Unraveling the mystery of the glacier bear: Genetic population structure of black bears (<i>Ursus americanus</i>) within the range of a rare pelage type
Bibliographic record
Abstract
Abstract Glacier bears are a rare grey color morph of American black bear (Ursus americanus) found only in northern Southeast Alaska and a small portion of western Canada. We examine contemporary genetic population structure of black bears within the geographic extent of glacier bears and explore how this structure relates to pelage color and landscape features of a recently glaciated and highly fragmented landscape. We used existing radiocollar data to quantify black bear home‐range size within the geographic range of glacier bears. The mean home‐range size of female black bears in the study area was 13 km2 (n = 11), whereas the home range of a single male was 86.9 km2. We genotyped 284 bears using 21 microsatellites extracted from noninvasively collected hair as well as tissue samples from harvested bears. We found ten populations of black bears in the study area, including several new populations not previously identified, divided largely by geographic features such as glaciers and marine fjords. Glacier bears were assigned to four populations found on the north and east side of Lynn Canal and the north and west side of Glacier Bay with a curious absence in the nonglaciated peninsula between. Lack of genetic relatedness and geographic continuity between black bear populations containing glacier bears suggest a possible unsampled population or an association with ice fields. Further investigation is needed to determine the genetic basis and the adaptive and evolutionary significance of the glacier bear color morph to help focus black bear conservation management to maximize and preserve genetic diversity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".