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Deciphering the oxygen isotope composition of nitrous oxide produced by nitrification

2011· article· en· W2164024489 on OpenAlexafffund
David Snider, Jason J. Venkiteswaran, Sherry L. Schiff, John Spoelstra

Bibliographic record

VenueGlobal Change Biology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsEnvironment and Climate Change CanadaUniversity of Waterloo
FundersUniversity of Waterloo
KeywordsNitrous oxideNitrificationHydroxylamineDenitrificationNitriteNitrous acidSoil waterEnvironmental chemistryChemistryNitrogenEnvironmental scienceInorganic chemistrySoil scienceNitrateOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The ability to use δ18O values of nitrous oxide (N2O) to apportion environmental emissions is currently hindered by a poor understanding of the controls on δ18O–N2O from nitrification (hydroxylamine oxidation to N2O and nitrite reduction to N2O). In this study fertilized agricultural soils and unfertilized temperate forest soils were aerobically incubated with different 18O/16O waters, and conceptual and mathematical models were developed to systematically explain the δ18O–N2O formed by nitrification. Modeling exercises used a set of defined input parameters to emulate the measured soil δ18O–N2O data (Monte Carlo approach). The Monte Carlo simulations implied that abiotic oxygen (O) exchange between nitrite (NO2−) and H2O is important in all soils, but that biological, enzyme‐controlled O‐exchange does not occur during the reduction of NO2− to N2O (nitrifier‐denitrification). Similarly, the results of the model simulations indicated that N2O consumption is not characteristic of aerobic N2O formation. The results of this study and a synthesis of the published literature data indicate that δ18O–N2O formed in aerobic environments is constrained between +13‰ and +35‰ relative to Vienna Standard Mean Ocean Water (VSMOW). N2O formed via hydroxylamine oxidation and nitrifier‐denitrification cannot be separated using δ18O unless 18O tracers are employed. The natural range of nitrifier δ18O–N2O is discussed and explained in terms of our conceptual model, and the major and minor controls that define aerobically produced δ18O–N2O are identified. Despite the highly complex nature of δ18O–N2O produced by nitrification this δ18O range is narrow. As a result, in many situations δ18O values may be used in conjunction with δ15N–N2O data to apportion nitrifier‐ and denitrifier‐derived N2O. However, when biological O‐exchange during denitrification is high and N2O consumption is low, there may be too much overlap in δ18O values to distinguish N2O formed by these pathways.

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 score0.004
Threshold uncertainty score0.008

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 studies0.0000.000
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 head0.039
GPT teacher head0.235
Teacher spread0.196 · 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

Citations61
Published2011
Admission routes2
Has abstractyes

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