Differences in individual bowhead whale Balaena mysticetus habitat use, foraging dive depth and diet during the peak feeding season
Bibliographic record
Abstract
Shifts in zooplankton quantity and quality caused by climate change could challenge the ability of bowhead whales to meet their energetic requirements. When facing such selection pressure, intra-population variation dampens the negative effects and provides population-level resilience. Previous studies observed inter-individual diet variation in bowhead whales, but the mechanism responsible for the variation was undetermined. We investigated foraging variability in Eastern Canada-West Greenland bowhead whales using dietary biomarkers (stable isotopes, fatty acids) and movement data (satellite telemetry with time-depth recorders) from the same individuals. We found that bowhead whale individuals using distinct summer and fall foraging habitats displayed differences in horizontal movements, foraging dive depth, and diet. For individuals using the Canadian Arctic Archipelago habitat (Foxe Basin, Gulf of Boothia, Prince Regent Inlet, Lancaster Sound and Admiralty Inlet, Nunavut), they performed long distance movements across regions, and their foraging dive depth was generally shallow, but increased from July to November. These whales displayed higher δ13C and δ15N values and ratios of C16:1n7/C16:0. Individuals using the West Baffin Bay habitat (Cumberland Sound, Baffin Bay, Davis Strait) were more localized in their horizontal movements and consistent over time in their foraging dive depth, which was generally deeper. These whales displayed lower δ13C and δ15N values and ratios of C16:1n7/C16:0. Overall, this inter-individual variation in diet and foraging behaviour could indicate some niche variation which would be beneficial for the population under changing habitats and prey availability.
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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 | 0.000 | 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".