Remating and Sperm Competition in Replicate Populations of Drosophila melanogaster Adapted to Alternative Environments
Bibliographic record
Abstract
The prevalence of sexual conflict in nature, as well as the supposedly arbitrary direction of the resulting coevolutionary trajectories, suggests that it may be an important driver of phenotypic divergence even in a constant environment. However, natural selection has long been central to the operation of sexual conflict within populations and may therefore constrain or otherwise direct divergence among populations. Ecological context may therefore matter with respect to the diversification of traits involved in sexual conflict, and if natural selection is sufficiently strong, such traits may evolve in correlation with environment, generating a pattern of ecologically-dependent parallel evolution. In this study we assess among-population divergence both within and between environments for several traits involved in sexual conflict. Using eight replicate populations of Drosophila melanogaster from a long-term evolution experiment, we measured remating rates and subsequent offspring production of females when housed with two separate males in sequence. We found no evidence of any variation in male reproductive traits (offense or defense). However, the propensity of females to remate diverged significantly among the eight populations with no evidence of any environmental effect, consistent with sexual conflict promoting diversification even in the absence of ecological differences. On the other hand, females adapted to one environment (ethanol) tended to produce a higher proportion of offspring sired by their first mate as compared to those adapted to the other (cadmium) environment, suggesting ecologically-based divergence of this conflict phenotype. Because we find evidence for both stochastic population divergence operating outside of an ecological context and environment-dependent divergence of traits under sexual conflict, the interaction of these two processes is an important topic for future work.
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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 | 0.001 |
| 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 | 0.001 | 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 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".