Hybridization but minimal introgression: ecologically-based divergent selection maintains a steep hybrid zone in parapatric stickleback fish
Bibliographic record
Abstract
Steep hybrid zones provide key insights into the mechanisms of speciation by reflecting incomplete reproductive isolation between diverging populations. However, the specific reproductive barriers preventing the fusion of such populations generally remain unclear, particularly the role of ecologically-based divergent selection. To address the latter, we investigate a steep zone of transition between lake and inlet stream ecotypes of threespine stickleback fish inhabiting contiguous habitats within a single watershed. Given the spatial proximity of these habitats and the system's postglacial age, historical allopatry is unlikely to have contributed to the evolution of reproductive isolation. Using individual whole-genome sequencing from clinal sampling sites, we identify ongoing hybridization that is limited to a narrow zone-just a few hundred meters long-around the transition between lake and stream habitat. Individuals in this contact zone exhibit strongly bimodal genome-wide ancestry, with a rapid shift toward the stream ecotype's genomic background across the lowest stream section, consistent with strong divergent selection and asymmetric gene flow. Individual-based simulations tailored to this system demonstrate that divergent ecological selection alone can maintain the sharp cline observed and illustrate sustained antagonism between gene flow and selection near the habitat transition. Our findings underscore the power of ecological divergence to generate and maintain reproductive isolation, even in the absence of historical separation, and motivate further empirical work on the ecological underpinnings of steep hybrid zones.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".