Soil organic carbon (SOC) storage plays a major role in the global carbon cycle and is affected by many factors including land use/management changes (e.g., biofuel production-oriented changes). However, the contributions of various factors to SOC changes are not well understood and quantified. This study was designed to investigate the impacts of changing farming practices, initial SOC levels, and biological enhancement of grain production on SOC dynamics and to attribute the relative contributions of major driving forces (CO2 enrichment and farming practices) using a fractional factorial modeling design. The case study at a crop site in Iowa in the United States demonstrated that the traditional corn-soybean (CS) rotation could still accumulate SOC over this century (from 4.2 to 6.8 kg C/m2) under the current condition; whereas the continuous-corn (CC) system might have a higher SOC sequestration potential than CS. In either case, however, residue removal could reduce the sink potential substantially. Long-term simulation results also suggested that the equilibrium SOC level may vary greatly (∼5.7 to ∼11 kg C/m2) depending on cropping systems and management practices, and projected growth enhancement could make the magnitudes higher (∼7.8 to ∼13 kg C/m2). Importantly, the factorial design analysis indicated that residue management had the most significant impact (contributing 49.4%) on SOC changes, followed by CO2 Enrichment (37%), Tillage (6.2%), the combination of CO2Enrichment-Residue removal (5.8%), and Fertilization (1.6%). In brief, this study is valuable for understanding the major forces driving SOC dynamics of agroecosystems and informative for decision-makers when seeking the enhancement of SOC sequestration potential and sustainability of biofuel production, especially in the Corn Belt region of the United States.
Additional publication details
|Publication Subtype||Journal Article|
|Title||Quantitative attribution of major driving forces on soil organic carbon dynamics|
|Series title||Journal of Advances in Modeling Earth Systems|
|Contributing office(s)||Earth Resources Observation and Science (EROS) Center|
|Google Analytic Metrics||Metrics page|