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Record W2164916053 · doi:10.5194/bg-11-3635-2014

Old carbon contributes to aquatic emissions of carbon dioxide in the Amazon

2014· article· en· W2164916053 on OpenAlexfundno aff
Leena Vihermaa, Susan Waldron, Mark H. Garnett, Jason Newton

Bibliographic record

VenueBiogeosciences · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsnot available
FundersNatural Environment Research CouncilUniversity of NottinghamNational Aeronautics and Space AdministrationUniversity of LethbridgeOhio State UniversityBournemouth UniversitySight Research UK
KeywordsCarbon cycleCarbon dioxideCarbon fibersCarbonateAmazon rainforestCarbon dioxide in Earth's atmosphereWeatheringEnvironmental scienceAtmosphere (unit)EcosystemEarth scienceEcologyGeologyChemistryPaleontologyBiologyGeographyMeteorologyMaterials science

Abstract

fetched live from OpenAlex

Abstract. Knowing the rate at which carbon is cycled is crucial to understanding the dynamics of carbon transfer pathways. Recent technical developments now support measurement of the 14C age of evaded CO2 from fluvial systems, which provides an important "fingerprint" of the source of C. Here we report the first direct measurements of the 14C age of effluxed CO2 from two small streams and two rivers within the western Amazonian Basin. The rate of degassing and hydrochemical controls on degassing are also considered. We observe that CO2 efflux from all systems except for the seasonal small stream was 14C-depleted relative to the contemporary atmosphere, indicating a contribution from "old" carbon fixed before ~ 1955 AD. Further, "old" CO2 was effluxed from the perennial stream in the rainforest; this was unexpected as here connectivity with the contemporary C cycle is likely greatest. The effluxed gas represents all sources of CO2 in the aquatic system and thus we used end-member analysis to identify the relative inputs of fossil, modern and intermediately aged C. The most likely solutions indicated a contribution from fossil carbon sources of between 3 and 9% which we interpret as being derived from carbonate weathering. This is significant as the currently observed intensification of weather has the potential to increase the future release of old carbon, which can be subsequently degassed to the atmosphere, and so renders older, slower C cycles faster. Thus 14C fingerprinting of evaded CO2 provides understanding which is essential to more accurately model the carbon cycle in the Amazon Basin.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.204
Teacher spread0.193 · 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

Citations20
Published2014
Admission routes1
Has abstractyes

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