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Improving Soil Carbon Estimates by Linking Conceptual Pools Against Measurable Carbon Fractions in the DAYCENT Model Version 4.5
Author(s) -
Dangal Shree R. S.,
Schwalm Christopher,
Cavigelli Michel A.,
Gollany Hero T.,
Jin Virginia L.,
Sanderman Jonathan
Publication year - 2022
Publication title -
journal of advances in modeling earth systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.03
H-Index - 58
ISSN - 1942-2466
DOI - 10.1029/2021ms002622
Subject(s) - soil carbon , initialization , carbon cycle , biogeochemical cycle , environmental science , soil science , carbon fibers , atmospheric sciences , chemistry , environmental chemistry , soil water , physics , algorithm , computer science , ecology , ecosystem , biology , programming language , composite number
Terrestrial soil organic carbon (SOC) dynamics play an important but uncertain role in the global carbon (C) 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 (DC frac ) led to better initialization of SOC stocks and distribution compared to default/SOC‐only‐constrained DAYCENT (DC def ) at long‐term research sites. Regional simulation using DC frac 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 DC def 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 DC frac whereas, SOC losses were 6.55 and 7.85 MgC ha −1 for grasslands and croplands, respectively, using DC def . The projected SOC loss using DC frac was 33% and 29% higher for croplands and grasslands compared to DC def . 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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