Quantification of the Carbon Sequestration Potential of a 31-year-old Tree-based Intercropping System in Southern Ontario, Canada
Bibliographic record
Abstract
Carbon (C) storage potential was quantified for four tree species which are commonly incorporated into tree-based intercropping (TBI) systems and compared with conventional agricultural systems in southern Ontario, Canada. In the 31-year-old TBI system at the University of Guelph's Agroforestry Research Station, Norway spruce (<italic>Picea abies</italic>), white cedar (<italic>Thuja occidentalis</italic>), black walnut (<italic>Juglans nigra</italic>) and red oak (<italic>Quercus rubra</italic>) were planted in tree rows, intercropped with soybean (<italic>Glycine max</italic>). In the conventional agricultural field, soybean was grown in a monocropping system. Above and belowground tree and crop C content, soil organic C (SOC) and system level C was quantified for each tree species as well as the conventional agricultural system. Red oak TBI systems had the highest SOC followed by black walnut, Norway spruce and white cedar with values of 93.2, 83.9, 78.1, and 72.2 t C ha<sup>-1</sup>, respectively. Red oak TBI systems also had the highest mean tree C content, followed by black walnut, Norway spruce and white cedar, with values of 299.7, 285.8, 255.4 and 70.1 kg C tree<sup>-1</sup>, respectively. Total system level C, which incorporated SOC, tree C content and tree planting densities was 134.8, 126.4, 115.7, 95.6 and 75.6 t C ha<sup>-1</sup> respectively for spruce, oak, walnut and cedar TBI systems and the agricultural field. TBI systems provide higher C sequestration potentials than conventional agricultural fields, and Norway spruce and red oak should be included into TBI systems in southern Ontario to maximize C sequestration benefits.
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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".