Knowledge-Guided Machine Learning Can Improve Carbon Cycle Quantification in Agroecosystems
by Licheng Liu, Wang Zhou, Kaiyu Guan, et al. (Nature Communications) Accurate and cost-effective quantification of the carbon cycle for agroecosystems at decision-relevant scales is critical to mitigating climate change and ensuring sustainable food production. However, conventional process-based or data-driven modeling