Experimental evolution of sperm count in protandrous self-fertilizing hermaphrodites
Bibliographic record
Abstract
Sperm count evolution is driven by sexual selection, with an added role of selection on gamete resource allocation for hermaphrodite spermatogenesis. However, self-fertilization by hermaphrodites retards sexual selection and results in the evolution of reduced investment in sperm or pollen. In contrast to reproduction limited by female gametes (Bateman's Principle), self-fertilizing Caenorhabditis elegans hermaphrodites exhibit sperm-limited reproduction. Caenorhabditis elegans hermaphrodites are thought to experience a fitness trade-off between lifetime fecundity and generation time: longer sperm production decreases the risk of self-sperm depletion, but at the same time delays the onset of selfing and thus increases egg-to-egg generation time. Theory predicts that shorter larval development will favor lower sperm counts and longer development will favor more sperm. To investigate how developmental trajectories affect the evolution of sperm production, we performed experimental evolution by directly competing alleles controlling hermaphrodite sperm count, conducted under different environmental conditions that alter development time. Results are partially consistent with theory: rapid larval development generally favored alleles encoding production of few sperm. However, we identify some previously unrecognized simplifications of the theory and its application to our experimental system. In addition, we evaluated the generality of sperm limitation in C. elegans. Although optimal growth conditions yield sperm limitation, non-optimal conditions induce oocyte limitation, suggesting that this species might conform to Bateman's Principle under many natural settings. These findings demonstrate how developmental trajectories can shape the fitness landscape for the evolution of reproduction and sperm traits, even without sexual selection.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".