Assessing the Interactions between CO2 and Microbial Activity in a Mississippi Corn Field Using the DNDC Model and Experiment Data

Lei, F., Hu, J., Miles, D. M., Adeli, A., Brooks, J. P., Podrebarac, F., Smith, R., & Moorhead, R. (2021). Assessing the Interactions between CO2 and Microbial Activity in a Mississippi Corn Field Using the DNDC Model and Experiment Data. ASA, CSSA, SSSA International Annual Meeting. Salt Lake City, UT: ASA-CSSA-SSSA.

Abstract

Greenhouse gas (GHG) emission from agricultural fields can be an indicator of soil health, microbial activity, and soil nutrient cycling. Agricultural management usually influences GHG emission and crop yield. With an improved understanding of the interactions among fertilizer, microbial activity, soil health, and crop yield, agricultural production can be enhanced or maintained with GHG mitigation and increased microbial activity. To analyze the relationships among these factors, an intensive field experiment was conducted, seeking to maximize crop yield in the humid southeastern U.S. Different fertilization and cover crop management practices were applied in a corn field in Mississippi. In-situ CO2 emissions and soil enzyme activities were measured along with crop biomass at different growth stages in 2019. In this study, we use the Denitrification-Decomposition (DNDC) model to simulate the corn crop management under different fertilization and cover-crop application scenarios and assess the interactions between GHG and microbial activity. The DNDC model is first calibrated and evaluated against in-situ GHG data. By connecting the measured enzyme activies with model simulated soil organic carbon and nitrogen, the microbial activity is linked to the crop yield and GHG emission. Further, through a model sensitivity analysis, the best practice (fertilization rate, fertilizer type, and cover-crop application) for long-term sustainable management of corn fields can be determined.