AFLP analyses of genetic variation of <i>Eupatorium adenophorum</i> (Asteraceae) populations in China
Bibliographic record
Abstract
The Eupatorium adenophorum is one of the most widespread invasive alien species in China. In the present study, the genetic variation and population structure of this species were analyzed using amplified fragment length polymorphism (AFLP) markers. Nine primer pairs were selected for the analysis and 685 bands were produced, among which 474 bands were polymorphic (PPB = 69.2%). Diversity levels within populations were relatively high (mean expected heterozygosity = 0.188, mean Shannon index = 0.296). Regression analysis showed a significant positive relationship between Shannon genetic diversity and altitude (R2 = 0.31). However, there was a negative correlation between Shannon genetic diversity and latitude (R2 = 0.16), as well as between Shannon genetic diversity and longitude (R2 = 0.45). Cluster analysis grouped the majority of the weed populations into three main clusters that corresponded with the geographic regions. At the regional level, the AMOVA indicated that about 70% of the variations in the data set were from genotypic variations within populations, 13.3% of the variations were due to regional differences, and the remaining 16.6% were due to differences among populations within the provincial regions. The results imply that most individuals tested in the present study should have been produced through seeds, and the process of colonization resulted in progressive loss of genetic diversity from the southwest to the northeast of China. Key words: Amplified fragment length polymorphism, invasive species, Eupatorium adenophorum, diversity, genetic variation, population 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".