Phylogenomics reveals a complex evolutionary history of lobed-leaf white oaks in western North America
Bibliographic record
Abstract
Species within the genus Quercus (oak) hybridize in complex patterns that have yet to be fully explored with phylogenomic data. Analyses to date have recovered reasonable divergent patterns, suggesting that the impact of introgression may not always be obvious in inferred oak phylogenies. We explore this phenomenon using RADseq data for 136 samples representing 54 oak species by conducting phylogenetic analyses designed to distinguish signals of lineage diversification and hybridization, focusing on the lobed-leaf species Quercus gambelii, Q. lobata, and Q. garryana in the context of a broad sampling of allied white oaks (Quercus section Quercus), and particularly the midwestern Q. macrocarpa. We demonstrate that historical introgressive hybridization between once sympatric species affects phylogeny estimation. Historical range expansion during periods of favorable climate likely explains our observations; analyses support genetic exchange between ancestral populations of Q. gambelii and Q. macrocarpa. We conclude that the genomic consequences of introgression caused the attraction of distant lineages in phylogenetic tree space, and that introgressive and divergent signals can be disentangled to produce a robust estimate of the phylogenetic history of the species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".