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.     

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.     

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.     

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.     

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.     

DNA-Based Population Demographics of Black Bears in Coastal North Carolina and Virginia

ABSTRACT Noninvasive genetic sampling has become a popular method for obtaining population parameter estimates for black (Ursus americanus) and brown (U. arctos) bears. These estimates allow wildlife managers to develop appropriate management strategies for populations of concern. Black bear populations at Great Dismal Swamp (GDSNWR), Pocosin Lakes (PLNWR), and Alligator River (ARNWR) National Wildlife Refuges in coastal Virginia and North Carolina, USA, were perceived by refuge biologists to be at or above cultural and perhaps biological carrying capacity, but managers had no reliable abundance estimates upon which to base population management. We derived density estimates from 3,150 hair samples collected noninvasively at each of the 3 refuges, using 6–7 microsatellite markers to obtain multilocus genotypes for individual bears. We used Program MARK to calculate population estimates from capture histories at each refuge. We estimated densities using both traditional buffer strip methods and Program DENSITY. Estimated densities were some of the highest reported in the literature and ranged from 0.46 bears/km² at GDSNWR to 1.30 bears/km² at PLNWR. Sex ratios were male-biased at all refuges. Our estimates can be directly utilized by biologists to develop effective strategies for managing and maintaining bears at these refuges, and noninvasive methods may also be effective for monitoring bear populations over the long term.     

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.     

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.     

Estimating Black Bear Density Using DNA Data From Hair Snares

ABSTRACT DNA-based mark-recapture has become a methodological cornerstone of research focused on bear species. The objective of such studies is often to estimate population size; however, doing so is frequently complicated by movement of individual bears. Movement affects the probability of detection and the assumption of closure of the population required in most models. To mitigate the bias caused by movement of individuals, population size and density estimates are often adjusted using ad hoc methods, including buffering the minimum polygon of the trapping array. We used a hierarchical, spatial capture-recapture model that contains explicit components for the spatial-point process that governs the distribution of individuals and their exposure to (via movement), and detection by, traps. We modeled detection probability as a function of each individual's distance to the trap and an indicator variable for previous capture to account for possible behavioral responses. We applied our model to a 2006 hair-snare study of a black bear (Ursus americanus) population in northern New York, USA. Based on the microsatellite marker analysis of collected hair samples, 47 individuals were identified. We estimated mean density at 0.20 bears/km². A positive estimate of the indicator variable suggests that bears are attracted to baited sites; therefore, including a trap-dependence covariate is important when using bait to attract individuals. Bayesian analysis of the model was implemented in WinBUGS, and we provide the model specification. The model can be applied to any spatially organized trapping array (hair snares, camera traps, mist nests, etc.) to estimate density and can also account for heterogeneity and covariate information at the trap or individual level.     

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.     

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.     

A noninvasive and integrative approach for improving density and abundance estimates of moose

Acquiring demographic data for moose (Alces alces) can be difficult because they are solitary in nature, they prefer densely vegetated and mountainous habitats, and they often occur at low density. Such data, however, are essential for long-term population monitoring, evaluating management practices, and effective conservation. Winter aerial surveys are the standard method for estimating moose population parameters, but they can be logistically challenging, expensive, and subject to sightability correction, which necessitates the capture of study animals for initial model development. Herein, we demonstrate a noninvasive alternative approach for estimating population parameters of moose in northern Yellowstone National Park, where aerial surveys were attempted but proved ineffective. We determined individual moose genotype and sex using microsatellite polymerase chain reaction amplification of DNA extracted from fecal pellets, integrated ancillary pellet sample data (i.e., metadata) in genotype analysis to aid in the identification of matching genotypes, and used spatially explicit capture-recapture (SECR) modeling to estimate sex-specific density and abundance. We collected 616 samples over 3 consecutive winters (Dec 2013–Apr 2016) and within 2 sampling occasions each winter. We recorded 514 captures of 142 individual moose (69 males, 73 females). Overall density ranged between 0.062 moose/km² and 0.076 moose/km² and averaged 0.034/km² for females and 0.033/km² for males. Abundance estimates were 150 moose in 2013 (female = 76, 95% CI = 55–105; male = 74, 95% CI = 54–103), 186 in 2014 (female = 95, 95% CI = 63–142; male = 91, 95% CI = 60–138), and 160 in 2015 (female = 79, 95% CI = 58–108; male = 81, 95% CI = 59–110). Average population sex ratio was 0.99 males/female. We demonstrate that SECR analysis of fecal DNA genotypes, using metadata in genotype analysis to help identify matching moose genotypes, is a promising alternative method for estimating sex-specific density and abundance of a low-density moose population in a mountainous and forested landscape.     

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.     

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     

Extensive Predator Space Use Can Limit the Efficacy of a Control Program

ABSTRACT Reduced to small isolated groups by anthropogenic habitat losses or habitat modifications, populations of many endangered species are sensitive to additive sources of mortality, such as predation. Predator control is often one of the first measures considered when predators threaten survival of a population. Unfortunately, predator ecology is often overlooked because relevant data are difficult to obtain. For example, the endangered Gaspésie caribou (Rangifer tarandus caribou) has benefited from 2 periods of predator control that targeted black bears (Ursus americanus) and coyotes (Canis latrans) in an attempt to reduce predation on caribou calves. Despite a high trapping effort, the number of predators removed has remained stable over time. To assess impact of predator movements on efficacy of a control program, we studied space use of 24 black bears and 16 coyotes over 3 years in and around the Gaspésie Conservation Park, Quebec, Canada, using Global Positioning System radiocollars. Annual home ranges of black bears averaged 260 km² and 10 individuals frequented area used by caribou. Annual home ranges of resident coyotes averaged 121 km², whereas dispersing coyotes covered >2,600 km². Coyotes were generally located at lower altitudes than caribou. However, because coyotes undertook long-distance excursions, they overlapped areas used by caribou. Simulations based on observed patterns showed that 314 bears and 102 coyotes potentially shared part of their home range with areas used by female caribou during the calving period. Despite low densities of both predator species, extensive movement and use of nonexclusive territories seem to allow predators to rapidly occupy removal areas, demonstrating the need for recurrent predator removals. Our results underscore the necessity of considering complementary and alternative solutions to predator control to assure long-term protection of endangered species.     

Challenges and opportunities for estimating abundance of a low-density moose population

Monitoring large herbivores across their core range has been readily accomplished using aerial surveys and traditional distance sampling. But for peripheral populations, where individuals may occur in patchy, low-density populations, precise estimation of population size and trend remains logistically and statistically challenging. For moose (Alces alces) along their southern range margin in northern New York, USA, we sought robust estimates of moose distribution, abundance, and population trend (2016–2019) using a combination of aerial surveys (line transect distance-sampling), repeated surveys in areas where moose were known to occur to boost the number of detections, and density surface modeling (DSM) with spatial covariates. We achieved a precise estimate of density (95% CI = 0.00–0.29 moose/km²) for this small population (656 moose, 95% CI = 501–859), which was patchily distributed across a large and heavily forested region (the 24,280-km² Adirondack Park). Local moose abundance was positively related to active timber management, elevation, and snow cover, and negatively related to large bodies of water. As expected, moose abundance in this peripheral population was low relative to its core range in other northern forest states. Yet, in areas where abundance was greatest, moose densities in New York approached those where epizootics of winter tick (Dermacentor albipictus) have been reported, underscoring the need for effective and efficient monitoring. By incorporating autocorrelation in observations and landscape covariates, DSM provided spatially explicit estimates of moose density with greater precision and no additional field effort over traditional distance sampling. Combined with repeated surveys of areas with known moose occurrence to achieve viable sample sizes, DSM is a useful tool for effectively monitoring low density and patchy 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.     

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.     

Population-level resource selection by sympatric brown and American black bears in Alaska

Distribution theory predicts that for two species living in sympatry, the subordinate species would be constrained from using the most suitable resources (e.g., habitat), resulting in its use of less suitable habitat and spatial segregation between species. We used negative binomial generalized linear mixed models with fixed effects to estimate seasonal population-level resource selection at two spatial resolutions for female brown bears (Ursus arctos) and female American black bears (U. americanus) in southcentral Alaska during May–September 2000. Black bears selected areas occupied by brown bears during spring which may be related to spatially restricted (i.e., restricted to low elevations) but dispersed or patchy availability of food. In contrast, black bears avoided areas occupied by brown bears during summer. Brown bears selected areas near salmon streams during summer, presumably to access spawning salmon. Use of areas with high berry production by black bears during summer appeared in response to avoidance of areas containing brown bears. Berries likely provided black bears a less nutritious, but adequate food source. We suggest that during summer, black bears were displaced by brown bears, which supports distribution theory in that black bears appeared to be partially constrained from areas containing salmon, resulting in their use of areas containing less nutritious forage. Spatial segregation of brown and American black bears apparently occurs when high-quality resources are spatially restricted and alternate resources are available to the subordinate species. This and previous work suggest that individual interactions between species can result in seasonal population-level responses.