Macroaggregate Characteristics in Cultivated Soils after 25 Annual Manure Applications
Bibliographic record
Abstract
Agricultural management practices that alter the soil organic matter (SOM) content are expected to cause changes in soil stability and aggregation. Animal manure is a source of organic matter (OM) that has been demonstrated to increase macroaggregate formation and stability. The objectives of this study were to determine how long term cattle manure applications to a calcareous Haploboroll clay loam (Lethbridge, AB, Canada) affected aggregate size distribution, the total C, N, and P content of aggregate size fractions, and water‐stable aggregates. Beef cattle manure applied at rates >30 Mg ha −1 yr −1 under dryland production and >60 Mg ha −1 yr −1 to soils under irrigation resulted in fewer dry‐sieved aggregates >7.1 mm and more dry‐sieved aggregates between 0.47 and 1.2 mm in the 0‐ to 5‐cm depth, compared with unamended soils. The dry‐sieved aggregate fractions between 0.47 and 1.2 mm include the <0.84‐mm fraction that has been associated with increased susceptibility to wind erosion in the Canadian semiarid prairies. There was more total C, N, and P in all dry‐sieved aggregate fractions of soils receiving >30 Mg manure ha −1 yr −1 than unamended soils, and dry‐sieved aggregates between 0.47 and 2.0 mm tended to have the highest C, N, and P contents. Water aggregate stability was higher in irrigated than dryland soils, but did not improve with increasing manure application rates. Dispersing agents in the cattle manure appear to have destabilized the larger soil macroaggregates.
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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 | 0.000 |
| 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".