Contemporary Diet of Bowhead Whales (Balaena mysticetus) from the Eastern Canadian Arctic Inferred from Fatty Acid Biomarkers
Bibliographic record
Abstract
The diet and feeding ecology of Eastern Canada – West Greenland bowhead whales were examined using fatty acid (FA) composition of the outer blubber layer of 50 individuals sampled during the summers of 2008 and 2009. Bowhead blubber was rich in the following FAs: 14:0, 16:0, 16:1n – 7, 18:0, 18:1n – 11, 18:1n – 9, 18:1n – 7, 20:1n – 11, 20:1n – 9, 20:1n – 7, 20:5n – 3, 22:1n – 11, 22:1n – 9, 22:5n – 3, and 22:6n – 3, which together accounted for 91 % of total FAs identified. Four groups of bowhead whales were identified from their FA signatures using multivariate analysis. Long-chain monounsaturated fatty acids (MUFAs) (20:1n – 9, 20:1n – 11, 22:1n – 9, and 22:1n – 11) and polyunsaturated fatty acids (PUFAs) (20:5n – 3, 22:5n – 3, 22:6n – 3) accounted for most of the variance among groups. Whales from a single sampling site segregated into different groups, some of which included whales from other sampling sites, suggesting summer mixing of whales from different wintering areas and prey assemblages, or alternatively, selective feeding. FA composition was similar in males and females and among whales of different age classes, which suggests that these different groups shared foraging areas and had similar diets. The blubber of bowhead whales from the eastern Canadian Arctic was composed of high proportions of calanoid copepod markers (20:1n – 9 and 22:1n – 11), especially compared to the adipose tissue of western Arctic bowhead whales. This finding suggests that Calanus spp. were likely a major prey item. Given the expected change in Arctic zooplankton assemblages with climate warming, bowhead whales, through their FA biomarkers, may serve as sentinels of change in Arctic ecosystems.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 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".