Journal
SCIENCE IN CHINA SERIES D-EARTH SCIENCES
Volume 52, Issue 2, Pages 257-268Publisher
SCIENCE PRESS
DOI: 10.1007/s11430-009-0010-6
Keywords
CO2 flux components; statistical uncertainty analysis; bootstrapping method; subtropical evergreen coniferous plantation; Qianyanzhou
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Funding
- National Natural Science Foundation of China [30570347]
- Chinese Academy of Sciences [CXTD-Z2005-1]
- National Basic Research Program of China [2002CB412502]
- Division Of Environmental Biology
- Direct For Biological Sciences [743778] Funding Source: National Science Foundation
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We present an uncertainty analysis of ecological process parameters and CO2 flux components (R (eco), NEE and gross ecosystem exchange (GEE)) derived from 3 years' continuous eddy covariance measurements 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 R-eco, NEE and GEE derived from MLE and those derived from OLS are 12.18% (176 g C center dot m(-2)center dot a(-1)), 34.33% (79 g C center dot m(-2)center dot a(-1)) and 5.4% (92 g C center dot m(-2)center dot a(-1)). However, for a given parameter optimization method, a temperature-dependent model (T_model) and the models derived from a temperature and water-dependent model (TW_model) are 1.31% (17.8 g C center dot m(-2)center dot a(-1)), 2.1% (5.7 g C center dot m(-2)center dot a(-1)), and 0.26% (4.3 g C center dot m(-2)center dot a(-1)), respectively, which suggested that the optimization methods are more important than the ecological models in influencing uncertainty in estimated carbon fluxes. (4) The relative uncertainty of CO2 flux derived from OLS is higher than that from MLE, and the uncertainty is related to timescale, that is, the larger the timescale, the smaller the uncertainty. The relative uncertainties of R-eco, NEE and GEE are 4%-8%, 7%-22% and 2%-4% respectively at annual timescale.
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