Temporal complexity of southern<scp>B</scp>eaufort<scp>S</scp>ea polar bear diets during a period of increasing land use
Bibliographic record
Abstract
Abstract From 2000 to 2013, use of land as a seasonal habitat by polar bears (Ursus maritimus) of the southern Beaufort Sea (SB) subpopulation substantially increased. This onshore use has been linked to reduced spatial and temporal availability of sea ice, as well as to the availability of subsistence‐harvested bowhead whale (Balaena mysticetus) bone piles. Here, we evaluated the role of climate conditions on consumption of traditional ice‐associated prey relative to onshore bowhead whale bone piles. We determined seasonal and interannual trends in the diets ofSBpolar bears using fatty acid‐based analysis during this period of increasing land use. Diet estimates of 569SBpolar bears from 2004 to 2012 showed high seasonal fluctuations in the proportions of prey consumed. Higher proportions of bowhead whale, as well as ringed seal (Pusa hispida) and beluga whale (Delphinapterus leucas), were estimated to occur in the winter–spring diet, while higher proportions of bearded seal (Erignathus barbatus) were estimated for summer–fall diets. Trends in the annual mean proportions of individual prey items were not found in either period, except for significant declines in the proportion of beluga in spring‐sampled bears. Nonetheless, in years following a high winter Arctic oscillation index, proportions of ice‐associated ringed seal were lower in the winter–spring diets of adult females and juveniles. Proportions of bowhead increased in the winter–spring diets of adult males with the number of ice‐free days over the continental shelf. In one or both seasons, polar bears that were in better condition were estimated to have consumed less ringed seal and/or more bowhead whale than those in worse condition. Therefore, climate variation over this recent period appeared to influence the extent of onshore vs. on‐ice food use, which in turn, appeared to be linked to fluctuating condition ofSBpolar bears.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".