Carbon sequestration in Canada's croplands: a review of multiple disciplines influencing the science–policy interface
Bibliographic record
Abstract
A widely considered climate change mitigation strategy in agriculture is enhancing soil carbon (C) sequestration—the process of capturing atmospheric carbon dioxide and storing it in the soil. By adopting natural climate solutions (NCS) such as cover crops, reduced tillage, and diverse crop rotations, farmers can increase soil C sequestration and co-benefits such as improved biodiversity. Canada is increasingly interested in better positioning farmers to adopt NCS via government cost-share programs, ecosystem marketplaces, and outreach and education initiatives. Given the policy and market-driven interest in soil C sequestration in agriculture, there is a need to advance the science–policy interface, ensuring foundational science, NCS implementation, and approaches to promote NCS are aligned. Herein, the objective is to present insights from multiple disciplines that can help build connections between soil C sequestration science and policy relevant to Canada's croplands. The method is a review of literature on soil and pedoclimate science, agricultural NCS adoption, agricultural NCS governance, and science–policy interfaces to achieve this objective. From this review, key insights underline that Canadian cropland soils do not have a homogenous history in NCS adoption and production type, nor are all regions influenced by the same contextual factors, have the same potential in C storage, or exist within the same agri-environmental conditions. Therefore, it is emphasized herein that policies that aim to enhance soil organic C in croplands should consider local context and C sequestration potential. Policies and programs implemented locally to enhance C sequestration across Canada should be complemented by nationally scalable measuring and monitoring to ensure outcomes are accounted for against climate goals. This review aims to contribute to building a common understanding of soil C sequestration in Canada's croplands and its science–policy interface. Efforts to further strengthen the science–policy interface for soil C sequestration in Canada's croplands might include greater integration and utilization of science and data from multiple disciplines, co-design and collaborative opportunities, and establishing on-the-ground test projects to explore innovation in policy and market design.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.027 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".