Concentrations of Herbicides in Wetlands on Organic and Minimum‐Tillage Farms
Bibliographic record
Abstract
Wetlands are abundant throughout the agricultural landscape of central Saskatchewan, Canada, and the biota present in these wetlands may be vulnerable to the toxic effects of pesticides used on nearby crops. We hypothesized that herbicide concentrations would be higher in wetlands on minimum‐tillage farms than on organic (no herbicide use) farms, and that the principal transport mechanisms of runoff versus atmospheric deposition could be identified based on the concentrations in these two wetland types. To test these hypotheses, 29 herbicides were monitored for 5 yr in 16 wetlands on minimum‐tillage farms and in seven wetlands on organic farms. Twenty herbicides were detected in wetlands on minimum‐tillage farms versus 12 in wetlands on organic farms. Clopyralid, MCPA, 2,4‐D, bromoxynil, dichlorprop, and dicamba were detected at a >50% frequency in wetlands on both minimum‐tillage and organic farms. Concentrations of clopyralid were significantly higher in wetlands on minimum‐tillage farms than in those on organic farms, whereas no significant difference was observed for any of the other five herbicides. Glyphosate, including its degradation product AMPA, was detected in >50% frequency only in wetlands on minimum‐tillage farms where the mean concentration (1278 ng L−1) was higher than the concentration of other herbicides. Mass applied, vapor pressure, and water solubility were important determinants of herbicide concentrations and detections in wetlands. Herbicide concentrations in all but two samples were less than their respective Canadian guideline for protection of aquatic life, suggesting that, overall, individual herbicide concentrations in the wetlands were not toxic to biota. Core Ideas Wetland biota may be at risk from toxic effects of herbicides. We assessed 29 herbicides in wetlands on minimum‐tillage and organic farms. Fewer herbicides and lower concentrations were detected in wetlands on organic farms. Detections were related to relative use, herbicide volatility, and water solubility. Herbicides in wetlands on minimum‐tillage farms were usually below toxic thresholds
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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 | 0.001 |
| 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 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".