On the choice of the driving temperature for eddy-covariance carbon dioxide flux partitioning

[摘要] Networks that merge and harmonise eddy-covariance measurements from manydifferent parts of the world have become an important observational resourcefor ecosystem science. Empirical algorithms have been developed which combinedirect observations of the net ecosystem exchange of carbon dioxide withsimple empirical models to disentangle photosynthetic (GPP) and respiratoryfluxes (R_eco). The increasing use of these estimates for the analysis ofclimate sensitivities, model evaluation and calibration demands a thoroughunderstanding of assumptions in the analysis process and the resultinguncertainties of the partitioned fluxes. The semi-empirical models used influx partitioning algorithms require temperature observations as input, butas respiration takes place in many parts of an ecosystem, it is unclear whichtemperature input – air, surface, bole, or soil at a specific depth –should be used. This choice is a source of uncertainty and potential biases.In this study, we analysed the correlation between different temperatureobservations and nighttime NEE (which equals nighttime respiration) acrossFLUXNET sites to understand the potential of the different temperatureobservations as input for the flux partitioning model. We found that thedifferences in the correlation between different temperature data streams andnighttime NEE are small and depend on the selection of sites. We investigatedthe effects of the choice of the temperature data by running two fluxpartitioning algorithms with air and soil temperature. We found the time lag(phase shift) between air and soil temperatures explains the differences inthe GPP and R_eco estimates when using either air or soil temperatures forflux partitioning. The impact of the source of temperature data on otherderived ecosystem parameters was estimated, and the strongest impact wasfound for the temperature sensitivity. Overall, this study suggests that thechoice between soil or air temperature must be made on site-by-site basis byanalysing the correlation between temperature and nighttime NEE. We recommendusing an ensemble of estimates based on different temperature observations toaccount for the uncertainty due to the choice of temperature and to assurethe robustness of the temporal patterns of the derived variables.

[学科分类] 地球化学与岩石