Our research focuses on the effects of changing climate and land management on carbon and nutrient cycling. We measure cropping systems and develop process-based modeling to predict the interactions between soil, plants, carbon storage and greenhouse gas emissions across different spatial and temporal scales.
Precision agriculture (PA) involves managing agricultural inputs in an environmentally sustainable manner. Our goal is to enhance the use efficiency of (1) fertilizers and agrochemicals, (2) seeds and planting materials, and (3) machinery and equipment through the application of various PA tools.
Agroecosystem modeling involves developing machine learning models and conducting simulations using existing ecosystem process models. Our goal is to gain a deeper understanding of the real-world biogeochemistry at large spatial and temporal scales.
Balancing agricultural inputs and outputs is crucial to prevent unintended consequences of crop production. Our goal is to manage and conserve key resources such as carbon, nitrogen, water, and other essential elements.
Agriculture is a major source of greenhouse gas emissions. Our goal is to monitor emissions from agricultural soils, assess their environmental impact, and inform effective mitigation strategies.
Plastic use in agriculture is widespread and constitutes a significant source of microplastic pollution. However, there is limited application of life cycle assessment or similar approaches to trace its dynamics and assess its impact on crop production and soil health. To address this gap, we initiated a preliminary project to develop a microplastic database specifically for cropland soils.