Surface Soil Quality Attributes following 12 Years of Conventional and Conservation Management on Irrigated Rotations in Southern Alberta
Bibliographic record
Abstract
Rapid expansion of irrigated row crop production, viz., potato ( Solanum tuberosum L.), dry bean ( Phaseolus vulgaris L.), and sugar beet ( Beta vulgaris L.), in southern Alberta in the late 1990s provided the impetus for a 12‐yr (2000–2011) study to evaluate cropping systems that maintained or improved soil quality. The study compared conservation (CONS) and conventional (CONV) management in rotations of 3‐ to 6‐yr duration. Conservation management included reduced tillage, cover crops, feedlot manure compost addition, and solid‐seeded narrow‐row dry bean production. After 12 yr, particulate organic matter C (POM‐C) and N (POM‐N) showed >145% increases (POM‐C, 2.2–5.8 Mg ha −1 ; POM‐N, 0.20–0.49 Mg ha −1 ) with CONS management compared with 45 to 50% increases in total organic C and N (TOC, 10.2–15.3 Mg ha −1 ; TN, 1.06–1.53 Mg ha −1 ) and 20% increases in fine organic matter (FOM)‐C and ‐N (FOM‐C, 8.3–10.1 Mg ha −1 ; FOM‐N, 0.87–1.04 Mg ha −1 ). Aggregate stability of the pre‐wet >1‐mm fraction increased significantly from 13% under CONV to 21% under CONS management. Overall, the 5‐yr CONS rotation (sugar beet–wheat ( Triticum aestivum L.)–dry bean–potato–wheat) ranked highest for soil quality (100%), with CONV rotations substantially lower (33–38%). Adoption of CONS management enhanced a wide range of soil quality attributes that could safeguard sustainable expansion of irrigated specialty cropping in southern Alberta.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".