Efficacy of “Verbenone Plus” for Protecting Ponderosa Pine Trees and Stands From <I>Dendroctonus brevicomis</I> (Coleoptera: Curculionidae) Attack in British Columbia and California
Bibliographic record
Abstract
The western pine beetle, Dendroctonus brevicomis LeConte (Coleoptera: Curculionidae, Scolytinae), is a major cause of ponderosa pine, Pinus ponderosa Douglas ex Lawson, mortality in much of western North America. We review several years of research that led to the identification of Verbenone Plus, a novel four-component semiochemcial blend [acetophenone, (E)-2-hexen-1-ol + (Z)-2-hexen-1-ol, and (-)-verbenone] that inhibits the response of D. brevicomis to attractant-baited traps, and examine the efficacy of Verbenone Plus for protecting individual trees and forest stands from D. brevicomis infestations in British Columbia and California. In all experiments, semiochemicals were stapled around the bole of treated trees at approximately equal to 2 m in height. (-)-Verbenone alone had no effect on the density of total attacks and successful attacks by D. brevicomis on attractant-baited P. ponderosa, but significantly increased the percentage of pitchouts (unsuccessful D. brevicomis attacks). Verbenone Plus significantly reduced the density of D. brevicomis total attacks and D. brevicomis successful attacks on individual trees. A significantly higher percentage of pitchouts occurred on Verbenone Plus-treated trees. The application of Verbenone Plus to attractant-baited P. ponderosa significantly reduced levels of tree mortality. In stand protection studies, Verbenone Plus significantly reduced the percentage of trees mass attacked by D. brevicomis in one study, but in a second study no significant treatment effect was observed. Future research should concentrate on determining optimal release rates and spacings of release devices in stand protection studies, and expansion of Verbenone Plus into other systems where verbenone alone has not provided adequate levels of tree protection.
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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".