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Spatiotemporal variability in infiltration through biopores: earthworms, macropores and infiltration patterns

This dataset consists of spatially and temporally resolved data of dye-infiltration patterns, earthworms and macropores as well as supporting data, such as land use, soil moisture content, soil temperature, bulk density, and soil texture, in the Wollefsbach area of the Attert Catchment in Luxembourg (Pfister et al., 2005).The data was gathered in six measurement campaigns in the period from May 2015 to March 2016. During each measurement campaign we measured at five random sites on each of six chosen fields: three grasslands and three agricultural fields. At each measurement site a combination of measurements was performed: infiltration patterns of blue stained water, earthworm abundance (species level), macropore counts on horizontal soil profiles (in three depths, discriminating three size classes and stained or non-stained), soil temperature and moisture contents in three depths. Finally, undisturbed soil core samples were taken during one campaign for the determination of the texture and bulk density at different sampling sites. In the data table we also include GIS derived values of elevation, slope, aspect, heat load index, and topographical wetness index. Details on all the measurement methods, GIS-analysis methods and units of the data are given below.This data was gathered as part of the Joint Research Project “Catchments as Organised Systems” (CAOS, Zehe et al., 2014) funded by the German Research Foundation.---------------------------------------------------Version history:10 February 2020, release of Version 1.1.:The authors discovered that some rows in the data table “Earthworms_Macropores_Data.csv” for September Field 3 and Field 4 were accidentally exchanged. Compared to version 1.0, the data in rows 71 to 75 (Sept_3_1 to Sept_3_5) were exchanged with the data in rows 76 to 80 (Sept_4_1 to Sept_4_5). The authors apologise for this and ask everyone who downloaded the data of version 1.0 are advised to only use version 1.1, because there was an error which could lead to wrong results. Nevertheless, version 1.0 of the data table is available in the "previous-versions" subfolder via the Data Download link. The infiltration data included in “2019-022_vanSchaik-et-al_Infiltration_patterns.zip” remain unchanged.

A Holocene relative sea-level database for the Baltic Sea

We present a compilation and analysis of 1099 Holocene relative shore-level (RSL) indicators including 867 relative sea-level data points and 232 data points from the Ancylus Lake and the following transitional phase from 10.7 to 8.5 ka BP located around the Baltic Sea. The spatial distribution covers the Baltic Sea and near-coastal areas fairly well, but some gaps remain mainly in Sweden. RSL data follow the standardized HOLSEA format and, thus, are ready for spatially comprehensive applications in, e.g., glacial isostatic adjustment (GIA) modelling. Sampling method The data set is a compilation of rather different samples from geological, geomorphological and archaeological studies. Most of the data was already published in different formats. In this compilation we homogenized the meta information of the available information according to the HOLSEA database format, https://www.holsea.org/archive-your-data, which is a modification of the recommendations given in Hijma et al. (2015). In addition to the reformatting, the majority of samples with radiocarbon dating were recalibrated with oxcal-software using the calib13 and marine13 curves. Furthermore, all sample descriptions were critically checked for consistency in positioning, levelling and indicative meaning by experts of the respective geographic region see Supplement 2. Analytical method In principle, it is a compilation, recalibration and revision of already published data. Data Processing Data of individual compilations were revised and imported into a relational database system. Therein, the data was transferred into the HOLSEA format by specified rules. By this procedure, a homogeneous categorisation was achieved without losing the original data. Also this is stored in the relational database system allowing for later updates of the transfer procedure or a recalibration of the data. Description of data table HOLSEA-baltic-yymmdd.xlsx The workbook in excel format contains 5 sheets, see https://www.holsea.org/archive-your-data: · Long-form, containing the complete information available for each sample · Short-form, a subset of attributes of the Long-form sheet · Radiocarbon, containing the radiocarbon dating information of the respective samples · U-series, a corresponding table containing the respective information of Uranium dating · References, a complete reference list of the primary publications in which the individual data sampling is described. All online sources for the compilation are included in the metadata. A full list of source references is provided in the data description file.

Soil chemical, physical and hydrological characteristics in two agroforestry systems in Malawi

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.

Software for analyzing Globe at Night data

This publication contains software that can be used to pre-process data from the Globe at Night citizen science project, and then run an analysis to determine the rate of change in sky brightness. The software requires input data, which can be obtained directly from Globe at Night. The data used for our publication "Citizen scientists report global rapid reductions in the visibility of stars from 2011 to 2022" is published here, and can be used as input to the software. The process requires access to the World Atlas of Artificial Night Sky Brightness, which is also available from GFZ Data Services.

Mineralogical, geochemical and magnetic susceptibility data from a deep hydrothermally altered profile in a semi-arid region (Chilean Coastal Cordillera)

This data publication contains mineralogical, geochemical and magnetic susceptibility data of an 87.2 m deep profile of hydrothermally altered plutonic rock in a semi-arid region of the Chilean Coastal Cordillera (Santa Gracia). The profile was recovered during a drilling campaign (March and April 2019) as part of the German Science Foundation (DFG) priority research program SPP-1803 “EarthShape: Earth Surface Shaping by Biota” which aims at understanding weathering of plutonic rock in dependency on different climatic conditions. The goal of the drilling campaign was to recover the entire weathering profile spanning from the surface to the weathering front and to investigate the weathering processes at depth. To this end, we used rock samples obtained by drilling and soil/saprolite samples from a manually dug 2 m deep soil pit next to the borehole. To elucidate the role of iron-bearing minerals for the weathering, we measured the magnetic susceptibility, determined the mineral content and analysed the geochemistry as well as the composition of Fe-bearing minerals (Mössbauer spectroscopy) in selected samples.

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