Effect of Verbenone on Attraction of Predatory and Woodboring Beetles (Coleoptera) to Kairomones in Lodgepole Pine Forests
Bibliographic record
Abstract
The response of bark beetle predators and woodboring beetles to the bark beetle anti-aggregation pheromone, verbenone, was tested in the field with multiple-funnel traps baited with attractant kairomones. Catches of the predators Thanasimus undatulus (Say), Enoclerus sphegeus (F.), Enoclerus lecontei (Wolcott) (Coleoptera: Cleridae), and Lasconotus complex LeConte (Coleoptera: Colydiidae) declined significantly with increasing release rates of verbenone. Lasconotus subcostulatus Kraus, and Corticeus praetermissus (Fall) (Coleoptera: Tenebrionidae) (in two of three experiments), showed no significant response to verbenone. In a third experiment, catches of C. praetermissus increased with verbenone dose. Likewise, catches of the striped ambrosia beetle, Trypodendron lineatum (Olivier) (Coleoptera: Scolytidae), increased with verbenone dose in one experiment, but there was no effect in two other experiments. Verbenone had no effect on the response of Spondylis upiformis Mannerheim (Coleoptera: Cerambycidae). We hypothesize that predators specializing on early successional bark beetles are repelled by verbenone since this compound indicates a late stage attack. Generalist predators and woodborers either do not respond to verbenone at all, or they may be attracted by it.
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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".