Evidence for widespread woody plant use of water stored in bedrock
Bibliographic record
Abstract
Abstract Woody plant transpiration is a major control on Earth’s climate system, streamflow, and human water supply. Soils are widely considered to be the primary reservoir of water for woody plants, however, plants also access water stored in the fractures and pores of bedrock, either as rock moisture (water stored in the unsaturated zone) (Schwinning, 2010) or bedrock groundwater (below the water table) (Miller et al., 2010). Bedrock as a water source for plants has not been evaluated over large scales, and consequently, its importance to terrestrial water and carbon cycling is poorly known (Fan et al., 2019). Here, we show that woody plants routinely access significant quantities of water stored in bedrock —commonly as rock moisture —for transpiration across diverse climates and biomes. For example, in California, the volume of bedrock water transpired by woody vegetation annually exceeds that stored in man-made reservoirs, and woody vegetation that withdraws bedrock water accounts for over 50% of the aboveground carbon stocks in the state. Our findings show that bedrock water storage dynamics are a critical element of terrestrial water cycling and therefore necessary to capture the effect of shifting climate on woody ecosystems, above- and belowground carbon storage, and water resources.
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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 | 0.001 |
| 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) | 0.005 | 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".