Simulating climate change effects on soil carbon dynamics in a soybean–maize ecosystem: Using improved CO2 emission and transport models

Abstract

Climate change has been reported to significantly alter the amount of carbon being stored in the soil, but it remains unclear how accurately the effect of high temperatures and elevated CO2 on soil organic carbon (SOC) dynamics can be predicted. We used process-based crop models, GLYCIM and MAIZSIM, to evaluate the effects of climatic changes on SOC accumulation in a maize-soybean cropping system. Models were initially improved with methods to account for tillage, surface residue decomposition, and soil CO2 respiration. Data from a 3-year FACE experiment from Illinois, USA were used for calibration and validation. Model performance was then evaluated against observed crop yield and SOC in this long-term cropping system for 1900 to 2020. Model predictions accurately matched soil CO2 flux, respiration associated with plant roots and rhizosphere (Rroot), soil heterotrophs (Rsoi), whole soil (Rtot), soil water content, and soil temperature, with indices of agreement (IA) ranging from 0.77 to 0.99 except for Rroot and soil water content. Our model projections, using an ensemble of five GCMs from the latest CMIP6 project, suggested that future warming temperatures would cause a long-term decline in SOC by the end of the 21st century, with losses of 6.0% and 14.6% under SSP245 and SSP585 scenarios without considering elevated CO2, respectively. However, incorporating elevated CO2 levels in simulations increased SOC content by 5.0 - 6.2%. This study highlights the importance of linking controlled experiments, long-term field observations, and future climate projections with process-based crop models in order to predict SOC sequestration assessment and evaluate impacts associated with long-term cropping systems.