Effects of age and weather during moult on mountain bluebird <i>Sialia currucoides</i> structural colouration
Bibliographic record
Abstract
Birds exhibit a vast array of colours and ornaments and while much work has focused on understanding the function and evolution of carotenoid‐based colours (red, orange, yellow), structural colouration (blue, green, purple, iridescent) can also play a key role in sexual signaling. Several studies have examined how factors such age may influence structural colour, however few studies have looked at how structural colour may be influenced by environmental conditions such as variation in weather conditions experienced during moult. In this study, we examined variation in structural colour expression in relation to age as well as rainfall and temperature during post‐breeding moult for a population of mountain bluebirds Sialia currucoides in western Canada over nine breeding seasons. Overall, we found structural colouration was explained by sex, age and weather patterns during moult. At a population level, tail and rump feathers from males were more colourful (higher brightness and chroma, hue values shifted more towards UV) than females, and adults were more colourful than juvenals. Male and female rump feathers generally became less colourful with age. Noise‐receptor colour models revealed colour differences were discernible among sexes, suggesting bluebird colouration is an important sexual signal. Tail and rump plumage variation was associated with weather during moulting periods, though the effects were sex‐ and age‐dependent. Female plumage was generally more colourful following wetter and warmer early summers, while males were more colourful following warmer late summers, and plumage of older birds was more resilient to colour variation due to weather patterns. We suggest that more rainfall may increase insect abundance and thus improve food intake and overall condition of mountain bluebirds. This is one of the first studies to examine how both age and weather conditions concurrently influence the expression of structural colours in birds.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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".