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.

The African continent is facing one of the driest periods in the past three decades as well as continued deforestation. These disturbances threaten vegetation carbon (C) stocks and highlight the need for improved capabilities of monitoring large-scale aboveground carbon stock dynamics. Here we use a satellite dataset based on vegetation optical depth derived from low-frequency passive microwaves (L-VOD) to quantify annual aboveground biomass-carbon changes in sub-Saharan Africa between 2010 and 2016. L-VOD is shown not to saturate over densely vegetated areas. The overall net change in drylands (53% of the land area) was -0.05 petagrams of C per year (Pg C yr) associated with drying trends, and a net change of -0.02 Pg C yr was observed in humid areas. These trends reflect a high inter-annual variability with a very dry year in 2015 (net change, -0.69 Pg C) with about half of the gross losses occurring in drylands. This study demonstrates, first, the applicability of L-VOD to monitor the dynamics of carbon loss and gain due to weather variations, and second, the importance of the highly dynamic and vulnerable carbon pool of dryland savannahs for the global carbon balance, despite the relatively low carbon stock per unit area.

Here we present results from a field experiment in an Arctic wetland situated in Zackenberg, NE Greenland. During one growing season we investigated how dominance of the sedge Eriophorum scheuchzeri affected the below-ground concentrations of low molecular weight carbon compounds (LMWOC) and the fluxes of CO 2 and CH 4 in comparison to dominance of other sedges (Carex stans and Dupontia psilosantha). Three groups of LMWOC were analysed using liquid chromatography-ionspray tandem mass spectrometry, i.e., organic acids (OAs), amino acids (AAs) and simple carbohydrates (CHs). To identify the effect of plant composition the experiments were carried out in a continuous fen area with very little between species variation in environmental conditions, e.g., water-table and active layer thickness and soil temperature. The pool of labile LMWOC compounds in this Arctic fen was dominated by OAs, constituting between 75 and 83% of the total pore water pool of OAs, CHs and AAs. The dominant OA was acetic acid, an easily available substrate for methanogens, which constituted !85% of the OA pool. We estimated that the concentration of acetic acid found in pore water would support 2 e2.5 h of CH 4 flux and an additional continuous input of acetic acid through root exudation that would support 1.3e1.5 h of CH 4 flux. Thus, the results clearly points to the importance of a continuous input for acetoclastic methanogenesis to be sustainable. Additionally, Eriophorum had a very strong effect on parts of the carbon cycle in the Arctic fen. The mean seasonal CH 4 flux was twice as high in Eriophorum dominated plots, most likely due to a 1.7 times higher concentration of OAs in these plots. Further, the ecosystem respiration was 1.3 times higher in Eriophorum dominated plots. In conclusion, the results offer further support to the importance of certain vascular plant species for the carbon cycle of wetland ecosystems.

Monitoring long-term biomass dynamics in drylands is of great importance for many environmental applications including land degradation and global carbon cycle modeling. Biomass has extensively been estimated based on the normalized difference vegetation index (NDVI) as a measure of the vegetation greenness. The vegetation optical depth (VOD) derived from satellite passive microwave observations is mainly sensitive to the water content in total aboveground vegetation layer. VOD therefore provides a complementary data source to NDVI for monitoring biomass dynamics in drylands, yet further evaluations based on ground measurements are needed for an improved understanding of the potential advantages. In this study, we assess the capability of a long-term VOD dataset (1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011) to capture the temporal and spatial variability of in situ measured green biomass (herbaceous mass and woody plant foliage mass) in the semi-arid Senegalese Sahel. Results show that the magnitude and peak time of VOD are sensitive to the woody plant foliage whereas NDVI seasonality is primarily governed by the green herbaceous vegetation stratum in the study area. Moreover, VOD is found to be more robust against typical NDVI drawbacks of saturation effect and dependence on plant structure (herbaceous and woody compositions) across the study area when used as a proxy for vegetation productivity. Finally, both VOD and NDVI well reflect the spatial and inter-annual dynamics of the in situ green biomass data; however, the seasonal metrics showing the highest degree of explained variance differ between the two data sources. While the observations in October (period of in situ data collection) perform best for VOD (r 2 = 0.88), the small growing season integral (sensitive to recurrent vegetation) have the highest correlations for NDVI (r 2 = 0.90). Overall, in spite of the coarse resolution, the study shows that VOD is an efficient proxy for estimating green biomass of the entire vegetation stratum in the semi-arid Sahel and likely also in other dryland areas.