Soil moisture control of sap-flow response to biophysical factors in a desert-shrub species, <i>Artemisia ordosica</i>
Bibliographic record
Abstract
Abstract. The current understanding of acclimation processes in desert-shrub species to drought stress in dryland ecosystems is still incomplete. In this study, we measured sap flow in Artemisia ordosica and associated environmental variables throughout the growing seasons of 2013 and 2014 (May–September period of each year) to better understand the environmental controls on the temporal dynamics of sap flow. We found that the occurrence of drought in the dry year of 2013 during the leaf-expansion and leaf-expanded periods caused sap flow per leaf area (Js) to decline significantly, resulting in transpiration being 34 % lower in 2013 than in 2014. Sap flow per leaf area correlated positively with radiation (Rs), air temperature (T), and water vapor pressure deficit (VPD) when volumetric soil water content (VWC) was greater than 0.10 m3 m−3. Diurnal Js was generally ahead of Rs by as much as 6 hours. This time lag, however, decreased with increasing VWC. The relative response of Js to the environmental variables (i.e., Rs, T, and VPD) varied with VWC, Js being more strongly controlled by plant-physiological processes during periods of dryness indicated by a low decoupling coefficient and low sensitivity to the environmental variables. According to this study, soil moisture is shown to control sap-flow (and, therefore, plant-transpiration) response in Artemisia ordosica to diurnal variations in biophysical factors. This species escaped (acclimated to) water limitations by invoking a water-conservation strategy with the regulation of stomatal conductance and advancement of Js peaking time, manifesting in a hysteresis effect. The findings of this study add to the knowledge of acclimation processes in desert-shrub species under drought-associated stress. This knowledge is essential in modeling desert-shrub-ecosystem functioning under changing climatic conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".