From comfort zone to mortality: Sequence of physiological stress thresholds in Robinia pseudoacacia seedlings during progressive drought
Bibliographic record
Abstract
Introduction Parameterizing the process of trees from the comfort zone to mortality during progressive drought is important for, but is not well represented in, vegetation models, given the lack of appropriate indices to gauge the response of trees to droughts. The objective of this study was to determine reliable and readily available tree drought stressindices and the thresholds at which droughts activate important physiological responses. Methods We analyzed the changes in the transpiration (T), stomatal conductance, xylem conductance, and leaf health status due to a decrease in soil water availability (SWA), predawn xylem water potential (ψpd), and midday xylem water potential (ψmd) in Robinia pseudoacacia seedlings during progressive drought. Results The results showed that ψmd was a better indicator of drought stress than SWA and ψpd, because ψmd was more closely related to the physiological response (defoliation and xylem embolization) during severe drought and could be measured more conveniently. We derived the following five stress levels from the observed responses to decreasing ψmd: comfort zone (ψmd > -0.9 MPa), wherein transpiration and stomatal conductance are not limited by SWA; moderate drought stress (-0.9 to -1.75 MPa), wherein transpiration and stomatal conductance are limited by drought; high drought stress (-1.75 to -2.59 MPa), wherein transpiration decreases significantly (T< 10%) and stomata closes completely; severe drought stress (-2.59 to -4.02 MPa), wherein transpiration ceases (T< 0.1%) and leaf shedding orwilting is > 50%; and extreme drought stress (< -4.02 MPa), leading to tree mortality due to xylem hydraulic failure. Discussion To our knowledge, our scheme is the first to outline the quantitative thresholds for the downregulation of physiological processes in R. pseudoacacia during drought, therefore, can be used to synthesize valuable information for process-based vegetation models.
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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) | 0.000 | 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".