Population divergence in the eastern North American boreal forests: Extensive gene flow and genetic swamping characterize the Palm Warbler subspecies hybrid zone (Parulidae: Setophaga palmarum )
Bibliographic record
Abstract
not-yet-known not-yet-known not-yet-known unknown Pleistocene glaciations have shaped much of the population divergence events in the coniferous forests of North America. However, while the evidence for forest fragmentation and population divergence associated with glacial cycles is well-established in western North America, whether glaciation has served a similar role in the boreal forests of eastern North America is unclear. Here, we present the first analyses for an avian hybrid zone in boreal eastern North America between two subspecies of Palm Warblers (Setophaga palmarum). Using both genomic and plumage datasets, we characterize the divergence history of the two subspecies and relate our findings to the larger biogeographic patterns in the region. The Palm Warbler subspecies diverged in the Pleistocene (around 775 KYA) and appears to have experienced near-continuous gene flow since initial splitting with little evidence for reproductive isolation. Demographic modelling indicates that following divergence, the western subspecies expanded eastwards in breeding range and displaced the genetic ancestry of its eastern counterpart, resulting in the current hybrid zone. The timing and patterns of divergence for the Palm Warbler subspecies is largely congruent with the sole other known case of avian divergence in the region, which likely reflects a shared biogeographic history involving multiple eastern boreal refugia. However, the apparent ongoing collapse of the Palm Warbler subspecies post-divergence suggests that the differentiation generated through these eastern refugia were likely not sufficient in establishing strong reproductive isolation, which perhaps explain why speciation events have been relatively rare in the eastern boreal forests of North America.
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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 | 0.000 |
| 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".