Resolving systematic errors in estimates of net ecosystem exchange of CO2 and ecosystem respiration in a tropical forest biome
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Munger, J. William
Saleska, Scott R.
Daube, Bruce C.
de Camargo, Plinio B.
Hutyra, Lucy R.Note: Order does not necessarily reflect citation order of authors.
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Citationde Camargo, Plinio B, Bruce C. Daube, Natalia Restrepo-Coupe, Scott R. Saleska, Eizabeth Hammond-Pyle, William J. Munger and Lucy R. Hutyra. Resolving systematic errors in estimates of net ecosystem exchange of CO2 and ecosystem respiration in a tropical forest biome. Agricultural and Forest Meteorology 148: 1266-1279.
AbstractThe controls on uptake and release of CO2 by tropical rainforests, and the responses to a changing climate, are major uncertainties in global climate change models. Eddy-covariance measurements potentially provide detailed data on CO2 exchange and responses to the environment in these forests, but accurate estimates of the net ecosystem exchange of CO2 (NEE) and ecosystem respiration (Reco) require careful analysis of data representativity, treatment of data gaps, and correction for systematic errors. This study uses the comprehensive data from our study site in an old-growth tropical rainforest near Santarem, Brazil, to examine the biases in NEE and Reco potentially associated with the two most important sources of systematic error in Eddy-covariance data: lost nighttime flux and missing canopy storage measurements. We present multiple estimates for the net carbon balance and Reco at our site, including the conventional “u* filter”, a detailed bottom-up budget for respiration, estimates by similarity with 222Rn, and an independent estimate of respiration by extrapolation of daytime Eddy flux data to zero light. Eddy-covariance measurements between 2002 and 2006 showed a mean net ecosystem carbon loss of 0.25 ± 0.04 μmol m−2 s−1, with a mean respiration rate of 8.60 ± 0.11 μmol m−2 s−1 at our site. We found that lost nocturnal flux can potentially introduce significant bias into these results. We develop robust approaches to correct for these biases, showing that, where appropriate, a site-specific u* threshold can be used to avoid systematic bias in estimates of carbon exchange. Because of the presence of gaps in the data and the day–night asymmetry between storage and turbulence, inclusion of canopy storage is essential to accurate assessments of NEE. We found that short-term measurements of storage may be adequate to accurately model storage for use in obtaining ecosystem carbon balance, at sites where storage is not routinely measured. The analytical framework utilized in this study can be applied to other Eddy-covariance sites to help correct and validate measurements of the carbon cycle and its components.
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