The evolution of stomatal traits along the trajectory towards C <sub>4</sub> photosynthesis
Bibliographic record
Abstract
Abstract C 4 photosynthesis optimizes plants carbon and water relations, allowing high photosynthetic rate with low stomatal conductance. Stomata have long been believed as a part of C 4 syndrome. However, it remains unclear how stomata traits evolved along the path from C 3 to C 4 . Stomatal patterning was examined in Flaveria genus, a model for studying C 4 evolution. Comparative, transgenic and semi- in-vitro experiments were used to study molecular basis that underlies stomatal traits along C 4 evolution. Novel results: the evolution from C 3 to C 4 species through intermediate species is accompanied by a stepwise rather than an abrupt change in the stomatal traits. The initial change occurs near Type II and dramatic change occurs at the C 4 -like species. On the road to C 4 , stomata become less in number but bigger in size and changes in stomatal density dominates changes in maximum stomatal conductance ( g smax ). The reduction of FSTOMAGEN expression underlies altered g smax between Flaveria species with different photosynthetic pathways and likely occurs in other C 4 lineages. Our study provides insight into the pattern, mechanism and role of stomatal evolution along the road towards C 4 . This work highlights the stomatal traits in the current C 4 evolutionary model and the co-evolution of photosynthetic pathway and stomata.
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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".