Genetic analyses reveal regional structure and demographic expansion of the predominant tea pest <scp><i>Empoasca onukii</i></scp> (Hemiptera: Cicadellidae) in China
Bibliographic record
Abstract
BACKGROUND: The tea green leafhopper, Empoasca onukii Matsuda, is the most destructive insect pest of tea plantations in East Asia. Despite its economic importance and previous studies on this species, it remains unclear as to how this small-sized pest can have such wide range. RESULTS: By sequencing three mitochondrial genes and 17 microsatellite loci, we revealed the regional structure and demographic expansion of 59 E. onukii populations in China. Bayesian analysis of population genetic structure (BAPS) on microsatellites identified four genetic groups with spatial discontinuities, while analysis on mitochondrial genes inferred five nested and differentiated clusters. Both the Mantel test and the generalized linear model indicated a significant pattern of isolation by geographic distance in E. onukii populations. Based on the approximate Bayesian computation approach, E. onukii was found to have originated from southwestern China and expanded northward and eastward. While MIGRATE-N and Bayesian stochastic search variable selection (BSSVS) procedure in BEAST confirmed the possible eastward and northward dispersal from Yunnan, they also detected more gene flow from the derived populations in central and southeastern China. CONCLUSION: Our results suggest that the current distribution and structure of E. onukii is complicatedly influenced by human activities of cultivation, wide dissemination of tea in ancient China as well as recent transportation of tea seedlings for establishing new tea plantations. Insights into genetic differentiation and demographic expansion patterns from this study provide an important basis for the development of area-wide management of the E. onukii populations. © 2022 Society of Chemical Industry.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 teacher head, 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".