Sharp genetic discontinuity across a unimodal<i>Heliconius</i>hybrid zone
Bibliographic record
Abstract
Hybrid zones are powerful natural systems to study evolutionary processes to gain an understanding of adaptation and speciation. In the Cauca Valley (Colombia), two butterfly races, Heliconius cydno cydnides and Heliconius cydno weymeri, meet and hybridize. We characterized this hybrid zone using a combination of mitochondrial DNA (mtDNA) sequences, amplified fragment length polymorphisms (AFLPs), microsatellites and sequences for nuclear loci within and outside of the genomic regions that cause differences in wing colour pattern. The hybrid zone is largely composed of individuals of mixed ancestry. However, there is strong genetic discontinuity between the hybridizing races in mtDNA and, to a lesser extent, in all nuclear markers surveyed. The mtDNA clustering of H. c. cydnides with the H. cydno race from the Magdalena Valley and H. c. weymeri with the H. cydno race from the pacific coast suggests that H. c. cydnides colonized the Cauca Valley from the north, whereas H. c. weymeri did so by crossing the Andes in the southern part, implying a secondary contact origin. Colonization of the valley by H. cydno was accompanied by mimicry shift. Strong ecological isolation, driven by locally adaptive differences in mimetic wing patterns, is playing an important role in maintaining the hybrid zone. However, selection on wing pattern alone is not sufficient to explain the genetic discontinuity observed. There is evidence for differences in male mating preference, but the contribution of additional barriers needs further investigation. Overall, our results support the idea that speciation is a cumulative process, where the combination of multiple isolation barriers, combined with major phenotypic differences, facilitates population divergence in face of gene flow.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".