Conditions on the Mexican moulting grounds influence feather colour and carotenoids in Bullock's orioles (<i>Icterus bullockii</i>)
Bibliographic record
Abstract
Abstract Carotenoid‐based plumage coloration plays a critical role for both inter‐ and intrasexual communication. Habitat and diet during molt can have important consequences for the development of the ornamental signals used in these contexts. When molt occurs away from the breeding grounds (e.g., pre‐alternate molt on the wintering grounds, or stopover molt), discerning the influence of habitat and diet can be particularly important, as these effects may result in important carryover effects that influence territory acquisition or mate choice in subsequent seasons. Several species of songbirds in western North America, including the Bullock's oriole (Icterus bullockii), migrate from the breeding grounds to undergo a complete prebasic (post‐breeding) molt at a stopover site in the region affected by the Mexican monsoon climate pattern. This strategy appears to have evolved several times independently in response to the harsh, food‐limited late‐summer conditions in the arid West, which contrast strongly with the high productivity driven by heavy rains that is characteristic of the Mexican monsoon region. Within this region, individuals may be able to optimize plumage coloration by molting in favourable areas characterized by high resource abundance. We used stable isotope analysis (δ13C, δ15N) to ask whether the diet and molt habitat/location of Bullock's orioles influenced their expression of carotenoid‐based plumage coloration as well as plumage carotenoid content and composition. Bullock's orioles with lower feather δ15N values acquired more colorful plumage (orange‐shifted hue) but had feathers with lower total carotenoid concentration, lower zeaxanthin concentration, and marginally lower canthaxanthin and lutein concentration. Examining factors occurring throughout the annual cycle are critical for understanding evolutionary and ecological processes. Here, we demonstrate that conditions experienced during a stopover molt, occurring hundreds to thousands of kilometers from the breeding grounds, influence the production of ornamental plumage coloration, which may carryover to influence inter‐ and intrasexual signaling in subsequent seasons.
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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 | 0.000 | 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".