Age before beauty? Relationships between fertilization success and age-dependent ornaments in barn swallows
Bibliographic record
Abstract
When males become more ornamented and reproduce more successfully as they grow older, phenotypic correlations between ornament exaggeration and reproductive success can be confounded with age effects in cross-sectional studies, and thus say relatively little about sexual selection on these traits. This is exemplified here in a correlative study of male fertilization success in a large colony of American barn swallows (Hirundo rustica erythrogaster). Previous studies of this species have indicated that two sexually dimorphic traits, tail length and ventral plumage coloration, are positively correlated with male fertilization success, and a mechanism of sexual selection by female choice has been invoked. However, these studies did not control for potential age-related variation in trait expression. Here, we show that male fertilization success was positively correlated with male tail length but not with plumage coloration. We also show that 1-year-old males had shorter tails and lower fertilization success than older males. This age effect accounted for much of the covariance between tail length and fertilization success. Still, there was a positive relationship between tail length and fertilization success among older males. But as this group consisted of males from different age classes, an age effect may be hidden in this relationship as well. Our data also revealed a longitudinal increase in both tail length and fertilization success for individual males. We argue that age-dependent ornament expression and reproductive performance in males complicate inferences about female preferences and sexual selection.
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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 | 0.001 |
| 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".