Rock water use by apple trees affected by physical properties of the underlying weathered rock
Bibliographic record
Abstract
The contribution of rock water to trees has been widely recognized, but how effective rock water to managed ecosystems remains uncertain. Here, we compared the contribution of rock water to apple tree transpiration in shallow soil overlying weathered rock (SOR) with that from a thick soil without weathered rock (TS). We measured physical properties, root distribution, water contents, water stable isotopes of soil and weathered rock. The weathered rock layer in SOR had significantly higher bulk density and gravel contents than that of soil layers in TS. The volumetric water content and water storage of soil under SOR were significantly higher than those under TS, but the opposite is true for the available water content. The weathered rock layer limited the vertical extension of apple roots, with the maximum root depth was only 100 cm, much smaller than 160 cm in TS; additionally, most of roots were in shallow soil in SOR, with the top 80 cm accounting for more than 91% of the total root length of the profile for SOR relative to 61% for the TS. Water sourcing analysis indicates that the water in the weathered rock contributed 17% to the total water uptake in 2021, while the same depth increment of TS contributed 45%. The low water uptake from the weathered rock limited the sap flow, resulting in 27% yield reduction compared to TS yield. Therefore, even though weathered rock is important for apple production, its contribution is much smaller than the soil at the same depth increment. To improve the rock water use is important for further improving the productivity of apple orchards on shallow soil underlain by weathered rock and should be incorporated into our routine orchard water management.
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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 | 0.001 |
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".