Stomatal Sensitivity to Vapor Pressure Deficit and the Loss of Hydraulic Conductivity Are Coordinated in Populus euphratica, a Desert Phreatophyte Species
Bibliographic record
Abstract
There are considerable variations in the percentage loss of hydraulic conductivity (PLC) at mid-day minimum water potential among and within species, but the underpinning mechanism(s) are poorly understood. This study tested the hypothesis that plants can regulate leaf specific hydraulic conductance (Kl) via precise control over PLC under variable ΔΨ (water potential differential between soil and leaf) conditions to maintain the -m/b constant (-m: the sensitivity of stomatal conductance to VPD; b: reference stomatal conductance at 1.0 kPa VPD), where VPD is vapor pressure deficit. We used Populus euphratica, a phreatophyte species distributed in the desert of Northwestern China, to test the hypothesis. Field measurements of VPD, stomatal conductance (gs), gs responses to VPD, mid-day minimum leaf water potential (Ψlmin), and branch hydraulic architecture were taken in late June at four sites along the downstream of Tarim River at the north edge of the Taklamakan desert. We have found that: 1) the -m/b ratio was almost constant (=0.6) across all the sites; 2) the average Ψ50 (the xylem water potential with 50% loss of hydraulic conductivity) was -1.63 MPa, and mid-day PLC ranged from 62 to 83%; 3) there were tight correlations between Ψ50 and wood density/leaf specific hydraulic conductivity (kl) and between specific hydraulic conductance sensitivity to water potential [d(ks)/dln(-Ψ)] and specific hydraulic conductivity (ks). A modified hydraulic model was applied to investigate the relationship between gs and VPD under variable ΔΨ and Kl conditions. It was concluded that P. euphratica was able to control PLC in order to maintain a relatively constant -m/b under different site conditions. This study demonstrated that branchlet hydraulic architecture and stomatal response to VPD were well coordinated in order to maintain relatively water homeostasis of P. euphratica in the desert. Model simulations could explain the wide variations of PLC across and within woody species that are often observed in the field.
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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".