Roles of weathered bedrock and soil in seasonal water relations of <i>Pinus Jeffreyi</i> and <i>Arctostaphylos patula</i>
Bibliographic record
Abstract
In the southern Sierra Nevada, California, relatively thin soils overlie granitic bedrock that is weathered to depths of several metres. The weathered granitic bedrock is porous and has a plant-available water capacity of 0.124 m 3 ·m 3 , compared with 0.196 m 3 ·m 3 for the overlying soil. Roots confined within bedrock joint fractures access this rock-held water, especially during late summer when overlying soils are dry. We sought to determine seasonal soil and bedrock water changes in a Jeffrey pine (Pinus jeffreyi Grev & Balf.) plantation and to examine concurrent effects on the water relations of Jeffrey pine and greenleaf manzanita (Arctostaphylos patula Greene). In 1996, plant-available water in the 75 cm thick soil was depleted by late June, with soil water potential (ψ soil ) <2.2 MPa, but below 75 cm, bedrock water potential (ψ bedrock ) was still > 2.2 MPa. Thus, the bedrock, not the soil, supplied water to plants for the remainder of the dry season. Higher values of, and smaller fluctuations in, seasonal predawn pressure potential (ψ predawn ) for Jeffrey pine indicated that it is deeply rooted, whereas active roots of greenleaf manzanita were interpreted to be mostly within the upper 100 cm. The extra rooting volume supplied by weathered bedrock is especially important to pine relative to manzanita.
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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".