A Bird’s Eye View of Speciation with Gene Flow: Insights from Genetic Clines Across the Yellow-Rumped Warbler Hybrid Zone
Bibliographic record
Abstract
When divergent populations come into contact and interbreed, incompatible genotypes can result in decreased hybrid fitness and partial reproductive isolation. By studying patterns of gene flow between populations, we can identify the genetic, phenotypic, and ecological components of partial reproductive isolation. Using whole-genome sequence data generated from 1201 yellow-rumped warblers (Setophaga coronata coronata, S. c. auduboni, and their hybrids), we measure variation of a hybrid zone’s position in space and over time, identify genomic regions where gene flow is restricted, and compare the genetic basis of reproductive barriers to the genetic basis of plumage traits. We find that reproductive isolation is generated by the effects of many loci throughout the genome, with a large influence of the sex-chromosomes, that “barrier loci” cluster in some highly differentiated regions, and that gene flow and introgression are broadly asymmetric. Barrier loci show strong linkage disequilibrium, which augments the strength of the barrier to gene flow and may indicate the presence of genetic incompatibilities. Clines in plumage traits and their associated SNPs suggest strong selection against some hybrid phenotypes, although loci with the strongest associations with plumage color traits do not exhibit the strongest barrier to 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".