Nine Maxims for the Ecology of Cold-Climate Winters
Bibliographic record
Abstract
Abstract Frozen winters define life at high latitudes and altitudes. However, recent, rapid changes in winter conditions have highlighted our relatively poor understanding of ecosystem function in winter relative to other seasons. Winter ecological processes can affect reproduction, growth, survival, and fitness, whereas processes that occur during other seasons, such as summer production, mediate how organisms fare in winter. As interest grows in winter ecology, there is a need to clearly provide a thought-provoking framework for defining winter and the pathways through which it affects organisms. In the present article, we present nine maxims (concise expressions of a fundamentally held principle or truth) for winter ecology, drawing from the perspectives of scientists with diverse expertise. We describe winter as being frozen, cold, dark, snowy, less productive, variable, and deadly. Therefore, the implications of winter impacts on wildlife are striking for resource managers and conservation practitioners. Our final, overarching maxim, “winter is changing,” is a call to action to address the need for immediate study of the ecological implications of rapidly changing winters.
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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 | 0.015 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.042 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| 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".