Optimizing Trap Design and Trapping Protocols for <I>Drosophila suzukii</I> (Diptera: Drosophilidae)
Why this work is in the frame
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Bibliographic record
Abstract
Drosophila suzukii Matsumura (Diptera: Drosophilidae) is a recent invasive pest of fruit crops in North America and Europe. Carpophagous larvae render fruit unmarketable and may promote secondary rot-causing organisms. To monitor spread and develop programs to time application of controls, further work is needed to optimize trap design and trapping protocols for adult D. suzukii. We compared commercial traps and developed a new, easy-to-use plastic jar trap that performed well compared with other designs. For some trap types, increasing the entry area led to increased D. suzukii captures and improved selectivity for D. suzukii when populations were low. However, progressive entry area enlargement had diminishing returns, particularly for commercial traps. Unlike previous studies, we found putting holes in trap lids under a close-fitting cover improved captures compared with holes on sides of traps. Also, red and black traps outperformed yellow and clear traps when traps of all colors were positioned 10-15 cm apart above crop foliage. In smaller traps, attractant surface area and entry area, but not other trap features (e.g., headspace volume), appeared to affect D. suzukii captures. In the new, plastic jar trap, tripling attractant volume (360 vs 120 ml) and weekly attractant replacement resulted in the highest D. suzukii captures, but in the larger commercial trap these measures only increased by-catch of large-bodied Diptera. Overall, the plastic jar trap with large entry area is affordable, durable, and can hold high attractant volumes to maximize D. suzukii capture and selectivity.
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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) | 0.001 | 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 it