Data from: Crowd control: sex ratio affects sexually selected cuticular hydrocarbons in male Drosophila serrata
Bibliographic record
Abstract
Although it is advantageous for males to express costly sexually selected signals when females are present, they may also benefit from suppressing these signals to avoid costly interactions with rival males. Cuticular chemical profiles frequently function as insect sexual signals; however, few studies have asked whether males alter these signals in response to their social environment. In Drosophila serrata, an Australian fly, there is sexual selection for a multivariate combination of male cuticular hydrocarbons (CHCs). Here, we show that the ratio of females to males that an adult male experiences has a strong effect on his CHC expression, with female-biased adult sex ratios eliciting greater expression of CHC profiles associated with higher male mating success. Classical models predict that male reproductive investment should be highest when there is a small but nonzero number of rivals, but we found that males expressed the most attractive combination of CHCs when there were no rivals. We found that male CHCs were highly sensitive to adult sex ratio, with males expressing higher values of CHC profiles associated with greater mating success as the ratio of females to males increased. Moreover, sex ratio has a stronger effect on male CHC expression than adult density. Finally, we explore whether sex ratio affects the variance among a group of males in their CHC expression, as might be expected if individuals respond differently to a given social environment, but find little effect. Our results reveal that subtle differences in social environment can induce plasticity in male chemical signal expression.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.071 | 0.019 |
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".