Potential Economic Impacts of the Asian Longhorned Beetle (Coleoptera: Cerambycidae) in Eastern Canada
Bibliographic record
Abstract
The Asian longhorned beetle (Anoplophora glabripennis Motschulsky) continues to pose a significant risk to deciduous forests around the world. We assess Asian longhorned beetle-related risks in eastern Canada by generating current and future climate suitability maps, import-based likelihood of introduction estimates for each urban center in our study area, and potential economic impacts in both urban and natural settings. For the current period, climatic suitability for Asian longhorned beetle was highest in southern Ontario, but was projected to expand significantly northward and eastward by midcentury. High likelihood of Asian longhorned beetle introduction was associated with large urban centers, but also smaller centers with high levels of pest-associated imports. Potential costs for the removal and replacement of Asian longhorned beetle-impacted street trees ranged from CDN$8.6 to $12.2 billion, with the exact amount and city-level ranking depending on the method used to calculate risk. Potential losses of merchantable maple (Acer) timber were estimated at CDN$1.6 billion using provincial stumpage fees and CDN$431 million annually when calculated using a combination of economic and forestry product statistics. The gross value of edible maple products, which could potentially be affected by Asian longhorned beetle, was estimated at CDN$358 million annually. These values can help inform the scale of early detection surveys, potential eradication efforts, and research budgets in the event of future Asian longhorned beetle introductions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".