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Record W2015850819 · doi:10.2166/wst.2011.719

Considerations for the mitigation of nitrate contamination: stable isotopes and insights into the importance of soil processes

2011· article· en· W2015850819 on OpenAlexafffund
George Somers, Martine M. Savard

Bibliographic record

VenueWater Science & Technology · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsGeological Survey of CanadaNatural Resources CanadaUniversity of Prince Edward Island
FundersDepartment of the Environment and Energy, Australian GovernmentNatural Resources CanadaU.S. Department of Energy
KeywordsFertilizerEnvironmental scienceNitrateNitrificationLeaching (pedology)Mineralization (soil science)NutrientGroundwaterOrganic matterDenitrificationSoil waterAgronomyEnvironmental chemistryNitrogenChemistrySoil science

Abstract

fetched live from OpenAlex

Nutrient management is widely promoted to minimize the impact of intensive fertilizer use on groundwater quality, however watershed-scale stable isotope studies in eastern North America suggest nitrogen transport to groundwater is dominated by non-growing season fluxes derived principally from the mineralization and nitrification of soil organic matter. In the current field scale study, delta15N ratios of nitrate in tile drain effluents from experimental potato plots treated with 300 kg/ha ammonia nitrate and those with no fertilizer both average +4.7 per thousand, close to the +4.0 per thousand ratios observed in soils of the same plots, and distinct from values near 0 per thousand for inorganic fertilizer. A source apportionment model using delta15N and delta18O in nitrate suggests that even with heavy fertilizer application, less than 10% of non-growing season N flux is derived from direct leaching of fertilizer, the remainder representing N from various sources, including residual fertilizer that has been assimilated into the broader soil organic matter pool and subsequently released via mineralization and nitrification. Factors controlling these losses could be as closely related to cropping practices as initial N application rates, providing potential opportunities for more efficiently utilizing N available in the soil profile and reducing initial N application rates.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.792
Threshold uncertainty score0.633

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 studies0.0000.002
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 head0.016
GPT teacher head0.204
Teacher spread0.188 · 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 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

Citations4
Published2011
Admission routes2
Has abstractyes

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