Deep Soil Water Availability Regulates the Transpiration of Afforested Apple Trees (Malus pumila Mill.) in a Sub-Humid Loess Region
Bibliographic record
Abstract
Many studies have investigated how soil water availability in shallow soil affects forest transpiration, but how deep soil water status (below 1 m depth) alters tree water use remains poorly understood. To improve our understanding of how deep soil water changes tree transpiration dynamics, we measured soil water content (SWC) in more than 20 m depths, the radial sap flow profile and the leaf area index (LAI) in the 2017 growing season in 9-, 12-, 16-, 19- and 23-year-old afforested apple (Rosaceae) trees on the Chinese Loess Plateau. SWC was also measured in long-term cultivated farmland to derive SWC before afforestation. The results showed that there was no statistical difference in SWC in shallow soil among orchards (p > 0.05), while SWC in deep soil reduced rapidly with increasing tree age. The average SWC at 1–20 m decreased from 0.27 ± 0.02 cm3 cm−3 in farmland to 0.21 ± 0.03 cm3 cm−3 in the 23-year-old orchard. Moreover, water storage in deep soil decreased by 139 mm yr−1 between the 9- and 12-year-old stands, 105 mm yr−1 between the 12- and 16-year-old stands, 44 mm yr−1 between the 16- and 19-year-old stands, and 9 mm yr−1 from the 19- to 23-year-old stands, indicating that gradually decreased SWC in deep soil has restricted tree water use. Due to the changes in SWC, growing-season transpiration and the LAI peaked in the 16-year-old orchard and then decreased with increasing stand age. Growing-season transpiration in the 23-year-old orchard was only 77% of that in the 16-year stands, despite the older trees having larger diameters at the breast height. Our results suggest that soil water availability in deep soil plays an important role in regulating trees’ transpiration.
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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 | 0.000 |
| 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 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".