Impacts of Cropping Systems on Glyphosate and Aminomethylphosphonic Acid Contents and Microbial Community in Field Crop Soils in Quebec (Canada)
Bibliographic record
Abstract
Glyphosate-based herbicide (GBH) usage is ubiquitous in Quebec field crops, apart from organic management. As glyphosate generally degrades rapidly in agricultural soils, aminomethylphosphonic acid (AMPA) is produced and persists longer than glyphosate. Repeated GBH applications year after year raise questions about glyphosate and AMPA pseudo-persistence in soils and its possible impacts on the soil microbial community. This research aims at understanding the influence of cropping systems and edaphic properties on glyphosate and AMPA contents and on the diversity and composition of the soil microbial community across nine field crop fields located in Southern Quebec (Canada) during 2019 and 2020. Average glyphosate soil contents (0.16 ± 0.15 µg·g−1 dry soil) were lower than average AMPA soil contents (0.37 ± 0.24 µg·g−1 dry soil). Glyphosate and AMPA contents were significantly lower at sites cultivated under organic management than conventional management. For conventional sites, cumulative GBH doses had a significant effect on glyphosate soil contents measured at the end of the growing season, but not on AMPA soil contents. Sites with higher GBH applications appear to accumulate glyphosate over time in the 0–40 cm soil horizon. Glyphosate and AMPA soil contents are inversely proportional to soil pH. Soil prokaryotic and fungal communities’ alpha-diversity, beta-diversity, and functional potential were not impacted by cumulative GBH doses, but rather by soil chemical properties, soil texture, crop rotation, and manure inputs.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".