Potential Geographic Distribution of Palmer Amaranth under Current and Future Climates
Bibliographic record
Abstract
Core Ideas CLIMEX model projections match known Palmer amaranth distribution. Sub‐Sahara Africa and Australia are at risk for Palmer amaranth establishment. Future climate scenarios indicate the potential for poleward range expansion. Herbicide‐resistant weeds are increasingly becoming a major challenge for agricultural production worldwide. Palmer amaranth [ Amaranthus palmeri (S.) Wats.] is an invasive annual forb that has recently emerged as one of the most widespread and severe agronomic weeds in the United States, due in part to its facility for evolving herbicide resistance. It has invaded several parts of the world, including key agricultural production regions in South America. Climate change will likely exacerbate the challenges of managing this species. To assess this, we developed a process‐oriented bioclimatic niche model of Palmer amaranth to examine its potential global distribution under current conditions and future climate scenarios. The model agreed well with all credible current distribution data. Projected future increases in temperatures will expand potential Palmer amaranth range northward into portions of Canada and Europe. Model projections under current and future climates highlight several agricultural production regions of increasing and emerging risk from this weed.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".