An experimental test of the effect of food and antioxidants on blue‐green eggshell coloration in mountain bluebirds <i>Sialia currucoides</i>
Bibliographic record
Abstract
Evolutionary biologists have long debated the functional relevance of the ornamental traits that occur in many animal taxa, and yet, female ornaments have received relatively little attention compared to those produced by males. A greater understanding of these traits, particularly those that are unique to females, may shed light on the potential for sexual selection to shape female phenotypes. Recently, blue‐green eggshell colour, derived from the antioxidant pigment biliverdin, has been proposed as a candidate trait that advertises female quality to males in species of birds with biparental care. However, studies have been equivocal in their support for blue‐green eggshell colour being an informative signal, and correlations between eggshell colour and other female characteristics have been inconsistent. We conducted a supplementation experiment to test if improving the access of female birds to food resources and micronutrients, thereby improving their condition prior to egg laying, would intensify the blue‐green colouration of the eggs they laid. We provided mountain bluebirds Sialia currucoides with food and carotenoids during nest building and egg laying in two breeding seasons, and assessed both within‐ and among‐clutch variation in colour. Supplementation did not affect patterns of within‐clutch variation, but did result in differences in colour among clutches. Specifically, we found that food, but not carotenoids, resulted in higher colour saturation, and decreased the brightness of blue‐green eggshells. Although this trend was observed in both years, the effect was statistically significant only in one year. Our results suggest that food supplementation influences eggshell colour, but that conditions, such as weather and natural food availability, which can vary annually, may also determine how female birds allocate pigment to eggshells.
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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 | 0.001 | 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) | 0.000 | 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".