TY - JOUR
T1 - Cross-site evaluation of eddy covariance GPP and RE decomposition techniques
AU - Desai, Ankur R.
AU - Richardson, Andrew D.
AU - Moffat, Antje M.
AU - Kattge, Jens
AU - Hollinger, David Y.
AU - Barr, Alan
AU - Falge, Eva
AU - Noormets, Asko
AU - Papale, Dario
AU - Reichstein, Markus
AU - Stauch, Vanessa J.
N1 - Funding Information:
We wish to acknowledge the site PIs Marc Aubinet (Vielsalm), Werner Kutsch (Hainich), André Granier (Hesse), Serge Rambal (Puechabon), Riccardo Valentini (Roccarespampani) and Timo Vesala (Hyytiala) for making their data available. Data have been collected in the context of Carboeuroflux and CarboeuropeIP research projects funded by the European Commission and part of the sites are also co-funded by local agencies. David Y. Hollinger and Andrew D. Richardson gratefully acknowledge support from the Office of Science (BER), U.S. Department of Energy, Interagency Agreement No. DE-AI02-00ER63028. Ankur R. Desai acknowledges support from the National Science Foundation (NSF), National Center for Atmospheric Research (NCAR) Advanced Study Program (ASP) Fellowship.
PY - 2008/6/30
Y1 - 2008/6/30
N2 - Eddy covariance flux towers measure net exchange of land-atmosphere flux. For the flux of carbon dioxide, this net ecosystem exchange (NEE) is governed by two processes, gross primary production (GPP) and a sum of autotrophic and heterotrophic respiration components known as ecosystem respiration (RE). A number of statistical flux-partitioning methods, often developed to fill missing NEE data, can also be used to estimate GPP and RE from NEE time series. Here we present results of the first comprehensive, multi-site comparison of these partitioning methods. An initial test was performed with a subset of methods in retrieving GPP and RE from NEE generated by an ecosystem model, which was also degraded with realistic noise. All methods produced GPP and RE estimates that were highly correlated with the synthetic data at the daily and annual timescales, but most were biased low, including a parameter inversion of the original model. We then applied 23 different methods to 10 site years of temperate forest flux data, including 10 different artificial gap scenarios (10% removal of observations), in order to investigate the effects of partitioning method choice, data gaps, and intersite variability on estimated GPP and RE. Most methods differed by less than 10% in estimates of both GPP and RE. Gaps added an additional 6-7% variability, but did not result in additional bias. ANOVA showed that most methods were consistent in identifying differences in GPP and RE across sites, leading to increased confidence in previously published multi-site comparisons and syntheses. Several methods produced outliers at some sites, and some methods were systematically biased against the ensemble mean. Larger model spread was found for Mediterranean sites compared to temperate or boreal sites. For both real and synthetic data, high variability was found in modeling of the diurnal RE cycle, suggesting that additional study of diurnal RE mechanisms could help to improve partitioning algorithms.
AB - Eddy covariance flux towers measure net exchange of land-atmosphere flux. For the flux of carbon dioxide, this net ecosystem exchange (NEE) is governed by two processes, gross primary production (GPP) and a sum of autotrophic and heterotrophic respiration components known as ecosystem respiration (RE). A number of statistical flux-partitioning methods, often developed to fill missing NEE data, can also be used to estimate GPP and RE from NEE time series. Here we present results of the first comprehensive, multi-site comparison of these partitioning methods. An initial test was performed with a subset of methods in retrieving GPP and RE from NEE generated by an ecosystem model, which was also degraded with realistic noise. All methods produced GPP and RE estimates that were highly correlated with the synthetic data at the daily and annual timescales, but most were biased low, including a parameter inversion of the original model. We then applied 23 different methods to 10 site years of temperate forest flux data, including 10 different artificial gap scenarios (10% removal of observations), in order to investigate the effects of partitioning method choice, data gaps, and intersite variability on estimated GPP and RE. Most methods differed by less than 10% in estimates of both GPP and RE. Gaps added an additional 6-7% variability, but did not result in additional bias. ANOVA showed that most methods were consistent in identifying differences in GPP and RE across sites, leading to increased confidence in previously published multi-site comparisons and syntheses. Several methods produced outliers at some sites, and some methods were systematically biased against the ensemble mean. Larger model spread was found for Mediterranean sites compared to temperate or boreal sites. For both real and synthetic data, high variability was found in modeling of the diurnal RE cycle, suggesting that additional study of diurnal RE mechanisms could help to improve partitioning algorithms.
KW - Carbon balance
KW - Eddy correlation
KW - GPP
KW - Net ecosystem exchange
KW - RE
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U2 - 10.1016/j.agrformet.2007.11.012
DO - 10.1016/j.agrformet.2007.11.012
M3 - Article
AN - SCOPUS:43749117280
SN - 0168-1923
VL - 148
SP - 821
EP - 838
JO - Agricultural and Forest Meteorology
JF - Agricultural and Forest Meteorology
IS - 6-7
ER -