Ecological niche modeling and potential dispersal of emerald ash borer in the Pacific Northwest
Bibliographic record
Abstract
The emerald ash borer, Agrilus planipennis Fairmire (Coleoptera: Buprestidae), is a notorious invasive pest that can devastate ash trees, Fraxinus spp. L., and embedded communities. While emerald ash borer is established in eastern North America, it was recently detected in Forest Grove, Oregon and in Vancouver, British Columbia, raising concerns that it may spread across the Pacific Northwest riparian ecosystems dominated by ash. A quarantine zone has been established in Oregon, but future mitigation depends on assessing the spread to new regions. Here, we used habitat suitability models and dispersal simulations to predict the potential spread of emerald ash borer. Specifically, we compared climate spaces occupied by Oregon and British Columbia populations with other native and introduced populations, and then used habitat suitability models and dispersal simulations to predict future distributions. We show that the newly established Oregon and British Columbia populations currently occupy relatively narrow climate niche, and many suitable niche spaces are unoccupied in the Pacific Northwest, indicating potential for range expansion. We also show there are vast areas of suitable habitat that extend south of the present quarantine zone throughout inland western Oregon and north into Washington. In Vancouver, the most suitable habitat was found along the Fraser River, where emerald ash borer could disperse inland. Dispersal models suggest that, without intervention, emerald ash borer could disperse into Washington within 2 yr, throughout western Oregon in 15 yr, and reach California in 20 yr. Our work supports intensive quarantine efforts for emerald ash borer and identifies areas where monitoring and management efforts should focus.
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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 | 0.000 | 0.000 |
| Open science | 0.001 | 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".