Phylogeographic Analysis to Understand the Origin, Speciation and Biogeographic Expansion of the Invasive Asian Hornet, Vespa velutina
Bibliographic record
Abstract
The Asian hornet, Vespa velutina, is an invasive species that has not only expanded its range in Asia but also invaded European countries, incurring significant costs on the local honey and bee industry. This phylogeographic study aims to trace the evolutionary trajectory of V. velutina and its close relatives, aiming to identify features that characterize an invasive species. The last successful invasion of Vespa velutina into France occurred in 2002.40, and into South Korea in 2002.77, estimated by fitting a logistic equation to the number of observations over time. The instantaneous rate of increase is 1.3667 for V. velutina in France and 0.2812 in South Korea, consistent with the interpretation of little competition in France and strong competition from local hornet species in South Korea. The invasive potential of two sister lineages can be compared by their distribution area when proper statistical adjustments are made to account for differences in sample size. V. velutina has a greater invasive potential than its sister lineage. The ancestor of V. velutina split into two lineages, one found in Indonesia/Malaysia and the other colonizing the Asian continent. The second lineage split into a sedentary clade inhabiting Pakistan and India, and an invasive lineage colonizing much of Southeast Asia. This latter lineage gave rise to subspecies V. v. nigrithorax that invaded France, South Korea, and Japan. My software PGT, which generates geophylogenies and computes geographic areas for individual taxa, is useful for understanding biogeography in general and invasive species in particular. I discussed the conceptual formulation of an index of invasiveness for comparison between sister lineages.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".