Origin-related differences in plumage coloration within an island population of great tits (Parus major)
Bibliographic record
Abstract
Several studies have described geographic variation in plumage coloration, providing important insights into the processes of local adaptation and speciation. Given that such variation appears to be common, individuals of different origin within a single population may vary accordingly. However, as yet no study has been able to test for such origin-related differences. The population of great tits ( Parus major L., 1758) on the small Dutch island of Vlieland is especially suitable for such a study, as we know of every breeding adult whether it has been born on the island or not, and if it is, where on the island it was born. Furthermore, we have previously found large differences in clutch size and survival among birds of different origin in the same population. Here, we measured the spectral reflectance of the yellow breast feathers, and found that yearling, but not older, birds born in the eastern part of the island had feathers that were of a less bright yellow and UV than birds born elsewhere, irrespective of where they were breeding. Interestingly, this difference in coloration among yearlings of different origin shows a remarkable similarity with the genetic differences found earlier in this population with respect to clutch size and local survival. We thus show that systematic differences in color signals may exist within populations, among individuals of different origin, and we argue that it is crucial that such variation and its potential implications be accounted for irrespective of whether these differences have a genetic or an environmental basis.
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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 | 0.000 | 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 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".