ALBERT

Description: The following authors were omitted from the original version of this Data Descriptor: Markus Reichstein and Nicolas Vuichard. Both contributed to the code development and N. Vuichard contributed to the processing of the ERA-Interim data downscaling. Furthermore, the contribution of the co-author Frank Tiedemann was re-evaluated relative to the colleague Corinna Rebmann, both working at the same sites, and based on this re-evaluation a substitution in the co-author list is implemented (with Rebmann replacing Tiedemann). Finally, two affiliations were listed incorrectly and are corrected here (entries 190 and 193). The author list and affiliations have been amended to address these omissions in both the HTML and PDF versions. © 2021, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.

Description: Over the past decade, several global maps of above-ground biomass (AGB) have been produced, but they exhibit significant differences that reduce their value for climate and carbon cycle modelling, and also for national estimates of forest carbon stocks and their changes. The number of such maps is anticipated to increase because of new satellite missions dedicated to measuring AGB. Objective and consistent methods to estimate the accuracy and uncertainty of AGB maps are therefore urgently needed. This paper develops and demonstrates a framework aimed at achieving this. The framework provides a means to compare AGB maps with AGB estimates from a global collection of National Forest Inventories and research plots that accounts for the uncertainty of plot AGB errors. This uncertainty depends strongly on plot size, and is dominated by the combined errors from tree measurements and allometric models (inter-quartile range of their standard deviation (SD) = 30–151 Mg ha−1). Estimates of sampling errors are also important, especially in the most common case where plots are smaller than map pixels (SD = 16–44 Mg ha−1). Plot uncertainty estimates are used to calculate the minimum-variance linear unbiased estimates of the mean forest AGB when averaged to 0.1∘. These are used to assess four AGB maps: Baccini (2000), GEOCARBON (2008), GlobBiomass (2010) and CCI Biomass (2017). Map bias, estimated using the differences between the plot and 0.1∘ map averages, is modelled using random forest regression driven by variables shown to affect the map estimates. The bias model is particularly sensitive to the map estimate of AGB and tree cover, and exhibits strong regional biases. Variograms indicate that AGB map errors have map-specific spatial correlation up to a range of 50–104 km, which increases the variance of spatially aggregated AGB map estimates compared to when pixel errors are independent. After bias adjustment, total pantropical AGB and its associated SD are derived for the four map epochs. This total becomes closer to the value estimated by the Forest Resources Assessment after every epoch and shows a similar decrease. The framework is applicable to both local and global-scale analysis, and is available at https://github.com/arnanaraza/PlotToMap. Our study therefore constitutes a major step towards improved AGB map validation and improvement.

Description: Inland waters receive and process large amounts of colored organic matter from the terrestrial surroundings. These inputs dramatically affect the chemical, physical, and biological properties of water bodies, as well as their roles as global carbon sinks and sources. However, manipulative studies, especially at ecosystem scale, require large amounts of dissolved organic matter with optical and chemical properties resembling indigenous organic matter. Here, we compared the impacts of two leonardite products (HuminFeed and SuperHume) and a freshly derived reverse osmosis concentrate of organic matter in a set of comprehensive mesocosm‐ and laboratory‐scale experiments and analyses. The chemical properties of the reverse osmosis concentrate and the leonardite products were very different, with leonardite products being low and the reverse osmosis concentrate being high in carboxylic functional groups. Light had a strong impact on the properties of leonardite products, including loss of color and increased particle formation. HuminFeed presented a substantial impact on microbial communities under light conditions, where bacterial production was stimulated and community composition modified, while in dark potential inhibition of bacterial processes was detected. While none of the browning agents inhibited the growth of the tested phytoplankton Gonyostomum semen, HuminFeed had detrimental effects on zooplankton abundance and Daphnia reproduction. We conclude that the effects of browning agents extracted from leonardite, particularly HuminFeed, are in sharp contrast to those originating from terrestrially derived dissolved organic matter. Hence, they should be used with great caution in experimental studies on the consequences of terrestrial carbon for aquatic systems.

Description: Marie Curie International Outgoing Fellowship

Description: Swedish Research Council Formas http://dx.doi.org/10.13039/501100001862

Description: Knut and Alice Wallenberg Foundation http://dx.doi.org/10.13039/501100004063