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Development of the SSiB5/TRIFFID/DayCent-SOM Model to study the impact of nitrogen dynamics on carbon cycle over terrestrial surface
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  • Zheng Xiang,
  • Yongkang Xue,
  • Weidong Guo,
  • Melannie Hartman,
  • Ye Liu,
  • Bill Julian Parton
Zheng Xiang
Nanjing University
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Yongkang Xue
University of California Los Angeles

Corresponding Author:[email protected]

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Weidong Guo
Institute for Climate and Global Change Research, School of Atmospheric Sciences, Nanjing University
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Melannie Hartman
Natural Resource Ecology Laboratory
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Ye Liu
Pacific Northwest National Laboratory (DOE)
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Bill Julian Parton
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It is important to adequately represent plant nitrogen (N) biogeochemistry and its respective processes in land surface models. Thus far, various N representations in models lead to uncertainty in estimating model responses to global warming. Through plant and microbial N dynamics, nitrogen availability regulates the capture, allocation, turnover of carbon (C), and photosynthetic capacity. In this study, to fully incorporate these N regulations, we have developed a plant C-N framework by coupling a biophysical and dynamic land model, SSiB4/TRIFFID, with a soil organic matter cycling model, DayCent-SOM, to simulate the impact of nitrogen on the plant growth and C cycling. To incorporate the N limitation in the coupled system, we first developed the parameterization for the C/N ratios. Then, after accounting for daily plant/soil N-cycling, N will not only limit the plant growth when not sufficient, causing the net primary productivity (NPP) to be down-regulated, but will also impact plant respiration rates and phenology. Using this newly-developed model named SSiB5/TRIFFID/DayCent-SOM, we conduct several simulations from 1948 to 2007 to predict the global vegetation distribution and terrestrial C cycling, and the results are evaluated with satellite-derived observational data. The sensitivity of the terrestrial C cycle to N processes is also assessed. In general, the coupled model can better reproduce observed emergent properties, including gross primary productivity (GPP), NPP, leaf area index (LAI), and respiration. The main improvement occurs in tropical Africa and boreal regions, accompanied by a decrease of the bias in global GPP and LAI by 16.3% and 27.1%, respectively.