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Abstract In eddy covariance measurements, the storage flux represents the variation in time of the dry molar fraction of a given gas in the control volume representative of turbulent flux. Depending on the time scale considered, and on the height above ground of the measurements, it can either be a major component of the overall net ecosystem exchange or nearly negligible. Instrumental configuration and computational procedures must be optimized to measure this change at the time step used for the turbulent flux measurement. Three different configurations are suitable within the Integrated Carbon Observation System infrastructure for the storage flux determination: separate sampling, subsequent sampling and mixed sampling. These configurations have their own advantages and disadvantages, and must be carefully selected based on the specific features of the considered station. In this paper, guidelines about number and distribution of vertical and horizontal sampling points are given. Details about suitable instruments, sampling devices, and computational procedures for the quantification of the storage flux of different GHG gases are also provided. 

Abstract The eddy covariance is a powerful technique to estimate the surface-atmosphere exchange of different scalars at the ecosystem scale. The EC method is central to the ecosystem component of the Integrated Carbon Observation System, a monitoring network for greenhouse gases across the European Continent. The data processing sequence applied to the collected raw data is complex, and multiple robust options for the different steps are often available. For Integrated Carbon Observation System and similar networks, the standardisation of methods is essential to avoid methodological biases and improve comparability of the results. We introduce here the steps of the processing chain applied to the eddy covariance data of Integrated Carbon Observation System stations for the estimation of final CO 2 , water and energy fluxes, including the calculation of their uncertainties. The selected methods are discussed against valid alternative options in terms of suitability and respective drawbacks and advantages. The main challenge is to warrant standardised processing for all stations in spite of the large differences in e.g . ecosystem traits and site conditions. The main achievement of the Integrated Carbon Observation System eddy covariance data processing is making CO 2 and energy flux results as comparable and reliable as possible, given the current micrometeorological understanding and the generally accepted state-of-the-art processing methods. 

Abstract The leaf economics spectrum 1,2 and the global spectrum of plant forms and functions 3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species 2 . Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities 4 . However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability 4,5 . Here we derive a set of ecosystem functions 6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems 7,8 . 

Abstract The Integrated Carbon Observation System Research Infrastructure aims to provide long-term, continuous observations of sources and sinks of greenhouse gases such as carbon dioxide, methane, nitrous oxide, and water vapour. At ICOS ecosystem stations, the principal technique for measurements of ecosystem-atmosphere exchange of GHGs is the eddy-covariance technique. The establishment and setup of an eddy-covariance tower have to be carefully reasoned to ensure high quality flux measurements being representative of the investigated ecosystem and comparable to measurements at other stations. To fulfill the requirements needed for flux determination with the eddy-covariance technique, variations in GHG concentrations have to be measured at high frequency, simultaneously with the wind velocity, in order to fully capture turbulent fluctuations. This requires the use of high-frequency gas analysers and ultrasonic anemometers. In addition, to analyse flux data with respect to environmental conditions but also to enable corrections in the post-processing procedures, it is necessary to measure additional abiotic variables in close vicinity to the flux measurements. Here we describe the standards the ICOS ecosystem station network has adopted for GHG flux measurements with respect to the setup of instrumentation on towers to maximize measurement precision and accuracy while allowing for flexibility in order to observe specific ecosystem features. 

Abstract. Plant transpiration links physiological responses ofvegetation to water supply and demand with hydrological, energy, and carbonbudgets at the land–atmosphere interface. However, despite being the mainland evaporative flux at the global scale, transpiration and its response toenvironmental drivers are currently not well constrained by observations.Here we introduce the first global compilation of whole-plant transpirationdata from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021).We harmonized and quality-controlled individual datasets supplied bycontributors worldwide in a semi-automatic data workflow implemented in theR programming language. Datasets include sub-daily time series of sap flowand hydrometeorological drivers for one or more growing seasons, as well asmetadata on the stand characteristics, plant attributes, and technicaldetails of the measurements. SAPFLUXNET contains 202 globally distributeddatasets with sap flow time series for 2714 plants, mostly trees, of 174species. SAPFLUXNET has a broad bioclimatic coverage, withwoodland/shrubland and temperate forest biomes especially well represented(80 % of the datasets). The measurements cover a wide variety of standstructural characteristics and plant sizes. The datasets encompass theperiod between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data areavailable for most of the datasets, while on-site soil water content isavailable for 56 % of the datasets. Many datasets contain data for speciesthat make up 90 % or more of the total stand basal area, allowing theestimation of stand transpiration in diverse ecological settings. SAPFLUXNETadds to existing plant trait datasets, ecosystem flux networks, and remotesensing products to help increase our understanding of plant water use,plant responses to drought, and ecohydrological processes. SAPFLUXNET version0.1.5 is freely available from the Zenodo repository (https://doi.org/10.5281/zenodo.3971689; Poyatos et al., 2020a). The“sapfluxnetr” R package – designed to access, visualize, and processSAPFLUXNET data – is available from CRAN. 

Abstract Research infrastructures play a key role in launching a new generation of integrated long-term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO 2 , CH 4 , N 2 O, H 2 O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. The use of open-access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.