Reproductive isolating mechanisms contributing to asymmetric hybridization in Killifishes ( <i>Fundulus</i> spp.)
Bibliographic record
Abstract
When species hybridize, one F1 hybrid cross type often predominates. Such asymmetry can arise from differences in a variety of reproductive barriers, but the relative roles and concordance of pre-mating, post-mating prezygotic, and post-zygotic barriers in producing these biases in natural animal populations have not been widely investigated. Here, we study a population of predominantly F1 hybrids between two killifish species (Fundulus heteroclitus and F. diaphanus) in which >95% of F1 hybrids have F. diaphanus mothers and F. heteroclitus fathers (D♀ × H♂). To determine why F. heteroclitus × F. diaphanus F1 hybrids (H♀ × D♂) are so rare, we tested for asymmetry in pre-mating reproductive barriers (female preference and male aggression) at a common salinity (10 ppt) and post-mating, pre-zygotic (fertilization success) and post-zygotic (embryonic development time and hatching success) reproductive barriers at a range of ecologically relevant salinities (0, 5, 10, and 15 ppt). We found that F. heteroclitus females preferred conspecific males, whereas F. diaphanus females did not, matching the observed cross bias in the wild. Naturally rare H♀ × D♂ crosses also had lower fertilization success than all other cross types, and a lower hatching success than the prevalent D♀ × H♂ crosses at the salinity found in the hybrid zone centre (10 ppt). Furthermore, the naturally predominant D♀ × H♂ crosses had a higher hatching success than F. diaphanus crosses at 10 ppt, which may further increase their relative abundance. The present study suggests that a combination of incomplete mating, post-mating pre-zygotic and post-zygotic reproductive isolating mechanisms act in concert to produce hybrid asymmetry in this system.
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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 | 0.000 |
| 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".