Early Impact of Topsoil Removal and Soil Amendments on Crop Productivity
Bibliographic record
Abstract
Wind erosion remains a common form of soil degradation on the semiarid northern Great Plains. This study was conducted to ascertain the effects of erosion on soil productivity and methods for its amelioration. Incremental depths (0, 5, 10, 15, and 20 cm) of surface soil or cuts were mechanically removed to simulate erosion at four sites (three dryland, one irrigated) in southern Alberta in 1990–1991. Three amendment treatments (N + P fertilizer, 5 cm of topsoil, or 75 Mg ha −1 of feedlot manure) and a check were superimposed on each of the cuts. In the first three years (1990–1992), there were highly significant relationships between cut and spring wheat ( Triticum aestivum L.) yield parameters (midseason biomass, grain and straw yield, head density, tillering capacity, and grain elemental concentrations). Removal of 20 cm of topsoil reduced grain yield by 53% (an average of 11 site‐years). Manure proved the best amendment for restoring productivity (e.g., an 11‐site‐year average increase of 158% in grain yield on the 20‐cm cut), with N + P fertilizer being the least effective (40% grain yield increase on the 20‐cm cut). Manure's ability to supply crop P, Mg, Mn, and Zn may partially explain its positive effect. Topsoil addition was intermediate in its restorative powers (89% yield increase after 20 cm topsoil removal). The study reinforces the need to prevent erosion and indicates that application of livestock manure is an option for restoring soil productivity in the short term.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.002 | 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 teacher head, 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".