Chin J Plan Ecolo ›› 2015, Vol. 39 ›› Issue (4): 388-397.DOI: 10.17521/cjpe.2015.0038

Special Issue: 碳水能量通量

• Orginal Article • Previous Articles     Next Articles

Optimization and evaluation of vegetation photosynthesis and respiration model using the measurements collected from the forest site of subtropical coniferous-evergreen

LIU Cheng1,*(), HUANG Jian-Ping1,**(), DIAO Yi-Wei1, WEN Xue-Fa2, XIAO Wei1, ZHANG Mi1, LEE Xu-Hui1, LIU Shou-Dong1   

  1. 1Yale-NUIST Center on Atmospheric Environment, Nanjing University of Information Science & Technology, Nanjing 210044, China
    2Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101,China
  • Received:2014-09-04 Accepted:2015-01-10 Online:2015-04-01 Published:2015-04-21
  • Contact: Cheng LIU,Jian-Ping HUANG
  • About author:

    # Co-first authors

Abstract: <i>Aims</i>

Determination of carbon cycling model parameters is critical to simulate the net ecosystem CO2 exchange (NEE). The objectives of this study were to determine the parameters of vegetation photosynthesis and respiration model (VPRM) and improve the calculation of NEE to benefit regional modeling of CO2.


Two schemes are examined in optimization of the parameters in VPRM. Two years CO2 flux and meteorological observational data in 2010-2011 at the Qianyanzhou (QYZ) eddy tower site are used to determine the parameters in VPRM and another full year flux observational data in 2012 are used to evaluate the model performance. Several statistics metrics are calculated to evaluate the model performance on NEE simulations.

<i>Important findings</i>

The results indicate, traditional method with Michaelis-Menten equation is not suitable to determine the parameters of VPRM, whereas the method with parameters retrieved from the VPRM calculation equation provides much more reasonable results. The parameter of maximum light use efficiency (λ) is critical for the VPRM calculation of NEE. Our result is larger than the typical value of C3 plant (1/6), but consistent with the other studies. Using the optimized parameters, VPRM is able to capture NEE variations for different seasons. The statistics calculation with one-year NEE simulation shows that, the mean bias is -0.86 μmol·m-2·s-1 and correlation coefficient is 0.72. Overall, the VPRM performs much better in growing season than the non-growing season when the peak value of NEE is underestimated by 52%. The VPRM simulated NEE shows better agreement with observations on sunny days than rainy or cloudy days.

Key words: net ecosystems exchange (NEE), parameter optimization, Qianyanzhou, vegetation photosynthesis and respiration model