Impact of Soil Type, Moisture, and Depth on Swede Midge (Diptera: Cecidomyiidae) Pupation and Emergence
Bibliographic record
Abstract
Contarinia nasturtii (Kieffer) (Diptera: Cecidomyiidae), a common insect pest in Europe and a new invasive pest in North America, causes severe damage to cruciferous crops. Currently, many counties in Canada and the United States in which C. nasturtii has not been previously reported are at risk of being infested by C. nasturtii. Effectiveness of chemical control is limited, especially under high population pressure in fields, because the cryptic habits of C. nasturtii protect them from insecticidal sprays. Alternative management strategies against C. nasturtii that are needed to protect crucifers and soil management for the pupal stage were studied as one option. Six different types of soils (loam fine sand, fine sand, clay loam, muck, Chenango shale loam, and silt loam soil) were collected from commercial cabbage fields in New York and studied in the laboratory for their impact on C. nasturtii pupation and emergence. The results indicated that extremely wet or dry soils significantly hindered C. nasturtii emergence, regardless of soil type, suggesting that soil type alone may not be a major factor regulating C. nasturtii abundance. Optimal moisture content for C. nasturtii emergence varied for different soils. Most C. nasturtii pupated within the top 1 cm of soil. Furthermore, we found that >5 cm of soil cover effectively reduced the emergence number and delayed the time of emergence. Based on these results, we suggest that soil manipulation (moisture content and cultivation practices) should be considered as an important component in an overall integrated pest management program for C. nasturtii.
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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".