Spatial and temporal harvest risk to polar bears in the Canadian Beaufort Sea
Bibliographic record
Abstract
Subsistence harvest in Arctic marine ecosystems is influenced by sea ice conditions affecting species distributions, abundance, and accessibility. We tracked 78 polar bears ( Ursus maritimus Phipps, 1774) of different age, sex, and reproductive classes via satellite telemetry in the Canadian Beaufort Sea (2007–2014, n = 71 258). We assessed vulnerability to harvest (no/low/medium/high) based on telemetry data overlap with density of historical harvest locations (1985–1987, n = 121). All classes of polar bears were detected in historical harvest areas of low to high risk in greater proportion than expected from available area during the harvest period (January to ice breakup), and all but solitary adult females had >50% of locations in the risk areas. Subadult males were proportionally more often inside risk areas yet were not observed in the high-risk areas. Other classes were observed <1% of the time in high-risk areas yet still proportionally greater than expected from available area. Landfast ice has declined in the pre-melt (January–March) and end-of-harvest (June–July) seasons (1980–2021), with the rate of decline being greater in lower-risk areas ( p ≤ 0.05). With sea ice predicted to decline in the future, we suggest that polar bears in the Beaufort Sea may become more concentrated into areas of higher harvest risk.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".