Postzygotic isolation drives genomic speciation between highly cryptic<i>Hypocnemis</i>antbirds from Amazonia
Bibliographic record
Abstract
How species evolve reproductive isolation in the species-rich Amazon basin is poorly understood in vertebrates. Here, we sequenced a reference genome and used a genome-wide sample of SNPs to analyze a hybrid zone between two highly cryptic species of Hypocnemis warbling-antbirds—the Rondonia warbling-antbird (H. ochrogyna) and Spix's warbling-antbird (H. striata)—in a headwater region of southern Amazonia. We found that both species commonly hybridize, producing F1s and a variety of backcrosses with each species but we detected only one F2-like hybrid. Patterns of heterozygosity, hybrid index, and interchromosomal linkage disequilibrium in hybrid populations closely match expectations under strong postzygotic isolation. Hybrid zone width (15.4 km) was much narrower than expected (211 km) indicating strong selection against hybrids. A remarkably high degree of concordance in cline centers and widths across loci, and a lack of reduced interspecific Fst between populations close to versus far from the contact zone, suggest that genetic incompatibilities have rendered most of the genome immune to introgression. These results support intrinsic postzygotic isolation as a driver of speciation in a moderately young cryptic species pair from the Amazon and suggest that species richness of the Amazon may be grossly underestimated.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".