Plasticity in moult speed and timing in an arctic‐nesting goose species
Bibliographic record
Abstract
Environmental constraints are strong in migratory species that breed in the Arctic. In addition to breeding, Anatidae have to renew all their flight feathers during the short arctic summer. We examine how temporal constraints and climate affect the phenology of flight feather moult in the greater snow goose Chen caerulescens atlantica , a High Arctic nesting species. We used a database of 1412 moulting adult females measured over 15 yr on Bylot Island, Nunavut. Ninth (9th) primary length was used to determine the moult stage and speed of feather growth. We found a positive relationship between median annual hatching and moult initiation dates and the slope did not differ from 1. The interval between hatching and moult initiation was thus rather fixed and geese did not initiate moult earlier when reproductive phenology was delayed. Nonetheless, there was no relationship between median hatching date and the date at which birds regained flight capacity, suggesting that date of end of moult is independent of the reproductive phenology. There was a trend for an increase in the speed of flight feather growth in years with delayed hatching date. This is the most likely mechanism that could explain moult phenology adjustment in this species. Finally, we found a positive relationship between 9th primary length (corrected for inter‐annual variations) and body condition, suggesting a delay in moulting for individuals in poor condition. These results suggest that moult plasticity is primarily governed by variations in feather growth speed. This phenotypic plasticity could be necessary to complete flight feather renewal before the end of the arctic summer, independently of reproductive phenology and spring environmental conditions. Our novel results suggest possible phenological adjustments through moult speed, which was considered constant in geese until now.
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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 | 0.000 | 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 | 0.000 | 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 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".