Modelling local and long‐distance dispersal of invasive emerald ash borer <i>Agrilus planipennis</i> (Coleoptera) in North America
Bibliographic record
Abstract
ABSTRACT Limiting the damage by non‐indigenous species requires rapid determination of current and potential distributions and vectors of dispersal, and development of appropriate management measures. The emerald ash borer ( Agrilus planipennis ), a wood‐boring beetle native to South‐East Asia, was first reported in the Great Lakes region during summer 2002. The beetle poses an enormous threat to native ash ( Fraxinus ) species of North America, as untreated trees in infested areas of Ontario, Michigan and Ohio suffer high mortality. We demonstrate that the borer has spread in North America through a combination of diffusive range extension, associated with local flights, and by long‐distance ‘jump’ dispersal associated with human movement of infested sapling or contaminated firewood. Probability of infestation was inversely related to distance from borer epicentres but positively related to the size of human population centres. At least 9 of 39 populations that were first reported in Michigan during 2004 cannot be accounted for by local diffusion, raising the possibility that other unidentified mechanisms may be contributing to the dispersal of the beetle. In the absence of quarantine, by 2005 all of Michigan's lower peninsula was contained within the boundaries of potential diffusive range expansion. Infested ash saplings also were introduced from Michigan to Maryland during 2003, and subsequently transplanted to five sites in Maryland and Virginia. Quarantine and eradication measures have had mixed results: in the south‐central USA, the species appears on the brink of eradication, whereas its distribution has continued to spread during 2005 in the Great Lakes region despite extensive containment and quarantine measures. Quarantine success in the Great Lakes region is encumbered by multiple dispersal vectors, larger borer population sizes and by the more extensive geographical distribution that was achieved prior to implementation of control measures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".