A Modeling Framework to Evaluate the Impacts of Future Climate on Soil Organic Carbon Dynamics

Soil organic C (SOC) is significantly affected by changes in climate that control the physical, chemical, and biological processes in the soil. Simulating the impacts of future climate on SOC is challenging due to the limited availability of soil and climate variables required to properly simulate future SOC dynamics. The main objective of this study was to develop a modeling framework to quantify the impacts of future climate on SOC dynamics. The framework was developed for the Model for Nitrogen and Carbon in Agro‐Ecosystems (MONICA) using the data collected from three University of Illinois Crop Science Research Centers. Projected precipitation and air temperature, collected from 32 global circulation models, were used to estimate the climate variables and cropping operation schedules required as inputs in MONICA. Six corn (Zea mays L.)–soybean [Glycine max (L.) Merr.] rotation scenarios were considered in the simulations. Results showed that the total SOC in the upper 30 cm of the soil was expected to decrease from 43 to 70% in 2015 to 2075, with an uncertainty range of 13 to 16% due to the variation in climate prediction. The SOC in corn–soybean rotation schemes did not vary significantly from that of continuous corn scheme. The ability of a model to simulate realistic results depends significantly on the reliability of input data used to parameterize the model. A methodology that comprehensively estimates the impacts of future climatic conditions on SOC allows for realistic model results that can be used as a basis for environmental options, leading to a sustainable agro‐production system. CORE IDEAS: Long‐term changes in SOC due to future climatic conditions were simulated. The impacts of climate projections on SOC from 32 global circulation models were evaluated. We studied the effects of corn–soybean rotations on SOC under changing climate. We made a modeling framework to asses SOC dynamics under scenario‐based climate projections.