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Record W2556285931 · doi:10.1111/nph.14288

The response of ecosystem water‐use efficiency to rising atmospheric <scp>CO</scp><sub>2</sub> concentrations: sensitivity and large‐scale biogeochemical implications

2016· article· en· W2556285931 on OpenAlexfundno aff
Jürgen Knauer, Sönke Zaehle, Markus Reichstein, Belinda E. Medlyn, Matthias Forkel, Stefan Hagemann, Christiane Werner

Bibliographic record

VenueNew Phytologist · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsnot available
FundersLawrence Berkeley National LaboratoryNatural Resources CanadaHorizon 2020 Framework ProgrammeEidgenössische Technische Hochschule ZürichNatural Sciences and Engineering Research Council of CanadaU.S. Department of EnergyEuropean CommissionOak Ridge National LaboratoryBiological and Environmental ResearchCanadian Foundation for Climate and Atmospheric SciencesMicrosoft ResearchUniversità degli Studi della TusciaEuropean Research CouncilNational Science Foundation
KeywordsEnvironmental scienceEddy covarianceEvapotranspirationWater-use efficiencyBiogeochemical cycleAtmospheric sciencesEcosystemStomatal conductanceClimatologyEcologyBiologyBotanyGeologyPhotosynthesis

Abstract

fetched live from OpenAlex

Summary Ecosystem water‐use efficiency ( WUE ) is an important metric linking the global land carbon and water cycles. Eddy covariance‐based estimates of WUE in temperate/boreal forests have recently been found to show a strong and unexpected increase over the 1992–2010 period, which has been attributed to the effects of rising atmospheric CO 2 concentrations on plant physiology. To test this hypothesis, we forced the observed trend in the process‐based land surface model JSBACH by increasing the sensitivity of stomatal conductance ( g s ) to atmospheric CO 2 concentration. We compared the simulated continental discharge, evapotranspiration ( ET ), and the seasonal CO 2 exchange with observations across the extratropical northern hemisphere. The increased simulated WUE led to substantial changes in surface hydrology at the continental scale, including a significant decrease in ET and a significant increase in continental runoff, both of which are inconsistent with large‐scale observations. The simulated seasonal amplitude of atmospheric CO 2 decreased over time, in contrast to the observed upward trend across ground‐based measurement sites. Our results provide strong indications that the recent, large‐scale WUE trend is considerably smaller than that estimated for these forest ecosystems. They emphasize the decreasing CO 2 sensitivity of WUE with increasing scale, which affects the physiological interpretation of changes in ecosystem WUE .

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.295

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.008
GPT teacher head0.215
Teacher spread0.207 · 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 designBench or experimental
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

Citations133
Published2016
Admission routes1
Has abstractyes

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