Long‐term Trends in Corn Yields and Soil Carbon under Diversified Crop Rotations
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".