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Record W2991350506

Water and carbon cycles in the Mississippi River basin: potential implications for the Northern Hemisphere "residual terrestrial sink"

2003· article· en· W2991350506 on OpenAlexaff
Dong Ki Lee, Ján Veizer

Bibliographic record

VenueEGS - AGU - EUG Joint Assembly · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsCarleton UniversityUniversity of Ottawa
Fundersnot available
KeywordsEnvironmental scienceEvapotranspirationTranspirationEddy covarianceSink (geography)InterceptionEcosystemHydrology (agriculture)Primary productionCarbon sinkAtmospheric sciencesCarbon cycleWater cycleEcologyPhotosynthesisChemistryGeology
DOInot available

Abstract

fetched live from OpenAlex

[1] The hydrologic cycle plays an important role in carbon cycling, due to the coupling of vapor release and CO2 uptake during photosynthesis. This coupling, expressed as Water Use Efficiency (WUE) or Transpiration Ratio, can provide an inexpensive alternative for estimating the Net Primary Productivity (NPP) of terrestrial ecosystems. The D/H and 18O/16O trends of river water in the Mississippi basin are mostly indistinguishable from those of precipitation. This, combined with isotopic mass balance relationships, suggests that direct evaporation of surface water is small and evapotranspiration (ET) flux from the basin therefore consists mostly of interception and transpiration, with interception approximated from field studies. The calculated water flux associated with transpiration is 1500.8 km3 (77.3% of the evapotranspiration flux). Utilizing the average WUE of 864 mol H2O for each mole of CO2, the NPP of the Mississippi River basin amounts to 1.16 Pg C/yr, similar to the model estimates of the heterotrophic soil respiration flux of 1.12 Pg C/yr. This does not favor the postulated existence of a major sink for atmospheric CO2 in the temperate Northern Hemispheric ecosystems of the conterminous United States, but due to uncertainties in the input parameters we cannot discount the possibility that these ecosystems act as a modest sink.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.506

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 head0.013
GPT teacher head0.218
Teacher spread0.205 · 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

Citations0
Published2003
Admission routes1
Has abstractyes

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