Agricultural adaptation in the native North American weed waterhemp, Amaranthus tuberculatus (Amaranthaceae)
Bibliographic record
Abstract
There is increasing interest in documenting adaptation of weedy plant species to agricultural ecosystems, beyond the evolution of herbicide resistance. Waterhemp (Amaranthus tuberculatus) is a native plant of the Midwestern U.S. that began infesting agricultural fields in the 20th century within the central portion of its range. We hypothesized that the vegetative growth and reproductive traits of waterhemp from this heavily infested central region provide differential fitness benefits in agricultural environments. We collected seeds from across the species' native range, representing regions with varying degrees of waterhemp infestation, and planted them together in common garden soybean plots. A 2010 common garden experiment was conducted within the range of agriculturally weedy waterhemp (in Missouri), and a 2011 common garden experiment was conducted outside of this range (in Ohio). Days to flowering and flowering plant height, mature plant size data (height, number of branches, and length of the longest branch), and above-ground biomass were measured to estimate relative fitness. In both common garden locations, plants from regions where waterhemp occurs as an agricultural weed - including those from the heavily infested Mississippi Valley region (Iowa, Illinois, and Missouri) and the less severely infested Plains region (Nebraska, Kansas, and Oklahoma) - had higher relative performance in almost all fitness-related measures than plants from the Northeast region (Ohio, Michigan, and Ontario), which had little to no agriculturally weedy waterhemp at the time of our study. Further analysis revealed that fewer days to flowering in the Northeast populations can be largely accounted for by latitude of origin, suggesting a strong genetic influence on this reproductive trait. These findings suggest intraspecific variation in agricultural adaptation in a native U.S. weed, and support the use of agricultural weeds to study adaptation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".