Spatial environmental complexity mediates sexual conflict and sexual selection in Drosophila melanogaster
Bibliographic record
Abstract
Sexual selection is an important agent of evolutionary change, but the strength and direction of selection often vary over space and time. One potential source of heterogeneity may lie in the opportunity for male–male and/or male–female interactions imposed by the spatial environment. It has been suggested that increased spatial complexity permits sexual selection to act in a complementary fashion with natural selection (hastening the loss of deleterious alleles and/or promoting the spread of beneficial alleles) via two (not mutually exclusive) pathways. In the first scenario, sexual selection potentially acts more strongly on males in complex environments, allowing males of greater genetic “quality” a greater chance of outcompeting rivals, with benefits manifested indirectly in offspring. In the second scenario, increased spatial complexity reduces opportunities for males to antagonistically harm females, allowing females (especially those of greater potential fecundities) to achieve greater reproductive success (direct fitness benefits). Here, using Drosophila melanogaster , we explore the importance of these mechanisms by measuring direct and indirect fitness of females housed in simple vial environments or in vials in which spatial complexity has been increased. We find strong evidence in favor of the female conflict‐mediated pathway as individuals in complex environments remated less frequently and produced more offspring than those housed in a simpler spatial environment, but no difference in the fitness of sons or daughters. We discuss these results in the context of other recent studies and what they mean for our understanding of how sexual selection operates.
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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 | 0.001 |
| 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".