Heightened awareness of global change issues within both science and political communities has increased interest in using the global network of eddy covariance flux towers to more fully understand the impacts of natural and anthropogenic phenomena on the global carbon balance. Comparisons of net ecosystem exchange (F NEE ) responses are being made among biome types, phenology patterns, and stress conditions. The comparisons are usually performed on annual sums of F NEE ; however, the average data coverage during a year is only 65%. Therefore, robust and consistent gap filling methods are required.We review several methods of gap filling and apply them to data sets available from the EUROFLUX and AmeriFlux databases. The methods are based on mean diurnal variation (MDV), look-up tables (LookUp), and nonlinear regressions (Regr.), and the impact of different gap filling methods on the annual sum of F NEE is investigated. The difference between annual F NEE filled by MDV compared to F NEE filled by Regr. ranged from −45 to +200 g C m −2 per year (MDV−Regr.). Comparing LookUp and Regr. methods resulted in a difference (LookUp−Regr.) ranging from −30 to +150 g C m −2 per year.We also investigated the impact of replacing measurements at night, when turbulent mixing is insufficient. The nighttime correction for low friction velocities (u * ) shifted annual F NEE on average by +77 g C m −2 per year, but in certain cases as much as +185 g C m −2 per year.Our results emphasize the need to standardize gap filling-methods for improving the comparability of flux data products from regional and global flux networks.

Measured surface-atmosphere fluxes of energy (sensible heat, H, and latent heat, LE) and CO 2 (FCO 2 ) represent the ''true'' flux plus or minus potential random and systematic measurement errors. Here, we use data from seven sites in the AmeriFlux network, including five forested sites (two of which include ''tall tower'' instrumentation), one grassland site, and one agricultural site, to conduct a cross-site analysis of random flux error. Quantification of this uncertainty is a prerequisite to model-data synthesis (data assimilation) and for defining confidence intervals on annual sums of net ecosystem exchange or making statistically valid comparisons between measurements and model predictions.We differenced paired observations (separated by exactly 24 h, under similar environmental conditions) to infer the characteristics of the random error in measured fluxes. Random flux error more closely follows a double-exponential (Laplace), rather than a normal (Gaussian), distribution, and increase as a linear function of the magnitude of the flux for all three scalar fluxes. Across sites, variation in the random error follows consistent and robust patterns in relation to environmental variables. For example, seasonal differences in the random error for H are small, in contrast to both LE and FCO 2 , for which the random errors are roughly three-fold larger at the peak of the growing season compared to the dormant season. Random errors also generally scale with R n (H and LE) and PPFD (FCO 2 ). For FCO 2 (but not H or LE), the random error decreases with increasing wind speed. Data from two sites suggest that FCO 2 random error may be slightly smaller when a closed-path, rather than open-path, gas analyzer is used.

Land management and land-cover change have impacts of similar magnitude on surface temperature" (2014). Papers in Natural Resources. 554.

Differences in the seasonal pattern of assimilatory and respiratory processes are responsible for divergences in seasonal net carbon exchange among ecosystems. Using FLUXNET data (http://www.eosdis.ornl.gov/FLUXNET) we have analyzed seasonal patterns of gross primary productivity (F GPP ), and ecosystem respiration (F RE ) of boreal and temperate, deciduous and coniferous forests, Mediterranean evergreen systems, a rainforest, temperate grasslands, and C 3 and C 4 crops. Based on generalized seasonal patterns classifications of ecosystems into vegetation functional types can be evaluated for use in global productivity and climate change models. The results of this study contribute to our understanding of respiratory costs of assimilated carbon in various ecosystems.Seasonal variability of F GPP and F RE of the investigated sites increased in the order tropical < Mediterranean < temperate coniferous < temperate deciduous < boreal forests. Together with the boreal forest sites, the managed grasslands and crops show the largest seasonal variability. In the temperate coniferous forests, seasonal patterns of F GPP and F RE are in phase, in the temperate deciduous and boreal coniferous forests F RE was delayed compared to F GPP , resulting in the greatest imbalance between respiratory and assimilatory fluxes early in the growing season.F GPP adjusted for the length of the carbon uptake period decreased at the sampling sites across functional types in the order C 4 crops, temperate and boreal deciduous forests (7.5-8.3 g C m −2 per day) > temperate conifers, C 3 grassland and crops (5.7-6.9 g C m −2 per day) > boreal conifers (4.6 g C m −2 per day). Annual F GPP and net ecosystem productivity (F NEP ) decreased across climate zones in the order tropical > temperate > boreal. However, the decrease in F NEP with latitude was greater than the decrease in F GPP , indicating a larger contribution of respiratory (especially heterotrophic) processes in boreal systems.

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