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Record W1991263622 · doi:10.2136/sssaj2004.1394

Persistence of Soil Organic Carbon after Plowing a Long‐Term No‐Till Field in Southern Ontario, Canada

2004· article· en· W1991263622 on OpenAlexafffundabout
A.J. VandenBygaart, B. D. Kay

Bibliographic record

VenueSoil Science Society of America Journal · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsUniversity of GuelphAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsTillageLoamPloughSoil carbonEnvironmental scienceSoil scienceSoil waterNo-till farmingAgronomySoil fertility

Abstract

fetched live from OpenAlex

There is abundant evidence that minimizing soil disturbance reduces mineralization of organic matter and can result in larger storage of soil organic carbon (SOC) relative to conventional tillage. However, little is known about the persistence of SOC when no‐till lands are plowed periodically. This study set out to determine the change in SOC when a long‐term (22 yr) no‐till field in southern Ontario, Canada, was plowed once. Four plots were located within three textural classes [sandy loam (SL), sandy clay loam (SCL), and silty clay loam (SiCL)] within two hydrologic conditions (well‐ and poorly drained) in the field. The plots were sampled before and three times after (3 d, 7 mo, and 18 mo) the no‐till field was moldboard plowed. The single tillage event homogenized the SOC through the profile and reduced the stratification. When calculated on an equivalent mass basis beyond the plow depth, there was no significant change in SOC 18 mo after plowing the SCL, SiCL, and SL high SOC plots. However, in the SL plot with low SOC, there was a loss of about 3 Mg SOC ha −1 after 18 mo, and the loss occurred primarily between the 15‐ and 30‐cm depths in the profile. The loss may have accounted for as much as two‐thirds of the SOC gained from no‐tillage. This study also emphasized the need for additional care to account for changes in bulk density when comparing the quantity of soil constituents, such as SOC, after plowing.

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 score0.329
Threshold uncertainty score0.299

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.186
Teacher spread0.178 · 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

Citations79
Published2004
Admission routes3
Has abstractyes

Explore more

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