The influence of ecological cropping practices on aggregate stability: results from two long-term studies
Bibliographic record
Abstract
Agricultural cropping practices, including crop rotations with annual grains and perennial forages, cover crops, and no-till and organic management influence soil processes. Aggregate stability is a soil property that relates to many different physical and biological functions of the soil, and as such is an important indicator of soil health. It was hypothesized that aggregate stability would be improved through the following cropping system interventions: 1) including two years of alfalfa (Medicago sativa L.) in an organic annual grain rotation; 2) adding composted manure to long-term organic systems; 3) including four years of perennial forages in rotation with annual grains as a one-time intervention for system rehabilitation; and 4) including cover crops in a no-till crop rotation. Furthermore, the first two cropping system interventions were compared to conventional rotations and long-term grasslands. This research took place at two long term studies, a rotation study in southern Manitoba and a cover crop study in south eastern Saskatchewan. The rotation study included an annual grain rotation, consisting of wheat (Triticum aestivum L.) - flax (Linum usitatissimum L.) - oat (Avena sativa L.) - hairy vetch (Vicia villosa Roth) / barley (Hordeum vulgare L.) green manure, and a perennial forage and grain rotation (wheat-flax-two years of alfalfa). Composted manure was added to the organic forage grain rotation every four years. The cover crop study used black medic (Medicago lupulina L.) as a self-regenerating cover crop. Black medic produces large amounts of seed and regrows each spring, to grow under the crop and continues to grow in the fall after harvest. It was grown in a no-till wheat-flax-canaryseed (Phalaris canariensis L.) rotation at two nitrogen fertilizer levels. Aggregate stability samples were taken in both wheat and flax phases of the rotations at both sites in the spring of 2017 and 2018. A wet sieving procedure using stacked sieves with five mesh sizes was used to determine mean weight diameter (MWD) of stable aggregates. At both study sites grassland areas had higher MWD and generally more 1-6.3mm aggregates and fewer 0.25-1mm aggregates than the arable treatments. In a few cases the rotations with a perennial forage component had similar AS to the grasslands. The perennial forage increased MWD under organic management at 10-20cm depth. Manure additions did not affect AS, and in most cases neither did the perennial forage in rotation. The presence of alfalfa in the alfalfa intervention increased AS but the number of years in alfalfa did not. The black medic cover crop increased MWD with low nitrogen fertilizer in the wheat phase but not the flax phase of rotation. It was concluded that long term grasslands and cover crops were the most effective ways to improve AS at these sites.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".