Coastal wetlands can serve as natural laboratories for assessing the future impacts of sea-level rise and the intricacies of the effect of sulfate (SO42-) on emissions of greenhouse gases, such as methane (CH4) and carbon dioxide. In the case of previously drained and freshened wetlands, we can observe how freshwater terrestrial microbial communities react and adapt to intrusion of SO42- rich saline waters. We conducted a 3-month anoxic incubation experiment with soil extracted from a peatland on the German Baltic coast which was rewetted with brackish water in late 2019 to examine how microbial communities at the site had adapted to the new conditions after two years. Soil slurries were incubated at a moderate temperature of 15 °C at two different salinities (reflecting surface water and average peat soil water salinity) and sampled at 8 timepoints. At each timepoint 5 replicates of each treatment were destructively harvested and sampled for concentrations of CH4, dissolved inorganic carbon (DIC), total aqueous organic carbon, SO42-, ammonium, and other major ions, pH values, qPCR analysis, and δ13DIC and δ13CH4 values.
The described dataset was the result of a field effort consisting of several campaigns to assess the influence of carbon increase as a result of agroforestry treatments on soil hydrological characteristics and water fluxes at two sites in Malawi. At the sites, two experimental trials have been established which differ in age and soil characteristics, while climatic conditions are roughly comparable. At both sites we focused on control plots of maize and agroforestry treatments including Gliricidia sepium (Jacq.) Walp. as the tree component. The dataset contains soil characteristics such as texture, porosity, carbon and nitrogen concentrations, carbon density fractions, dispersible clay proportions, soil hydraulic conductivity and water retention curves. To assess the differences in water fluxes between treatments and sites, we installed soil moisture and matric potential sensors and a small weather station at the sites and monitored the fluxes over the course of about three months. The resulting time series are also part of the dataset, as well as some measurements of maize heights. The file structure of the dataset as well as details on the sites, sampling procedures, measurements and methodology are included in the data description.
sandbox is an R-tool for probabilistic numerical modelling of sediment properties. A flexible framework for definition and application of time/depth- based rules for sets of parameters for single grains that can be used to create artificial sediment profiles. Such profiles can be used for virtual sample preparation and synthetic, for instance, luminescence measurements.
Central Europe is an intraplate domain which is characterized by low to moderate seismicity with records of larger seismic events occurring in historical and recent times. These records of seismicity are restricted to just over one thousand years. This does not reflect the long seismic cycles in Central Europe which are expected to be in the order of tens of thousands of years.
Therefore, we have developed a paleoseismic database (PalSeisDB) that documents the records of paleoseismic evidence (trenches, soft-sediment deformation, mass movements, etc.) and extends the earthquake record to at least one seismic cycle. It is intended to serve as one important basis for future seismic hazard assessments. In the compilation of PalSeisDB, paleoseismic evidence features are documented at 129 different locations in the area of Germany and adjacent regions.
A brief explanation of the folder structure, file list and file contents included in the data publication of PalSeisDB is provided in the data description .A detailed explanation of the data collection, the content of the data files and the table headers is available (Hürtgen et al., 2020). A full list of source references for PalSeisDB is provided in Hürtgen (2017, Appendix 8.3, p. 128 ff) and also included in the zip folder here