Brood size manipulations reveal relationships among physiological performance, body condition and plumage colour in Northern Flicker <i>Colaptes auratus</i> nestlings
Bibliographic record
Abstract
Visual signals of quality in offspring, such as plumage colour, should honestly advertise need and/or body condition, but links between nutritional status, physiological performance and the expression of colours are complex and poorly understood. We assess how food stress during rearing affected two physiological measures (T‐cell‐mediated immune function and corticosterone level in feathers: CORTf) and how these two variables were related to carotenoid and melanin coloration in Northern Flicker Colaptes auratus nestlings. We were also interested in how these two physiological measures were influenced by the sex of the nestling. We experimentally manipulated brood size to alter levels of food availability to nestlings during development. We measured carotenoid‐based colour (chroma and brightness) in wing feathers and the size of melanin spots on breast feathers. In agreement with our prediction, nestlings in the reduced brood treatment had better body condition and stronger immune responses than those in the control and brood enlargement treatments. This supports the hypothesis that immune responses are energetically costly. In contrast, CORTf was not related to nestling body condition or sex and was unaffected by brood size manipulation. Nestlings of both sexes with stronger T‐cell‐mediated immune responses had larger melanin spots but only males with higher immune responses also had brighter flight feathers. Feather brightness decreased with increasing CORTf levels. Our study is one of the few to examine the relationship between multiple physiological and plumage measures in nestlings and shows that plumage colour and immune function signalled body condition of nestlings, but that feather corticosterone levels did not.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".