Alpine marmot ( <i>Marmota marmota</i> ) pups emerge increasingly earlier with the ongoing climate change
Bibliographic record
Abstract
Abstract Advance in the phenology of plants and animals is a widely observed response to climate change. The magnitude of the observed changes is, however, very variable across species. Several biological factors could influence the strength of the phenological advances, including lifestyle. Hibernation has evolved in response to harsh environmental conditions and could, hence, potentially buffer organisms against changing climatic conditions. In the Alps, the alpine marmot hibernates for almost 6 months. During that time individuals are sheltered from cold and lack of food, so we could expect alpine marmots to be less responsive to earlier springs than non-hibernating mountain-dwelling species. Here we investigate temporal variation in the date at which pups emerge from their natal burrow for the first time. Using quantile regressions, we provide clear evidence of an earlier pup emergence between 1990 and 2023. Over the study period, the predicted change is of about 4.7 days. In particular, late emergence dates are becoming especially rare over time. Our findings are in line with previous work on other mountain species, which suggests a general advance in reproductive phenology among the organisms living in Alps. The rate of change of pup emergence dates over years is, however, weaker in the alpine marmot than in most other mammalian species studied so far.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".