Assortative mating in hybrid zones is remarkably ineffective in promoting speciation
Bibliographic record
Abstract
Partial prezygotic isolation is often viewed as more important than partial postzygotic isolation (low fitness of hybrids) early in the process of speciation. I simulate secondary contact between two populations (‘species’) to examine effects of assortative mating and low hybrid fitness in preventing blending. A small reduction in hybrid fitness (e.g., by 10%) produces a narrower hybrid zone than a strong but imperfect mating preference (e.g., 10x stronger preference for conspecific over heterospecific mates). In the latter case, rare F1 hybrids find each other attractive (due to assortative mating), leading to the buildup of a continuum of intermediates. The weakness of assortative mating compared to reduced fitness of hybrids in preventing blending is robust to varying genetic bases of these traits. Assortative mating is most powerful in limiting blending when it is encoded by a single locus, is essentially complete, or when there is a large mate search cost. In these cases assortative mating is likely to cause hybrids to have low fitness, due to frequency-dependent mating disadvantage of individuals of rare mating types. These results prompt a questioning of the concept of partial prezygotic isolation, since it is not very isolating unless there is also postzygotic isolation.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.048 | 0.057 |
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".