Drought survival in conifer species is related to the time required to cross the stomatal safety margin
Bibliographic record
Abstract
The regulation of water loss and the spread of xylem embolism have mostly been considered separately. The development of an integrated approach taking into account the temporal dynamics and relative contributions of these mechanisms to plant drought responses is urgently needed. Do conifer species native to mesic and xeric environments display different hydraulic strategies and temporal sequences under drought? A dry-down experiment was performed on seedlings of four conifer species differing in embolism resistance, from drought-sensitive to extremely drought-resistant species. A set of traits related to drought survival was measured, including turgor loss point, stomatal closure, minimum leaf conductance, and xylem embolism resistance. All species reached full stomatal closure before the onset of embolism, with all but the most drought-sensitive species presenting large stomatal safety margins, demonstrating that highly drought-resistant species do not keep their stomata open under drought conditions. Plant dry-down time to death was significantly influenced by the xylem embolism threshold, stomatal safety margin, and minimum leaf conductance, and was best explained by the newly introduced stomatal margin retention index (SMRIΨ50) which reflects the time required to cross the stomatal safety margin. The SMRIΨ50 may become a key tool for the characterization of interspecific drought survival variability in trees.
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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".