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

Abstract

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 ()-soybean [ (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.

Measurements and Models to Identify Agroecosystem Practices That Enhance Soil Organic Carbon under Changing Climate

“…Some of these limitations of course derive directly from uncertainties in RCPs and future climate predictions. As pointed out here by Chu et al (2018), there is a need for the temperature and precipitation predictions of large-scale climate models to be translated to more temporally and spatially meaningful climate variables that will drive local-scale crop responses as well as management constraints (e.g., planting and harvesting dates). Additional limitations of crop response models derive from a large uncertainty in the ability of crop genetic improvements to keep pace with climate-induced stresses, including both direct climate effects (e.g., drought, heat stress) and indirect effects (e.g., shifts in weeds, insects, and diseases).…”

“…Chu et al (2018) used projected precipitation and air temperature, collected from 32 global circulation models, to estimate local‐scale climate variables and cropping operation schedules. The local‐scale parameters and cropping operations were input into the process‐based MONICA to quantify the impacts of future climate on SOC dynamics for three rotation experiments at the University of Illinois Crop Science Research Centers.…”

“…Increasing crop yield by 10 and 30% was sufficient to raise SOC by 2 and 7%, respectively, above the climate-only scenario under both CT and NT from 2012 to 2052, indicating that the negative impact of climate change on SOC levels could be mitigated by increasing crop yield if improved varieties or technology were to be developed for the southern Mid-Atlantic region of the United States. Chu et al (2018) used projected precipitation and air temperature, collected from 32 global circulation models, to estimate local-scale climate variables and cropping operation schedules. The local-scale parameters and cropping operations were input into the process-based MONICA to quantify the impacts of future climate on SOC dynamics for three rotation experiments at the University of Illinois Crop Science Research Centers.…”