Stomatal conductance patterns of <i>Equisetum giganteum</i> stems in response to environmental factors in South America
Bibliographic record
Abstract
As the most basal monilophytes, eusporangiate ferns can provide key insights into the origins of plant physiological adaptations. The genus Equisetum, the most morphologically and physiologically unusual genus of eusporangiate ferns, has a stomatal apparatus that is unique among all plants. Patterns of stomatal diffusive conductance (gw) were measured in the giant horsetail, Equisetum giganteum L. in southern South America. Maximum gw values (<200 mmol·m−2·s−1) were low in comparison with typical angiosperm leaves, but were in the range measured in other pteridophytes. The range of measured gw was similar in contrasting environments of the Atacama Desert and northwestern Argentina. Stems in shade had a significantly lower gw than those in light. Developing stems had a higher average gw than mature stems. Stomatal conductance was higher for upper stem internodes than for middle internodes. Late-morning gw was primarily related to stem diameter, stem surface temperature, and interactions among these factors and vapor pressure deficit (VPD), light, elevation, and groundwater salinity. Equisetum giganteum likely has a passive system of stomatal regulation depending on overall stem turgor and red light. The stomatal conductance of patterns of this species exhibited a diurnal pattern typical of other pteridophytes, despite its unusual structure.
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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".