Grizzly bear movements relative to roads: application of step selection functions

Access management is among the most important conservation actions for grizzly bears in North America. In Alberta, Canada, nearly all grizzly bear mortalities are caused by humans and occur near roads and trails. Consequently, understanding how bears move relative to roads is of crucial importance for grizzly bear conservation. We present the first application of step‐selection functions to model habitat selection and movement of grizzly bears. We then relate this to a step‐length analysis to model the rate of movement through various habitats. Grizzly bears of all sex and age groups were more likely to select steps closer to roads irrespective of traffic volume. Roads are associated with habitats attractive to bears such as forestry cutblocks, and models substituting cutblocks for roads outperformed road models in predicting bear selection during day, dawn, and dusk time periods. Bear step lengths increased near roads and were longest near highly trafficked roads indicating faster movement when near roads. Bear selection of roads was consistent throughout the day; however, time of day had a strong influence over selection of forest structure and terrain variables. At night and dawn, bears selected forests of intermediate age between 40 and 100 yr, and bears selected older forests during the day. At dawn, bears selected steps with higher solar radiation values, whereas, at dusk, bears chose steps that were significantly closer to edges. Because grizzly bears use areas near roads during spring and most human‐caused mortalities occur near roads, access management is required to reduce conflicts between humans and bears. Our results support new conservation guidelines in western North America that encourage the restriction of human access to roads constructed for resource extraction.     

The Impact of Roads on the Demography of Grizzly Bears in Alberta

One of the principal factors that have reduced grizzly bear populations has been the creation of human access into grizzly bear habitat by roads built for resource extraction. Past studies have documented mortality and distributional changes of bears relative to roads but none have attempted to estimate the direct demographic impact of roads in terms of both survival rates, reproductive rates, and the interaction of reproductive state of female bears with survival rate. We applied a combination of survival and reproductive models to estimate demographic parameters for threatened grizzly bear populations in Alberta. Instead of attempting to estimate mean trend we explored factors which caused biological and spatial variation in population trend. We found that sex and age class survival was related to road density with subadult bears being most vulnerable to road-based mortality. A multi-state reproduction model found that females accompanied by cubs of the year and/or yearling cubs had lower survival rates compared to females with two year olds or no cubs. A demographic model found strong spatial gradients in population trend based upon road density. Threshold road densities needed to ensure population stability were estimated to further refine targets for population recovery of grizzly bears in Alberta. Models that considered lowered survival of females with dependant offspring resulted in lower road density thresholds to ensure stable bear populations. Our results demonstrate likely spatial variation in population trend and provide an example how demographic analysis can be used to refine and direct conservation measures for threatened species.     

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.     

Hazards Affecting Grizzly Bear Survival in the Greater Yellowstone Ecosystem

Abstract: During the past 2 decades, the grizzly bear (Ursus arctos) population in the Greater Yellowstone Ecosystem (GYE) has increased in numbers and expanded its range. Early efforts to model grizzly bear mortality were principally focused within the United States Fish and Wildlife Service Grizzly Bear Recovery Zone, which currently represents only about 61% of known bear distribution in the GYE. A more recent analysis that explored one spatial covariate that encompassed the entire GYE suggested that grizzly bear survival was highest in Yellowstone National Park, followed by areas in the grizzly bear Recovery Zone outside the park, and lowest outside the Recovery Zone. Although management differences within these areas partially explained differences in grizzly bear survival, these simple spatial covariates did not capture site-specific reasons why bears die at higher rates outside the Recovery Zone. Here, we model annual survival of grizzly bears in the GYE to 1) identify landscape features (i.e., foods, land management policies, or human disturbances factors) that best describe spatial heterogeneity among bear mortalities, 2) spatially depict the differences in grizzly bear survival across the GYE, and 3) demonstrate how our spatially explicit model of survival can be linked with demographic parameters to identify source and sink habitats. We used recent data from radiomarked bears to estimate survival (1983–2003) using the known-fate data type in Program MARK. Our top models suggested that survival of independent (age ≥ 2 yr) grizzly bears was best explained by the level of human development of the landscape within the home ranges of bears. Survival improved as secure habitat and elevation increased but declined as road density, number of homes, and site developments increased. Bears living in areas open to fall ungulate hunting suffered higher rates of mortality than bears living in areas closed to hunting. Our top model strongly supported previous research that identified roads and developed sites as hazards to grizzly bear survival. We also demonstrated that rural homes and ungulate hunting negatively affected survival, both new findings. We illustrate how our survival model, when linked with estimates of reproduction and survival of dependent young, can be used to identify demographically the source and sink habitats in the GYE. Finally, we discuss how this demographic model constitutes one component of a habitat-based framework for grizzly bear conservation. Such a framework can spatially depict the areas of risk in otherwise good habitat, providing a focus for resource management in the GYE.     

Influence of whitebark pine decline on fall habitat use and movements of grizzly bears in the Greater Yellowstone Ecosystem

When abundant, seeds of the high‐elevation whitebark pine (WBP; Pinus albicaulis) are an important fall food for grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem. Rates of bear mortality and bear/human conflicts have been inversely associated with WBP productivity. Recently, mountain pine beetles (Dendroctonus ponderosae) have killed many cone‐producing WBP trees. We used fall (15 August–30 September) Global Positioning System locations from 89 bear years to investigate temporal changes in habitat use and movements during 2000–2011. We calculated Manly–Chesson (MC) indices for selectivity of WBP habitat and secure habitat (≥500 m from roads and human developments), determined dates of WBP use, and documented net daily movement distances and activity radii. To evaluate temporal trends, we used regression, model selection, and candidate model sets consisting of annual WBP production, sex, and year. One‐third of sampled grizzly bears had fall ranges with little or no mapped WBP habitat. Most other bears (72%) had a MC index above 0.5, indicating selection for WBP habitats. From 2000 to 2011, mean MC index decreased and median date of WBP use shifted about 1 week later. We detected no trends in movement indices over time. Outside of national parks, there was no correlation between the MC indices for WBP habitat and secure habitat, and most bears (78%) selected for secure habitat. Nonetheless, mean MC index for secure habitat decreased over the study period during years of good WBP productivity. The wide diet breadth and foraging plasticity of grizzly bears likely allowed them to adjust to declining WBP. Bears reduced use of WBP stands without increasing movement rates, suggesting they obtained alternative fall foods within their local surroundings. However, the reduction in mortality risk historically associated with use of secure, high‐elevation WBP habitat may be diminishing for bears residing in multiple‐use areas.     

Predicting Grizzly Bear Density in Western North America

Conservation of grizzly bears (Ursus arctos) is often controversial and the disagreement often is focused on the estimates of density used to calculate allowable kill. Many recent estimates of grizzly bear density are now available but field-based estimates will never be available for more than a small portion of hunted populations. Current methods of predicting density in areas of management interest are subjective and untested. Objective methods have been proposed, but these statistical models are so dependent on results from individual study areas that the models do not generalize well. We built regression models to relate grizzly bear density to ultimate measures of ecosystem productivity and mortality for interior and coastal ecosystems in North America. We used 90 measures of grizzly bear density in interior ecosystems, of which 14 were currently known to be unoccupied by grizzly bears. In coastal areas, we used 17 measures of density including 2 unoccupied areas. Our best model for coastal areas included a negative relationship with tree cover and positive relationships with the proportion of salmon in the diet and topographic ruggedness, which was correlated with precipitation. Our best interior model included 3 variables that indexed terrestrial productivity, 1 describing vegetation cover, 2 indices of human use of the landscape and, an index of topographic ruggedness. We used our models to predict current population sizes across Canada and present these as alternatives to current population estimates. Our models predict fewer grizzly bears in British Columbia but more bears in Canada than in the latest status review. These predictions can be used to assess population status, set limits for total human-caused mortality, and for conservation planning, but because our predictions are static, they cannot be used to assess population trend.     

Seasonal habitat use and selection by grizzly bears in Northern British Columbia

We defined patterns of habitat use and selection by female grizzly bears (Ursus arctos) in the Besa-Prophet watershed of northern British Columbia. We fitted 13 adult females with Geographic Positioning System (GPS) radio-collars and monitored them between 2001 and 2004. We examined patterns of habitat selection by grizzly bears relative to topographical attributes and 3 potential surrogates of food availability: land-cover class, vegetation biomass or quality (as measured by the Normalized Difference Vegetation Index), and selection value for prey species themselves (moose [Alces alces], elk [Cervus elaphus], woodland caribou [Rangifer tarandus], Stone's sheep [Ovis dalli stonei]). Although vegetation biomass and quality, and selection values for prey were important in seasonal selection by some individual bears, land-cover class, elevation, aspect, and vegetation diversity most influenced patterns of habitat selection across grizzly bears, which rely on availability of plant foods and encounters with ungulate prey. Grizzly bears as a group avoided conifer stands and areas of low vegetation diversity, and selected for burned land-cover classes and high vegetation diversity across seasons. They also selected mid elevations from what was available within seasonal ranges. Quantifying relative use of different attributes helped place selection patterns within the context of the landscape. Grizzly bears used higher elevations (1,595 ± 31 m SE) in spring and lower elevations (1,436 ± 27 m) in fall; the range of average elevations used among individuals was highest (500 m) during the summer. During all seasons, grizzly bears most frequented aspects with high solar gain. Use was distributed across 10 land-cover classes and depended on season. Management and conservation actions must maintain a diverse habitat matrix distributed across a large elevational gradient to ensure persistence of grizzly bears as levels of human access increase in the northern Rocky Mountains. © 2011 The Wildlife Society.     

Grizzly bear responses to restrictions of recreation in Yellowstone National Park

Avoiding humans will be more difficult and energetically costly for animals as outdoor recreation increases and people venture farther into wildland areas that provide high-quality habitat for wildlife. Restricting human access can be an attractive management tool to mitigate effects of human recreation activities on wildlife; however, the efficacy of such measures is rarely assessed. In 1982, Yellowstone National Park identified areas important to grizzly bears (Ursus arctos) to help protect critical grizzly bear habitat and reduce the likelihood of human injuries by bears. Referred to as bear management areas (BMAs), human access is restricted in these areas for 2–8 months each year, with timing and type of restrictions varying by area. We examined 2 datasets to evaluate grizzly bear selection of BMAs and differences of bear density in BMAs and non-BMAs. First, we used 17 years of recent global positioning system telemetry data for grizzly bears to assess their selection of BMAs during periods when human access was allowed, and when access was restricted. We used step-selection functions to test the hypothesis that bears spend time in places that allow them to avoid people and select quality food sources. There was support that grizzly bears differentially select for BMAs regardless of whether human access was restricted at the time, compared with areas outside BMAs, and that selection changed with sex and season. Only males during the summer and hyperphagic seasons changed their selection of BMAs based on whether access restrictions were in place, and overall, male bears preferred unrestricted BMAs (BMAs without restrictions in place). Females preferentially selected BMAs regardless of whether the area had access restrictions in place only during the mating season. Individuals varied widely in their preference for BMAs and access restrictions. Bears likely choose to spend time in BMAs based on available food resources rather than restrictions to human access. Supporting this interpretation, our analyses indicated that a greater proportion of BMA in an area was associated with higher densities of grizzly bear. Thus, restrictions to human access likely help reduce the potential for human–bear interactions, accomplishing one of the original objectives for establishing the BMAs.     

Using spatially‐explicit capture–recapture models to explain variation in seasonal density patterns of sympatric ursids

Understanding how environmental factors interact to determine the abundance and distribution of animals is a primary goal of ecology, and fundamental to the conservation of wildlife populations. Studies of these relationships, however, often assume static environmental conditions, and rarely consider effects of competition with ecologically similar species. In many parts of their shared ranges, grizzly bears Ursus arctos and American black bears U. americanus have nearly complete dietary overlap and share similar life history traits. We therefore tested the hypothesis that density patterns of both bear species would reflect seasonal variation in available resources, with areas of higher primary productivity supporting higher densities of both species. We also hypothesized that interspecific competition would influence seasonal density patterns. Specifically, we predicted that grizzly bear density would be locally reduced due to the ability of black bears to more efficiently exploit patchy food resources such as seasonally abundant fruits. To test our hypotheses, we used detections of 309 grizzly and 597 black bears from two independent genetic sampling methods in spatially‐explicit capture–recapture (SECR) models. Our results suggest grizzly bear density was lower in areas of high black bear density during spring and summer, although intraspecific densities were also important, particularly during the breeding season. Black bears had lower densities in areas of high grizzly bear density in spring; however, density of black bears in early and late summer was best explained by primary productivity. Our results are consistent with the hypothesis that smaller‐bodied, more abundant black bears may influence the density patterns of behaviorally‐dominant grizzly bears through exploitative competition. We also suggest that seasonal variation in resource availability be considered in efforts to relate environmental conditions to animal density.     

Evaluating habitat selection models to predict critical habitat for mountain goats in northwest British Columbia

Anthropogenic activity imposes increasing pressure on wildlife populations globally; these pressures can affect habitat suitability and function, modify wildlife space use, and influence population viability. Native mountain goat (Oreamnos americanus) populations can be negatively affected by anthropogenic disturbance and modify their space use in response to land development and recreational activity. From 2018 to 2020, we studied space use of mountain goats northeast of Smithers, British Columbia, Canada, an area that is subject to increasing anthropogenic development and yearlong recreational activities. We aimed to generate models that would improve our ability to identify habitat for mountain goats relative to existing survey data and established ungulate winter ranges. Using resource selection function (RSF) analyses generated from global positioning system (GPS) collar data, we identified influential habitat covariates and compared these covariates and RSF values to existing habitat models. Additionally, we compared the extent to which our models were congruent with existing resource selection probability functions, were congruent with aerial survey data, and overlapped existing ungulate winter ranges previously derived from predictive models inside and outside of the study area. Overall, our models noted higher RSF values among GPS data relative to aerial survey data for winter months, while results for summer habitats were comparable. In extending our RSFs outside of the study area and evaluating the overlap with ungulate winter ranges in adjacent areas, values were similar, albeit lower, as is expected given that the models were developed elsewhere. Ultimately, these models, combined with existing methods, improve the accuracy and reliability of identified, important areas of habitat for mountain goats. We recommend that the RSF models generated here be used in conjunction with aerial survey data and existing methods to delineate ungulate winter ranges for mountain goats in similar eco-regions in British Columbia. The models developed here support existing methods that have been used to delineate or validate ungulate winter ranges for mountain goats in British Columbia and help facilitate mitigation measures to support the continued use of important winter habitat and significant landscape features that play a role in ensuring population viability and resilience through time.     

Contrasting Activity Patterns of Sympatric and Allopatric Black and Grizzly Bears

ABSTRACT The distribution of grizzly (Ursus arctos) and American black bears (U. americanus) overlaps in western North America. Few studies have detailed activity patterns where the species are sympatric and no studies contrasted patterns where populations are both sympatric and allopatric. We contrasted activity patterns for sympatric black and grizzly bears and for black bears allopatric to grizzly bears, how human influences altered patterns, and rates of grizzly-black bear predation. Activity patterns differed between black bear populations, with those sympatric to grizzly bears more day-active. Activity patterns of black bears allopatric with grizzly bears were similar to those of female grizzly bears; both were crepuscular and day-active. Male grizzly bears were crepuscular and night-active. Both species were more night-active and less day-active when ≤1 km from roads or developments. In our sympatric study area, 2 of 4 black bear mortalities were due to grizzly bear predation. Our results suggested patterns of activity that allowed for intra- and inter-species avoidance. National park management often results in convergence of locally high human densities in quality bear habitat. Our data provide additional understanding into how bears alter their activity patterns in response to other bears and humans and should help park managers minimize undesirable bear-human encounters when considering needs for temporal and spatial management of humans and human developments in bear habitats.     

A spatially explicit method for evaluating accuracy of species distribution models

Aim Models predicting the spatial distribution of animals are increasingly used in wildlife management and conservation planning. There is growing recognition that common methods of evaluating species distribution model (SDM) accuracy, as a global overall value of predictive ability, could be enhanced by spatially evaluating the model thereby identifying local areas of relative predictive strength and weakness. Current methods of spatial SDM model assessment focus on applying local measures of spatial autocorrelation to SDM residuals, which require quantitative model outputs. However, SDM outputs are often probabilistic (relative probability of species occurrence) or categorical (species present or absent). The goal of this paper was to develop a new method, using a conditional randomization technique, which can be applied to directly spatially evaluate probabilistic and categorical SDMs. Location Eastern slopes, Rocky Mountains, Alberta, Canada. Methods We used predictions from seasonal grizzly bear (Ursus arctos) resource selection functions (RSF) models to demonstrate our spatial evaluation technique. Local test statistics computed from bear telemetry locations were used to identify areas where bears were located more frequently than predicted. We evaluated the spatial pattern of model inaccuracies using a measure of spatial autocorrelation, local Moran’s I. Results We found the model to have non‐stationary patterns in accuracy, with clusters of inaccuracies located in central habitat areas. Model inaccuracies varied seasonally, with the summer model performing the best and the least error in areas with high RSF values. The landscape characteristics associated with model inaccuracies were examined, and possible factors contributing to RSF error were identified. Main conclusions The presented method complements existing spatial approaches to model error assessment as it can be used with probabilistic and categorical model output, which is typical for SDMs. We recommend that SDM accuracy assessments be done spatially and resulting accuracy maps included in model metadata.     

Identifying Habitat Linkages for American Black Bears in North Carolina,USA

ABSTRACT Understanding landscape structure and the role of habitat linkages is important to managing wildlife populations in fragmented landscapes. We present a data-based method for identifying local- and regional-scale habitat linkages for American black bears (Ursus americanus) on the Albemarle-Pamlico Peninsula of North Carolina, USA. We used weights-of-evidence, a discrete multivariate technique for combining spatial data, to make predictions about bear habitat use from 1,771 telemetry locations on 2 study areas (n = 35 bears). The model included 3 variables measured at a 0.2-km² scale: forest cohesion, forest diversity, and forest-agriculture edge density, adequately describing important habitat characteristics for bears on our study area. We used 2 categories of unique habitat conditions to delineate favorable bear habitat, which correctly classified 79.5% of the bear locations in a 10-fold model validation. Forest cohesion and forest-agriculture edge density were the most powerful predictors of black bear habitat use. We used predicted probabilities of bear occurrence from the model to delineate habitat linkages among local and regional areas where bear densities were relatively high. Our models clearly identified 2 of the 3 sites previously recommended for wildlife underpasses on a new, 4-lane highway in the study area. Our approach yielded insights into how landscape metrics can be integrated to identify linkages suitable as habitat and dispersal routes.     

Evaluating the role of environmental familiarity and behaviour in the success of wildlife translocation: A grizzly bear case study using agent-based modelling

Human-carnivore systems are built on multi-scalar complex processes often resulting in conflicts that force wildlife managers to address what are conceived as problem individuals. In North America, the grizzly bear (Ursus arctos) is often involved in human-bear conflict with management measures such as translocations, in which problem individuals are moved to new areas, being used to reduce conflict risk. While translocations offer a non-lethal alternative to managing conflict animals, they show varying levels of success. Our objective was to perform a novel assessment of grizzly bear translocation success through agent-based simulation by evaluating how familiarity with landscape features coupled with behavioral traits affects the way individuals use resources in a new environment. Our results showed that bears translocated to familiar habitat used high-quality habitat more than bears moved to areas with unfamiliar landscape characteristics. Increased exploration led to greater use of high-quality habitat in the long run but resulted in reduced use of high-quality habitat during the first two years following a translocation. Habitat quality use depended on scale, with bears translocated to less familiar environments accessing higher quality areas at a finer scale than bears translocated to familiar habitats. We emphasize the need to account for wildlife behavioral traits and habitat characteristics at multiple scales when selecting suitable translocation locations. Understanding the role of factors such as these on translocation outcome will help ensure the success of translocations not only as a method for managing problem wildlife, but also for population restoration, species reestablishment, and conservation translocations across the globe.     

Landscape partitioning and spatial inferences of competition between black and grizzly bears

Population effects of competition between large carnivore species may be evident by contrasting actual distributions of putative competitors against predictions of inherent landscape quality for each species. Such comparison can be insightful if covariation with external factors known to influence the occurrence, density, or persistence of each species over space and time can be controlled. We used systematically‐distributed DNA hair‐trap stations to sample the occurrence of black bears (Ursus americanus) and grizzly bears (U. arctos) across 5496 km² in southeastern British Columbia, Canada. We describe interspecific landscape partitioning according to terrain, vegetation and land‐cover variables at 2 spatial scales. We developed multivariate models to predict the potential distribution of each species. At sampling site‐session combinations that detected either species, we then investigated whether the expected or actual occurrence of each influenced the likelihood of detecting the other while controlling for human influence and inherent landscape quality. Black bears were more likely than grizzly bears to occur in gentle, valley bottom terrain with lower proportions of open habitats. Each species also was detected less frequently with the other species than predicted by their respective models; however, the strength of this relationship decreased as landscapes became more characteristic of black bear habitat. As landscapes showed higher inherent potential to support grizzly bears, black bears occurred more than model prediction in areas with higher human access and proximity to major highways but less in national parks. As potential to support black bears increased, grizzly bears occurred more than model prediction only in national parks and less with increasing human access and proximity to major highways. Results suggest that competition is occurring between the species, and that the differential response of each species to human disturbance or excessive mortality may influence the outcome and hence landscape partitioning. Moreover, black bears are more likely to benefit from human encroachment into landscapes of high inherent value for grizzly bears than vice versa. Conservation implications relate to potential mediating effects of habitat and human influence on competitive interactions between the species.     

Perception of Human-Derived Risk Influences Choice at Top of the Food Chain

On human-used landscapes, animal behavior is a trade-off between maximizing fitness and minimizing human-derived risk. Understanding risk perception in wildlife can allow mitigation of anthropogenic risk, with benefits to long-term animal fitness. Areas where animals choose to rest should minimize risk from predators, which for large carnivores typically equate to humans. We hypothesize that high human activity leads to selection for habitat security, whereas low activity enables trading security for forage. We investigated selection of resting (bedding) sites by GPS radiocollared adult grizzly bears (n = 10) in a low density population on a multiple-use landscape in Canada. We compared security and foods at resting and random locations while accounting for land use, season, and time of day. On reclaimed mines with low human access, bears selected high horizontal cover far from trails, but did not avoid open (herbaceous) areas, resting primarily at night. In protected areas bears also bedded at night, in areas with berry shrubs and Hedysarum spp., with horizontal cover selected in the summer, during high human access. On public lands with substantial human recreation, bears bedded at day, selected resting sites with high horizontal cover in the summer and habitat edges, with bedding associated with herbaceous foods. These spatial and temporal patterns of selection suggest that bears perceive human-related risk differentially in relation to human activity level, season and time of day, and employ a security-food trade-off strategy. Although grizzly bears are presently not hunted in Alberta, their perceived risks associated with humans influence resting-site selection.     

Land tenure shapes black bear density and abundance on a multi‐use landscape

Global biodiversity is decreasing rapidly. Parks and protected lands, while designed to conserve wildlife, often cannot provide the habitat protection needed for wide‐ranging animals such as the American black bear (Ursus americanus). Conversely, private lands are often working landscapes (e.g., farming) that have high human footprints relative to protected lands. In southwestern Alberta, road densities are highest on private lands and black bears can be hunted year‐round. On protected lands, road densities are lowest, and hunting is prohibited. On public lands under the jurisdiction of the provincial government (Crown lands), seasonal hunting is permitted. Population estimates are needed to calculate sustainable harvest levels and to monitor population trends. In our study area, there has never been a robust estimate of black bear density and spatial drivers of black bear density are poorly understood. We used non‐invasive genetic sampling and indices of habitat productivity and human disturbance to estimate density and abundance for male and female black bears in 2013 and 2014 using two methods: spatially explicit capture–recapture (SECR) and resource‐selection functions (RSF). Land tenure best explained spatial variation in black bear density. Black bear densities for females and males were highest on parkland and lowest on Crown lands. Sex ratios were female‐biased on private lands, likely a result of lower harvests and movement of females out of areas with high male density. Synthesis and application: Both SECR and RSF methods clearly indicate spatial structuring of black bear density, with a strong influence based on how lands are managed. Land tenure influences the distribution of available foods and risk from humans. We emphasize the need for improved harvest reporting, particularly for non‐licensed hunting on private land, to estimate the extent of black bear harvest mortality.     

Are polar bear habitat resource selection functions developed from 1985–1995 data still useful?

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Estimating grizzly and black bear population abundance and trend in Banff National Park using noninvasive genetic sampling

We evaluated the potential of two noninvasive genetic sampling methods, hair traps and bear rub surveys, to estimate population abundance and trend of grizzly (Ursus arctos) and black bear (U. americanus) populations in Banff National Park, Alberta, Canada. Using Huggins closed population mark-recapture models, we obtained the first precise abundance estimates for grizzly bears (N=?73.5, 95% CI?=?64-94 in 2006; N=?50.4, 95% CI?=?49-59 in 2008) and black bears (N=?62.6, 95% CI?=?51-89 in 2006; N=?81.8, 95% CI?=?72-102 in 2008) in the Bow Valley. Hair traps had high detection rates for female grizzlies, and male and female black bears, but extremely low detection rates for male grizzlies. Conversely, bear rubs had high detection rates for male and female grizzlies, but low rates for black bears. We estimated realized population growth rates, lambda, for grizzly bear males (λ=?0.93, 95% CI?=?0.74-1.17) and females (λ=?0.90, 95% CI?=?0.67-1.20) using Pradel open population models with three years of bear rub data. Lambda estimates are supported by abundance estimates from combined hair trap/bear rub closed population models and are consistent with a system that is likely driven by high levels of human-caused mortality. Our results suggest that bear rub surveys would provide an efficient and powerful means to inventory and monitor grizzly bear populations in the Central Canadian Rocky Mountains.     

Spatial Analysis of Factors Influencing Long-Term Stress in the Grizzly Bear (Ursus arctos) Population of Alberta,Canada

Non-invasive measures for assessing long-term stress in free ranging mammals are an increasingly important approach for understanding physiological responses to landscape conditions. Using a spatially and temporally expansive dataset of hair cortisol concentrations (HCC) generated from a threatened grizzly bear (Ursus arctos) population in Alberta, Canada, we quantified how variables representing habitat conditions and anthropogenic disturbance impact long-term stress in grizzly bears. We characterized spatial variability in male and female HCC point data using kernel density estimation and quantified variable influence on spatial patterns of male and female HCC stress surfaces using random forests. Separate models were developed for regions inside and outside of parks and protected areas to account for substantial differences in anthropogenic activity and disturbance within the study area. Variance explained in the random forest models ranged from 55.34% to 74.96% for males and 58.15% to 68.46% for females. Predicted HCC levels were higher for females compared to males. Generally, high spatially continuous female HCC levels were associated with parks and protected areas while low-to-moderate levels were associated with increased anthropogenic disturbance. In contrast, male HCC levels were low in parks and protected areas and low-to-moderate in areas with increased anthropogenic disturbance. Spatial variability in gender-specific HCC levels reveal that the type and intensity of external stressors are not uniform across the landscape and that male and female grizzly bears may be exposed to, or perceive, potential stressors differently. We suggest observed spatial patterns of long-term stress may be the result of the availability and distribution of foods related to disturbance features, potential sexual segregation in available habitat selection, and may not be influenced by sources of mortality which represent acute traumas. In this wildlife system and others, conservation and management efforts can benefit by understanding spatial- and gender-based stress responses to landscape conditions.