ECOScience du 28 novembre 2025

Abstract: Carbon farming aims to reduce greenhouse gas emissions and to store carbon in soils and vegetation through practices such as cover cropping, reduced tillage, agroforestry or precision fertilization. Carbon farming frameworks are designed to quantify climate benefits so that farmers can receive subsidies or carbon credits based on the amount of emissions reduced or carbon sequestered. Credible carbon farming frameworks require reliable estimates of soil organic carbon (SOC) stocks and their change over time, to ensure that the climate benefits are real and measurable. By combining field data, remote sensing, and process-based modeling, this work demonstrates how multiple information sources can be combined to improve the transparency and robustness of SOC assessments for carbon farming applications.