Delineating Canadian and Greenland polar bear (<i>Ursus maritimus</i>) populations by cluster analysis of movements
Bibliographic record
Abstract
Within their circumpolar range, polar bears (Ursus maritimus) are not subject to absolute barriers. However, physiographic features do cause discontinuities in their movements. These discontinuities in distribution can be used to delineate population units. Based on satellite telemetry of the movements of female polar bears carried out in 19891998, we used cluster analysis to identify 6 regions within the Canadian and western Greenland Arctic in which movements appear to be restricted enough to identify distinct populations. These regions generally correspond to management units that have been previously identified as Viscount Melville Sound, Lancaster Sound, Norwegian Bay, Kane Basin, Baffin Bay, and Davis Strait. A northsouth substructure was identified for the Baffin Bay population, but it was weaker than the structure identified for the 6 primary units. The 6 units were consistent with genetic information, except for the Baffin Bay Kane Basin separation, and with markrecapture observations and the traditional knowledge of Inuit hunters. Only 2 of 65 bears that provided telemetry information for more than 1 year were classified in different populations in different years. However, annual rates of exchange, measured as the percentage of locations outside the population boundary, ranged from 0.4 to 8.9%. Analysis of markrecapture movements indicated no difference in large-scale movements between the sexes or long-term movements with age. Although our validation criteria for demographic closure were satisfied, the observed rates of exchange between adjacent populations suggest that population dynamics in adjacent populations may not be completely independent.
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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 | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".