Large‐scale geographic variation in iridescent structural ornaments of a long‐distance migratory bird
Bibliographic record
Abstract
Iridescent colours produced during moult likely play an important role in pair formation in birds. We sought to quantify geographic variation in such colouration in a duck species, Eurasian teal Anas crecca , in winter (when mating occurs) to evaluate whether this variation reflects birds’ breeding origins or differential individual migration strategies in both males and females. We combined information on feather production region and individual attributes (body size, sex and age) of Eurasian teal from 82 wintering sites in France. Feather production region (moult site or natal origin) was inferred using feather deuterium values (δD f ). We performed spectral measurements to evaluate speculum colour and brightness contrasts for 1052 teal collected over four years. Colouration differed strongly among wintering regions, with birds wintering in eastern France exhibiting higher colour contrast than those wintering in the west. Body size and colouration were positively related. There were no differences in cohort‐specific δD f values between separate wintering regions in France, indicating that within a winter quarter teal originated from areas across the entire breeding range. Overall, patterns of spatial variation in feather colouration were related most closely to body size which was consistent with predictions of a differential migration hypothesis, with larger and more colour‐contrasting birds wintering closer to their breeding grounds. Because moult speed is also known to affect colour production, early breeders or individuals that skipped reproduction may have invested more or earlier in their feather quality to gain potential advantages in monopolizing future mates.
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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 | 0.001 | 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 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".