COMPARATIVE EVIDENCE FOR THE EVOLUTION OF SPERM SWIMMING SPEED BY SPERM COMPETITION AND FEMALE SPERM STORAGE DURATION IN PASSERINE BIRDS
Bibliographic record
Abstract
Sperm swimming speed is an important determinant of male fertility and sperm competitiveness. Despite its fundamental biological importance, the underlying evolutionary processes affecting this male reproductive trait are poorly understood. Using a comparative approach in a phylogenetic framework, we tested the predictions that sperm swim faster with (1) increased risk of sperm competition, (2) shorter duration of female sperm storage, and (3) increased sperm length. We recorded sperm swimming speed in 42 North American and European free-living passerine bird species, representing 35 genera and 16 families. We found that sperm swimming speed was positively related to the frequency of extrapair paternity (a proxy for the risk of sperm competition) and negatively associated with clutch size (a proxy for the duration of female sperm storage). Sperm swimming speed was unrelated to sperm length, although sperm length also increased with the frequency of extrapair paternity. These results suggest that sperm swimming speed and sperm length are not closely associated traits and evolve independently in response to sperm competition in passerine birds. Our findings emphasize the significance of both sperm competition and female sperm storage duration as evolutionary forces driving sperm swimming speed.
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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 | 0.001 |
| 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".