Smaller, faster stomata: scaling of stomatal size, rate of response, and stomatal conductance
Bibliographic record
Abstract
Maximum and minimum stomatal conductance, as well as stomatal size and rate of response, are known to vary widely across plant species, but the functional relationship between these static and dynamic stomatal properties is unknown. The objective of this study was to test three hypotheses: (i) operating stomatal conductance under standard conditions (g (op)) correlates with minimum stomatal conductance prior to morning light [g (min(dawn))]; (ii) stomatal size (S) is negatively correlated with g (op) and the maximum rate of stomatal opening in response to light, (dg/dt)(max); and (iii) g (op) correlates negatively with instantaneous water-use efficiency (WUE) despite positive correlations with maximum rate of carboxylation (Vc (max)) and light-saturated rate of electron transport (J (max)). Using five closely related species of the genus Banksia, the above variables were measured, and it was found that all three hypotheses were supported by the results. Overall, this indicates that leaves built for higher rates of gas exchange have smaller stomata and faster dynamic characteristics. With the aid of a stomatal control model, it is demonstrated that higher g (op) can potentially expose plants to larger tissue water potential gradients, and that faster stomatal response times can help offset this risk.
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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 | 0.001 |
| 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 | 0.001 |
| 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".