This dataset contains geochemical variables measured in six depth profiles from ombrotrophic peatlands in North and Central Europe. Peat cores were taken during the spring and summer of 2022 from Amtsvenn (AV1), Germany; Drebbersches Moor (DM1), Germany; Fochteloër Veen (FV1), the Netherlands; Bagno Kusowo (KR1), Poland; Pichlmaier Moor (PI1), Austria and Pürgschachen Moor (PM1), Austria. The cores AV1, DM1 and KR1 were taken using a Wardenaar sampler (Royal Eijkelkamp, Giesbeek, the Netherlands) and had diameter of 10 cm. The cores FV1, PM1 and PI1 had an 8 cm diameter and were obtained using an Instorf sampler (Royal Eijkelkamp, Giesbeek, the Netherlands). The cores FV1, DM1 and KR1 were 100 cm, core AV1 was 95 cm, core PI1 was 85 cm and core PM1 was 200 cm. The cores were subsampeled in 1 cm (AV1, DM1, KR1, FV1) and 2 cm (PI1, PM1) sections. The subsamples were milled after freeze drying in a ballmill using tungen carbide accesoires. X-Ray Fluorescence (WD-XRF; ZSX Primus II, Rigaku, Tokyo, Japan) was used to determine Al (μg g-1), As (μg g-1), Ba (μg g-1), Br (μg g-1), Ca (g g-1), Cl (μg g-1), Cr (μg g-1), Cu (μg g-1), Fe (g g-1), K (g g-1), Mg (μg g-1), Mn (μg g-1), Na (μg g-1), P (μg g-1), Pb (μg g-1), Rb (μg g-1), S (μg g-1), Si (μg g-1), Sr (μg g-1), Ti (μg g-1) and Zn (μg g-1). These data were processed and calibrated using the iloekxrf package (Teickner & Knorr, 2024) in R. C, N and their stable isotopes were determined using an elemental analyser linked to an isotope ratio mass spectrometer (EA-3000, Eurovector, Pavia, Italy & Nu Horizon, Nu Instruments, Wrexham, UK). C and N were given in units g g-1 and stable isotopes were given as δ13C and δ15N for stable isotopes of C and N, respectively. Raw data C, N and stable isotope data were calibrated with certified standard and blank effects were corrected with the ilokeirms package (Teickner & Knorr, 2024). Using Fourier Transform Mid-Infrared Spectroscopy (FT-MIR) (Agilent Cary 670 FTIR spectromter, Agilent Technologies, Santa Clara, Ca, USA) humification indices (HI) were determined. Spectra were recorded from 600 cm-1 to 4000 cm-1 with a resolution of 2 cm-1 and baselines corrected with the ir package (Teickner, 2025) to estimate relative peack heights. The HI (no unit) for each sample was calculated by taking the ratio of intensities at 1630 cm-1 to the intensities at 1090 cm-1. Bulk densities (g cm-3) were estimated from FT-MIR data (Teickner et al., in preparation).
This dataset contains geochemical variables measured in six depth profiles from ombrotrophic peatlands in North and Central Europe. Peat cores were taken during the spring and summer of 2022 from Amtsvenn (AV1), Germany; Drebbersches Moor (DM1), Germany; Fochteloër Veen (FV1), the Netherlands; Bagno Kusowo (KR1), Poland; Pichlmaier Moor (PI1), Austria and Pürgschachen Moor (PM1), Austria. The cores AV1, DM1 and KR1 were taken using a Wardenaar sampler (Royal Eijkelkamp, Giesbeek, the Netherlands) and had diameter of 10 cm. The cores FV1, PM1 and PI1 had an 8 cm diameter and were obtained using an Instorf sampler (Royal Eijkelkamp, Giesbeek, the Netherlands). The cores FV1, DM1 and KR1 were 100 cm, core AV1 was 95 cm, core PI1 was 85 cm and core PM1 was 200 cm. The cores were subsampeled in 1 cm (AV1, DM1, KR1, FV1) and 2 cm (PI1, PM1) sections. The subsamples were milled after freeze drying in a ballmill using tungen carbide accesoires. X-Ray Fluorescence (WD-XRF; ZSX Primus II, Rigaku, Tokyo, Japan) was used to determine Al (μg g-1), As (μg g-1), Ba (μg g-1), Br (μg g-1), Ca (g g-1), Cl (μg g-1), Cr (μg g-1), Cu (μg g-1), Fe (g g-1), K (g g-1), Mg (μg g-1), Mn (μg g-1), Na (μg g-1), P (μg g-1), Pb (μg g-1), Rb (μg g-1), S (μg g-1), Si (μg g-1), Sr (μg g-1), Ti (μg g-1) and Zn (μg g-1). These data were processed and calibrated using the iloekxrf package (Teickner & Knorr, 2024) in R. C, N and their stable isotopes were determined using an elemental analyser linked to an isotope ratio mass spectrometer (EA-3000, Eurovector, Pavia, Italy & Nu Horizon, Nu Instruments, Wrexham, UK). C and N were given in units g g-1 and stable isotopes were given as δ13C and δ15N for stable isotopes of C and N, respectively. Raw data C, N and stable isotope data were calibrated with certified standard and blank effects were corrected with the ilokeirms package (Teickner & Knorr, 2024). Using Fourier Transform Mid-Infrared Spectroscopy (FT-MIR) (Agilent Cary 670 FTIR spectromter, Agilent Technologies, Santa Clara, Ca, USA) humification indices (HI) were determined. Spectra were recorded from 600 cm-1 to 4000 cm-1 with a resolution of 2 cm-1 and baselines corrected with the ir package (Teickner, 2025) to estimate relative peack heights. The HI (no unit) for each sample was calculated by taking the ratio of intensities at 1630 cm-1 to the intensities at 1090 cm-1. Bulk densities (g cm-3) were estimated from FT-MIR data (Teickner et al., in preparation).
Recent and predicted increases in extremely dry and hot summers emphasise the need for silvicultural approaches to increase the drought tolerance of existing forests in the short-term, before adaptation through species changes may be possible. We aim to investigate whether resistance during droughts, as well as the recovery following drought events (resilience), can be increased by allocating more growing space to individual trees through thinning. Thinning increases access of promoted trees to soil stored water, as long as this is available. However, these trees may also be disadvantaged through a higher transpirational surface, or the increased neighbourhood competition by ground vegetation. To assess whether trees with different growing space differ in drought tolerance, tree discs and cores from thinning experiments of Pinus sylvestris and Pseudotsuga menziesii stands will be used to examine transpirational stress and growth reduction during previous droughts as well as their subsequent recovery. Dendroecology and stable isotopes of carbon and oxygen in tree-rings will be used to quantify how assimilation rate and stomatal conductance were altered through thinning. The results will provide crucial information for the development of short-term silvicultural adaptation strategies to adapt forest ecosystems to climate change. In addition, this study will improve our understanding of the relationship between resistance and resilience of trees in relation to extreme stress events.
Die Gemeinde Geeste liegt im Landkreis Emsland und umfasst die Ortsteile Bramhar, Dalum, Geeste, Groß Hesepe, Klein Hesepe, Osterbrock und Varloh.
We measured total alkalinity (TA) and dissolved inorganic carbon (DIC) in the Ems Estuary (Germany). The cruise took place on two consecutive days in June 2020 (11.06.-12.06.2020) on the German research vessel Ludwig Prandtl. We sampled approx. every 20min along the salinity gradient from the Wadden Sea around Borkum island upstream to Papenburg. Two additional samples were collected from shore at Rhede Brücke and weir Herbrum. We took discrete water samples for TA and DIC. Physical parameters (salinity, temperature) were measured in situ with the on board flow-through FerryBox system, for which water was pumped on board from 1.2m below the surface. These data and complementary data for nutrients and stable nitrate isotopes are accessible in: https://doi.org/10.1594/PANGAEA.942222
• Überwachung der Radioaktivität in der Umwelt nach dem Strahlenschutzvorsorgegesetz für den Freistaat Sachsen • Überwachung der anlagenbezogenen Radioaktivität nach dem Atomgesetz am Forschungsstandort Rossendorf • Überwachung von Lebensmitteln (u. a. Amtshilfe für die Landesuntersuchungsanstalt für das Gesundheits- und Veterinärwesen Sachsen) • Betrieb der Radonberatungsstelle • Überwachung der anlagenbezogenen Radioaktivität nach der Verordnung zur Gewährleistung von Atomsicherheit und Strahlenschutz an den Standorten der Wismut GmbH • Überwachung der anlagenbezogenen Radioaktivität an den Altstandorten des Uranerzbergbaus • Aufsichtliche Messungen nach der Strahlenschutzverordnung inkl. Sicherheitstechnisch bedeutsame Ereignisse und Nukleare Nachsorge • Der Geschäftsbereich ist akkreditiert nach ISO 17025 für alle relevanten Prüfverfahren im Bereich Immission und Emission. Fachbereich 20 - Zentrale Aufgaben • Probenentnahmen und Feldmessungen (ohne Messungen und Probenentnahmen im Rahmen der Radonberatung) u. a. Probenentnahmen aus Fließgewässern, Messung der nuklidspezifischen Gammaortsdosisleistung • Organisation und Logistik für die von externen Probenehmern gewonnenen und dem Geschäftsbereich 2 zu übergebenden Proben. Betrieb der Landesdatenzentrale und der Datenbank zur Umweltradioaktivität im Freistaat Sachsen • Unterstützung der beiden Landesmessstellen bei der Einführung und Pflege radiochemischer Verfahren Fachbereiche 21, 22 - Erste und Zweite Landesmessstelle für Umweltradioaktivität Laboranalysen • nach dem Strahlenschutzvorsorgegesetz • zur Überwachung der Wismut-Standorte • zur Überwachung des Forschungsstandort Rossendorf • zur Überwachung der Altstandorte des Uranbergbaus • zur Lebensmittelüberwachung • zu den aufsichtlichen Kontrolltätigkeiten des Sächsischen Landesamtes für Umwelt, Landwirtschaft und Geologie und des Sächsischen Staatsministeriums für Umwelt und Landwirtschaft u. a. in den Medien Wasser, Boden, Luft, Nahrungs- und Futtermittel. Analysierte Parameter: u. a. gamma- und alphastrahlende Radionuklide (z. B. Cäsium-137, Cobalt-60, Kalium-40, Uran-238); Strontium-90; Radium-226 und Radium-228). Fachbereich 23 - Immissionsmessungen Kontinuierliche Überwachung der Luftqualität durch Betrieb des stationären Luftmessnetzes des Freistaates (Online-Betrieb von 30 stationären Messstationen mit Übergabe der Messdaten ins Internet): • Laufende Messung der Luftgüteparameter SO2, NOx, Ozon, Benzol, Toluol, Xylole, Schwebstaub, Ruß • Gewinnung meteorologischer Daten zur Einschätzung der Luftgüteparameter • Sammlung von Schwebstaub (PM 10- und PM 2,5-Fraktionen) und Sedimentationsstaub zur analytischen Bestimmung von Schwermetallen, polyzyklischen Kohlenwasserstoffen (PAK) und Ruß • Absicherung der Messdatenverarbeitung und Kommunikation • Betreiben einer Messnetzzentrale, Plausibilitätskontrolle der Daten und deren Übergabe an das Landesamt für Umwelt, Landwirtschaft und Geologie und an die Öffentlichkeit • Absicherung und Überwachung der vorgegebenen Qualitätsstandards bei den Messungen durch den Betrieb eines Referenz- und Kalibrierlabors • Sicherung der Verfügbarkeit aller Messdaten zu > 95% • Weiterentwicklung des Luftmessnetzes entsprechend den gesetzlichen Anforderungen • Betreuung eines Depositionsmessnetzes (Niederschlag) mit zehn Messstellen • Betrieb von drei verkehrsnahen Sondermessstellen an hoch belasteten Straßen • Durchführung von Sondermessungen mit Immissionsmesswagen und mobilen Containern • Betrieb von Partikelmesssystemen im Submikronbereich (Zählung ultrafeiner Partikel) in Dresden • Betrieb von Verkehrszähleinrichtungen und Übernahmen dieser Verkehrszähldaten sowie von Pegelmessstellen der Städte in den Datenbestand des Luftmessnetzes Fachbereich 24 - Emissionsmessungen, Referenz- und Kalibrierlabor Der Fachbereich befasst sich mit der Durchführung von Emissionsmessungen an ausgewählten Anlagen aus besonderem Anlass im Auftrag des LfULG. Beispiele: • Emissionsmessungen an Blockheizkraftwerken in der Landwirtschaft (Geruch, Stickoxide, Gesamtkohlenstoff und Formaldehyd). • Ermittlung der Stickstoff-Deposition aus Tierhaltungsanlagen für Geflügel und Rinder (Emissionsmessungen von Ammoniak, Lachgas, Methan, Wasser, Kohlendioxid, Feuchte, Temperatur und Luftströmung , Ammoniak-Immissionsmessung mit DOAS-Trassenmesssystem). • Untersuchung von Emissionen aus holzgefeuerten Kleinfeuerungsanlagen zur Abschätzung von Auswirkungen der novellierten 1. BImSchV. • Unterstützung des LfULG bei der Überwachung bekannt gegebener Messstellen nach § 26 BImSchG.
Variations in the strength of arctic freshwater export via the East Greenland Current (EGC) can affect thermohaline circulation and the strength of the Subpolar Gyre and, therefore, can modulate the northward heat transport in the North Atlantic Ocean. To assess the role of the EGC in the mid to late Holocene North Atlantic climate variability, its palaeoceanographic history and spatial extent will be studied at three key sites; two sites in the EGC core (Foster Bugt and Nansen Trough) and one site in the Subpolar Front area (SPF; Reykjanes Ridge). For the first time, palaeoceanographic data sets, spanning the last 6000 years, for the EGC core will be produced at a multi-decadal to centennial time scale. A multi-proxy approach, combining foraminifera, diatom, dinoflagellate as well as stable isotope, trace element (Mg/Ca) and IP25 analyses on the same sample set will be performed in close collaboration with national and international project partners. The proposed reconstructions will be linked to marine and terrestrial high-resolution studies from the North Atlantic Drift, the West Greenland Current, the Fram Strait, the Baltic Sea and continental Europe, in order to investigate the timing (in-phase/out-of-phase) of mid to late Holocene climatic oscillations in the different regions. Reconstructing the role of the EGC at high resolution will increase our understanding of trigger mechanisms underlying natural mid to late Holocene climate variability in the North Atlantic region.
Water is an intrinsic component of ecosystems acting as a key agent of lateral transport for particulate and dissolved nutrients, forcing energy transfers, triggering erosion, and driving biodiversity patterns. Given the drastic impact of land use and climate change on any of these components and the vulnerability of Ecuadorian ecosystems with regard to this global change, indicators are required that not merely describe the structural condition of ecosystems, but rather capture the functional relations and processes. This project aims at investigating a set of such functional indicators from the fields of hydrology and biogeochemistry. In particular we will investigate (1) flow regime and timing, (2) nutrient cycling and flux rates, and (3) sediment fluxes as likely indicators. For assessing flow regime and timing we will concentrate on studying stable water isotopes to estimate mean transit time distributions that are likely to be impacted by changes in rainfall patterns and land use. Hysteresis loops of nitrate concentrations and calculated flux rates will be used as functional indicators for nutrient fluxes, most likely to be altered by changes in temperature as well as by land use and management. Finally, sediment fluxes will be measured to indicate surface runoff contribution to total discharge, mainly influenced by intensity of rainfall as well as land use. Monitoring of (1) will be based on intensive sampling campaigns of stable water isotopes in stream water and precipitation, while for (2) and (3) we plan to install automatic, high temporal-resolution field analytical instruments. Based on the data obtained by this intensive, bust cost effective monitoring, we will develop the functional indicators. This also provides a solid database for process-based model development. Models that are able to simulate these indicators are needed to enable projections into the future and to investigate the resilience of Ecuadorian landscape to global change. For the intended model set up we will couple the Catchment Modeling Framework, the biogeochemical LandscapeDNDC model and semi-empirical models for aquatic diversity. Global change scenarios will then be analyzed to capture the likely reaction of functional indicators. Finally, we will contribute to the written guidelines for developing a comprehensive monitoring program for biodiversity and ecosystem functions. Right from the beginning we will cooperate with four SENESCYT companion projects and three local non-university partners to ensure that the developed monitoring program will be appreciated by locals and stakeholders. Monitoring and modelling will focus on all three research areas in the Páramo (Cajas National Park), the dry forest (Reserva Laipuna) and the tropical montane cloud forest (Reserva Biologica San Francisco).
Hydrological science depends on reliable observations. At the same time, many hydrological datasets are distributed across numerous national and regional services, each with its own access routes, documentation, and terms of use. This fragmentation can make it difficult to clearly document where data come from and to reproduce data retrieval in a consistent way. To provide more transparent and reproducible access to hydrological observations, GRDC has developed hydrodownloadR . The R package offers a standardized way to discover hydrological stations and download daily time series such as discharge, water level, water temperature and selected water-quality parameters directly from public national and regional APIs. Transparency in data retrieval is crucial because hydrological assessments and scientific results must be explainable and verifiable across institutions. This is particularly relevant for the annually released WMO State of the Global Water Resources Report , for which GRDC provides data. The hydrodownloadR package supports data retrieval workflows for both routine GRDC data updates and the WMO report. However, the package can also benefit users who require stations that are not yet included in the GRDC database. In such cases, the package provides a straightforward way to access time series directly from the original provider while keeping the data source explicit. It is important that hydrodownloadR , where available, highlights licensing and terms of use information for each API. Furthermore it is designed to access services responsibly by avoiding excessive requests. Nevertheless, users remain responsible for complying with the providers’ terms of use and citation requirements. Coverage and available parameters depend on the underlying public APIs and their data policies. Call to action: If you know a public hydrology API or you operate one, please share with us the documentation link, licensing information, terms of use and, if possible, stable endpoints. Also, if you encounter errors or unexpected behavior, please report them via the project’s GitHub issue tracker so we can address them efficiently. This will help to further improve the package and optimize the discoverability and accessibility of hydrological data. Links: Documentation Source code and issue tracker
Der Datensatz Agricultural And Aquaculture Facilities / Tierhaltungs- und Aufzuchtanlagen in Brandenburg ist die Datengrundlage der interoperablen INSPIRE-Darstellungs- (WMS) und Downloaddienste (WFS): Tierhaltungsanlagen nach BImSchG in Brandenburg - Interoperabler INSPIRE View-Service (WMS-AF-TIERE) Tierhaltungsanlagen nach BImSchG in Brandenburg - Interoperabler INSPIRE Download-Service (WFS-AF-TIERE) Der Datenbestand beinhaltet die Punktdaten zu den betriebenen Tierhaltungsanlagen aus dem Anlageninformationssystem LIS-A. Die Angaben zu den Anlagen enthalten jeweils den Standort und die genehmigte Leistung. Dabei erfolgte eine sog. Schematransformation und Belegung der INSPIRE-relevanten Attribute. Der Datensatz Agricultural And Aquaculture Facilities / Tierhaltungs- und Aufzuchtanlagen in Brandenburg ist die Datengrundlage der interoperablen INSPIRE-Darstellungs- (WMS) und Downloaddienste (WFS): Tierhaltungsanlagen nach BImSchG in Brandenburg - Interoperabler INSPIRE View-Service (WMS-AF-TIERE) Tierhaltungsanlagen nach BImSchG in Brandenburg - Interoperabler INSPIRE Download-Service (WFS-AF-TIERE) Der Datenbestand beinhaltet die Punktdaten zu den betriebenen Tierhaltungsanlagen aus dem Anlageninformationssystem LIS-A. Die Angaben zu den Anlagen enthalten jeweils den Standort und die genehmigte Leistung. Dabei erfolgte eine sog. Schematransformation und Belegung der INSPIRE-relevanten Attribute. Der Datensatz Agricultural And Aquaculture Facilities / Tierhaltungs- und Aufzuchtanlagen in Brandenburg ist die Datengrundlage der interoperablen INSPIRE-Darstellungs- (WMS) und Downloaddienste (WFS): Tierhaltungsanlagen nach BImSchG in Brandenburg - Interoperabler INSPIRE View-Service (WMS-AF-TIERE) Tierhaltungsanlagen nach BImSchG in Brandenburg - Interoperabler INSPIRE Download-Service (WFS-AF-TIERE) Der Datenbestand beinhaltet die Punktdaten zu den betriebenen Tierhaltungsanlagen aus dem Anlageninformationssystem LIS-A. Die Angaben zu den Anlagen enthalten jeweils den Standort und die genehmigte Leistung. Dabei erfolgte eine sog. Schematransformation und Belegung der INSPIRE-relevanten Attribute.
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