Sex-specific development of avian flight performance under experimentally altered rearing conditions
Bibliographic record
Abstract
Numerous studies have examined predation risk resulting from the costs of impaired flight performance associated with many key life-history stages such as reproduction and migration. Interestingly, although avian nestlings experience multiple resource-based physiological trade-offs and undergo considerable morphological and physiological changes during postnatal development, there is no data available on how nestlings manage the competing demands of growth and the development of flight ability at this critical life-history stage. We examined numerous morphological traits to determine which are responsible for variation in flight performance in juvenile European starlings (Sturnus vulgaris), a sexually size-dimorphic passerine. We then manipulated maternal quality during chick rearing (via feather clipping) to examine sex-specific sensitivity of fledgling flight performance to the quality of the rearing environment. Results suggest that the mechanics underlying variation in juvenile flight performance are relatively simple, being principally determined by the ratio of pectoral muscle mass to body mass (BM) and the surface area of the wings. Interestingly, although the maternal quality manipulation decreased BM and structural size in daughters, only the flight performance of sons was negatively affected. Our results suggest that a survival-related trait can be significantly affected in the larger sex when raised under stressful conditions. Furthermore, measuring only BM and structural size may not be sufficient in understanding how the sexes are affected by stressful rearing conditions in sexually size-dimorphic species.
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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".