REDUCED DROUGHT TOLERANCE DURING DOMESTICATION AND THE EVOLUTION OF WEEDINESS RESULTS FROM TOLERANCE-GROWTH TRADE-OFFS
Bibliographic record
Abstract
The increased reproductive potential, size, shoot allocation, and growth rate of weedy plants may result from reduced resource allocation to other aspects of plant growth and defense. To investigate whether changes in resource allocation occurred during domestication or the evolution of weediness, we compared the mycorrhizal responsiveness, growth, and drought tolerance of nine native ruderal, nine agriculturally weedy (four U.S. weedy and five Australian weedy), and 14 domesticated populations (eight ancient landraces and six improved cultivars) of the common sunflower (Helianthus annuus). Domesticated sunflower cultivars were less drought tolerant, but had higher plant growth and fecundity and coarser roots than wild populations. There were no changes in level of drought tolerance between improved cultivars and ancient landrace plants, but there was an increase in allocation to flowers with recent selection. Weedy populations were intermediate between domesticated cultivars and native ruderal populations for plant growth rate, root architecture, and drought tolerance. Weedy populations benefited most from mycorrhizal inoculation by having fewer wilted leaves and wetter soil. Overall, we found that trade-offs between drought tolerance and several aspects of plant growth, including growth rate, allocation to flowering, and root architecture, govern evolution during sunflower domestication and the invasion of disturbed habitat.
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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".