Long-Term Monitoring of Soil Carbon Sequestration in Woody and Herbaceous Bioenergy Crop Production Systems on Marginal Lands in Southern Ontario, Canada
Bibliographic record
Abstract
Enhancement of terrestrial carbon (C) sequestration on marginal lands in Canada using bioenergy crops has been proposed. However, factors influencing system-level C gain (SLCG) potentials of maturing bioenergy cropping systems, including belowground biomass C and soil organic carbon (SOC) accumulation, are not well documented. This study, therefore, quantified the long-term C sequestration potentials at the system-level in nine-year-old (2009–2018) woody (poplar clone 2293–29 (Populus spp.), hybrid willow clone SX-67 (Salix miyabeana)), and herbaceous (miscanthus (Miscanthus giganteus var. Nagara), switchgrass (Panicum virgatum)) bioenergy crop production systems on marginal lands in Southern Ontario, Canada. Results showed that woody cropping systems had significantly higher aboveground biomass C stock of 10.02 compared to 7.65 Mg C ha−1 in herbaceous cropping systems, although their belowground biomass C was not significantly different. Woody crops and switchgrass were able to increase SOC significantly over the tested period. However, when long term soil organic carbon (∆SOC) gains were compared, woody and herbaceous biomass crops gained 11.0 and 9.8 Mg C ha−1, respectively, which were not statistically different. Results also indicate a significantly higher total C pool [aboveground + belowground + soil organic carbon] in the willow (103 Mg ha−1) biomass system compared to other bioenergy crops. In the nine-year study period, woody crops had only 1.35 Mg C ha−1 more SLCG, suggesting that the influence of woody and herbaceous biomass crops on SLCG and ∆SOC sequestrations were similar. Further, among all tested biomass crops, willow had the highest annual SLCG of 1.66 Mg C ha−1 y−1.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".