Fatty acids and stable isotopes (δ<sup>13</sup>C and δ<sup>15</sup>N) reveal temporal changes in narwhal (<i>Monodon monoceros</i>) diet linked to migration patterns
Bibliographic record
Abstract
Abstract Narwhals (Monodon monoceros) are sentinel species in the Arctic and to investigate marine food web changes from 1982–2011 we examined diet using fatty acids, δ15N, and δ13C, in narwhals from Baffin Bay (BB) and northern Hudson Bay (NHB). We predicted temporal changes would be greater inNHBdue to a significant reduction in summer ice cover. InNHB, δ15N significantly increased, δ13C displayed a parabolic trend, and fatty acids gradually shifted, albeit not significantly, over time. δ15N was stable, δ13C decreased, and fatty acids significantly changed over time inBB. Stable isotope mixing models indicated a dietary reduction in capelin and increase in Greenland halibut from 1994–2000 to 2006–2011 inBB, while capelin was an important dietary component for narwhals inNHBin recent years (2006–2011). These dietary changes may be attributed to changes in sea ice and narwhal migration. Seasonal dietary changes, as evidenced by changes in blubber fatty acids and skin and muscle stable isotopes, were not as apparent in theNHBpopulation, which may be indicative of a reduced migratory distance. Long‐term monitoring of narwhal diet and migratory patterns associated with reduced sea ice provides invaluable information about how the marine ecosystem will redistribute with global warming.
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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 | 0.000 | 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".