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Record W4293771237 · doi:10.3389/fenvs.2022.897221

Winter warming effects on soil nitrate leaching under cover crops: A field study using high-frequency weighing lysimeters

2022· article· en· W4293771237 on OpenAlexafffundabout
Jared Lapierre, Pedro Vitor Ferrari Machado, Zachary Debruyn, Shannon E. Brown, Seán F. Jordan, Aaron Berg, Asim Biswas, Hugh A. L. Henry, Claudia Wagner‐Riddle

Bibliographic record

VenueFrontiers in Environmental Science · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsWestern UniversityAgriculture and Agri-Food CanadaUniversity of Guelph
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaOntario Agri-Food Innovation AllianceGrain Farmers of OntarioOntario Ministry of Agriculture, Food and Rural AffairsUniversity of GuelphMinistry of Agriculture, Food and Rural AffairsCanada Foundation for Innovation
KeywordsLysimeterEnvironmental scienceLeaching (pedology)LoamSoil waterAgronomyDrainageCover cropWater contentHydrology (agriculture)Soil scienceAgroforestryEcology

Abstract

fetched live from OpenAlex

Leaching of nitrate (NO 3 − )—a reactive nitrogen form with impacts on ecosystem health—increases during the non-growing season (NGS) of agricultural soils under cold climates. Cover crops are effective at reducing NGS NO 3 − leaching, but this benefit may be altered with less snow cover inducing more soil freezing under warmer winters. Our objective was to quantify the effect of winter warming on NO 3 − leaching from cover crops for a loamy sand (LS) and a silt loam (SIL) soil. This research was conducted over 2 years in Ontario, Canada, using 18 high-precision weighing lysimeters designed to study ecosystem services from agricultural soils. Infra-red heaters were used to simulate warming in lysimeters under a wheat-corn-soybean rotation planted with a cover crop mixture with (+H) and without heating (-H). Nitrate leaching determination used NO 3 − concentration at 90 cm (discrete sampling) and high temporal resolution drainage volume measurements. Data were analyzed for fall, overwinter, spring-thaw, post-planting, and total period (i.e., November 1 to June 30 of 2017/2018 and 2018/2019). Warming significantly affected soil temperature and soil water content—an effect that was similar for both years. As expected, experimental units under + H presented warmer soils at 5 and 10 cm, along with higher soil water content in liquid form than –H lysimeters, which translated into higher drainage values for + H than –H, especially during the overwinter period. NO 3 − concentrations at 90 cm were only affected by winter heating for the LS soil. The drainage and NO 3 − concentrations exhibited high spatial variation, which likely reduced the sensitivity to detect significant differences. Thus, although absolute differences in NO 3 − leaching between LS vs. SIL and +H (LS) vs. –H (LS) were large, only a trend occurred for higher leaching in LS in 2018/2019. Our research demonstrated that soil heating can influence overwinter drainage (for LS and SIL soils) and NO 3 − concentration at 90 cm in the LS soil—important NO 3 − leaching controlling factors. However, contrary to our initial hypothesis, the heating regime adopted in our study did not promote colder soils during the winter. We suggest different heating regimes such as intermittent heating to simulate extreme weather freeze/thaw events as a future research topic.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.499
Threshold uncertainty score0.649

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.008
GPT teacher head0.204
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 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

Citations5
Published2022
Admission routes3
Has abstractyes

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