Dangal, S. R., C. Schwalm, M. A. Cavigelli, H. T. Gollany, V. L. Jin, and J. Sanderman. 2022. Improving soil carbon estimates by linking conceptual pools against measurable carbon fractions in the DAYCENT Model Version 4.5. Journal of Advances in Modeling Earth Systems 14:e2021MS002622.
Terrestrial soil organic carbon (SOC) dynamics play an important but uncertain role in the global carbon © cycle. Current modeling efforts to quantify SOC dynamics in response to global environmental changes do not accurately represent the size, distribution and flux of C from the soil. Here, we modified the daily Century (DAYCENT) biogeochemical model by tuning decomposition rates of conceptual SOC pools to match measurable C fraction data, followed by historical and future simulations of SOC dynamics. Results showed that simulations using fraction-constrained DAYCENT (DCfrac) led to better initialization of SOC stocks and distribution compared to default/SOC-only-constrained DAYCENT (DCdef) at long-term research sites. Regional simulation using DCfrac demonstrated higher SOC stocks for both croplands (34.86 vs. 26.17 MgC ha-1) and grasslands (54.05 vs. 40.82 MgC ha-1) compared to DCdef for the contemporary period (2001-2005 average), which better matched observationally constrained data-driven maps of current SOC distributions. Projection of SOC dynamics in response to land cover change under a high warming climate showed average absolute SOC loss of 8.44 and 10.43 MgC ha-1 for grasslands and croplands, respectively, using DCfrac whereas, SOC losses were 6.55 and 7.85 MgC ha-1 for grasslands and croplands, respectively, using DCdef. The projected SOC loss using DCfrac was 33% and 29% higher for croplands and grasslands compared to DCdef. Our modeling study demonstrates that initializing SOC pools with measurable C fraction data led to more accurate representation of SOC stocks and distribution of SOC into individual carbon pools resulting in the prediction of greater sensitivity to agricultural intensification and warming.
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