Uncertainty analysis of CO 2 flux components in sub- tropical evergreen coniferous plantation

urements of CO2 fluxes at subtropical evergreen coniferous plantation, Qianyanzhou of ChinaFlux. Daily-differencing approach was used to analyze the random error of CO2 fluxes measurements and bootstrapping method was used to quantify the uncertainties of three CO2 flux components. In addition, we evaluated different models and optimization methods in influencing estimation of key parameters and CO2 flux components. The results show that: (1) Random flux error more closely follows a double-exponential (Laplace), rather than a normal (Gaussian) distribution. (2) Different optimization methods result in different estimates of model parameters. Uncertainties of parameters estimated by the maximum likelihood estimation (MLE) are lower than those derived from ordinary least square method (OLS). (3) The differences between simulated Reco, NEE and GEE derived from MLE and those derived from OLS are 12.18% (176 g C·m −2 ·a −1 ), 34.33% (79 g C·m

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