Evidence for Asymmetrical Divergence-Gene Flow of Nuclear Loci, but Not Mitochondrial Loci, between Seabird Sister Species: Blue-Footed (Sula nebouxii) and Peruvian (S. variegata) Boobies
Bibliographic record
Abstract
Understanding the process of speciation requires understanding how gene flow influences divergence. Recent analyses indicate that divergence can take place despite gene flow and that the sex chromosomes can exhibit different levels of gene flow than autosomes and mitochondrial DNA. Using an eight marker dataset including autosomal, z-linked, and mitochondrial loci we tested the hypothesis that blue-footed (Sula nebouxii) and Peruvian (S. variegata) boobies diverged from their common ancestor with gene flow, paying specific attention to the differences in gene flow estimates from nuclear and mitochondrial markers. We found no gene flow at mitochondrial markers, but found evidence from the combined autosomal and z-linked dataset that blue-footed and Peruvian boobies experienced asymmetrical gene flow during or after their initial divergence, predominantly from Peruvian boobies into blue-footed boobies. This gene exchange may have occurred either sporadically between periods of allopatry, or regularly throughout the divergence process. Our results add to growing evidence that diverging species can remain distinct but exchange genes.
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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 | 0.002 |
| 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 | 0.000 |
| 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".