Extensive multi-species hybridization between Leuciscidae minnow species
Bibliographic record
Abstract
Abstract Anthropogenic disturbances can disrupt ecosystems and alter species population dynamics. Interspecific hybridization is common between genetically related organisms, especially once reproductive barriers such as spatial isolation have been removed. We used genotyping- by-sequencing data to assess outcomes of hybridization between several Leuciscidae minnow species and to identify to what extent land use type and environmental variables influence the frequency of hybridization. We found that both two-species and multi-species hybridization was widespread; hybrids were sampled at all 25 sampling sites and made up almost 30% of all individuals sampled. While most species hybridized with at least one other sampled species, the amount of hybridization was variable. We used logistic regression to estimate the influence of anthropogenic disturbance on hybridization, and found significant but weak relationships between hybridization and environmental factors. This research improves our understanding of hybridization dynamics in species-rich clades like the Leuciscidae with low reproductive isolation, and points to the need for additional work to better understand predictors of hybridization in multi-species 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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".