Predicting Grizzly Bear (Ursus arctos) densities in British Columbia using a multiple regression model

We determined the relationships between Grizzly Bear density and ultimate measures of ecosystem productivity and mortality at a landscape scale using multiple linear regression and field based density estimates from Grizzly Bear populations across western North America. We found that Grizzly Bear densities in non-coastal environments were positively related to the mean annual rainfall, to the presence of salmon, and to the proportion of the population's perimeter that was contiguous with other Grizzly Bear populations. Grizzly Bear densities in non-coastal environments were negatively related to human and livestock density, and to the reported mortality rate (r 2 = 0.62, n = 33). We could not predict Grizzly Bear density on the BC coast because the single Grizzly Bear density estimate on the coast did not appear to be related to the same factors as those in the BC interior or in coastal Alaska. We used the multiple linear regression model to predict Grizzly Bear density and associated confidence limits in 61 Grizzly Bear population sub-units in BC, in areas with few or no salmon. Five of the 61 sub-units (Alta, Atlin, North Cascades, Taiga and Tatshenshini) had unrealistically high predictions. We estimated that the remaining 56 sub-units contained about 14,000 Grizzly Bears, which is a mean density of 16 Grizzly Bears /1000 km 2. The model also accurately predicted zero Grizzly Bears in 5 areas of the province where the species has been extirpated: Lower Mainland,