A shift in foraging behaviour of beluga whales Delphinapterus leucas from the threatened Cumberland Sound population may reflect a changing Arctic food web
Bibliographic record
Abstract
Cumberland Sound, an inlet on Baffin Island, Nunavut, Canada, is undergoing changes in sea ice cover, which is affecting the marine food web. A small population of beluga whales Delphina pterus leucas inhabits Cumberland Sound year round and this population is currently listed as threatened. Relatively little is known about the foraging behaviour of these belugas, but we expected that food web changes, primarily an increased abundance of capelin in the region, would have an impact on their diet and dive behaviour. We evaluated fatty acids in blubber samples collected from subsistence-hunted belugas in Cumberland Sound from the 1980s to 2010, and analyzed satellite tag information from 7 belugas tagged in 2006 to 2008 to gain a better understanding of their foraging behaviour. There was a change in the fatty acid profile of beluga blubber from the 1980s compared to the 1990s and 2000s. Specific fatty acids indicative of capelin and Arctic cod increased and decreased over time respectively, suggesting an increased consumption of capelin with a reduction in Arctic cod in summer in more recent years. Dive behaviour suggested different foraging tactics across seasons. Shallow short dives occurred in summer, which may indicate foraging on capelin, while deeper longer dives were made in autumn and winter, possibly indicating foraging on deeper prey such as Arctic cod and Greenland halibut. Potentially, autumn and winter are important foraging seasons for belugas, amassing energy reserves as blubber and creating a possible competitive conflict for resource use between belugas and expanding commercial fisheries.
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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 | 0.001 | 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".