Changes in soil carbon stocks under perennial and annual bioenergy crops
Bibliographic record
Abstract
Abstract Bioenergy crops are expected to provide biomass to replace fossil resources and reduce greenhouse gas emissions. In this context, changes in soil organic carbon (SOC) stocks are of primary importance. The aim of this study was to measure changes in SOC stocks in bioenergy cropping systems comparing perennial ( Miscanthus × giganteus and switchgrass), semi‐perennial (fescue and alfalfa), and annual (sorghum and triticale) crops, all established after arable crops. The soil was sampled at the start of the experiment and 5 or 6 years later. SOC stocks were calculated at equivalent soil mass, and δ 13 C measurements were used to calculate changes in new and old SOC stocks. Crop residues found in soil at the time of SOC measurements represented 3.5–7.2 t C ha −1 under perennial crops vs. 0.1–0.6 t C ha −1 for the other crops. During the 5‐year period, SOC concentrations under perennial crops increased in the surface layer (0–5 cm) and slightly declined in the lower layers. Changes in δ 13 C showed that C inputs were mainly located in the 0–18 cm layer. In contrast, SOC concentrations increased over time under semi‐perennial crops throughout the old ploughed layer (ca. 0–33 cm). SOC stocks in the old ploughed layer increased significantly over time under semi‐perennials with a mean increase of 0.93 ± 0.28 t C ha −1 yr −1 , whereas no change occurred under perennial or annual crops. New SOC accumulation was higher for semi‐perennial than for perennial crops (1.50 vs. 0.58 t C ha −1 yr −1 , respectively), indicating that the SOC change was due to a variation in C input rather than a change in mineralization rate. Nitrogen fertilization rate had no significant effect on SOC stocks. This study highlights the interest of comparing SOC changes over time for various cropping systems.
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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) | 0.001 | 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".