from 4.06–5.38 bears/10km² depending on the average speed value used). Average speed values obtained from different populations had minor impacts on REM estimates when the difference in average speed between populations was low. Bias in speed values for slow‐moving species had more influence on REM density estimates than for fast‐moving species. We pointed out that a potential overestimation of density occurs when average speed is underestimated, that is, using GPS telemetry locations with large fix‐rate intervals. Our study suggests that REM could be an affordable alternative to conventional spatial capture–recapture, but highlights the need for further research to control for potential bias associated with speed values determined using GPS telemetry data.