Gross nitrogen mineralization in pulse-crop rotations on the Northern Great Plains
Bibliographic record
Abstract
Pulse crops represent an ever-increasing proportion of cropping systems in the Northern Great Plains. Previous studies have noted apparent benefits associated with pulse crop production that extend beyond the reduced need for N fertilizer in the year of production; these benefits have been attributed to the quality of pulse residues and their effects on N dynamics in subsequent years. This study used isotope dilution techniques to quantify the N-cycling effects of pulse crops in the rotation. Gross N mineralization was measured over three growing seasons at two Agriculture and Agri-Food Canada research sites in Saskatchewan, Canada: Scott (four rotations; one with pulse crop) and Swift Current (three rotations; one with pulse crop). Gross nitrification and the relative contribution of nitrification vs. denitrification to N2O emissions were also measured. Across all dates and rotations, the average gross mineralization rate at Scott was 2.0 ± 4.0 mg NH4 +-N kg−1 soil d−1 and at Swift Current was 1.4 ± 3.9 mg NH4 +-N kg−1 soil d−1. At both sites, rates were highly variable across the growing season, but tended to be higher at anthesis than either pre-seeding or post-harvest. The only significant difference among rotations was at Swift Current, where the fertilized continuous wheat rotation had the highest gross mineralization rates (rotation average: 2.3 mg NH4 +-N kg−1 soil d−1). The lack of difference among most rotations was particularly notable given the differences in residue quantity among the crops. Ultimately, the lower quantity of residues produced by pulse crops appears to be offset by their higher quality.
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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 | 0.000 | 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".