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Record W2935296577 · doi:10.1029/2018wr023265

Characterizing the Fluxes and Age Distribution of Soil Water, Plant Water, and Deep Percolation in a Model Tropical Ecosystem

2019· article· en· W2935296577 on OpenAlexafffund
Jaivime Evaristo, Minseok Kim, Joost van Haren, Luke Pangle, C. J. Harman, P. A. Troch, Jeffrey J. McDonnell

Bibliographic record

VenueWater Resources Research · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsGlobal Institute for Water SecurityUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaGlobal Institute for Water Security, University of Saskatchewan
KeywordsGroundwater rechargeTranspirationEnvironmental scienceSoil waterHydrology (agriculture)GroundwaterBiomeWater potentialEcosystemEvapotranspirationSoil scienceEcologyAquiferGeologyChemistryBiology

Abstract

fetched live from OpenAlex

Abstract Recent field observations indicate that in many forest ecosystems, plants use water that may be isotopically distinct from soil water that ultimately contributes to streamflow. Such an assertion has been met with varied reactions. Of the outstanding questions, we examine whether ecohydrological separation of water between trees and streams results from a separation in time, or in space. Here we present results from a 9‐month drought and rewetting experiment at the 26,700‐m 3 mesocosm, Biosphere 2‐Tropical Rainforest biome. We test the null hypothesis that transpiration and groundwater recharge water are sampled from the same soil volume without preference for old nor young water. After a 10‐week drought, we added 66 mm of labeled rainfall with 152‰ δ 2 H distributed over four events, followed by background rainfall (−60‰ δ 2 H) distributed over 13 events. Our results show that mean transit times through groundwater recharge and plant transpiration were markedly different: groundwater recharge was 2–7 times faster (~9 days) than transpired water (range 17–62 days). The “age” of transpired water showed strong dependence on species and was linked to the difference between midday leaf water potential and soil matric potential. Moreover, our results show that trees used soil water (89% ±6) and not the “more mobile” (represented by “zero tension” seepage) water (11% ±6). The finding, which rejects our null hypothesis, is novel in that this partitioning is established based on soil water residence times. Our study quantifies mean transit times for transpiration and seepage flows under dynamic conditions.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.888
Threshold uncertainty score0.191

Codex and Gemma teacher scores by category

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

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 head0.017
GPT teacher head0.234
Teacher spread0.217 · 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 designSimulation or modeling
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

Citations130
Published2019
Admission routes2
Has abstractyes

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