Tracing the invasion of a leaf-mining moth in the Palearctic through DNA barcoding of historical herbaria
Bibliographic record
Abstract
Abstract Historical herbaria are valuable sources of data in invasion biology. Here we study the invasion history of the lime leaf-miner, Phyllonorycter issikii , by surveying over 15 thousand herbarium specimens of limes ( Tilia spp.) collected in the Palearctic during last 253 years (1764–2016). The majority of herbarium specimens with the pest’s mines (89%) originated from East Asia (1859–2015), whereas remaining 11% of specimens with the mines came from Europe, European Russia and Western Siberia (1987–2015). These results support the hypothesis of a recent Ph. issikii invasion from Eastern to Western Palearctic. Single molecule real-time sequencing of the COI barcode region of 93 archival larvae and pupae (7–162 years old) dissected from the mines on historical herbaria allowed to distinguish between Ph. issikii and Ph. messaniella , a polyphagous species rarely feeding on Tilia , which mines were found in herbarium from Europe dated by 1915–1942. We discovered 25 haplotypes of Ph. issikii , of which 16 haplotypes were present solely in East Asia, and revealed wide distribution of the species in China. Six haplotypes shared between Eastern and Western Palearctic suggest the contribution of Ph. issikii populations from the Russian Far East, China and Japan to the westward invasion.
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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 | 0.002 | 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".