Do Traits Travel? Multiple-Herbicide-Resistant A. tuberculatus, an Alien Weed Species in Israel
Bibliographic record
Abstract
Amaranthus tuberculatus is the most common weed in soybean and corn in the USA and Canada. In Israel, it has been a minor riverbank weed. However, in recent years, growing densities of this plant have been observed in field crops, orchards, and roadsides. Between 2017 and 2022, we surveyed the distribution of A. tuberculatus and collected seeds for further study. We identified three main distribution zones in Israel: the Jezreel Valley, Hula Valley, and Coastal Plain. Most of the populations were found near water sources, fishponds, barns, dairies, or bird-feeding sites, suggesting the involvement of imported grain in introducing A. tuberculatus to Israel. Populations were screened for their responses to various post-emergence herbicides (i.e., ALS, EPSPS, PPO, HPPD, and PSII inhibitors). Several populations from the Jezreel Valley were found to be putatively resistant to ALS, EPSPS, and PPO inhibitors. The responses of those populations to trifloxysulfuron, glyphosate, and carfentrazone-ethyl were also studied. A single ALS-, EPSPS- and PPO-resistant plant was vegetatively propagated to create a clonal population, which was treated with foramsulfuron, glyphosate, and carfentrazone-ethyl. No resistance to PSII or HPPD inhibitors was observed, but resistance to herbicides that inhibit ALS, EPSPS, and PPO was observed. A clonal propagation assay revealed the existence of a population that was resistant to ALS, EPSPS, and PPO inhibitors. Since the local A. tuberculatus populations have not been exposed to herbicide selection pressure, these traits probably reached Israel through seed-mediated gene flow via imported grain.
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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".