Grizzly Ursus arctos and black bear U. americanus densities in the interior mountains of North America
Bibliographic record
Abstract
We collected hair samples from bears and used microsatellite genotyping to identify individual bears on three study areas near the Canadian Rocky Mountains. We estimated density of grizzly bears Ursus arctos in eight different ecosystems across five study areas, including the reanalysis of two previously published data sets. We also estimated black bear U. americanus density for two ecosystems in one study area. Grizzly bear density was lowest in boreal and sub-boreal plateau areas, moderate in the Rocky Mountain east slopes and highest in the Rocky Mountain west slopes. Presumably these gross differences are related to ecosystem productivity. In the Rocky Mountain west slopes, grizzly bear density was lower in populations that were partially isolated from the continuous bear population to the north. Presumably, these differences have more to do with human impacts on habitat and survival than ecosystem productivity, because productivity in partially isolated areas was similar to productivity in adjacent continuous populations. We show that large differences in bear density occur down to the ecoregion scale; broader ecosystem classes such as Banci's (1991) grizzly bear zones, ecoprovinces or ecozones would include areas with major differences in density and are therefore too coarse a scale at which to predict grizzly bear density. There appears to be little movement across ecoregion boundaries further suggesting that this may be an appropriate scale at which to extrapolate density. Differences in density across finer-scale ecosystems are likely due to seasonal movements and not population level differences in density. Average bear movements were longer in less productive ecosystems. Female grizzly bears did not appear to leave their home ranges to fish for salmon Oncorhynchus spp., and extra-territorial movements by males appeared to be rare, in both ecosystems which supported spawning salmon.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".