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Record W1964022924 · doi:10.4141/s99-045

Quantifying short-term effects of crop rotations on soil organic carbon in southwestern Saskatchewan

2000· article· en· W1964022924 on OpenAlexaffvenueabout
C. A. Campbell, R.P. Zentner, F. Selles, V. O. Biederbeck, B.G. McConkey, B. Blomert, P. G. Jefferson

Bibliographic record

VenueCanadian Journal of Soil Science · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsSoil carbonCrop rotationChernozemAgronomyCrop residueEnvironmental scienceTillageStrawHumusSoil fertilityCalcareousCropSoil waterSoil scienceAgricultureGeographyBiology

Abstract

fetched live from OpenAlex

Crop management practices can have a major influence on soil fertility and soil organic C (SOC) sequestration. We need to accurately measure and estimate changes in SOC in the short term (<20 yr). A 10-yr crop rotation experiment, conducted on a medium-textured Orthic Brown Chernozem at Swift Current, in southwestern Saskatchewan, was sampled in 1990 (3 yr after initiation of the study) and in 1993 and 1996, to measure SOC changes under nine crop rotation treatments. Minimum tillage practices were used. The stubble was cut high to enhance snow trap and N and P fertilizer applied based on soil tests. Grain and straw yields of the cereals, and hay yields of the crested wheatgrass (CWG) [Agropyron cristatum (L.) Gaeertn.] were measured annually. An empirical equation which uses two simultaneous first order kinetic expressions, one to estimate crop residue decomposition and the other to estimate soil humus C mineralization was used, together with crop residue (straw and estimated root) C inputs, to estimate SOC changes over the 1987 to 1996 period. The estimated SOC values for the 1990 to 1996 period were generally similar to the measured values (r 2 = 0.64, P < 0.0001). Significant (P < 0.10) changes in SOC were not observed below 15 cm depth, perhaps because shallow tillage (10- to 12.5-cm depth) is practiced. A change from cropland to CWG did not increase SOC, and this treatment, chemical fallow-winter wheat (Triticum aestivum L.)-spring wheat (F-WW-W), and F-high-yielding (Hy) Canada Prairie Spring (CPS) wheat-Hy (F-Hy-Hy) rotations, had the lowest SOC gains among the rotations. The CPS wheat had a higher harvest index (0.46) than hard red spring (HRS) wheat (0.39), but it increased SOC less than the comparable HRS wheat rotation between 1990 and 1996 indicating that higher grain yields do not always equate to higher SOC. Weather conditions were favourable for cereals from 1990 to 1996 and we measured significant increases in SOC (up to 5.5 Mg ha −1 in 6 yr). This is encouraging for producers who may be contemplating participating in "C trading", although this also suggests that periods of less favourable weather will limit gains in SOC. Summerfallowing once in 4 yr in this semiarid environment did not reduce SOC gains compared to continuous wheat (Cont W). For example, a F-W-W-W rotation gained 4.88 Mg C ha −1 in 6 yr while continuous wheat gained 5 Mg ha −1 . Growing Indianhead lentil (Lens culinaris Medikus) as a legume green manure crop (GM) with wheat in a GM-W-W rotation did not increase SOC more than F-W-W. The efficiencies of conversion of residue C to SOC were high, ranging between 9% for frequently fallowed systems to 29% for continuously cropped systems, likely due to the favourable weather conditions experienced. Key words: Carbon sequestration, legume green manure, crested wheatgrass, harvest index effect, C conversion efficiencies

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.232
Threshold uncertainty score0.466

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.226
Teacher spread0.208 · 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 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

Citations122
Published2000
Admission routes3
Has abstractyes

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