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Record W2790622287 · doi:10.2134/jeq2017.08.0317

Long‐term Trends in Corn Yields and Soil Carbon under Diversified Crop Rotations

2018· article· en· W2790622287 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Environmental Quality · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Guelph
FundersMinistry of Agriculture, Food and Rural AffairsOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsAgronomySoil carbonCrop rotationEnvironmental scienceRed CloverCrop yieldYield (engineering)CropCropping systemSoil waterBiologySoil science

Abstract

fetched live from OpenAlex

Agricultural practices such as including perennial alfalfa ( Medicago sativa L.), winter wheat ( Triticum aestivum L.), or red clover ( Trifolium pratense L.) in corn ( Zea mays L.) rotations can provide higher crop yields and increase soil organic C (SOC) over time. How well process‐based biogeochemical models such as DeNitrification‐DeComposition (DNDC) capture the beneficial effects of diversified cropping systems is unclear. To calibrate and validate DNDC for simulation of observed trends in corn yield and SOC, we used long‐term trials: continuous corn (CC) and corn–oats ( Avena sativa L.)–alfalfa–alfalfa (COAA) for Woodslee, ON, 1959 to 2015; and CC, corn–corn–soybean [ Glycine max (L.) Merr.]–soybean (CCSS), corn–corn–soybean–winter wheat (CCSW), corn–corn–soybean–winter wheat + red clover (CCSW+Rc), and corn–corn–alfalfa–alfalfa (CCAA) for Elora, ON, 1981 to 2015. Yield and SOC under 21st century conditions were projected under future climate scenarios from 2016 to 2100. The DNDC model was calibrated to improve crop N stress and was revised to estimate changes in water availability as a function of soil properties. This improved yield estimates for diversified rotations at Elora (mean absolute prediction error [MAPE] decreased from 13.4–15.5 to 10.9–14.6%) with lower errors for the three most diverse rotations. Significant improvements in yield estimates were also simulated at Woodslee for COAA, with MAPE decreasing from 24.0 to 16.6%. Predicted and observed SOC were in agreement for simpler rotations (CC or CCSS) at both sites (53.8 and 53.3 Mg C ha −1 for Elora, 52.0 and 51.4 Mg C ha −1 for Woodslee). Predicted SOC increased due to rotation diversification and was close to observed values (58.4 and 59 Mg C ha −1 for Elora, 63 and 61.1 Mg C ha −1 for Woodslee). Under future climate scenarios the diversified rotations mitigated crop water stress resulting in trends of higher yields and SOC content in comparison to simpler rotations. Core Ideas Corn grown in rotation had higher yield than corn grown in monoculture. Improvements in the DNDC model captured the yield increases in diversified rotations. Diversified rotations had higher SOC stock than corn in monoculture. DNDC‐predicted and observed values agreed well for yield and soil carbon. Benefits from diversified rotations were predicted by DNDC for future scenarios.

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.

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 score0.102
Threshold uncertainty score0.349

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 head0.036
GPT teacher head0.266
Teacher spread0.229 · 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