Field-scale examination of neonicotinoid insecticide persistence in soil as a result of seed treatment use in commercial maize (corn) fields in southwestern Ontario
Bibliographic record
Abstract
Neonicotinoid insecticides, especially as seed treatments, have raised concerns about environmental loading and impacts on pollinators, biodiversity, and ecosystems. The authors measured concentrations of neonicotinoid residues in the top 5 cm of soil before planting of maize (corn) in 18 commercial fields with a history of neonicotinoid seed treatment use in southwestern Ontario in 2013 and 2014 using liquid chromatography-tandem mass spectrometry with electrospray ionization. A simple calculator based on first-order kinetics, incorporating crop rotation, planting date, and seed treatment history from the subject fields, was used to estimate dissipation rate from the seed zone. The estimated half-life (the time taken for 50% of the insecticide to have dissipated by all mechanisms) based on 8 yr of crop history was 0.64 (range, 0.25-1.59) yr and 0.57 (range, 0.24-2.12) yr for 2013 and 2014, respectively. In fields where neonicotinoid residues were measured in both years, the estimated mean half-life between 2013 and 2014 was 0.4 (range, 0.27-0.6) yr. If clothianidin and thiamethoxam were used annually as a seed treatment in a typical crop rotation of maize, soybean, and winter wheat over several years, residues would plateau rather than continue to accumulate. Residues of neonicotinoid insecticides after 3 yr to 4 yr of repeated annual use tend to plateau to a mean concentration of less than 6 ng/g in agricultural soils in southwestern Ontario.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 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".