Evaluation of pheromone- and floral-baited traps for monitoring western corn rootworm (Coleoptera: Chrysomelidae) beetles in Canada
Bibliographic record
Abstract
Western corn rootworm (WCR), Diabrotica virgifera virgifera, was first detected in British Columbia (BC) in 2016, resulting in the need for a trapping method that can detect beetles at low population levels and that can potentially mass trap beetles in sweet corn processing and distribution outlets. Based on early field experiments run in BC in 2019 and 2020, four trap types, baited with sex pheromone or floral lures, were evaluated in BC, Ontario, and Quebec for two 2-week periods during the swarming period in 2021. Trap captures were scored 0–10 based on relative captures, with the method with greatest captures scored as 10. Captures of male beetles were greatest on pheromone-baited PAL (“cloak”) (mean score of all 2021 experiments = 9.6) and PALs traps (8.6), and significantly lower with pheromone-baited Delta (3.4) and KLP (“hat”) (1.5), or floral-baited PAL (2.1) and PALs traps (1.9). Captures of female beetles were greatest on floral-baited PALs (8.7), PAL (8.4), and Delta traps (5.0), and low on KLP (1.5) and all other trapping methods (<1). In follow-up experiments run in 2023, pheromone-baited PAL traps captured >180× more beetles than non-baited Pherocon AM traps. Together these results indicate that PAL, PALs, and Delta traps can be used for the early detection of male and female WCR when baited with pheromone and floral lures, respectively, in Canada, both to determine the onset of the beetle swarming season for timing of foliar insecticide applications, and to monitor the spread of WCR to new areas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".