Can arctic migrants adjust their phenology based on temperature encountered during the spring migration? The case of the greater snow goose
Bibliographic record
Abstract
The reproductive phenology of many long-distance migrants breeding at high latitudes remains unresponsive or responds only slightly to climate warming. In order to adjust migration speed and arrival time on the breeding grounds, environmental cues encountered during the migration must be related to conditions prevailing at the breeding site. However, heterogeneity in rate of climate warming across latitudes may hamper the ability of birds to adjust their migration speed adequately. We examined to what extent temperatures encountered at stopovers were a good predictor of temperatures at subsequent stopovers and at the breeding site in greater snow geese ( Anser caerulescens atlanticus ), an Arctic species that showed little change in its breeding phenology over the past 3 decades. We also examined temperature trends at various stopovers used by geese and at the breeding site over a 40-year period. We found that warming was stronger at the Arctic stopovers and the breeding site than at southern staging areas. The mean temperature and rate of temperature change encountered at the southern stopover, where this species accumulates most of its body reserves, was weakly correlated to temperatures prevailing at more northern stopovers and the breeding site located 3,000 km further north. Correlations in temperatures between stopovers and the breeding site increased with decreasing distance between sites and as geese moved further north. Lastly, laying date was strongly related to temperature during the arrival and pre-laying period on the breeding grounds but not to temperatures encountered at stopovers during migration. Temperatures encountered along the migratory route are thus a poor predictor of temperatures prevailing at the breeding site in any given year except when geese are getting close to their breeding grounds. This may be a major constraint preventing geese from adjusting their migratory schedule to conditions on their breeding grounds and may explain why their reproductive phenology did not change despite a warming trend at the breeding site.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".