Satellite tracking and stable isotope analysis link wintering and feeding grounds of North Atlantic baleen whales
Bibliographic record
Abstract
Knowledge of the distribution of baleen whales throughout their annual cycle is critical for understanding their ecology, life history and behavior, and for their effective conservation. We combined analysis of stable isotopes (δ15N and δ13C) and satellite tracking data of blue (Balaenoptera musculus), fin (B. physalus) and sei whales (B. borealis) encountered in the Azores to determine their wintering ranges, foraging behaviour, and movements towards feeding grounds. Blue, fin and sei whales occupied distinct isotopic spaces and distance between species was mainly driven by differences in δ 13C, suggesting use of different wintering habitats. Fin whales had the lowest δ13C values, consistent with prey sources from offshore areas, whereas the δ13C-enriched signal of sei whales indicate foraging in coastal NW African waters. Blue whales’ δ13C values were intermediate between those of fin and sei whales. Fin whales showed the broadest range and highest δ15N values, suggesting a more diverse prey base with a greater contribution of higher-trophic level organisms. Sex had no effect on isotopic signal in any of the species, indicating similar trophic levels and dietary sources for males and females. Satellite-derived movements of blue (n=10) and fin whales (n=16) indicated foraging at middle latitudes and a mid-Atlantic corridor between the Azores and Iceland-Greenland. Tracks of 8 sei whales provided no evidence of foraging until whales reached the Labrador Sea. One sei whale tagged in September moved towards Canary Islands, where the tag stopped transmitting. Our work suggests a wintering range in temperate-tropical pelagic waters for fin and blue whales migrating through the Azores to Iceland-Greenland. It also shows that part of the sei whale population feeding in the Labrador Sea winter, and possibly breed, in the eastern Atlantic. We discuss these findings in light of current knowledge on the migration strategy and population structure of each whale species
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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) | 0.000 | 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".