Soil and root carbon storage is key to climate benefits of bioenergy crops
Bibliographic record
Abstract
Most bioenergy feedstock studies focus on maximizing aboveground biomass production. Cropland with fertile soils can produce high aboveground biomass yields but its diversion to bioenergy causes greenhouse gas emissions from direct and indirect land use changes. Here, we analyze three grassland experiments that minimize land use changes by using abandoned and degraded agricultural land. We find that soil and root carbon storage is a greater determinant of the climate change mitigation potential of biofuels than aboveground biomass, and tends to be higher for treatments with high plant diversity. Aboveground biomass yield ranged from 450-650 g ha-2 yr-1 for the productive treatments with moderate intensification, but its climate benefit via converting into biofuels and displacing fossil fuels can be substantially reduced by the rebound effect of fuel market. Because of high soil and root C storage rates (152-483 g CO2 ha-2 yr-1), many treatments are carbon negative even without the fossil fuel displacement benefit. To effectively mitigate greenhouse gas emissions, we should focus on increasing belowground carbon storage and explore the potential benefits of high-diversity plant species mixtures.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".