Carbon Sequestration and Carbon Markets for Tree-Based Intercropping Systems in Southern Quebec, Canada
Bibliographic record
Abstract
Since agriculture directly contributes to global anthropogenic greenhouse gas (GHG) emissions, integrating trees into agricultural landscapes through agroforestry systems is a viable adaptive strategy for climate change mitigation. The objective of this study was to evaluate the carbon (C) sequestration and financial benefits of C sequestration according to Quebec’s Cap-and-Trade System for Greenhouse Gas Emissions Allowances (C & T System) or the Système de plafonnement et d’échange de droits d’émission de gaz à effet de serre du Québec (SPEDE) program for two experimental 10-year-old tree-based intercropping (TBI) systems in southern Quebec, Canada. We estimated total C stored in the two TBI systems with hybrid poplar and hardwoods and adjacent non-TBI systems under agricultural production, considering soil, crop and crop roots, litterfall, tree and tree roots as C stocks. The C sequestration of the TBI and adjacent non-TBI systems were compared and the market value of the C payment was evaluated using the net present value (NPV) approach. The TBI systems had 33% to 36% more C storage than adjacent non-TBI systems. The financial benefits of C sequestration after 10 years of TBI practices amounted to of $2,259–$2,758 CAD ha−1 and $1,568–$1,913 CAD ha−1 for St. Edouard and St. Paulin sites, respectively. We conclude that valorizing the C sequestration of TBI systems could be an incentive to promote the establishment of TBI for the purpose of GHG mitigation in Quebec, Canada.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".