Blubber cortisol in four Canadian beluga whale populations is unrelated to diet
Bibliographic record
Abstract
Changing conditions in the Arctic have had severe consequences for many marine mammals. In this study, we examined blubber cortisol using radioimmunoassay in 4 Canadian beluga whaleDephinapterus leucaspopulations. The endangered Cumberland Sound population had higher cortisol levels (mean ± SE: 0.65 ± 0.11 ng g-1) than populations not at risk: Eastern Beaufort Sea (0.31 ± 0.03 ng g-1; p < 0.001), Eastern High Arctic-Baffin Bay (0.32 ± 0.09 ng g-1; p = 0.004), and Western Hudson Bay (0.44 ± 0.04 ng g-1; p = 0.004). To evaluate if measured cortisol differences were due to differences in diet, we compared stable isotope ratios of carbon and nitrogen (δ13C and δ15N) and dietary fatty acids among populations. Beluga whales from Eastern Beaufort Sea had lower δ13C (p ≤ 0.017) and higher δ15N (p < 0.001) values than other measured populations, while Western Hudson Bay beluga dietary fatty acid profiles differed from other measured populations (p < 0.001). Population and sex were significant predictors of blubber cortisol (p ≤ 0.017). Females exhibited higher cortisol than males. Despite diet differences among populations, neither stable isotopes nor fatty acids were significant predictors of cortisol, suggesting differences in cortisol levels were unrelated to diet. Other factors, such as increased risk of predation, hunting pressure, vessel traffic, or differences in baseline blubber cortisol concentrations may be contributing to elevated cortisol levels in Cumberland Sound beluga whales. Measuring blubber cortisol in combination with chemical indicators of diet provides a useful method for monitoring population health and can be used to inform management and conservation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".