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Record W2105570658 · doi:10.1029/2002gb001966

Atmospheric sulfur deposition alters pathways of gaseous carbon production in peatlands

2003· article· en· W2105570658 on OpenAlexfundno aff
Melanie A. Vile, Scott D. Bridgham, R. Kelman Wieder, Martin Novák

Bibliographic record

VenueGlobal Biogeochemical Cycles · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsnot available
FundersČeská geologická službaSociety of Wetland ScientistsUniversity of AlbertaNational Science Foundation
KeywordsMethanogenesisPeatSulfateMineralization (soil science)Environmental chemistryEnvironmental scienceSulfurSink (geography)Deposition (geology)ChemistryMethaneEcologyGeologySoil scienceSoil waterSedimentBiology

Abstract

fetched live from OpenAlex

Peatlands represent large carbon (C) reservoirs that can act as a source or sink for greenhouse gases. The response of peatland gaseous C fluxes to global climate change and atmospheric sulfate deposition, however, remains uncertain. Methanogenesis is thought to be one of the most important anaerobic C mineralization pathways in peatlands, especially in regions where input of sulfate from acid deposition is low. However, sulfate reduction has been quantified rarely in freshwater wetlands. Here we report greater anaerobic C flow through sulfate reduction than through methanogenesis at all sites situated along a global atmospheric sulfur deposition gradient. Stoichiometric mass balance suggests that fermentation is a dominant anaerobic C mineralization pathway in unpolluted peatlands, while methanogenesis contributed minimally to total anaerobic carbon mineralization in these sites. Furthermore, global increases of atmospheric sulfur deposition minimize the impacts of climatic warming by simultaneously decreasing rates of methanogenesis while causing little change in rates of total anaerobic C mineralization in Sphagnum ‐dominated peatlands.

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 score0.330
Threshold uncertainty score0.488

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 head0.007
GPT teacher head0.205
Teacher spread0.198 · 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

Citations123
Published2003
Admission routes1
Has abstractyes

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