loading page

Development of the SSiB5/TRIFFID/DayCent-SOM Model and study of the impacts of nitrogen dynamics on terrestrial carbon cycle
  • +3
  • zheng xiang,
  • Yongkang Xue,
  • Weidong Guo,
  • Melannie Hartman,
  • Ye Liu,
  • Bill Julian Parton
zheng xiang
Nanjing University, Nanjing University
Author Profile
Yongkang Xue
University of California Los Angeles, University of California Los Angeles

Corresponding Author:[email protected]

Author Profile
Weidong Guo
Institute for Climate and Global Change Research, School of Atmospheric Sciences, Nanjing University, Institute for Climate and Global Change Research, School of Atmospheric Sciences, Nanjing University
Author Profile
Melannie Hartman
Natural Resource Ecology Laboratory, Natural Resource Ecology Laboratory
Author Profile
Ye Liu
Pacific Northwest National Laboratory (DOE), Pacific Northwest National Laboratory (DOE)
Author Profile
Bill Julian Parton
Author Profile


Plant and microbial nitrogen (N) dynamics and nitrogen availability regulate the photosynthetic capacity and capture, allocation, turnover of carbon (C) in terrestrial ecosystem. It is important to adequately represent plant N processes in land surface models. In this study, a plant C-N framework was developed by coupling a biophysical and dynamic land surface processes model, SSiB4/TRIFFID, with a soil organic matter cycling model, DayCent-SOM, to fully incorporate N regulations to investigate the impact of N on plant growth and C cycling. To incorporate the N limitation in the coupled system, the parameterization for dynamic C/N ratios for each plant functional type (PFT) was developed first. Then, after accounting for plant/soil N-cycling, when available N is less than demand, N would restrict the plant growth, reducing the net primary productivity (NPP), but also impact plant respiration rates and phenology. The improvements of the newly-developed model, the SSiB5/TRIFFID/DayCent-SOM, was preliminary verified at three flux tower sites with different PFTs. Furthermore, several offline global simulations were conducted from 1948 to 2007 to predict the long-term mean 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, new model can better reproduce observed emergent properties, including gross primary productivity (GPP), leaf area index (LAI), and respiration. The main improvements occur 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.