Soil carbon stocks in cultivated Luvisols respond positively to long-term agronomic practices with different degrees of perennial forage inclusion
Bibliographic record
Abstract
Data that are relevant, substantive, and reliable are needed to verify long-term management effects on carbon (C) stocks in agricultural soils. The Breton Plots research facility in West Central Alberta, Canada, provides a unique opportunity to investigate how diverse long-term agricultural practices have influenced C storage in low-fertility Luvisolic soils from boreal regions. The Classical Plots experiment (est. 1930) includes unamended, conventionally fertilized, and manured sub-treatments of a wheat-fallow and 5-year rotation comprising annual grains (3 yr) and perennial forage (2 yr). The Hendrigan Plots experiment (est. 1980) includes a continuous forage system; a continuous grain system; and an 8-year agroecological rotation of annual grains (4 yr), leguminous green manure (1 yr), and perennial forage (3 yr). Soil organic carbon (SOC) stocks were reported on an equivalent soil mass basis in various intervals corresponding to a maximum depth of 90 cm. Compared to continuous grain cropping, total SOC stock was 49 % lower under fallow and, on average, 9 % higher under forage-inclusive rotations. Compared to unamended treatments, conventional fertilizer and manure increased SOC stocks by an average of 7 % and 39 %, respectively. Compared to continuous grain cropping, using the 2024 valuation of carbon ($80 t CO 2 -e −1 ) in Canada, SOC stock differences translated into a loss of approximately $11,000 CAD ha −1 under fallow, and gains exceeding $5000 CAD ha −1 under continuous forage or agroecological management. This work clarifies how Luvisolic soils can be managed to optimize SOC stocks and how C valuation could incentivize agricultural practices conducive to this goal.
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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".