MétaCan
Menu
Back to cohort
Record W3119868322 · doi:10.21203/rs.3.rs-138459/v1

Evidence for widespread woody plant use of water stored in bedrock

2021· preprint· en· W3119868322 on OpenAlexaff
Erica McCormick, David Dralle, W. Jesse Hahm, A. K. Tune, Logan Schmidt, K. Dana Chadwick, Daniella Rempe

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsBedrockWoody plantEnvironmental scienceAgroforestryBusinessGeologyBiologyEcologyPaleontology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.280
GPT teacher head0.401
Teacher spread0.121 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueResearch SquareSame topicTree-ring climate responsesFrench-language works237,207