Simulating no-tillage effects on crop yield and greenhouse gas emissions in Kentucky corn and soybean cropping systems: 1980–2018

Abstract

CONTEXTNo-tillage (NT) is a conservation practice that aims to minimize soil disturbance and improve crop production. However, NT effects on crop production remain controversial due to the spatial heterogeneity of climate and soil conditions. Some studies argued that NT might offset its greenhouse gas (GHG) mitigation potential in agriculture by promoting soil N2O emissions. OBJECTIVEThis study used a process-based agroecosystem model (DLEM-Ag) along with spatially explicit environmental datasets to quantify the long-term effects of NT on crop yield and GHG emissions in corn and soybean cropping systems in the state of Kentucky (USA) from 1980 to 2018. METHODSThe DLEM-Ag was used to quantify the long-term effects of NT on crop yield and GHG emissions in corn and soybean cropping systems in the state of Kentucky. Three spatiotemporal tillage scenarios, i.e., historical varying tillage, consistent conventional tillage (CT), and consistent NT, were adopted to simulate changes in crop yield and GHG emissions. RESULTS AND CONCLUSIONSOverall, our results showed that NT could reduce soil CO2 (−1.6% for corn and −4.53% for soybean) and N2O emissions (−10.5% for corn and −19.6% for soybean) in Kentucky, as compared to CT, although corn and soybean yields with NT were not significantly different from those with CT. Our further analysis suggested that air temperature and soil clay content were the two main factors influencing NT advantages in reducing GHG emissions. The increased temperature decreased the benefits of mitigating GHG emissions, while high clay content soils had less N2O emission under NT. SIGNIFICANCEThis study represents one of few attempts to quantify the effects of NT on crop yield and soil GHG emissions at the regional scale using an agroecosystem modeling approach. The findings from this study provide insights into how NT can enhance agroecosystem production stability and support climate change mitigation. This information may be used by the scientific community and policymakers working on practical technologies to mitigate climate change from agriculture.