Female promiscuity promotes the evolution of faster sperm in cichlid fishes
Bibliographic record
Abstract
Sperm competition, the contest among ejaculates from rival males to fertilize ova of a female, is a common and powerful evolutionary force influencing ejaculate traits. During competitive interactions between ejaculates, longer and faster spermatozoa are expected to have an edge; however, to date, there has been mixed support for this key prediction from sperm competition theory. Here, we use the spectacular radiation of cichlid fishes from Lake Tanganyika to examine sperm characteristics in 29 closely related species. We provide phylogenetically robust evidence that species experiencing greater levels of sperm competition have faster-swimming sperm. We also show that sperm competition selects for increases in the number, size, and longevity of spermatozoa in the ejaculate of a male, and, contrary to expectations from theory, we find no evidence of trade-offs among sperm traits in an interspecific analysis. Also, sperm swimming speed is positively correlated with sperm length among, but not within, species. These different responses to sperm competition at intra- and interspecific levels provide a simple, powerful explanation for equivocal results from previous studies. Using phylogenetic analyses, we also reconstructed the probable evolutionary route of trait evolution in this taxon, and show that, in response to increases in the magnitude of sperm competition, the evolution of sperm traits in this clade began with the evolution of faster (thus, more competitive) sperm.
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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 | 0.001 | 0.001 |
| 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".