Use of semiochemical-baited traps to monitor the range expansion of the invasive <i>Sitona lineatus</i> (Curculionidae: Coleoptera) and the presence of associated ground beetles
Bibliographic record
Abstract
Abstract The invasive pea leaf weevil, Sitona lineatus (Linnaeus) (Coleoptera: Curculionidae), damages field peas, Pisum sativum Linnaeus (Fabaceae), and faba beans, Vicia faba Linnaeus (Fabaceae), on the Canadian prairies. We used semiochemical-baited pitfall traps to monitor and detect S. lineatus range expansion and capture associated predaceous ground beetles (Coleoptera: Carabidae) in pulse-growing regions across Alberta. Traps captured male and female S. lineatus in all pulse-growing regions in the spring and fall, including a first record of S. lineatus in the Peace River region of northwestern Alberta. Pheromone-baited traps captured more weevils than unbaited traps did, and the addition of host plant volatiles did not increase the catch. More weevils were captured in traps in pea fields compared to in faba bean fields. Rubber septa lures released more pheromones and attracted a similar number or more weevils to traps than microcentrifuge tube lures did. Ground beetle capture was not affected by semiochemical baits targeting S. lineatus. Ground beetle diversity varied by region and collection period, but the most frequently collected species was Pterostichus melanarius, a potential predator of S. lineatus. This study shows that pitfall traps baited with rubber septa pheromone lures can be used to monitor new and expanding S. lineatus populations, as well as potential natural enemy communities.
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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".