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Record W2768500565 · doi:10.1038/s41467-017-01406-6

Anaerobic microsites have an unaccounted role in soil carbon stabilization

2017· article· en· W2768500565 on OpenAlexfundno aff
Marco Keiluweit, Tom Wanzek, Markus Kleber, Peter Nico, Scott Fendorf

Bibliographic record

VenueNature Communications · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
FundersPacific Northwest National LaboratoryNational Research Council CanadaWestern Economic Diversification CanadaBiological and Environmental ResearchNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchOffice of ScienceUniversity of SaskatchewanCanadian Light SourceU.S. Department of Energy
KeywordsEnvironmental scienceCarbon cycleSoil carbonEcosystemAnaerobic exerciseMineralization (soil science)Soil respirationAnaerobic respirationSoil waterEcologyCarbon fibersEnvironmental chemistryChemistrySoil scienceBiology

Abstract

fetched live from OpenAlex

Soils represent the largest carbon reservoir within terrestrial ecosystems. The mechanisms controlling the amount of carbon stored and its feedback to the climate system, however, remain poorly resolved. Global carbon models assume that carbon cycling in upland soils is entirely driven by aerobic respiration; the impact of anaerobic microsites prevalent even within well-drained soils is missed within this conception. Here, we show that anaerobic microsites are important regulators of soil carbon persistence, shifting microbial metabolism to less efficient anaerobic respiration, and selectively protecting otherwise bioavailable, reduced organic compounds such as lipids and waxes from decomposition. Further, shifting from anaerobic to aerobic conditions leads to a 10-fold increase in volume-specific mineralization rate, illustrating the sensitivity of anaerobically protected carbon to disturbance. The vulnerability of anaerobically protected carbon to future climate or land use change thus constitutes a yet unrecognized soil carbon-climate feedback that should be incorporated into terrestrial ecosystem models.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.275
Teacher spread0.256 · 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 designBench or experimental
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

Citations519
Published2017
Admission routes1
Has abstractyes

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Same venueNature CommunicationsSame topicSoil Carbon and Nitrogen DynamicsFrench-language works237,207