High potential for foliar water uptake in early stages of leaf development of three woody angiosperms
Bibliographic record
Abstract
Abstract Foliar water uptake (FWU) is a widespread mechanism that may help plants cope with drought stress in a wide range of ecosystems. FWU can be affected by various leaf traits, which change during leaf development. We exposed cut and dehydrated leaves to rainwater and measured FWU, changes in leaf water potential after 19 h of FWU (ΔΨ), minimum leaf conductance (gmin), and leaf wettability (abaxial and adaxial) of leaves of Acer platanoides, Fagus sylvatica, and Sambucus nigra at three developmental stages: unfolding (2–5‐day‐old), young (1.5‐week‐old) and mature leaves (8‐week‐old). FWU and gmin were higher in younger leaves. ΔΨ corresponded to FWU and gmin in all cases but mature leaves of F. sylvatica, where ΔΨ was highest. Most leaves were highly wettable, and at least one leaf surface (adaxial or abaxial) showed a decrease in wettability from unfolding to mature leaves. Young leaves of all studied species showed FWU (unfolding leaves: 14.8 ± 1.1 μmol m−2 s−1), which may improve plant water status and thus counterbalance spring transpirational losses due to high gmin. The high wettability of young leaves probably supported FWU. We observed particularly high FWU and respective high ΔΨ in older leaves of F. sylvatica, possibly aided by trichomes.
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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".