An invasive urban forest pest invades natural environments — Asian longhorned beetle in northeastern US hardwood forests
Bibliographic record
Abstract
An infestation of Asian longhorned beetle (ALB) ( Anoplophora glabripennis (Motschulsky)) was detected in Worcester, Massachusetts, in 2008. The discovery of this pest, previously only seen in urban environments of North America, led to the unprecedented establishment of a 243 km 2 quarantine zone that included urban parks, neighborhoods, and natural forests. Because ALB behavior in forested stands is virtually unknown, two closed-canopied forested stands (Bovenzi and Delaval) infested with ALB within this zone were sampled during 2008–2010 to document stand conditions, assess ALB host selection, and determine ALB impact on tree growth. Thirty-two percent of the Acer sampled in Bovenzi were infested with ALB compared with 63% in Delaval. In Delaval where three maple host species were available, ALB was found more often in Acer rubrum L. than in Acer saccharum Marsh. or Acer platanoides L. Radial growth patterns did not differ between ALB-infested and uninfested Acer trees in Bovenzi. In contrast, ALB-infested trees in Delaval were significantly older and larger than uninfested trees and exhibited slower radial growth and ring width index patterns compared with uninfested trees. Results suggest that if left uncontrolled, ALB can readily disperse into natural forest landscapes and alter the makeup of North America’s hardwood forest region.
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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 | 0.000 |
| 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) | 0.001 | 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".