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Waterbase - Biology, 2024

Waterbase serves as the EEA’s central database for managing and disseminating data regarding the status and quality of Europe's rivers, lakes, groundwater bodies, transitional, coastal, and marine waters. It also includes information on the quantity of Europe’s water resources and the emissions from point and diffuse sources of pollution into surface waters. Specifically, Waterbase - Biology focuses on biology data from rivers, lakes, transitional and coastal waters collected annually through the Water Information System for Europe (WISE) – State of Environment (SoE) reporting framework. The data are expected to be collected within monitoring programs defined under the Water Framework Directive (WFD) and used in the classification of the ecological status or potential of rivers, lakes, transitional and coastal water bodies. These datasets provide harmonised, quality-assured biological monitoring data reported by EEA member and cooperating countries, as Ecological Quality Ratios (EQRs) from all surface water categories (rivers, lakes, transitional and coastal waters).

WISE WFD Reference Spatial Datasets reported under Water Framework Directive 2010 - INTERNAL VERSION - version 1.9, Sep. 2025

The dataset contains information on the European river basin districts, the river basin district sub-units, the surface water bodies and the groundwater bodies delineated for the 1st River Basin Management Plans (RBMP) under the Water Framework Directive (WFD) as well as the European monitoring sites used for the assessment of the status of the abovementioned surface water bodies and groundwater bodies. This data set is available only for internal use of the European Commission and the European Environment Agency. Please use the "PUBLIC VERSION": https://sdi.eea.europa.eu/catalogue/srv/eng/catalog.search#/metadata/6b55632c-63df-4542-97f0-363dfb6d3431 for external use. The information was reported to the European Commission under the Water Framework Directive (WFD) reporting obligations. The dataset compiles the available spatial data related to the 1st RBMPs which were due in 2010 (hereafter WFD2010). See http://rod.eionet.europa.eu/obligations/521 for further information on the WFD2010 reporting. It was prepared to support the reporting of the 2nd RBMPs due in 2016 (hereafter WFD2016). See http://rod.eionet.europa.eu/obligations/715 for further information on the WFD2016 reporting. See also https://rod.eionet.europa.eu/obligations/766 for information on the Environmental Quality Standards Directive - Preliminary programmes of measures and supplementary monitoring. The data reported in WFD2010 were updated using data reported in WFD2016, whenever the spatial objects are identical in 2010 and 2016. For WFD2010 objects, some information may be missing, if the objects no longer exist in the 2nd River Basin Management Plans, and were not reported in WFD2016. Where available, spatial data related to the 3rd RBMPs due in 2022 (hereafter WFD2022) was used to update the WFD2016 data. See https://rod.eionet.europa.eu/obligations/780 for further information on the WFD2022 reporting. Note: * This dataset has been reported by the member states. The subsequent QC revealed some problems caused by self-intersections elements. Data in GPKG-format should be processed using QGIS.

WISE WFD Reference Spatial Datasets reported under Water Framework Directive 2016 - INTERNAL VERSION - version 1.7, Jul. 2024

The dataset contains information on the European river basin districts, the river basin district sub-units, the surface water bodies and the groundwater bodies delineated for the 2nd River Basin Management Plans (RBMP) under the Water Framework Directive (WFD) as well as the European monitoring sites used for the assessment of the status of the above mentioned surface water bodies and groundwater bodies. This data set is available only for internal use of the European Commission and the European Environment Agency. Please use the "PUBLIC VERSION": https://sdi.eea.europa.eu/catalogue/srv/eng/catalog.search#/metadata/a0731ebf-6bcc-4afe-bab0-39e7aa88eaba for external use. The information was reported to the European Commission under the Water Framework Directive (WFD) reporting obligations. The dataset compiles the available spatial data related to the 2nd RBMPs due in 2016 (hereafter WFD2016). See http://rod.eionet.europa.eu/obligations/715 for further information on the WFD2016 reporting. See also https://rod.eionet.europa.eu/obligations/766 for information on the Environmental Quality Standards Directive - Preliminary programmes of measures and supplementary monitoring. Where available, spatial data related to the 3rd RBMPs due in 2022 (hereafter WFD2022) was used to update the WFD2016 data. See https://rod.eionet.europa.eu/obligations/780 for further information on the WFD2022 reporting.

GISCO - Nomenclature of Territorial Units for Statistics 2021 (NUTS 2021), May 2021

The 'GISCO NUTS 2021' data set represents the NUTS 2021 regulation and statistical regions by means of multipart polygon, polyline and point topology. The NUTS geographical information is completed by attribute tables and a set of cartographic help lines to better visualize multipart polygonal regions. The NUTS nomenclature is a hierarchical classification of statistical regions defined by Eurostat. The NUTS classification subdivides the EU economic territory into 3 statistical levels. The NUTS 2021 classification has been established through the Commission Delegated Regulation 2019/1755, which entered into force on 8th August 2019 and applies from 1st January 2021. A non official NUTS-like classification has been defined for the EFTA countries and the candidate countries. At present, six scale ranges (100K, 1M, 3M, 10M and 20M, 60M) are maintained in the GISCO geodatabase. The polygon and boundary classes delineate the regions, while the points provide an anchor for each region. Associated tables contain basic information such as the name of the region. The public data set will be available at 1M, 3M, 10M, 20M, 60M, while the full data set at 100K is restricted. The data set covers EU Member States, EFTA countries, EU candidate countries and the UK. Following the departure of the UK from the European Union, the UK is no longer flagged as an EU Member State but retains its place in the NUTS and statistical regions data set. This dataset (NUTS_2021) is derived from the EuroBoundary Map 2020 (EBM2020) from Eurogeographics as well as GISCO NUTS 2016 (from Türkiye). The list of NUTS2021 codes including changes with respect to NUTS2016 is available on https://ec.europa.eu/eurostat/documents/345175/629341/NUTS2021.xlsx. The public metadata for NUTS 2021 released by Eurostat is available here: https://gisco-services.ec.europa.eu/distribution/v2/nuts/nuts-2021-metadata.xml. This revision (May 2021) includes minor changes in the dataset such as (see https://gisco-services.ec.europa.eu/distribution/v2/nuts/nuts-2021-release-notes.txt): * 2020-10-05 Point snapping is disabled in all datasets, number of decimals increased for 01M datasets. * 2020-11-18 Inclusion of Jan Mayen and Svalbard in to Norways Statistical Regions. Amendment to Serbia NUTS BN line status. * 2020-12-05 Fixed broken utf-8 encoding. * 2021-03-15 Added LAU 2011,2012,2013,2014,2015,2020 * 2021-04-26 Fixed country labels 2001, 2006 (incorrect Kosovo coordinates) IMPORTANT NOTE: Additional information, including the conditions of use and acknowledgement notice is included in the document provided with the dataset "GISCO NUTS 2021 Additional Information.pdf". Public access to this data set is restricted due to intellectual property rights. It shall only be used internally by the EEA, its ETCs and subcontractors working on behalf of the EEA. This metadata has been slightly adapted from the original metadata information provided by Eurostat (European Commission) and is to be used only for internal EEA purposes. An introduction to the NUTS classification is available here: http://ec.europa.eu/eurostat/web/nuts/overview.

Continuous water level observations at station BEFmate_I4upp, 2020-01 to 2021-07

Data presented here were collected between 2020-01 and 2021-07 at station BEFmate_I4upp within the research unit DynaCom (Spatial community ecology in highly dynamic landscapes: From island biogeography to metaecosystems, https://uol.de/dynacom/ ) involving the Universities of Oldenburg, Göttingen, and Münster, the iDiv Leipzig and the Nationalpark Niedersächsisches Wattenmeer. Experimental islands and saltmarsh enclosed plots were established in the back-barrier tidal flat and in the saltmarsh zone of the island of Spiekeroog (Germany). Groundwater levels at different elevation zones were measured using pressure loggers deployed in dip wells within the experimental islands as well as in the saltmarsh enclosed plots. Measurements were obtained using Hobo U20L Water Level Loggers (Onset Computer Corporation, Bourne, MA/USA). All devices were pre-calibrated by the manufacturer. Logged data were retrieved in the field using a Hobo Underwater Shuttle (U-DTW-1) and were read out with the HOBOware Pro (V3.7.28) software, Subsequent data processing was done using MATLAB (R2024b). Atmospheric pressure correction for water-level calculations was applied using data from a nearby weather station. Post-processing and quality control included (a) the removal of data covering maintenance activities, (b) an outlier detection, and (c) visual checks. Outliers in water level and temperature time series were detected using a moving-median filter and a 3-sigma criterion, with additional cross-checking against a reference sensor. Identified outliers were removed, and height-corrected water level series were produced to ensure consistency across sensors and years.

Daily rescued meteorological observations across Europe (1917-1990)

In the INDECIS project, around 610K meteorological station-based observations were rescued over the Balkans and Central Europe for the main climate variables (maximum and minimum temperature, rainfall, sunshine duration and snow depth) along the 20th century at daily scale. Digitizing was carried out by using a strict "key as you see" method, meaning that the digitizers type the values provided by data images, rather than using any coding system. Digitizers carefully cross-checked the typed values against original sources for the 10th, 20th and 30th day of each month to make sure that no days were skipped or repeated during the digitizing process. Monthly totals and statistical summaries were computed from transcribed data and were compared with monthly totals and summaries provided by data sources to check accuracy as preliminary quality control. This dataset is considered as raw data since any consistent quality control and homogenisation testing were applied to identify potential errors and data biases.

Raw data of physical oceanography during RV HEINCKE cruise HE491

Raw physical oceanography data was acquired by a ship-based Seabird SBE911plus CTD-Rosette system onboard RV HEINCKE. The CTD was equipped with duplicate sensors for temperature (SBE3plus) and conductivity (SBE4) as well as one sensor for oxygen (SBE43). Additional sensors such as a WET Labs C-Star transmissometer, a WET Labs ECO-AFL fluorometer (FLRTD) and an altimeter (Teledyne Benthos PSA-916) were mounted to the CTD. The data was recorded using pre-cruise calibration coefficients. No correction, post-cruise calibration or quality control was applied. Processed profile data are available via the link below.

Continuous thermosalinograph oceanography along RV ALKOR cruise track AL639

Underway temperature and salinity data was collected along the cruise track with a SBE21 thermosalinograph (TSG) together with a SBE38 Thermometer. Both systems worked throughout the cruise. While temperature is taken at the water inlet in about 4 m depth, salinity is calculated within the interior TSG from conductivity and interior temperature. No temperature validation was performed. Salinity was validated with independent water samples taken at the water inlet. For details to all processing steps see Data Processing Report.

CRM-geothermal Database: Geoscientific and Geochemical Data on Geothermal Systems, with Emphasis on Fluids and Critical Raw Materials in Europe and Eastern Africa

The CRM-geothermal database was created within the Horizon Europe CRM-geothermal project (Grant Agreement No. 101058163) to support the assessment of geothermal systems as sources of both renewable energy and critical raw materials (CRMs). The primary purpose of data collection was to compile, harmonise, and make openly available geoscientific and geochemical data relevant to the occurrence, enrichment, and potential co-production of CRMs from geothermal environments in Europe and East Africa. The database integrates legacy data compiled from peer-reviewed literature, national geological and geothermal databases, and previous European research projects (notably REFLECT), together with new data generated by project partners through field sampling and laboratory analyses. Sampling campaigns targeted geothermal wells and surface manifestations in selected regions, including Türkiye, the East African Rift (Kenya, Tanzania, Malawi), Cornwall (UK), and Iceland. Laboratory analyses include major ion chemistry, trace and critical element concentrations, mineralogical composition, and gas data, determined using methods such as ICP-MS, XRF, and XRD. All records were harmonised using a unified metadata schema, standardised units, and consistent reporting formats. Quality control involved automated validation routines and manual expert review. Each record includes spatial coordinates, sampling context, analytical method, references, and a quality flag indicating data origin and traceability. The database is provided as a structured Excel file and contains interconnected datasets on geothermal wells, fluids, rocks, gases, and mineral precipitates. In total, the dataset comprises 9,773 records covering a wide range of geological settings, from volcanic and metamorphic systems to sedimentary basins. The CRM-geothermal database is FAIR-aligned, openly available, and intended for reuse in geothermal research, resource assessment, and studies on the sustainable co-production of geothermal energy and critical raw materials. Method: The CRM-geothermal database was compiled using a combined approach integrating literature-based data collection, database harmonisation, and new data generation through field sampling and laboratory analysis. Legacy data were collected from peer-reviewed scientific publications, national geological and geothermal databases, technical reports, and previous European research projects, with a particular emphasis on the REFLECT project. Relevant parameters were manually extracted, digitised where necessary, and cross-checked against original sources to ensure consistency and traceability. New data were generated within the CRM-geothermal project through targeted sampling campaigns at selected geothermal sites in Europe and Eastern Africa. Samples of geothermal fluids, rocks, gases, and mineral precipitates were collected from wells and surface manifestations following standard geochemical sampling protocols. Laboratory analyses were performed by project partner institutions using established analytical techniques, including inductively coupled plasma mass spectrometry (ICP-MS) for trace and critical elements, X-ray fluorescence (XRF) for bulk chemical composition, and X-ray diffraction (XRD) for mineralogical characterisation. Gas compositions were determined using gas chromatography and noble gas mass spectrometry where applicable. Detection limits and analytical uncertainties follow laboratory-specific standards and are documented where available. All data were harmonised using a unified metadata schema. Units, parameter names, and reporting formats were standardised, and spatial information was converted to WGS 84 decimal degrees. Quality control was applied through automated validation scripts checking metadata completeness, coordinate validity, and numerical plausibility, followed by manual expert review to ensure scientific coherence and correct sample attribution. The final dataset was organised into interconnected thematic tables (wells, fluids, rocks, gases, and scales) and exported as a structured Excel file for dissemination. Each record includes references, analytical method information, and a quality flag indicating data origin and traceability. Technical Info: The CRM-geothermal data publication is provided as a structured multi-sheet Excel (XLSX) file representing a curated snapshot of the CRM-geothermal database at the time of publication. The dataset was generated through controlled export workflows following data validation and harmonisation. The Excel file contains separate worksheets for thematic data tables (wells, fluids, rocks, gases, and mineral precipitates). Each worksheet preserves unique identifiers, standardised metadata fields, and cross-references between related records, allowing the dataset to be used independently of any external system or software platform.

Ecosystem functions of rare arable plants - field study: Carabidae data

Partly taken from the materials and methods of https://doi.org/10.1016/j.baae.2022.12.003: To compare the activity densities of ground-dwelling predators between treatments with and without RAPs, carabids were sampled using pitfall traps, which were set up after each round of aphid counting (one per plot, twice per year; Brown & Matthews, 2016). The traps (with a volume of 400 ml and a width of 90 mm) were filled with a mixture of water and ethylene glycol (1:1; 120 ml) and dug at ground level into the middle of each plot. The traps were covered with a plastic roof and a metal grid (15 × 15 mm grid size) to avoid overflowing during rain and accidental rodent catches (Császár et al., 2018). The traps were activated for 7 days. Subsequently, all arthropods were transferred into 70% ethanol. Carabids were identified to species according to Hůrka (1996). Carabid feeding behavior was classified according to Homburg et al. (2014). To simplify the dataset, carabid feeding behavior was classified as predominantly granivorous (species mainly feed on seeds and fruits) or as carnivorous/omnivorous, because carnivorous and omnivorous species are potentially feeding on aphids and other non-plant material.

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