Efficacy of the pheromone (3<i>Z</i>)‐lactone and the host kairomone (3<i>Z</i>)‐hexenol at detecting early infestation of the emerald ash borer, <i><scp>A</scp>grilus planipennis</i>
Bibliographic record
Abstract
Abstract The invasive emerald ash borer, Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), is a major pest of ash trees, Fraxinus spp., in its introduced range in North America. Field studies were conducted to quantify the efficacy of traps baited with kairomone and pheromone lures for early detection of A. planipennis infestation. A trapping experiment demonstrated that green traps baited with the kairomone (3Z)‐hexenol detected at least one adult A. planipennis in 55.3% of plots with ‘nil to low’‐density infestations and in 100% of plots with ‘moderate to high’‐density A. planipennis infestations. Mean trap captures increased significantly with increasing infestation density. In terms of the optimal number of traps per plot, when one (3Z)‐hexenol‐baited trap was placed per plot, the trap detected populations in 62% of the plots with ‘low to moderate’‐density infestations through branch sampling. Detectability was increased to 82% when two traps were placed per plot. Finally, addition of female‐produced (3Z)‐lactone pheromone to traps significantly increased detection rates at both the trap and plot level, as compared with traps baited with the host volatile, (3Z)‐hexenol, alone (88 vs. 60%, respectively). Our results are the first to demonstrate the efficacy of baited green sticky traps for detecting low‐density A. planipennis infestations, particularly when the (3Z)‐lactone pheromone is used. This combination is therefore recommended for development of early‐detection protocols against A. planipennis.
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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 | 0.001 | 0.001 |
| 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".