Effects of crop rotation, crop type and tillage on soil organic carbon in a semiarid climate
Bibliographic record
Abstract
Shrestha, B. M., McConkey, B. G., Smith, W. N., Desjardins, R. L., Campbell, C. A., Grant, B. B. and Miller, P. R. 2013. Effects of crop rotation, crop type and tillage on soil organic carbon in a semiarid climate. Can. J. Soil Sci. 93: 137-146. There is uncertainty about how crop rotation and tillage affect soil organic C (SOC) on the Canadian prairies. We compared SOC amount and change (ΔSOC) for one continuous crop and four 3-yr fallow-containing crop rotations under no-tillage (NT), and two fallow-containing crop rotations under minimum-tillage (MT), from 1995 to 2005 in semiarid southwestern Saskatchewan. After 11 yr, SOC (0- to 15-cm depth) was 0.2 Mg C ha-1 higher under continuous crop compared with fallow-containing systems. There were no significant differences in SOC and ΔSOC among fallow-containing rotations or between MT and NT. Total C inputs were weakly (R 2=0.18) but significantly (P<0.05) correlated to ΔSOC, which changed by ±0.33 Mg C ha-1 for each Mg ha-1 C input above or below 2.4 Mg C ha-1 yr-1. Carbon inputs were typically less than this amount and SOC generally decreased over the experiment. Simulations of SOC with the Century model were consistent with our observations regarding ΔSOC per unit of C input. There was slight loss of SOC for the above-average precipitation regime during the study. Simulations also supported our finding that SOC differences between crop mix and tillage systems may require several decades to become distinguishable in this semiarid climate with small and variable C inputs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".