TY - JOUR
T1 - Resolving systematic errors in estimates of net ecosystem exchange of CO2 and ecosystem respiration in a tropical forest biome
AU - Hutyra, Lucy R.
AU - Munger, J. William
AU - Hammond-Pyle, Elizabeth
AU - Saleska, Scott R.
AU - Restrepo-Coupe, Natalia
AU - Daube, Bruce C.
AU - de Camargo, Plinio B.
AU - Wofsy, Steven C.
N1 - Funding Information:
This study was part of the Brazil-led Large Scale Biosphere-atmosphere Experiment in Amazonia and was funded by NASA grants NCC5-341, NCC5-684, and NNG06GG69A to Harvard University. The authors would like to thank Elaine Gottlieb, Dan Curran, John Budney, Daniel Amaral, Lisa Merry, Bethany Reed, Dan Hodkinson, and the staff of the LBA Santarem office for their extensive data processing, logistical and field assistance. We wish to also thank Simone Vieira, Amy Rice, Greg Santoni, and Joost van Haren for their extensive assistance with the biometric field measurements. We also thank Allison Dunn and the two anonymous reviewers for their valuable comments on earlier drafts of this paper. Finally, the authors are also extremely grateful to Eric Davidson, Dan Nepstad, Jeff Chambers, Michael Keller, Mike Goulden, Scott Miller, and David Fitzjarrald for sharing the data that made the independent comparisons in this paper possible.
PY - 2008/7/4
Y1 - 2008/7/4
N2 - The 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.
AB - The 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.
KW - Amazon
KW - Carbon
KW - Eddy correlation
KW - LBA
KW - Respiration
KW - Tropical rainforest
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U2 - 10.1016/j.agrformet.2008.03.007
DO - 10.1016/j.agrformet.2008.03.007
M3 - Article
AN - SCOPUS:44749094265
SN - 0168-1923
VL - 148
SP - 1266
EP - 1279
JO - Agricultural and Forest Meteorology
JF - Agricultural and Forest Meteorology
IS - 8-9
ER -