Glyphosate remains in forest plant tissues for a decade or more
Bibliographic record
Abstract
Glyphosate-based herbicides are highly effective, non-selective, and broad-spectrum herbicides that have been used in British Columbia’s forest industry since the early 1980’s. Over this time, long-term persistence of glyphosate has not been measured, largely due to the inability to analyze glyphosate at low concentrations. Given the advancements in analytical techniques that are now available, we have extended the persistence curve of glyphosate to elucidate the actual length of time of persistence in northern British Columbia, rather than relying on estimations of persistence based on half-life curves that are quite often modelled from incomparable environments. We collected plant tissues from five forest understory perennial species growing in two distinct biogeoclimatic regions of northern BC to map out how glyphosate residue quantities change over time according to species, plant tissue type, and climate regime. We found that residues persisted for up to 12 years in some tissue types, and that root tissues generally retained glyphosate residues longer than shoot tissue types. We also found that samples from the colder, more northern biogeoclimatic zone investigated retained significantly higher levels of glyphosate for longer than samples collected from the warmer biogeoclimatic zone.
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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 | 0.000 | 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".