Refuge facilitates the preservation and accumulation of herbicide resistance traits in <i>Conyza canadensis</i>
Bibliographic record
Abstract
Herbicide resistance is selected for within a weed population through the recurrent use of an herbicide. Once the use of the herbicide is reduced or discontinued, the trait may persist in the population unless resistance endows a fitness penalty. Few studies have examined the long-term persistence of an herbicide resistance trait in a weed population once the selection pressure that led to its prevalence has been removed. The objective of this research was to re-survey the locations described by A.J.J. Smisek in her 1995 study of a paraquat resistant biotype of C. canadensis on the grounds of the Harrow Research and Development Centre. Results indicate that, ∼20 yr after paraquat use was significantly reduced, a glyphosate resistant biotype had replaced the paraquat resistant biotype at all but one of the original locations surveyed by Smisek. The sole location where the paraquat resistant biotype was observed was an old, un-treed orchard row currently managed by mowing. This location not only served as a refuge for the paraquat resistant biotype, ensuring its persistence in the face of strong selection for glyphosate resistance at all other locations, but it facilitated the co-occurrence of glyphosate and paraquat resistant biotypes. The observation of a multiple resistant biotype at this location alone, with resistance to both paraquat and glyphosate, suggests a role for refugia in the stacking of herbicide resistance traits. Given that this stacking occurred in the absence of either herbicide, we hypothesize that the multiple resistant biotype arose through pollen mediated gene flow among biotypes.
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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 | 0.000 | 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) | 0.001 | 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".