The Persistence of Glyphosate in Vegetation One Year after Application
Bibliographic record
Abstract
Glyphosate-based herbicides are the most widely used herbicides in the world, including in Canadian forestry. In general, glyphosate-based herbicides are considered relatively non-toxic to wildlife species due, in part, to rapid breakdown of the chemical in the environment. However, recent work has shown that glyphosate can persist for at least one year after application at low concentrations leading to concern over the persistence of trace levels in the environment. Using two independent studies we characterize the short- (18 days) and long-term (1 year) persistence of glyphosate in vegetation which are commonly, but differentially, browsed by WhiteiTailed Deer (Odocoileus virginianus), Moose (Alces alces), and Black Bear (Ursus americanus), or used as traditional medicines by Indigenous people and compare the residues to exposure thresholds. In the short-term study, glyphosate concentrations within the application block exceeded the general and maximum residue level (MRL) for fresh fruit set by Health Canada (0.1 ppm) for up to 18 days after application. In the long-term study, glyphosate concentrations were above the MRL one week after application and below the MRL one month and one year after application. Under the assumptions that all vegetation contained glyphosate at the highest observed concentration, animals only consume vegetation from herbicide treated areas, and animals consume the physiological maximum level of vegetation daily, Moose, White-Tailed Deer, and Black Bears could exceed the Acceptable Daily Intake for glyphosate (0.3 mg/kg/day) for up to 18 days after application. Subsequently, given dissipation of residues in vegetative matrices as observed in this study, we consider it highly unlikely that the species considered herein could consume enough vegetation throughout their lives to pose a risk to their health. Overall, our two independent studies demonstrate that trace levels of glyphosate persist in vegetation for up to one year after application, however, observed concentrations are unlikely to pose risk to wildlife. We caution that operational practices as typically imposed in Canadian forestry are very important and effective in minimizing risk.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".