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Record W2541961784 · doi:10.1002/2016jg003464

Fluvial carbon export from a lowland Amazonian rainforest in relation to atmospheric fluxes

2016· article· en· W2541961784 on OpenAlexaff
Leena Vihermaa, Susan Waldron, Tomas F. Domingues, John Grace, Eric G. Cosio, Fabián Limonchi, Chris Hopkinson, Humberto Ribeiro da Rocha, Emanuel Gloor

Bibliographic record

VenueJournal of Geophysical Research Biogeosciences · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsUniversity of Lethbridge
FundersNatural Environment Research CouncilSight Research UKSixth Framework ProgrammeScottish Alliance for Geoscience, Environment and Society
KeywordsFluvialEnvironmental scienceDrainage basinHydrology (agriculture)Eddy covarianceTotal organic carbonTributaryParticulatesCarbon sinkDissolved organic carbonCarbon cycleEcosystemEnvironmental chemistryAtmospheric sciencesGeologyChemistryClimate changeEcologyStructural basinGeomorphologyOceanographyGeographyBiology

Abstract

fetched live from OpenAlex

Abstract We constructed a whole carbon budget for a catchment in the Western Amazon Basin, combining drainage water analyses with eddy covariance (EC) measured terrestrial CO 2 fluxes. As fluvial C export can represent permanent C export it must be included in assessments of whole site C balance, but it is rarely done. The footprint area of the flux tower is drained by two small streams (~5–7 km 2 ) from which we measured the dissolved inorganic carbon (DIC), dissolved organic carbon (DOC), particulate organic carbon (POC) export, and CO 2 efflux. The EC measurements showed the site C balance to be +0.7 ± 9.7 Mg C ha −1 yr −1 (a source to the atmosphere) and fluvial export was 0.3 ± 0.04 Mg C ha −1 yr −1 . Of the total fluvial loss 34% was DIC, 37% DOC, and 29% POC. The wet season was most important for fluvial C export. There was a large uncertainty associated with the EC results and with previous biomass plot studies (−0.5 ± 4.1 Mg C ha −1 yr −1 ); hence, it cannot be concluded with certainty whether the site is C sink or source. The fluvial export corresponds to only 3–7% of the uncertainty related to the site C balance; thus, other factors need to be considered to reduce the uncertainty and refine the estimated C balance. However, stream C export is significant, especially for almost neutral sites where fluvial loss may determine the direction of the site C balance. The fate of C downstream then dictates the overall climate impact of fluvial export.

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)0.001
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 score0.017
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.022
GPT teacher head0.290
Teacher spread0.267 · 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

Citations18
Published2016
Admission routes1
Has abstractyes

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