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Record W1931423081 · doi:10.1029/2001gb001702

Methane efflux from boreal wetlands: Theory and testing of the ecosystem model Ecosys with chamber and tower flux measurements

2002· article· en· W1931423081 on OpenAlexaff
R. F. Grant, Nigel T. Roulet

Bibliographic record

VenueGlobal Biogeochemical Cycles · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsMcGill UniversityUniversity of Alberta
Fundersnot available
KeywordsEnvironmental scienceFlux (metallurgy)EcosystemWetlandBorealHydrology (agriculture)VolatilisationAtmospheric sciencesMethaneEcologyChemistryGeology

Abstract

fetched live from OpenAlex

A robust model of CH4 emission from terrestrial ecosystems should be capable of simulating the temporal and spatial variability that characterizes field measurements. Such a model should couple a biologically based treatment of microbial CH4 transformations with a physically based treatment of heat, solute, and gas transfer vertically and laterally through soils. These processes are coupled in the ecosystem model Ecosys, which was tested against CH4 effluxes measured with surface chambers and a flux tower at a beaver pond in the BOREAS Northern Study Area. Spatial and temporal variation of CH4 effluxes in the model encompassed that measured by surface chambers and the flux tower. Both modeled and measured CH4 effluxes rose from <0.05 μmol m−2 s−1 and <0.01 g C m−2 d−1 at sites above the pond to >1.0 μmol m−2 s−1 and >0.5 g C m−2 d−1 at the pond margin. Larger effluxes occurred in the model when warming pond sediments generated episodic bubbling events. Annual CH4 effluxes in the model rose from <1 g C m−2 at sites above the pond to 76 g C m−2 at the pond margin. Annual totals included several brief but rapid efflux events during thawing and warming of soil and pond sediments that are frequently missed by surface measurements. Annual CH4 effluxes predicted after 100 years under an IS92a‐driven climate change scenario rose by ∼20% from the pond, but changed little from the surrounding landscape, indicating topographic variation in response of CH4 effluxes to climate change.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.019
GPT teacher head0.214
Teacher spread0.195 · 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 source (direct Gemma or distilled Codex), 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

Citations81
Published2002
Admission routes1
Has abstractyes

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