Twenty-four years of contrasting cropping systems on a brown chernozem in Southern Alberta: crop yields, soil carbon, and subsoil salinity
Bibliographic record
Abstract
Cropping systems with perennial forages and reduced fallow frequency generally increase soil organic carbon and thus subsequent soil health and crop yield. We evaluated the impact of prior cropping systems on subsequent yields and soil properties in a semiarid region by using crop yields as a bioassay of soil health following the termination of a 24-year crop rotation study in the Brown soil zone in Alberta. During 24 growing seasons from 1992 to 2015, the study included three fallow-containing rotations, two annual crop rotations that were cropped continuously, and perennial grass hay, each with two to six fertilizer treatments. During the bioassay period from 2016 through 2020, all plots in the study were uniformly cropped. Compared to unfertilized fallow wheat, soil organic C in the fall of 2015 was 54% higher after 24 years of fertilized grass and up to 14% higher following annual crops in rotations without fallow. The most notable impact of the previous cropping system on yield during the bioassay years was low yield following perennial grass in 2016 and 2018. Soil electrical conductivity measurements showed that subsoil salinity was elevated following perennial grass, demonstrating the importance of subsoil characteristics for healthy soils. Crop yields in the fifth year of the crop bioassay were 10%–20% greater due to reduced fallow frequency or increased crop diversity. The long-term impact of the cropping system on crop yield in this study depended on drought intensity due to counteracting changes in soil organic matter and subsoil salinity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".