Intraspecific and temporal variability in the diet composition of female polar bears in a seasonal sea ice regime
Bibliographic record
Abstract
Predator foraging behaviour is influenced by intrinsic and extrinsic factors, including energetic requirements, resource availability, and habitat conditions.Polar bears (Ursus maritimus) are specialized predators of marine mammals adapted to a seasonal sea ice regime in much of their range.We used quantitative fatty acid signature analysis to estimate diet of 374 female polar bears from 2004 to 2014 in western Hudson Bay, Canada.Ringed seal (Pusa hispida) was the dominant prey, followed by bearded seal (Erignathus barbatus) and harbour seal (Phoca vitulina), with minimal consumption of beluga whale (Delphinapterus leucas), harp seal (Pagophilus groenlandica) and walrus (Odobenus rosmarus).Solitary adults and females with yearlings consumed more bearded seal than subadults or females with cubs-of-the-year (COY).Subadults may be too small or inexperienced to capture bearded seal and females with COY may avoid offshore pack ice where densities of bearded seal, and potentially infanticidal adult male polar bears, may be highest.A high dietary diversity in subadults and females with COY suggest less selective foraging and opportunistic scavenging.Bears consumed more harbour seal and less ringed seal in congruent years suggesting variable local prey availability.Date of sea ice breakup influenced diet of subadults and family groups more so than solitary females, suggesting differential sensitivity to sea ice conditions.Inter-annual variability in diet may be a consequence of differing responses of polar bears and prey species to sea ice conditions in Hudson Bay.
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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) | 0.001 | 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".