Seasonal warming drives epidermal shedding in northern bottlenose whales
Bibliographic record
Abstract
Animals move for access to better conditions, resources, or mating opportunities. However, evidence from cetaceans suggests that some long-distance travel to warmer waters may be primarily related to physiological maintenance, specifically the shedding of epidermal diatoms and parasites. Here we test this “physiological maintenance hypothesis” for cetacean movement from a new angle, asking whether changes in temperature influence epidermal shedding in a localized, resident population. We used a long-term dataset of northern bottlenose whales (Hyperoodon ampullatus) on the Scotian Shelf to test whether large seasonal changes in sea surface temperature predict levels of diatom coverage. Generalized linear mixed models and generalized additive mixed models showed that a seasonal change in SST from 8° to 21° Celsius was associated with a decrease in diatom coverage from approximately 26% to 11%. We also found that males had less diatom coverage than females overall, and that diatom coverage tended to increase with estimated (minimum) age. Epidermal shedding is important in health maintenance for cetaceans as diatoms and skin lesions are thought to be linked to immune function. Our results support the hypothesis that health can be a driving factor in animal movements and demonstrates how environmental change can have major effects on behaviour.
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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 | 0.001 |
| 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".