Can cryptic female choice prevent invasive hybridization in external fertilizing fish?
Bibliographic record
Abstract
Abstract Polyandrous mating systems result in females mating with multiple males, generating opportunities for strong pre‐mating and post‐mating sexual selection. Polyandry also creates the potential for unintended matings and subsequent sperm competition with hybridizing species. Cryptic female choice allows females to bias paternity towards preferred males under sperm competition and may include conspecific sperm preference when under hybridization risk. The potential for hybridization becomes particularly important in context of invasive species that can novelly hybridize with natives, and by definition, have evolved allopatrically. We provide the first examination of conspecific sperm preference in a system of three species with the potential to hybridize: North American native Atlantic salmon ( Salmo salar ) and brook char ( Salvelinus fontinalis ), and invasive brown trout ( Salmo trutta ) from Europe. Using naturalized populations on the island of Newfoundland, we measured changes in sperm swimming performance, a known predictor of paternity, to determine the degree of modification in sperm swimming to female cues related to conspecific sperm preference. Compared to water alone, female ovarian fluid in general had a pronounced effect and changed sperm motility (by a mean of 53%) and swimming velocity (mean 30%), but not linearity (mean 6%). However, patterns in the degree of modification suggest there is no conspecific sperm preference in the North American populations. Furthermore, female cues from both native species tended to boost the sperm of invasive males more than their own. We conclude that cryptic female choice via ovarian fluid mediated sperm swimming modification is too weak in this system to prevent invasive hybridization and is likely insufficient to promote or maintain reproductive isolation between the native North American species.
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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 | 0.000 |
| 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".