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Record W3123514839 · doi:10.3390/agronomy11010187

Topography Controls N2O Emissions Differently during Early and Late Corn Growing Season

2021· article· en· W3123514839 on OpenAlexafffund
Waqar Ashiq, Hiteshkumar B. Vasava, Uttam Ghimire, Prasad Daggupati, Asim Biswas

Bibliographic record

VenueAgronomy · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsGrowing seasonEnvironmental scienceAgronomyAgricultureNitrous oxideSoil waterHydrology (agriculture)Atmospheric sciencesSoil scienceEcologyGeologyBiology

Abstract

fetched live from OpenAlex

Topography affects soil hydrological, pedological, and biochemical processes and may influence nitrous oxide (N2O) emissions into the atmosphere. While N2O emissions from agricultural fields are mainly measured at plot scale and on flat topography, intrafield topographical and crop growth variability alter soil processes and might impact N2O emissions. The objective of this study was to examine the impact of topographical variations on crop growth period dependent soil N2O emissions at the field scale. A field experiment was conducted at two agricultural farms (Baggs farm; BF and Research North; RN) with undulating topography. Dominant slope positions (upper, middle, lower and toeslope) were identified based on elevation difference. Soil and gas samples were collected from four replicated locations within each slope position over the whole corn growing season (May–October 2019) to measure soil physio-chemical properties and N2O emissions. The N2O emissions at BF ranged from −0.27 ± 0.42 to 255 ± 105 g ha−1 d−1. Higher cumulative emissions were observed from the upper slope (1040 ± 487 g ha−1) during early growing season and from the toeslope (371 ± 157 g ha−1) during the late growing season with limited variations during the mid growing season. Similarly, at RN farm, (emissions ranged from −0.50 ± 0.83 to 70 ± 15 g ha−1 d−1), the upper slope had higher cumulative emissions during early (576 ± 132 g ha−1) and mid (271 ± 51 g ha−1) growing season, whereas no impact of slope positions was observed during late growing season. Topography controlled soil and environmental properties differently at different crop growth periods; thus, intrafield variability must be considered in estimating N2O emissions and emission factor calculation from agricultural fields. However, due to large spatial variations in N2O emissions, further explorations into site-specific analysis of individual soil properties and their impact on N2O emissions using multiyear data might help to understand and identify hotspots of N2O emissions.

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 score0.366
Threshold uncertainty score0.191

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 head0.009
GPT teacher head0.190
Teacher spread0.181 · 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

Citations15
Published2021
Admission routes2
Has abstractyes

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