Coping Mechanisms of Alpine and Arctic Breeding Birds: Extreme Weather and Limitations to Reproductive Resilience
Bibliographic record
Abstract
As ground nesting homeotherms, alpine and arctic birds must meet similar physiological requirements for breeding as other birds, but must do so in more extreme conditions. Annual spring snowfall and timing of snow melt can vary by up to 1 month and daily temperatures near the ground surface vary from below freezing to over 45°C in alpine and arctic habitats. Species breeding in these environments have various behavioral, physiological, and morphological adaptations to cope with energetically demanding conditions. We review the ways birds cope with harsh and variable weather, and present data from long term field studies of ptarmigan to examine effects of spring weather on reproduction. In variable but normal spring conditions, timing of breeding was not influenced by snow melt, snow depth or daily temperatures in the alpine, as breeding did not commence until conditions were generally favorable. Arctic ptarmigan tended to vary breeding onset in response to spring conditions. Generally, birds breeding in alpine and arctic habitats suffer a seasonal reproductive disadvantage compared to birds at lower latitudes or elevations because the breeding window is short and in late years, nest failure may be high with little opportunity for renesting. Coping mechanisms may only be effective below a threshold of climactic extremes. Despite strong resilience in fecundity parameters, when snowmelt is extremely delayed breeding success is greatly reduced. Alpine and arctic birds will be further challenged as they attempt to cope with anticipated increases in the frequency and severity of weather events (climate variability), as well as general climate warming.
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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 | 0.000 | 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) | 0.001 | 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".