Soil carbon dynamics in perennial biomass crops on marginally productive cropland in southern Canada
Bibliographic record
Abstract
Predicting changes in soil organic carbon (SOC) in perennial biomass crops using process-based models provides a greater understanding of land management impacts on climate mitigation through long-term soil carbon sequestration. The objective of this study was to predict long-term SOC dynamics in different perennial biomass crops [miscanthus ( Miscanthus giganteus L.), switchgrass ( Panicum virgatum L.), willow ( Salix miyabeana L.)] as compared to secondary regrowth vegetation (successional site) and a row crop system. The Century model accurately predicted SOC when simulated values were compared to measured field data. Average SOC stocks over the 162-year simulation period to 20 cm, were highest in miscanthus (8521 g C m −2 ), followed by the successional site (6877 g C m −2 ), switchgrass (6480 g C m −2 ), willow (5448 g C m −2 ) and lowest in the row crop system (3995 g C m −2 ). Higher SOC stocks in the miscanthus than the successional site indicates that, despite frequent biomass harvest, perennial biomass crops can accumulate higher carbon in soil than when a marginally productive cropland is left to undergo secondary regrowth. However, this depends on the crop species, since the miscanthus was the only biomass crop that reached pre-cultivation (1911) SOC stock of 8288 g C m −2 . Moreover, the perennial biomass crops enhanced SOC in the slow fraction, whereas row crops depleted SOC in this fraction. This indicates the vital contribution of perennial biomass crops in long-term SOC sequestration and their role in climate change mitigation, especially when grown on marginally productive croplands. • Perennial biomass crops can enhance SOC storage. • The Century model accurately predicted SOC stocks in perennial biomass crops. • Perennial biomass crops on marginally productive land yielded greater SOC storage. • Soil organic carbon in biomass crops was associated with stabilized C fractions. • Biomass crops on marginal land can mitigate climate change via soil 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".