Differences in diving and movement patterns of two groups of beluga whales in a changing Arctic environment reveal discrete populations
Bibliographic record
Abstract
Harvest and global climate change are among the major ongoing threats to most Arctic marine mammal populations. Affected by commercial hunting in the past, beluga whales Delphinapterus leucas are still harvested for subsistence in many coastal areas of the Canadian Arctic, while ongoing climate changes are suspected to modify factors that may have determined the distribution and degree of interaction of the different populations. Although several populations have been clearly identified, the global discreteness of the Arctic metapopulation is not yet clearly established. In this study, seasonal diving activity and movement patterns of 46 belugas from 2 neighbouring groups in Hudson Bay (Canada) were analysed in relation to physical environmental characteristics and revealed significantly different migratory and habitat use patterns. Likely affected by local environmental conditions, the Eastern Hudson Bay beluga migrate, while the James Bay beluga remain resident, suggesting little overlap between the groups at all times of the year. This study provides useful baseline data for determining population interactions and habitat use. The information is also potentially useful in identifying critical habitat, which is an essential component to design and implement management and conservation policy, e.g. quota and harvesting regulations and the design of marine protected areas.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".