Variation in winter diet of southern Beaufort Sea polar bears inferred from stable isotope analysis
Bibliographic record
Abstract
Ringed seals ( Phoca hispida Schreber, 1775 = Pusa hispida (Schreber, 1775)) and bearded seals ( Erignathus barbatus (Erxleben, 1777)) represent the majority of the polar bear ( Ursus maritimus Phipps, 1774) annual diet. However, remains of lower trophic level bowhead whales ( Balaena mysticetus L., 1758) are available in the southern Beaufort Sea and their dietary contribution to polar bears has been unknown. We used stable isotope (13C/12C, δ13C,15N/14N, and δ15N) analysis to determine the diet composition of polar bears sampled along Alaska’s Beaufort Sea coast in March and April 2003 and 2004. The mean δ15N values of polar bear blood cells were 19.5‰ (SD = 0.7‰) in 2003 and 19.9‰ (SD = 0.7‰) in 2004. Mixing models indicated bowhead whales composed 11%–26% (95% CI) of the diets of sampled polar bears in 2003, and 0%–14% (95% CI) in 2004. This suggests significant variability in the proportion of lower trophic level prey in polar bear diets among individuals and between years. Polar bears depend on sea ice for hunting seals, and the temporal and spatial availabilities of sea ice are projected to decline. Consumption of low trophic level foods documented here suggests bears may increasingly scavenge such foods in the future.
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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 | 0.000 |
| 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) | 0.000 | 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 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".