Divergence maintained by climatic selection despite recurrent gene flow: a case study of <i>Castanopsis carlesii</i> (Fagaceae)
Bibliographic record
Abstract
Local adaptation to different environments has the potential to maintain divergence between populations despite recurrent gene flow and is an important driver for generating biological diversity. In this study, we investigate the role of adaptation in the maintenance of two parapatric varieties of a forest tree. We used sequence variation of chloroplastic DNA and restriction site-associated DNA to investigate the genetic structure of two varieties of Castanopsis carlesii in subtropical China and relate it to climatic variation. We used niche reconstruction methods to investigate niche differentiation between the two varieties and to estimate the past distribution of this species. A deep divergence was observed between the two varieties, but evidence of introgression and genetic admixture was detected in two phenotypically and geographically intermediate populations. Niche reconstruction suggests that the distribution of the two varieties was disjunct during periods of global cooling and that the two varieties occupy significantly different niches. The genetic structure was mainly driven by environmental factors, and 13 outlier loci under divergent selection were correlated with climatic variation. These results suggest that the two varieties evolved in allopatry and came back into secondary contact after the last glacial maximum and that they are an evolutionary example of divergence maintained by climatic selection despite recurrent 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 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".