Management alternatives for climate-smart agriculture at two long-term agricultural research sites in the United States: A model ensemble case study

Greenhouse gas (GHG) emissions reduction efforts are underway to mitigate climate change worldwide. Climate-smart agriculture (CSA) practices have been shown to both increase soil organic carbon (SOC) inputs and reduce net greenhouse gas emissions (GHGnet). We evaluated the GHGnet of several management practices with three biogeochemical models (APSIM, Daycent, and RothC) at two sites with contrasting soils, climates, and cropping systems. Additionally, two future climate scenarios (baseline and high-emissions) provided alternative outcomes of SOC, N₂O, and CH₄ by 2050. In Michigan, most biochar and residue retention with no-till treatments increased SOC stocks; leguminous cover crops, no-till, and reducing fertilizer input lowered N₂O emissions. The lowest biochar treatment lowered GHGnet in the baseline climate scenario, but all other management treatments increased GHGnet under both baseline and high emissions, and all management scenarios increased a mean of 8.0 Mg CO₂-equivalent GHG (CO₂e) ha⁻¹ from baseline to high emissions. Conversely, in Texas, most treatments increased SOC, and N₂O was relatively constant. Every no-till treatment reversed GHGnet in both the baseline and high-emissions climate scenarios but all management scenarios increased a mean of 0.6 Mg CO₂e ha⁻¹ under high emissions. At both sites under high-emissions climate change, cover crops and no-till resulted in the lowest GHGnet overall. Overall, the study showed that no-till, especially with residue retention, and cover crops are important CSA practices to lower the GHGnet of agriculture, but there remains much room to find even more effective solutions to adapt to climate change.