Evolution of drought resistance strategies following the introduction of white clover (Trifolium repens L.)
Bibliographic record
Abstract
Background and Aims: Success during colonization likely depends on growing quickly and tolerating novel and stressful environmental conditions. However, rapid growth, stress avoidance, and stress tolerance are generally considered divergent physiological strategies. Methods: We evaluate how white clover (Trifolium repens) has evolved to a divergent water regime following introduction to North America. We conduct RNAseq within a dry-down experiment utilizing accessions from low and high latitude populations from native and introduced ranges, and assess variation in dehydration avoidance (avoidance of wilting) and dehydration tolerance (ability to survive wilting). Key Results: Introduced populations are better at avoiding dehydration, but poorer at tolerating dehydration than native populations. There is a strong negative correlation between avoidance and tolerance traits and expression of most drought-associated genes exhibits similar tradeoffs. Candidate genes with expression strongly associated with dehydration avoidance are linked to stress signaling, closing stomata and producing osmoprotectants. However, genes with expression linked to dehydration tolerance are associated with avoiding excessive ROS production and toxic bioproducts of stress responses. Several candidate genes show differential expression patterns between native and introduced ranges, and could underlie differences in drought resistance syndromes between ranges. Conclusions: These results suggest there has been strong selection following introduction for deyhydration avoidance at the cost of surviving dehydration.
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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 | 0.001 |
| 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".