The FLUXNET2015 dataset provides ecosystem-scale data on CO 2 , water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

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Abstract:The availability of new fAPAR satellite products requires simultaneous efforts in validation to provide users with a better comprehension of product performance and evaluation of uncertainties. This study aimed to validate three fAPAR satellite products, GEOV1, MODIS C5, and MODIS C6, against ground references to determine to what extent the GCOS requirements on accuracy (maximum 10% or 5%) can be met in a deciduous beech forest site in a gently and variably sloped mountain site. Three ground reference fAPAR, differing for temporal (continuous or campaign mode) and spatial sampling (single points or Elementary Sampling Units-ESUs), were collected using different devices: (1) Apogee (defined as benchmark in this study); (2) PASTIS; and (3) Digital cameras for collecting hemispherical photographs (DHP). A bottom-up approach for the upscaling process was used in the present study. Radiometric values of decametric images (Landsat-8) were extracted over the ESUs and used to develop empirical transfer functions for upscaling the ground measurements. The resulting high-resolution ground-based maps were aggregated to the spatial resolution of the satellite product to be validated considering the equivalent point spread function of the satellite sensors, and a correlation analysis was performed to accomplish the accuracy assessment. PASTIS sensors showed good performance as fAPAR PASTIS appropriately followed the seasonal trends depicted by fAPAR APOGEE (benchmark) (R 2 = 0.84; RMSE = 0.01). Despite small dissimilarities, mainly attributed to different sampling schemes and errors in DHP classification process, the agreement between fAPAR PASTIS and fAPAR DHP was noticeable considering all the differences between both approaches. The temporal courses of the three satellite products were found to be consistent with both Apogee and PASTIS, except at the end of the summer season when ground data were more affected by senescent leaves, with both MODIS C5 and C6 displaying larger short-term variability due to their shorter temporal composite period. MODIS C5 and C6 retrievals were obtained with the backup algorithm in most cases. The three green fAPAR satellite products under study showed good agreement with ground-based maps of canopy fAPAR at 10 h, with RMSE values lower than 0.06, very low systematic differences, and more than 85% of the pixels within GCOS requirements. Among them, GEOV1 fAPAR showed up to 98% of the points lying within Remote Sens. 2017, 9, 126; doi:10.3390/rs9020126 www.mdpi.com/journal/remotesensing Remote Sens. 2017, 9, 126 2 of 28 the GCOS requirements, and slightly lower values (mean bias = −0.02) as compared with the ground canopy fAPAR, which is expected to be only slightly higher than green fAPAR in the peak season.

In the Mediterranean region, ecosystems are severely affected by climate variability. The Italian Peninsula is a hot spot for biodiversity thanks to its heterogeneous landscape and the Mediterranean, Continental, and Alpine climates hosting a broad range of plant functional types along a limited latitudinal range from 40 ′ to 46 ′ N. In this study we applied a comparative approach integrating descriptive statistics, time series analysis, and multivariate techniques to answer the following questions: (i) do the climatic variables affect Gross Primary Productivity (GPP), Reco, Water Use Efficiency (WUE), and ET to a similar extent among different sites? (ii) Does a common response pattern exist among ecosystems along a latitudinal gradient in Italy? And, finally (iii) do these ecosystems respond synchronically to meteorological conditions or does a delayed response exist? Six sites along a latitudinal, altitudinal, and vegetational gradient from semi-arid (southern Italy), to a mountainous Mediterranean site (central Italy), and sub-humid wet Alpine sites (northern Italy) were considered. For each site, carbon and water fluxes, and meteorological data collected during two hydrologically-contrasting years (i.e., a dry and a wet year) were analyzed. Principal Component Analysis (PCA) was adopted to identify temporal and spatial variations in GPP, Ecosystem Respiration (Reco), WUE, and Evapotranspiration (ET). The model outlined differences among Mediterranean semi-arid, Mediterranean mountainous, and Alpine sites in response to contrasting precipitation regimes. GPP, Reco, WUE, and ET increased up to 16, 19, 25, and 28%, respectively in semi-arid Mediterranean sites and up to 15, 32, 15, and 11%, respectively in Alpine sites in the wet year compared to the dry year. Air temperature was revealed to be one of the most important variables affecting GPP, Reco, WUE, and ET in all the study sites. While relative air humidity was more important in southern Mediterranean sites, Conte et al. Forest Responses to Rainfall Variability global radiation was more significant in northern Italy. Our work suggests that a realistic prediction of the main responses of Italian forests under climate change should also take in account delayed responses due to acclimation to abiotic stress or changing environmental conditions.