Movement and diet of humpback whales (Megaptera novaeangliae) in relation to capelin (Mallotus villosus) off the east coast of Newfoundland
Bibliographic record
Abstract
Knowledge of critical foraging areas in time and space, of large marine predators are important to inform management plans. An important foraging ground for humpback whales is coastal Newfoundland. The goal of this study was to investigate the foraging movements and site fidelity of humpback whales, as well as diet in relation to their primary prey, capelin, on their summer foraging grounds off the east coast of Newfoundland. I determined that humpback whale movement patterns within their Newfoundland foraging grounds were associated with the availability of capelin. At the regional scale, humpback whales were consistently abundant within bays when capelin was present. At bay scale, humpback whale presence was influenced by the timing of spawning, rather than capelin shoal characteristics, and individual humpback whales returned to a small area (10 km2) centered on a cluster of capelin deep-water spawning sites. Using stable isotope analysis, I found minimal dietary niche overlap between years (9%). These differences, were driven by inter-annual variation in prey 13C values and, thus, diet reconstruction resulted in capelin/herring comprising > 90% of humpback whale diet in both years. Together, our findings suggest that persistent capelin deep-water spawning sites may be important foraging areas for humpback whales in coastal Newfoundland.
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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 | 0.000 | 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".