Understanding factors that influence and predict grizzly bear (Ursus arctos) distribution and abundance is fundamental to their conservation. In southeast British Columbia, Canada, we applied DNA hair‐trap sampling (1) to evaluate relationships of grizzly bear detections with landscape variables of habitat and human activity, and (2) to model the spatial distribution and abundance of grizzly bears. During 1996–1998, we sampled grizzly bear occurrence across 5,496 km2 at sites distributed according to grid cells. We compared 244 combinations of sampling sites and sessions where grizzly bears were detected (determined by nDNA analyses) to 845 site–sessions where they were not. We tested for differences in 30 terrain, vegetation, land cover, and human influence variables at 3 spatial scales. Grizzly bears more often were detected in landscapes of relatively high elevation, steep slope, rugged terrain, and low human access and linear disturbance densities. These landscapes also were comprised of more avalanche chutes, alpine tundra, barren surfaces, burned forests, and less young and logged forests. Relationships with forest productivity and some overstory species were positive at broader scales, while associations with forest overstory and productivity were negative at the finest scale. At the finest scale, the strong negative association with very young, logged forests and with increasing values of the Landsat‐derived green vegetation index became positive when analyzed in a multivariate context. For multivariate analyses, we considered 2 variables together with 11 principal components that describe ecological gradients among 4 variable groupings. We applied multiple logistic regression and used AIC to rank and weight competing subset models. We derived coefficients for interpretation and prediction using multi‐model inference. The resulting function was highly predictive, which we confirmed against an independent dataset. We transformed the output using a multi‐annual population estimate for the sampling area, and we applied the resulting grizzly bear density and distribution model across our greater study area as a strategic‐level planning tool. We discuss conservation applications and design considerations of this DNA‐based approach for grizzly bears and other forest‐dwelling species.

Over a 3-year period, we assessed 2 sampling designs for estimating grizzly bear (Ursus arctos) population size using DNA capture-mark-recapture methods on a population of bears that included radiomarked individuals. We compared a large-scale design (with 8 × 8-km grid cells and sites moved for 4 sessions) and a small-scale design (5 × 5-km grid cells with sites not moved for 5 sessions) for closure violation, capture-probability variation, and estimate precision. We used joint telemetry/capture-mark-recapture ( JTMR) analysis and traditional closure tests to analyze the capture-mark-recapture data with each design. A simulation study compared the performance of each design for robustness to heterogeneity bias caused by reduced capture probabilities of cubs. Our results suggested that the 5 × 5-km grid cell design was more precise and more robust to potential sample biases, but the risk of closure violation due to smaller overall grid size was greater. No design exhibited complete closure as estimated by JTMR. The results of simulation studies suggested that CAPTURE heterogeneity models are relatively robust to probable forms of capture-probability variation when capture probabilities are >0.2. Only the 5 × 5-km designs exhibited this capture-probability level, suggesting that this design is preferred to ensure estimator robustness when population size is <100. The power of the CAPTURE model selection routine to detect capture probability variation was low regardless of sampling design used. Our study illustrated the trade-off between intensive sampling to ensure robustness and adequate precision of estimators while being extensive enough to avoid closure violation bias. JOURNAL OF WILDLIFE MANAGEMENT 68(3):457-469

Ecological segregation of species is difficult to determine using conventional dietary analysis techniques. However, stable-isotope analysis may provide a convenient means of establishing trophic segregation of species and of groups of animals within a species in the same area. We measured stable carbon (δ13C) and nitrogen (δ15N) isotope values in hair of black bears (Ursus americanus) and grizzly bears (Ursus arctos) inhabiting the upper Columbia River basin in southeastern British Columbia, together with samples of potential foods ranging from plant material through invertebrates and ungulate meat. We found extensive overlap in both δ15N and δ13C values of hair from male grizzly bears and black bears of both sexes. Female grizzly bears, however, had lower δ15N values in their hair than the other groups of bears, indicating either less animal protein in their diet or a reliance on foods more depleted in 15N, possibly related to altitude. Our isotopic model generally confirmed a herbivorous diet for both bear species (a mean estimated plant contribution of 91%). Bears showing the highest δ15N values were those captured because they posed a management problem. We suggest that the slope of the relationship between tissue δ15N and δ13C values might provide a convenient means of evaluating the occurrence of consumption of animal protein in populations, regardless of local isotopic end-points for dietary samples. We examined three black bear cubs from dens and found them to be about a trophic level higher than adult females, reflecting their dependence on mother's milk, a result generally confirmed by an analysis of eight mother-cub pairs from Minnesota. Our study demonstrates how stable-isotope analysis of bear tissue can be used to monitor the feeding habits of populations, as well as provide dietary histories that may reveal dietary specializations among individuals.

Trends of grizzly bear (Ursus arctos) populations are most sensitive to female survival; thus, understanding rates and causes of grizzly bear mortality is critical for their conservation. Survival rates were estimated and causes of mortalities investigated for 388 grizzly bears radiocollared for research purposes in 13 study areas in the Rocky and Columbia mountains of Alberta, British Columbia, Montana, Idaho, and Washington between 1975 and 1997. People killed 77-85% of the 99 grizzly bears known or suspected to have died while they were radiocollared. In jurisdictions that permitted grizzly bear hunting, legal harvest accounted for 39-44% of the mortalities. Other major causes of mortality included control killing for being close to human habitation or property, self-defense, and malicious killings. The mortality rate due to hunting was higher (P = 0.006) for males than females, and subadult males had a higher probability (P = 0.007) of being killed as problem animals than did adult males or females. Adult females had a higher (P = 0.009) mortality rate from natural causes than males. Annual survival rates of subadult males (0.74-0.81) were less than other sex-age classes. Adult male survival rates varied between 0.84 and 0.89 in most areas. Survival of females appeared highest (0.95-0.96) in 2 areas dominated by multiple-use land and were lower (0.91) in an area dominated by parks, although few bears were killed within park boundaries. Without radiotelemetry, management agencies would have been unaware of about half (46-51%) of the deaths of radiocollared grizzly bears. The importance of well-managed multiple-use land to grizzly bear conservation should be recognized, and land-use plans for these areas should ensure no human settlement and low levels of recreational activity.

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