Simulating the effectiveness of three potential management options to slow the spread of emerald ash borer (<i>Agrilus planipennis</i>) populations in localized outlier sites
Bibliographic record
Abstract
The emerald ash borer, Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), is a devastating, invasive insect pest of ash trees, Fraxinus spp., in North America. Using a simulation model, we evaluated three potential management options to slow the spread of A. planipennis in discrete outlier sites: (i) removing ash trees to reduce available host phloem resource, (ii) girdling ash trees to attract ovipositing female beetles and destroying the trees before larvae complete development, and (iii) applying a highly effective systemic insecticide. Simulations indicate that systemic insecticide applications provided the greatest reduction in the radial spread of A. planipennis. In simulations in which management options were applied only within a 300 m radius from the origin of the infestation, insecticide applications reduced the radial spread by 30% and larval consumption of ash phloem by 40% beyond the treated area. In contrast, girdling ash trees reduced the radial spread by 15% and larval consumption of ash phloem by 20% beyond the treated area. Both of these management options significantly reduced the spread of A. planipennis when treatments were applied 1 to 4 years after infestations were initiated. Reducing ash phloem by removing ash trees decreased population size within treated areas but did not reduce the radial spread, population size, or larval consumption of ash phloem beyond treated areas.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".