Abstract
Ecological agriculture is increasingly recognized as a critical paradigm for addressing the coupled challenges of food security, resource constraints, environmental degradation, and climate change; however, its transition toward scalable, system-level implementation remains constrained by fragmented knowledge across technological, biological, and socio-ecological domains. This study synthesizes four interconnected frontier directions in ecological agriculture research: (i) AI- and big data–enabled intelligent agroecosystems, which integrate sensing, modeling, and decision-support systems to enhance whole-chain efficiency and sustainability; (ii) soil microbiome engineering and soil health management, leveraging multi-omics approaches to elucidate microbial community structure–function relationships and optimize low-input, environmentally friendly farming practices; (iii) quantification and value realization of agroecosystem services, focusing on integrated assessment frameworks and emerging incentive mechanisms such as ecological compensation and carbon markets; and (iv) climate-resilient agricultural systems, encompassing stress-tolerant crop improvement, water-efficient management, biochar-based carbon sequestration, and remote sensing–driven prediction for adaptation and mitigation. These advances highlight the convergence of digital technologies, ecological processes, and policy instruments in reshaping agricultural systems.
