Postcopulatory sexual selection is associated with accelerated evolution of sperm morphology
Bibliographic record
Abstract
Rapid diversification of sexual traits is frequently attributed to sexual selection, though explicit tests of this hypothesis remain limited. Spermatozoa exhibit remarkable variability in size and shape, and studies report a correlation between sperm morphology (sperm length and shape) and sperm competition risk or female reproductive tract morphology. However, whether postcopulatory processes (e.g., sperm competition and cryptic female choice) influence the speed of evolutionary diversification in sperm form is unknown. Using passerine birds, we quantified evolutionary rates of sperm length divergence among lineages (i.e., species pairs) and determined whether these rates varied with the level of sperm competition (estimated as relative testes mass). We found that relative testes mass was significantly and positively associated with more rapid phenotypic divergence in sperm midpiece and flagellum lengths, as well as total sperm length. In contrast, there was no association between relative testes mass and rates of evolutionary divergence in sperm head size, and models suggested that head length is evolutionarily constrained. Our results are the first to show an association between the strength of sperm competition and the speed of sperm evolution, and suggest that postcopulatory sexual selection promotes rapid evolutionary diversification of sperm morphology.
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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 | 0.001 | 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) | 0.002 | 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".