Extrapolated grizzly bear densities and population sizes for a selection of areas in western North America that are currently unoccupied, occupied at low densities, or are considered threatened.

<p>Current population estimates were taken from government sources in British Columbia and the US and predicted population sizes were derived using our top coastal or interior model.</p>a<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757-Hamilton2" target="_blank">[92]</a>.</p>b<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757-Apps2" target="_blank">[68]</a>.</p>c<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757-Proctor2" target="_blank">[93]</a>.</p>d<p>C. Servheen, USFWS, Montana, pers. com.</p>e<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757-Kendall1" target="_blank">[64]</a>.</p>f<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757-Servheen1" target="_blank">[67]</a>.</p

A summary of predicted numbers of grizzly bears in Canada and in National Parks by province, based on the coastal and interior models developed in this paper.

<p>–5 WMUs), and territorial guide territory boundaries which were roughly similar to WMUs in size. We predicted density for small portions of each province using ecological unit mapping (ecoregions-the largest units used), provincial wildlife management units (WMUs), provincial grizzly bear population units (GBPUs, groups of 1</p><p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757-FestaBianchet1" target="_blank">[94]</a> with corrections for portions of the National Parks that were not included.^a</p>b<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757-Hamilton2" target="_blank">[92]</a>.</p>c<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757-McLoughlin1" target="_blank">[9]</a>.</p

The top 10 model selection results for study areas in interior North America (n = 90) relating grizzly density to variables that were hypothesized to be functionally related to density.

<p> =  precipitation, NDVI = normalized differential vegetation index, AET =  actual evapotranspiration, H50 =  herbaceous and shrub cover >50%, T25 =  tree cover >25%, Meat  =  terrestrial meat in diet, SP = presence of salmon in diet, LHum =  log human density, Live  =  livestock density, Harv  =  human-caused mortality, Rug  =  ruggedness. The top-ranked model was excluded from this list, because it contained 2 uninformative variables. Variables are: Prcp</p

Factors hypothesized to limit grizzly bear density in interior ecosystems in North America and the variables we derived to index these factors.

<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757.s001" target="_blank">Appendix S1</a> for detailed description of GIS derived variables. We digitized the study area boundary for each study area and calculated the average for each index using a GIS. See Table S1 in </p><p> =  the proportion of the study with pixels rated as >50% herb/shrub.¹ This is the sum of all pixels with >the stated percentage of described cover. For example, herb50</p><p>² This is the mean human and livestock (sheep and cattle) density (summed) for the area within 10 or 50 km of the study area boundary.</p

The relationship between grizzly bear density and mean annual precipitation.

<p>Study areas where grizzly bears were allopatric are denoted by squares and where black and brown bears were sympatric by diamonds. Open symbols denote coastal study areas where salmon was a major component of the diet; filled symbols show study areas where salmon were few. Unoccupied areas and one coastal area where brown bears were allopatric and at very high density (856) are not shown.</p

Descriptive statistics for data used to predict grizzly bear density in coastal North America.

<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082757#pone.0082757.s001" target="_blank">Appendix S1</a> for detailed description of GIS derived variables. We separated areas where black bears were absent, because there were large difference in density between these areas. See Table S1 in </p

Criteria used to evaluate individual model predictions that were independent of the model process.

<p>These criteria can be used to confirm residency, to identify suspect predictions, evaluate a predicted level of harvest, or help decide what level of harvest to allow.</p

Observed versus predicted values of grizzly bear density (bears/1000 km²) using the best fit interior model described in Table 4.

<p>Data included 76 inventoried study areas and 14 unoccupied areas across the interior of western North America. Error bars are 95% confidence limits for observed data derived from the survey results or estimated subjectively, based on survey methods (see Methods for detailed description). The cases with the largest residuals often had the greatest error and were hence weighted lower in the regression.</p

The relationship between vegetation cover and grizzly bear density.

<p>These are 76 sites from across interior North America where salmon is a minor component of the diet. We compare this relationship between 2 variables, tree cover (a–b) and herb-shrub cover (c–d). We also present 2 levels of summary within each study area for each variable. For example, tree>10% means that we summed the pixels where tree cover was >10% and calculated the proportion of the study area where this occurred. Black bears appear to be absent from areas where grizzlies are present and trees cover < about 20% of the study area. The proportion of the study with >25% tree cover appears to best describe this process.</p

Observed versus predicted values of grizzly bear density (bears/1000 km²) using the best fit coastal model described in Table 5.

<p>Data included 15 inventoried study areas and 2 unoccupied areas across the interior of western North America. Error bars are 95% confidence limits for observed data derived from the survey results or, estimated subjectively based on survey methods (see Methods for detailed description).</p