Walking on water: terrestrial mammal migrations in the warming Arctic
Bibliographic record
Abstract
Abstract Caribou and reindeer migrations are the tip of the iceberg when one considers migration among the 70 species of Arctic terrestrial mammals. About 26% of species indeed have migratory individuals, while 33% are non-migratory and 41% are data deficient. Such figures demonstrate the need to both better document and better understand seasonal movements in these vertebrates. Whereas spatiotemporal variations in resources are key drivers of Arctic terrestrial mammal migrations, the changes of water phase around 0°C, from liquid to solid and vice versa, have considerable impacts given that liquid water, snow, and ice differ so strongly in their physical properties. We explore how the interplay between resources and water phase shape Arctic terrestrial mammal migrations, demonstrate that a rich set of research questions emerges from this interaction, and introduce new concepts such as the micro-migrations of small mammals. We also list key questions about the migrations of Arctic terrestrial mammals, with emphasis on the impacts of climate change. We conclude by arguing that the strong exposure of the Arctic to climate change, combined with the quick development of biologging techniques, rapidly increase both the need and the capacity to enhance our knowledge of migration in Arctic terrestrial mammals.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".