Soil Nitrogen and Phosphorus Dynamics and Uptake by Wheat Grown in Drained Prairie Soils under Three Moisture Scenarios
Bibliographic record
Abstract
Core Ideas Nutrient fate and form was investigated in drained soils under various moisture scenarios. Drained soils had greater aboveground biomass and N and P uptake than undrained soils. Mineralization and water holding capacity appeared to affect nutrient losses. In semiarid and sub‐humid Saskatchewan, Canada, there is growing interest in draining depressional areas within the landscape (prairie potholes) despite a clear understanding of the potential nutrient loss to nearby water sources. Nutrient fate and form can vary greatly depending on soil moisture regime; the aim of this study was to determine how drainage duration affects the nitrogen (N) and phosphorus (P) availability and mobility under varying moisture levels. A greenhouse experiment was conducted using four depressional soils from south‐eastern Saskatchewan, which had been drained for 0, 14, 20, and 42 yr, and one undrained midslope soil for comparison. The potted soils were seeded with wheat ( Triticum aestivum L. ), three different moisture scenarios applied, and leachate was collected weekly. Drained soils had greater aboveground biomass and N and P plant uptake compared with undrained soil. These differences were most pronounced in the 20 yr drained soil, which had a 30% increase in growth, 45% greater N uptake, and 62% greater P uptake than the undrained soil. Nitrogen mineralization and water holding capacity appeared to affect nutrient losses. The soil that contributed the most to nutrient losses varied under different moisture scenarios; low water holding capacity contributed to nutrient leaching under lower moisture scenarios, whereas enhanced mineralization increased losses under above‐average moisture.
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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".