Travel through time and space: Temporal and geographical patterns of resistance gene copy number variation, and variation in flowering phenology in glyphosate resistant Amaranthus palmeri
Bibliographic record
Abstract
Herbicide-resistant weeds offer key insights into rapid adaptation under anthropogenic stress. Amaranthus palmeri, a major agricultural weed native to the southwestern U.S. and Mexico, has developed glyphosate resistance primarily through 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) gene copy number variation (CNV), with up to 160 copies in contemporary populations. A critical question is whether this CNV predates glyphosate’s commercialization in 1974, potentially indicating standing genetic variation's role in resistance evolution. I analyzed herbarium samples from three time periods (pre-1974: n = 383, 1974-1995: n = 286, post-1995: n = 246). No CNV was detected prior to 1974, with all individuals carrying a single EPSPS copy. After 1974 but before GM crops, occasional CNV was observed (max of 8 copies), but no significant relationship with year. Post-1995, CNV increased significantly, reaching up to 110 copies, suggesting resistance evolved primarily through de novo mutations under glyphosate selection. I also examined geographical patterns and the impact of EPSPS CNV on flowering phenology through a greenhouse experiment involving 19 populations from Georgia, North Carolina, and Illinois. Despite wide CNV variation, no significant relationship was found between CNV and flowering time, indicating resistance does not drive key phenological shifts. However, latitude significantly influenced flowering phenology and inflorescence length, though not plant growth. With the expansion of A. palmeri across North America and currently into Canada, it is imperative we understand historical and contemporary factors that contribute to evolution of herbicide resistance. The historical samples are useful resources to elucidate temporal variation of herbicide resistance, and the contemporary samples are used to understand the relationship between herbicide resistance and geography on flowering phenology.
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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 | 0.001 |
| 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) | 0.001 | 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".