Migration phenology of beluga whales in a changing Arctic
Bibliographic record
Abstract
Global warming has been linked to dramatic environmental changes, particularly in polar marine environments, where water temperatures and sea-ice cover are especially affected. Using satellite telemetry, we investigated how local changes in sea-surface temperatures (2002−2004) affected the movement patterns of belugas Delphinapterus leucas in eastern Hudson Bay (EHB), Canada. Of 26 whales equipped with satellite transmitters, 17 had records that extended beyond the summer season and showed a fall migration pattern. During summer, foraging activity of individuals was either aggregated, at small spatial scales of <90 km (Strategy A), or dispersed, at larger spatial scales of >120 km (Strategy D). In 2002 and 2003, belugas preferentially selected cold water temperatures <4°C, while, in 2004, no selection occurred. In 2002−2003, the range of water temperatures was larger than in 2004. Moreover, while cold waters were found mainly to the north of the Belcher Islands in 2002–2003, cold waters were broadly scattered throughout the whole bay in 2004. Independent of year, animals employing Strategy A left their summer habitat late (31 October, ±14 d), while those using Strategy D left about 3 wk earlier (4 October, ±2 d). In 2002−2003, the range of water temperatures was larger than in 2004. Moreover, while cold waters were found mainly to the north of the Belcher Islands in 2002–2003, cold waters were broadly scattered throughout the whole bay in 2004. Therefore, it appeared that the strategy used in summer, and hence the migration timing among EHB belugas, was related to sea-surface temperature conditions. Although other factors may also trigger migration, the present study is among the first to reveal a relationship between environmental conditions and habitat use and the migration patterns of beluga whales. Consequently, this work indicates alterations in a well-established migration phenology due to longer term effects of climate change on this Arctic 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".