Management effects on the dynamics and storage rates of organic matter in long-term crop rotations
Bibliographic record
Abstract
Factors controlling soil organic matter (SOM) dynamics in soil C sequestration and N fertility were determined from multi-site analysis of long-term, crop rotation experiments in Western Canada. Analyses included bulk density, organic and inorganic C and N, particulate organic C (POM-C) and N (POM -N), and CO2-C evolved during laboratory incubation. The POM-C and POM-N contents varied with soil type. Differences in POM-C contents between treatments at a site (δPOM-C) were related (r2= 0.68) to treatment differences in soil C (δSOC). The CO2-C, evolved during laboratory incubation, was the most sensitive indicator of management effects. The Gray Luvisol (Breton, AB) cultivated plots had a fivefold difference in CO2-C release relative to a twofold difference in soil organic carbon (SOC). Soils from cropped, Black Chernozems (Melfort and Indian Head, SK) and Dark Brown Chernozems (Lethbridge, AB) released 50 to 60% as much CO2-C as grassland soils. Differences in CO2 evolution from the treatment with the lowest SOM on a site and that of other treatments (δCO2-C) in the early stages of the incubation were correlated to δPOM-C and this pool reflects short-term SOC storage. Management for soil fertility, such as N release, may differ from management for C sequestration.
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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 | 0.000 | 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".