Phylogeographic pattern of Populus cathayana in the southeast of Qinghai-Tibetan Plateau of China revealed by cpSSR markers
Bibliographic record
Abstract
The vegetation in the Qinghai-Tibetan Plateau is thought to be highly sensitive and more vulnerable to global climate change than that of other areas. The uplift of the plateau as well as the climatic oscillations during glacial periods had a profound impact on plant species distribution and genetic diversity there. In the present study, seven pairs of cpSSR (chloroplast Simple Sequence Repeat) primers were utilized to detect genetic varieties of Populus cathayana Rehd populations from their natural range in the southeastern areas of Qinghai-Tibetan Plateau. A total of 28 alleles and 12 different haplotypes were detected. The proportion of haplotype variation among populations (G = 0.794, N = 0.900) indicated high level of genetic differentiation among populations and a significant phylogeographic structure (N > G, P < 0.05). This appears to support the hypothesis that these populations were derived from multiple refugia areas during the Quaternary climatic oscillations. Based on the haplotype network and mismatch distribution analyses, we found no evidence of postglacial range recolonization and expansion by P. cathayana in this region. This might be mainly due to the complex topography of the southeastern part of the Qinghai-Tibetan Plateau. The lofty mountain ranges and deep valleys in this region might have prevented long-distance migrations of this species during the climatic amelioration.STSTSTST
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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".