ALBERT

Description: 29 April 2020: Release of Version 0.3 This is an updated version of Reyer et al., (2019, V. 0.1.12, http://doi.org/10.5880/PIK.2019.008). All changes and updates are documented in the changelog available via the data download section. Current process-based vegetation models are complex scientific tools that require proper evaluation of the different processes included in the models to prove that the models can be used to integrate our understanding of forest ecosystems and project climate change impacts on forests. The PROFOUND database (PROFOUND DB) described here aims to bring together data from a wide range of data sources to evaluate vegetation models and simulate climate impacts at the forest stand scale. It has been designed to fulfill two objectives: - Allow for a thorough evaluation of complex, process-based vegetation models using multiple data streams covering a range of processes at different temporal scales - Allow for climate impact assessments by providing the latest climate scenario data. Therefore, the PROFOUND DB provides general a site description as well as soil, climate, CO2, Nitrogen deposition, tree-level, forest stand-level and remote sensing data for 9 forest stands spread throughout Europe. Moreover, for a subset of 5 sites, also time series of carbon fluxes, energy balances and soil water are available. The climate and nitrogen deposition data contains several datasets for the historic period and a wide range of future climate change scenarios following the Representative Emission Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). In addition, we also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND Database is available freely but we incite users to respect the data policies of the individual datasets as provided in the metadata of each data file. The database can also be accessed via the PROFOUND R-package, which provides basic functions to explore, plot and extract the data. The data (PROFOUND DB) are provided in two different versions (ProfoundData.sqlite download as ProfoundData.zip, ProfoundData_ASCII.zip) accompanied by a change-log to the previous published version (changelog_Profound-DB_v03.pdf), auxiliary data of reconstructed single tree data at the site Sorø (Soroe_DBH_H_AGE_20200428.zip) and documented by the three explanatory documents: (1) PROFOUNDdatabase.pdf: describes the structure, organisation and content of the PROFOUND DB. (2) PROFOUNDsites.pdf: displays the main data of the PROFOUND DB for each of the 9 forest sites in tables and plots. (3) ProfoundData.pdf: explains how to use the PROFOUND R-Package "ProfoundData" to access the PROFOUND DB and provides example scripts on how to apply it.

Description: The scope of the Science Plan is to describe the scientific background, applications, and activities of the Environmental Mapping and Analysis Program (EnMAP) imaging spectroscopy mission. Primarily, this document addresses scientists and funding institutions, but it may also be of interest to environmental stakeholders and governmental agencies. It is designed to be a living document that will be updated throughout the entire mission lifetime. Chapter 1 provides a brief overview of the principles and current state of imaging spectroscopy. This is followed by an introduction to the EnMAP mission, including its objectives and impact on international programs as well as major environmental and societal challenges. Chapter 2 describes the EnMAP system together with data products and access, calibration/validation, and synergies with other missions. Chapter 3 gives an overview of the major fields of application such as vegetation and forests, geology and soils, coastal and inland waters, cryosphere, urban areas, atmosphere and hazards. Finally, Chapter 4 outlines the scientific exploitation strategy, which includes the strategy for community building and training, preparatory flight campaigns and software developments. A list of abbreviations is provided in the annex to this document and an extended glossary of terms and abbreviations is available on the EnMAP website.

Description: The new unconstrained GRACE monthly solution SWPU-GRACE2021 is recently developed with the dynamic approach. The reprocessed GRACE L1B RL03 data and de-aliasing product AOD1B RL06 are applied to compute SWPU-GRACE2021. The arc length is variable according to the L1B data quality, but the maximum is no more than 24 hours. The bias vector and scale matrix of the GRACE Accelerometer observation ACC1B product are estimable parameters. The data covers the period from April 2002 to Mai 2017. Due to data quality problems, there are some data gaps between September 2016 and April 2017.

Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Gosselin, K. M., Nelson, R. K., Spivak, A. C., Sylva, S. P., Van Mooy, B. A. S., Aeppli, C., Sharpless, C. M., O’Neil, G. W., Arrington, E. C., Reddy, C. M., & Valentine, D. L. Production of two highly abundant 2-methyl-branched fatty acids by blooms of the globally significant marine cyanobacteria Trichodesmium erythraeum. ACS Omega, 6(35), (2021): 22803–22810, https://doi.org/10.1021/acsomega.1c03196.

Description: The bloom-forming cyanobacteria Trichodesmium contribute up to 30% to the total fixed nitrogen in the global oceans and thereby drive substantial productivity. On an expedition in the Gulf of Mexico, we observed and sampled surface slicks, some of which included dense blooms of Trichodesmium erythraeum. These bloom samples contained abundant and atypical free fatty acids, identified here as 2-methyldecanoic acid and 2-methyldodecanoic acid. The high abundance and unusual branching pattern of these compounds suggest that they may play a specific role in this globally important organism.

Description: This work was funded with grants from the National Science Foundation grants OCE-1333148, OCE-1333162, and OCE-1756254 and the Woods Hole Oceanographic Institution (IR&D). GCxGC analysis made possible by WHOI’s Investment in Science Fund.

Description: Iron is an indispensable metabolic cofactor in both pro- and eukaryotes, which engenders a natural competition for the metal between bacterial pathogens and their human or animal hosts. Bacteria secrete siderophores that extract Fe3+ from tissues, fluids, cells, and proteins; the ligand gated porins of the Gram-negative bacterial outer membrane actively acquire the resulting ferric siderophores, as well as other iron-containing molecules like heme. Conversely, eukaryotic hosts combat bacterial iron scavenging by sequestering Fe3+ in binding proteins and ferritin. The variety of iron uptake systems in Gram-negative bacterial pathogens illustrates a range of chemical and biochemical mechanisms that facilitate microbial pathogenesis. This document attempts to summarize and understand these processes, to guide discovery of immunological or chemical interventions that may thwart infectious disease.

Description: On 26th of November 2019 an Mw 6.4 earthquake ruptured near the port town of Durres, only 25 km from Tirana, the capital of Albania. The earthquake caused major damage and killed 51 people, making it the deadliest earthquake in 2019 worldwide. The mainshock was relatively deep (~25 km) and of thrust type. In December 2019, a Hazard and Risk team (HART) from German Center for Geosciences (GFZ), Karslruhe Institute of Technology (KIT) in cooperation with the Institute of Geosciences, Energy, Water and Environment (IGEWE) of the Polytechnic University of Tirana, Albania installed a 30-station seismic network in the epicentral region to record aftershocks. Stations were equipped with short-period (1 Hz or 4.5 Hz) 3-component seismometers and CUBE data loggers recording continuously 100 sps. Waveform data are available from the GEOFON data centre, under network code 9K under CC-BY 4.0 license and are embargoed until January 2024.

Description: Py4HIP is an open-source software tool for Heat-In-Place calculations implemented as a self-explanatory Jupyter notebook written in Python (Py4HIP.ipynb) Calculating the Heat In Place (HIP) is a standard method for assessing the geothermal potential for a defined geological unit (e.g., Nathenson, 1975; Muffler and Cataldi, 1978; Garg and Combs, 2015). The respective implementation in Py4HIP is based on a volumetric quantification of contained energy after Muffler and Cataldi (1978), where the geological unit at hand is considered spatially variable in terms of its temperature, thickness, porosity, density and volumetric heat capacity of its solid and fluid (brine) components. The energy values

Description: We provide a single file (exodus II format) that contains all results of the modeling efforts of the associated paper. This encompasses all structural information as well as the pore pressure, temperature, and fluid velocity distribution through time. We also supply all files necessary to rerun the simulation, resulting in the aforementioned output file. The model area covers a rectangular area around the Central European Basin System (Maystrenko et al., 2020). The data publication is compeiment to Frick et al., (2021). The file published here is based on the structural model after Maystrenko et al., (2020) which resolves 16 geological units. More details about the structure and how it was derived can be found in Maystrenko et al., (2020). The file presented contains information on the regional variation of the pore pressure, temperature and fluid velocity of the model area in 3D. This information is presented for 364 time steps starting from 43,000 years before present and ending at 310000 years after present.

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: The basin sediments of Lake Constance encompass superior records of glacial to late glacial and Holocene environmental conditions but were hitherto not recovered from greater depths due to the lack of high-quality but inexpensive coring instruments. In a test and commissioning campaign in 2019, a new scientific coring device, called Hipercorig, was deployed and recovered from two parallel boreholes a 20 and a 24 m long drillcore and one two-m-long surface core (Harms et al. 2020, Schaller et al. 2022). The drill site is in 200 m deep waters close to the northwestern lake shoreline near the town of Hagnau and was selected based on new seismic surveys. They revealed an up to 150 m thick sediment fill of the overdeepened Lake Constance basin created by several advance and retreat cycles of the Rhine Glacier during the mid to late Quaternary. The deposits comprise proglacial sediments overlain by glaciolacustrine and finally lake strata. The latter make up the top 12 m of the core recovered while below sandy intercalations indicate downward increasing influence of dynamic sedimentation pulses that were deposited through subaquatic channel systems fed by declining glaciers and meltwater pulses from the north. The cores retrieved were sampled for microbiology and pore fluids at University of Constance (Germany). They were opened at Bern University (Switzerland) in fall 2019, sedimentologically described, instrumentally logged, and sampled for further studies including age dating. These data served to identify 14 lithotypes that were differentiated into three chronostratigraphic units based on a 14C- and OSL-based age model. The cores section base with the proglacial unit is about 13.7 ka BP old while the lacustrine strata cover Bølling-Alerød and Holocene ages. A prominent turbiditic event layer could be dated at 9.5 ka BP, coeval with the largest Holocene Alpine rock slide, the Flimser Bergsturz, that caused damming of the river Rhine and finally an outburst reaching as turbidite even northern Lake Constance. These initially gained data sets and the instruments utilized are described in the data description.