Reproductive fluids enabling cryptic female choice of paternity do not induce concomitant ejaculate-mediated paternal effects in embryos of hybridizing salmonid fishes
Bibliographic record
Abstract
Post-ejaculatory sexual selection in the form of cryptic female choice provides opportunities for females to bias paternity to favour preferred males. However, little is known regarding how cryptic female choice might affect offspring outside of paternity, via female-modified changes to environments that sperm experience prior to fertilization. Ejaculate-mediated paternal effects are widespread, and female alteration of sperm experience may play an unrecognized role in shaping cryptic female choice. Using hybridizing salmonid fishes that have documented female reproductive fluid-mediated conspecific sperm precedence, we created artificial split-brood and split-ejaculate fertilizations to determine if sperm experience in different fluids influences offspring development. Prior to contact with eggs, sperm experienced 20 s of swimming in either water, or water with the addition of conspecific female fluid or heterospecific female fluid. Over 186 days, we quantified hatch timing, hatchling size, and developmental stage and found that reproductive fluid from different species created biologically irrelevant (average effect size of 1.05%) changes on offspring development, which were much smaller than the effects of hybridization itself (average effect size of 10.44% for the species of the father). Since female reproductive fluid drastically changes fertilization conditions when compared to water, we conclude that females can use reproductive fluid to bias paternity without concomitant consequences to offspring development.
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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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".