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: This data publication is supplementary material to McCutcheon et al. (2021): "Melting of the Greenland Ice Sheet is a leading cause of land-ice mass loss and cryosphere-attributed sea level rise. Blooms of pigmented glacier ice algae lower ice albedo and accelerate surface melting in the ice sheet’s southwest sector. Although glacier ice algae cause up to 13% of the surface melting in this region, the controls on bloom development remain poorly understood. Here we show a direct link between mineral phosphorus in surface ice and glacier ice algae biomass through the quantification of solid and fluid phase phosphorus reservoirs in surface habitats across the southwest ablation zone of the ice sheet. We demonstrate that nutrients from mineral dust likely drive glacier ice algal growth, and thereby identify mineral dust as a secondary control on ice sheet melting." Tables included in this data publication: Supplementary Table 1. Locations, dates and sample types collected for particulate analyses. Sites 4a and 4b were the base camp locations for 2016 and 2017, respectively. Supplementary Table 2. Results of a Tukey HSD test with a 95% family-wise confidence interval for Fv/Fm measurements made at 24 h and 120 h in the nutrient addition experiment. Supplementary Table 3. Results of a Tukey HSD test with a 95% family-wise confidence interval for rETRmax measurements made at 24 h and 120 h in the nutrient addition experiment. Supplementary Table 4. Glacier algal cell concentrations (cells·mL-1) at the end of the 120 h nutrient incubation experiment. Glacier algae assemblage used for the incubations had an initial mean cell concentration of 8.0 ± 2.1  103 cells·mL-1. Supplementary Table 5. Carbon, nitrogen, and phosphorus content of solid LAPs collected from melted surface ice. TC: total carbon. TOC: total organic carbon, IC: inorganic carbon, Pexch: exchangeable/loosely bound phosphorus, Pmin: mineral phosphorus, Porg: organic phosphorus. Supplementary Table 6. Mineral phase abundances in 2016 and 2017 particulate samples as determined by Rietveld refinement with powder X-ray diffraction data. Abundances given as weight percent of total mineral dust (n=20). Supplementary Table 7. Mineral class abundances in high algal biomass (Hbio) ice sampled across the ablation zone in 2016. Values listed in weight percent of total mineral dust % (+/- standard error where applicable). Two-sided t-test comparing of mineral class abundances between site 3 and 4a. Supplementary Table 8. Major cation and anion concentrations in the fluid phase and pH, conductivity and total dissolved solids (TDS) of supraglacial stream water and melted ice and snow samples. LOD: level of detection, LOQ: level of quantification, ND: no data. Supplementary Table 9. Number of raw and processed sequences after each quality filtering step for 16S, ITS2 and 18S. Supplementary Table 10. Table shows the full bacterial community composition with the taxonomic assignments of each ASV on the lowest possible level. Values represent the relative abundances of the 16S ASVs in percentage of the total number of sequences and collapsed on the species level. Values are rounded to one decimal place, thus “〈” represents relative abundance values 〈 0.05 and 〉 0. Supplementary Table 11. Table shows the full eukaryotic community composition collapsed into higher eukaryotic taxonomic groups. Values represent the relative abundance of the 18S ASVs in percentage of the total number of sequences and collapsed on the species level. Values are rounded to one decimal place, thus “〈” represents relative abundance 〈 0.05 and 〉 0. Supplementary Table 12. Table shows the fungal community composition with the taxonomic assignments of the ten most abundant ASV on the lowest possible level. The representative sequences were blasted against NCBI and the closest accession number with the respective similarity were recorded. If several hits shared the similarity one hit was chosen as an example (“e.g.”). Values represent the relative abundance of the ITS2 ASVs in percentage of the total number of sequences. Values are rounded to one decimal place, thus “〈” represents relative abundance values 〈 0.05 and 〉 0. Supplementary Table 13. Table shows the full algal community composition with the taxonomic assignments of each ASV on the lowest possible level. Values represent the relative abundance of the 18S ASVs in percentage of the total number of sequences. All ASVs were blasted against NCBI and the closest accession number with the respective similarity were recorded. If several hits shared the similarity one hit was chosen as an example (“e.g.”). Values are rounded to one decimal place, hence “〈” represents relative abundance 〈 0.05 and 〉 0. *Based on light microscopic identifications in Lutz et al. (2018), this ASV likely represents Mesotaenium sp. (99.4% similarity with M. berggrenii var. alaskana) and not Ancylonema nordenskioeldii despite the slightly higher similarity (99.6%). Supplementary Table 14. Rare Earth Element (REE) analysis concentrations (µg·g-1) for the mineral dust in particulate samples.

Description: For monitoring and reporting forest carbon stocks and fluxes, many countries in the tropics and subtropics rely on default values of forest aboveground biomass (AGB) from the Intergovernmental Panel on Climate Change (IPCC) guidelines for National Greenhouse Gas (GHG) Inventories. Default IPCC forest AGB values originated from 2006, and are relatively crude estimates of average values per continent and ecological zone. The 2006 default values were based on limited plot data available at the time, methods for their derivation were not fully clear, and no distinction between successional stages was made. As part of the 2019 Refinement to the 2006 IPCC Guidelines for GHG Inventories, we updated the default AGB values for tropical and subtropical forests based on AGB data from 〉25 000 plots in natural forests and a global AGB map where no plot data were available. We calculated refined AGB default values per continent, ecological zone, and successional stage, and provided a measure of uncertainty. AGB in tropical and subtropical forests varies by an order of magnitude across continents, ecological zones, and successional stage. Our refined default values generally reflect the climatic gradients in the tropics, with more AGB in wetter areas. AGB is generally higher in old-growth than in secondary forests, and higher in older secondary (regrowth 〉20 years old and degraded/logged forests) than in young secondary forests (⩽20 years old). While refined default values for tropical old-growth forest are largely similar to the previous 2006 default values, the new default values are 4.0–7.7-fold lower for young secondary forests. Thus, the refined values will strongly alter estimated carbon stocks and fluxes, and emphasize the critical importance of old-growth forest conservation. We provide a reproducible approach to facilitate future refinements and encourage targeted efforts to establish permanent plots in areas with data gaps.

Description: The denudation of rocks in mountain belts exposes a range of fresh minerals to the surface of the Earth that are chemically weathered by acidic and oxygenated fluids. The impact of the resulting coupling between denudation and weathering rates fundamentally depends on the types of minerals that are weathering. Whereas silicate weathering sequesters CO2, the combination of sulfide oxidation and carbonate dissolution emits CO2 to the atmosphere. Here, we combine the concentrations of dissolved major elements in stream waters with 10Be basin-wide denudation rates from 35 small catchments in eastern Tibet to elucidate the importance of lithology in modulating the relationships between denudation rate, chemical weathering pathways, and CO2 consumption or release. Our catchments span 3 orders of magnitude in denudation rate in low-grade flysch, high-grade metapelites, and granitoid rocks. For each stream, we estimate the concentrations of solutes sourced from silicate weathering, carbonate dissolution, and sulfide oxidation using a mixing model. We find that for all lithologies, cation concentrations from silicate weathering are largely independent of denudation rate, but solute concentrations from carbonates and, where present, sulfides increase with increasing denudation rate. With increasing denudation rates, weathering may therefore shift from consuming to releasing CO2 in both (meta)sedimentary and granitoid lithologies. For a given denudation rate, we report dissolved solid concentrations and inferred weathering fluxes in catchments underlain by (meta)sedimentary rock that are 2–10 times higher compared to catchments containing granitoid lithologies, even though climatic and topographic parameters do not vary systematically between these catchments. Thus, varying proportions of exposed (meta)sedimentary and igneous rocks during orogenesis could lead to changes in the sequestration and release of CO2 that are independent of denudation rate.

Description: Rapidly evolving floods are rare but powerful drivers of landscape reorganisation that have severe and long-lasting impacts on both the functions of a landscape’s subsystems and the affected society. The July 2021 flood that particularly hit several river catchments of the Eifel region in western Germany and Belgium was a drastic example. While media and scientists highlighted the meteorological and hydrological aspects of this flood, it was not just the rising water levels in the main valleys that posed a hazard, caused damage, and drove environmental reorganisation. Instead, the concurrent coupling of landscape elements and the wood, sediment, and debris carried by the fast-flowing water made this flood so devastating and difficult to predict. Because more intense floods are able to interact with more landscape components, they at times reveal rare non-linear feedbacks, which may be hidden during smaller events due to their high thresholds of initiation. Here, we briefly review the boundary conditions of the 14–15 July 2021 flood and discuss the emerging features that made this event different from previous floods. We identify hillslope processes, aspects of debris mobilisation, the legacy of sustained human land use, and emerging process connections and feedbacks as critical non-hydrological dimensions of the flood. With this landscape scale perspective, we develop requirements for improved future event anticipation, mitigation, and fundamental system understanding.

Description: Snow and ice melt processes are a key in Earth's energy-balance and hydrological cycle. Their quantification facilitates predictions of meltwater runoff as well as distribution and availability of fresh water. They control the balance of the Earth's ice sheets and are acutely sensitive to climate change. These processes decrease the surface reflectance with unique spectral patterns due to the accumulation of liquid water and light absorbing particles (LAP), that require imaging spectroscopy to map and measure. Here we present a new method to retrieve snow grain size, liquid water fraction, and LAP mass mixing ratio from airborne and spaceborne imaging spectroscopy acquisitions. This methodology is based on a simultaneous retrieval of atmospheric and surface parameters using optimal estimation (OE), a retrieval technique which leverages prior knowledge and measurement noise in an inversion that also produces uncertainty estimates. We exploit statistical relationships between surface reflectance spectra and snow and ice properties to estimate their most probable quantities given the reflectance. To test this new algorithm we conducted a sensitivity analysis based on simulated top-of-atmosphere radiance spectra using the upcoming EnMAP orbital imaging spectroscopy mission, demonstrating an accurate estimation performance of snow and ice surface properties. A validation experiment using in-situ measurements of glacier algae mass mixing ratio and surface reflectance from the Greenland Ice Sheet gave uncertainties of ±16.4 μg/gice and less than 3%, respectively. Finally, we evaluated the retrieval capacity for all snow and ice properties with an AVIRIS-NG acquisition from the Greenland Ice Sheet demonstrating this approach's potential and suitability for upcoming orbital imaging spectroscopy missions.