Soil organic carbon pools as influenced by 21 years of conservation agriculture management practices in Saskatchewan
Bibliographic record
Abstract
Soil organic carbon (SOC) content is a key metric of soil quality and limited work has been done to examine the effect of long-term conservation agriculture management practices (CAMP) on SOC pools within western Canadian soils. We assessed the nature and permanence of sequestered SOC within 90 diverse Saskatchewan surface (0–10 cm) agricultural soils before and after 21 years of CAMP. Comparisons were made of total SOC, labile and dynamic SOC fractions (light fraction, water-extractable, and microbial biomass), respirable CO 2 –C during a 6-week incubation, along with spectroscopic characterization using 13 C/ 12 C stable isotope ratio and ATR-FTIR. Among soil climatic zones, the SOC content increased in the semi-arid Brown and Dark Brown soils, ranging from 2.4 to 3.7 Mg C ha −1 (111.4–187.7 kg C ha −1 year −1 ), but did not change in the subhumid Black, Dark Gray, and Gray soils. Overall, soils having the smallest initial SOC level were most responsive to CAMP and accumulated more SOC. According to the δ 13 C data, CAMP appeared to reduce annual crop moisture stress, especially within the Brown soil zone. Decreased light fraction and water-extractable SOC contents in Black, Dark Gray, and Gray soils could reflect more intense decomposition and greater surface stratification of crop residues. Brown soils experienced the largest increase in microbial biomass-C content. The CO 2 –C emissions from the Brown, Dark Brown, and Gray soils under CAMP suggest greater SOC stability in 2018 compared with 1996. The ATR-FTIR data pointed to enhanced SOC persistence, via more stabilized SOC forms and mineral-associated organic C fractions.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".