Applied Chemical Ecology of the Western Pine Beetle, an Important Pest of Ponderosa Pine in Western North America
Bibliographic record
Abstract
Western pine beetle (Dendroctonus brevicomis LeConte) is a major cause of ponderosa pine (Pinus ponderosa Dougl. ex. Laws.) mortality in western North America. Twenty-first century epidemics are among the largest in history and have affected hundreds of thousands of hectares. We synthesize literature on the chemical ecology of western pine beetle and on efforts to exploit our understanding of the western pine beetle-ponderosa pine system to reduce host tree losses. This literature dates back to the early 20th century and focuses on populations in California and Oregon, U.S., where western pine beetle exerts its largest impacts. Research in the 1960s–1970s yielded an effective semiochemical attractant (exo-brevicomin, frontalin, and myrcene) that helped inform understanding of the biology, ecology, and management of this species. Later, research focused on isolation and identification of semiochemical repellents. To date, Verbenone Plus (acetophenone, (E)-2-hexen-1-ol + (Z)-2-hexen-1-ol, and verbenone) is the only semiochemical repellent demonstrated effective for protecting ponderosa pines from mortality attributed to western pine beetle in multiple studies in Canada and the U.S.
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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 | 0.001 | 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".