Response of <i>Dendroctonus brevicomis</i> to different release rates of nonhost angiosperm volatiles and verbenone in trapping and tree protection studies
Bibliographic record
Abstract
Abstract A blend of eight nonhost angiosperm volatiles (benzyl alcohol, benzaldehyde, guaiacol, nonanal, salicylaldehyde, (E)‐2‐hexenal, (E)‐2‐hexen‐1‐ol and (Z)‐2‐hexen‐1‐ol) without [NAV] and with [NAVV] (–)‐verbenone (4,6,6‐trimethylbicyclo[3.1.1]hept‐3‐en‐2‐one) were tested at low (L), medium (M) and high (H) release rates for their ability to reduce attraction of western pine beetle, Dendroctonus brevicomis LeConte, to attractant‐baited (exo‐brevicomin [racemic, 3 mg/d], frontalin [racemic, 3 mg/d] and myrcene [18 mg/d]) multiple funnel traps. NAV‐L (40 mg/d) had no significant effect. Verbenone alone (50 mg/d) and NAV‐M (240 mg/d) both significantly reduced attraction, but no significant difference was observed between the two treatment means. NAV‐H (430 mg/d) significantly reduced catches by ∼60% and 78% compared to verbenone alone and the baited control, respectively. In a second experiment, combining (–)‐verbenone with NAV (NAVV) increased the effects observed in Experiment 1. NAVV‐M (240 mg/d) resulted in an ∼69% and 83% reduction in trap catch compared to verbenone alone and the baited control, respectively. Significantly fewer D. brevicomis were captured in NAVV‐H (430 mg/d) than any other treatment resulting in an ∼93% reduction in trap catch compared to the baited control. In a third experiment, NAVV was tested at three release rates for its ability to protect individual ponderosa pines, Pinus ponderosa Dougl. ex Laws., from attack by D. brevicomis. Cumulative release rates varied in direct proportion to tree diameter, but represented quarter, half and full NAVV rates. NAVV significantly reduced the density of D. brevicomis attacks, D. brevicomis successful attacks, and levels of tree mortality on attractant‐baited trees. Only three of 15 NAVV‐treated trees died from D. brevicomis attack while ∼93% mortality (14/15) was observed in the untreated, baited control. Quarter and half rates were ineffective for reducing tree mortality.
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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".