Fine-scale genetic structure in populations of<i>Quercus variabilis</i>(Fagaceae) from southern Korea
Bibliographic record
Abstract
Quercus variabilis Blume (Fagaceae) is a deciduous broad-leaved tree, and an important forest element among the hillsides of southern Korea. To date, there are contrasting results with respect to fine-scale spatial genetic structure among adults in populations of several oak species; some studies have shown evidence of significant within-population spatial genetic structure, while others found weak or little evidence of fine-scale genetic structuring within populations. We used allozyme loci, Wright's F statistics, and multilocus spatial autocorrelation statistics to examine the distribution of genetic diversity and the spatial genetic structure within three undisturbed populations at a landscape level (72.5 ha, 500 × 1450 m) on Dolsan Island, South Korea. The spatial autocorrelation analyses of adults showed little evidence of fine-scale genetic structuring within populations, which could be due to random mortality among related seedlings, resulting in extensive thinning within maternal half-sib groups. Alternatively, low genetic differentiation between adjacent populations (mean FST= 0.023) and little within-population spatial genetic structure suggest probable secondary acorn movement by animals. Our results are very similar to those observed in three populations of Quercus acutissima at a landscape level (15 ha, 250 × 600 m) on Oenaro Island, South Korea. Together, these studies describe relatively subtle differences in genetic structure among adjacent populations of oaks on southern islands in Korea.Key words: allozymes, Quercus variabilis, Fagaceae, landscape level, multiple populations, spatial genetic structure.
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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) | 0.000 | 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".