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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.

Many North American river otter (Lontra canadensis) populations are threatened or recovering but are difficult to study because they occur at low densities, it is difficult to visually identify individuals, and they inhabit aquatic environments that accelerate degradation of biological samples. Single nucleotide polymorphisms (SNPs) can improve our ability to monitor demographic and genetic parameters of difficult to study species. We used restriction site associated DNA (RAD) sequencing to discover 20,772 SNPs present in Montana, USA, river otter populations, including 14,512 loci that were also variable in at least one other population range-wide. After applying careful filtering criteria meant to minimize ascertainment bias and identify high quality, highly heterozygous (Ho = 0.2–0.50) SNPs, we developed and tested 52 independent SNP qPCR genotyping assays, including 41 that performed well with diluted DNA. The 41 loci provided high power for population assignment tests with only 1 misassignment (1.6 %) between closely neighboring populations. Our SNPs showed high power to differentiate individuals and assign them to population of origin, as well as strong concordance of genotypes from high and diluted concentrations of DNA, and between original RAD and the SNP qPCR array.

Both black (Ursus americanus) and grizzly bears (U. arctos) are known to rub on trees and other objects, producing a network of repeatedly used and identifiable rub sites. In 2012, we used a resource selection function to evaluate hypothesized relationships between locations of 887 bear rubs in northwestern Montana, USA, and elevation, slope angle, density of open roads and distance from areas of heightened plant-productivity likely containing forage for bears. Slope and density of open roads were negatively correlated with rub presence. No other covariates were supported as explanatory variables. We also hypothesized that bear rubs would be more strongly associated with closed roads and developed trails than with game trails. The frequencies of bear rubs on 30 paired segments of developed tracks and game trails were not different. Our results suggest bear rubs may be associated with bear travel routes, and support their use as “random” sampling devices for non-invasive spatial capture–recapture ...

Noninvasively collected hair samples have been used in numerous studies to answer questions about the demographic and genetic status and trends of wildlife populations. In particular, these methods are well-suited for researching and monitoring ursid populations, which are typically difficult to study because of their rare and cryptic nature. Recently, researchers have taken increasing advantage of natural bear behaviors to obtain hair samples for genetic analyses by conducting surveys of bear rubs (objects that bears rub against such as trees and power poles). The low quality and quantity DNA in noninvasively collected samples, however, can result in low genotyping success rates, which may be exacerbated by potentially lengthy duration of environmental exposure. We investigated the effects of environmental exposure (sunlight, moisture, and duration of exposure) on genotyping success rates of brown bear Ursus arctos and American black bear Ursus americanus hair samples. We exposed a total of 238 hair samples from one brown bear and one black bear to multiple treatments for either 30-d or 60-d, periods consistent with collection intervals of recent bear rub survey projects. Sample treatments consisted of full or dappled sunlight, kept dry or saturated with water one to two times daily. We genotyped each sample at three microsatellite loci commonly used in noninvasive genetic studies of bear populations. Our results were consistent with predictions, with all three factors significantly reducing genotyping success rates. Based on our results, we recommend that the specific conditions of field exposure be considered when selecting a suite of microsatellite markers for noninvasive genetic sampling projects, and that researchers carefully consider the duration and environmental conditions that hair samples will be exposed to when designing field studies. Limiting exposure to moisture and sunlight by collecting hairs from bear rubs at relatively short intervals and selecting dry and shaded sites should reduce DNA degradation and thus result in higher genotyping success rates.

We report the first abundance and density estimates for American black bears (Ursus americanus) in Glacier National Park (NP), Montana, USA. We used data from 2 independent and concurrent noninvasive genetic sampling methods—hair traps and bear rubs—collected during 2004 to generate individual black bear encounter histories for use in closed population mark–recapture models. We improved the precision of our abundance estimate by using noninvasive genetic detection events to develop individual-level covariates of sampling effort within the full and one-half mean maximum distance moved (MMDM) from each bear's estimated activity center to explain capture probability heterogeneity and inform our estimate of the effective sampling area. Models including the one-half MMDM covariate received overwhelming Akaike's Information Criterion support suggesting that buffering our study area by this distance would be more appropriate than no buffer or the full MMDM buffer for estimating the effectively sampled area and thereby density. Our model-averaged super-population abundance estimate was 603 (95% CI = 522–684) black bears for Glacier NP. Our black bear density estimate (11.4 bears/100 km2, 95% CI = 9.9–13.0) was consistent with published estimates for populations that are sympatric with grizzly bears (U. arctos) and without access to spawning salmonids. Published 2013. This article is a U.S. Government work and is in the public domain in the USA

Non-invasive genetic sampling (NGS) methods have been instrumental in providing robust population abundance and density estimates of bears. We conducted a small pilot study to (1) evaluate 2 NGS methods of hair traps and bear rubs in the Russian Far East (RFE) on sympatric populations of Asiatic black bears (Ursus thibetanus) and brown bears (Ursus arctos), and (2) to identify potential DNA marker sets for future study. Genetic analysis required 6 microsatellite markers to definitively identify individuals plus a gender marker, and closed population models estimated 142 Asiatic black bears and 18 brown bears. Spatially-explicit mark–recapture (SECR) density estimates for brown bears were 3 bears/100 km2. Inflated Asiatic black bear estimates resulted from a lack of recaptures, although using combined detection data from the 2 NGS methods was found to improve precision for abundance estimates. Capture probabilities were higher for brown bears than for Asiatic black bears, but overall recapture pro...

Few studies link habitat to grizzly bear Ursus arctos abundance and these have not accounted for the variation in detection or spatial autocorrelation. We collected and genotyped bear hair in and around Glacier National Park in northwestern Montana during the summer of 2000. We developed a hierarchical Markov chain Monte Carlo model that extends the existing occupancy and count models by accounting for (1) spatially explicit variables that we hypothesized might influence abundance; (2) separate sub-models of detection probability for two distinct sampling methods (hair traps and rub trees) targeting different segments of the population; (3) covariates to explain variation in each sub-model of detection; (4) a conditional autoregressive term to account for spatial autocorrelation; (5) weights to identify most important variables. Road density and per cent mesic habitat best explained variation in female grizzly bear abundance; spatial autocorrelation was not supported. More female bears were predicted in places with lower road density and with more mesic habitat. Detection rates of females increased with rub tree sampling effort. Road density best explained variation in male grizzly bear abundance and spatial autocorrelation was supported. More male bears were predicted in areas of low road density. Detection rates of males increased with rub tree and hair trap sampling effort and decreased over the sampling period. We provide a new method to (1) incorporate multiple detection methods into hierarchical models of abundance; (2) determine whether spatial autocorrelation should be included in final models. Our results suggest that the influence of landscape variables is consistent between habitat selection and abundance in this system.

Conventional methods for monitoring cougar, Puma concolor, populations involve capture, tagging, and radio-collaring, but these methods are time-consuming, expensive, and logistically challenging. For difficult-to-study species such as cougars, noninvasive genetic sampling (NGS) may be a useful alternative. The ability to identify individuals from samples collected through NGS methods provides many opportunities for developing population-monitoring tools, but the utility of these survey methods is dependent upon collection of samples and accurate genotyping of those samples. In January 2003, we initiated a 3-yr evaluation of NGS methods for cougars using a radio-collared population in Yellowstone National Park (YNP), USA. Our goals were to: 1) determine which DNA collection method, hair snares or snow tracking, provided a better method for obtaining samples for genetic analysis, 2) evaluate reliability of the genetic data derived from hair samples collected in the field, and 3) evaluate the potential of NGS for demographic monitoring of cougar populations. Snow tracking yielded more hair samples and was more cost effective than snagging hair with rub pads. Samples collected from bed sites and natural hair snags (e.g., branch tips, thorn bushes) while snow tracking accurately identified and sexed 22 individuals (9 F, 13 M). The ratio of the count from snow tracking to the count from radio-telemetry was 15:24 in winter 2004, 13:12 in 2005, and 22:29 for both years combined. Annual capture probabilities for obtaining DNA from snow tracking varied considerably between years for females (0.42 in 2004 and 0.88 in 2005) but were more consistent for males (0.77 in 2004 and 0.88 in 2005). Our results indicate that snow tracking can be an efficient, reliable NGS method for cougars in YNP and has potential for estimating demographic and genetic parameters of other carnivore populations in similar climates. 2011 The Wildlife Society.

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.

Grizzly bears (brown bears; Ursus arctos) are imperiled in the southern extent of their range worldwide. The threatened population in northwestern Montana, USA, has been managed for recovery since 1975; yet, no rigorous data were available to monitor program success. We used data from a large noninvasive genetic sampling effort conducted in 2004 and 33 years of physical captures to assess abundance, distribution, and genetic health of this population. We combined data from our 3 sampling methods (hair trap, bear rub, and physical capture) to construct individual bear encounter histories for use in Huggins–Pledger closed mark–recapture models. Our population estimate, N = 765 (95% CI = 715–831) was more than double the existing estimate derived from sightings of females with young. Based on our results, the estimated known, human-caused mortality rate in 2004 was 4.6% (95% CI = 4.2–4.9%), slightly above the 4% considered sustainable; however, the high proportion of female mortalities raises conce...

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 i...

A fundamental challenge to estimating population size with mark-recapture methods is heterogeneous capture probabilities and subsequent bias of population estimates. Confronting this problem usually requires substantial sampling effort that can be difficult to achieve for some species, such as carnivores. We developed a methodology that uses two data sources to deal with heterogeneity and applied this to DNA mark-recapture data from grizzly bears (Ursus arctos). We improved population estimates by incorporating additional DNA "captures" of grizzly bears obtained by collecting hair from unbaited bear rub trees concurrently with baited, grid-based, hair snag sampling. We consider a Lincoln-Petersen estimator with hair snag captures as the initial session and rub tree captures as the recapture session and develop an estimator in program MARK that treats hair snag and rub tree samples as successive sessions. Using empirical data from a large-scale project in the greater Glacier National Park, Montana, USA, area and simulation modeling we evaluate these methods and compare the results to hair-snag-only estimates. Empirical results indicate that, compared with hair-snag-only data, the joint hair-snag-rub-tree methods produce similar but more precise estimates if capture and recapture rates are reasonably high for both methods. Simulation results suggest that estimators are potentially affected by correlation of capture probabilities between sample types in the presence of heterogeneity. Overall, closed population Huggins-Pledger estimators showed the highest precision and were most robust to sparse data, heterogeneity, and capture probability correlation among sampling types. Results also indicate that these estimators can be used when a segment of the population has zero capture probability for one of the methods. We propose that this general methodology may be useful for other species in which mark-recapture data are available from multiple sources.

Genetic diversity is the foundation for all biological diversity; the persistence and evolutionary potential of species depend on it. World leaders have agreed on the conservation of genetic diversity as an explicit goal of the Convention on Biological Diversity (CBD). Nevertheless, actions to protect genetic diversity are largely lacking. With only months left to the 2010-biodiversity target, when the 191 parties to the CBD have agreed on achieving a significant reduction of the rate of biodiversity loss, gene-level diversity is still not being monitored, and indicators and thresholds that can be used to devise strategies to conserve this important component of biodiversity are missing. Immediate action is needed to ensure that genetic diversity is not neglected in conservation targets beyond 2010.

We examined fecal glucocorticoid (fGC) measures of nutrition and thermoregulatory demands on wild bears in Glacier National Park, Montana, and assessed how these measures changed in samples left in the field. Both ambient temperature and exposure can impact thermoregulation and sample degradation. Bear diets vary markedly with season, affecting body condition and thus fGC. We collected fecal samples during September and October, 2001, when ambient temperatures ranged from 30°C to -5°C. We collected half of each sample immediately and left the other half in its original location for 1-28 days. We used generalized linear models (GLM) to first predict fGC concentrations in fresh samples based on proxies of nutrition, ambient temperature, thermal exposure, and precipitation. These same covariates were then used to predict degradation-based differences in fGC concentrations between the paired sample halves. Variation in fGC was predicted by diet, Julian date, aspect, and the interaction between Julian date and aspect in both fresh and exposed samples. Cumulative precipitation was also a significant predictor of fGC concentrations in the exposed samples, independent of time, indicating that precipitation contributes to sample degradation but not enough to mask effects of other environmental factors on fGC concentrations. Differences between sample halves were only predicted by cumulative precipitation and exposure time; cumulative precipitation decreased, whereas exposure time increased, fGC concentrations in the exposed sample halves. Results indicate that fGC can provide reliable indices of nutrition and thermoregulatory demands in bears and that sample degradation impacts on these relations are minimal and can be virtually eliminated by controlling for cumulative precipitation over the estimated exposure times.