Prediction of the potential global distribution of the Asian longhorned beetle <i>Anoplophora glabripennis</i> (Coleoptera: Cerambycidae) under climate change
Bibliographic record
Abstract
Abstract The Asian longhorned beetle (ALB) Anoplophora glabripennis (Motschulsky) (Coleoptera: Cerambycidae) is an important wood‐boring pest that has caused substantial damage to broadleaf trees in Asia, North America, and Europe. We used the modelling software CLIMEX to project the potential global distribution of ALB based on both historical (1987–2016) and future (2021–2050) climate conditions. ALB has possible hosts in 37 genera, and their known distributions were incorporated into the model to assess their effect on pest distribution. Suitable regions for ALB are predicted to be widely distributed under both historical and future climate conditions, and across all continents except Antarctica. With climate change, climate suitability would increase in the regions north of 30°N and decline in most regions south of 30°N. The area of most climate‐suitable regions would be covered by potential hosts, and optimum hosts would dominate. The possibility of ALB outbreaks in the Northern Hemisphere is much higher than in the Southern Hemisphere, owing to the richer abundance of hosts. These results provide theoretical guidance for developing effective ALB monitoring and mitigation 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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".