This dataset comprises hydrochemical and soil data collected along the first 1.3 km downstream of the White Main spring in northern Bavaria, Germany, from March 2023 to April 2024. Stream water samples were analyzed for in-situ parameters (discharge, water temperature [°C], pH [-], redox potential [mV], electrical conductivity [µS/cm], Table Y1), and laboratory-measured parameters, including major ions and trace metals [mmol/L] (Table Y3), alkalinity [mmol/L], , dissolved inorganic and organic carbon (DIC, DOC [mmol/L]) and their stable isotope ratios (δ13CDIC/DOC ‰-VPDB). In addition, calculated partial pressure of CO2 (pCO2, [µatm]) and carbon dioxide fluxes (FCO2, [mmol/m2 d]), are provided for the stream water samples (Table Y2). The dataset also contains laboratory measurements related to soil-derived natural organic matter from acid and base soil extracts, including zeta potential ([mV], Table X1), particle size distribution ([%], Table X2), ultraviolet-visible absorbance (UV-VIS, Table X3), and fluorescence measurements (Table X4). UV-VIS (Table X5) and fluorescence measurements (Table X6) were additionally done for stream water samples. The datasets were collected to characterize hydrochemistry, carbon concentrations, carbon dioxide dynamics, and soil-derived organic matter properties in a granitic headwater stream and to provide a basis for reuse in studies of headwater biogeochemistry, carbon cycling, and soil-water interactions.
This dataset comprises hydrochemical and soil data collected along the first 1.3 km downstream of the White Main spring in northern Bavaria, Germany, from March 2023 to April 2024. Stream water samples were analyzed for in-situ parameters (discharge, water temperature [°C], pH [-], redox potential [mV], electrical conductivity [µS/cm], Table Y1), and laboratory-measured parameters, including major ions and trace metals [mmol/L] (Table Y3), alkalinity [mmol/L], , dissolved inorganic and organic carbon (DIC, DOC [mmol/L]) and their stable isotope ratios (δ13CDIC/DOC ‰-VPDB). In addition, calculated partial pressure of CO2 (pCO2, [µatm]) and carbon dioxide fluxes (FCO2, [mmol/m2 d]), are provided for the stream water samples (Table Y2). The dataset also contains laboratory measurements related to soil-derived natural organic matter from acid and base soil extracts, including zeta potential ([mV], Table X1), particle size distribution ([%], Table X2), ultraviolet-visible absorbance (UV-VIS, Table X3), and fluorescence measurements (Table X4). UV-VIS (Table X5) and fluorescence measurements (Table X6) were additionally done for stream water samples. The datasets were collected to characterize hydrochemistry, carbon concentrations, carbon dioxide dynamics, and soil-derived organic matter properties in a granitic headwater stream and to provide a basis for reuse in studies of headwater biogeochemistry, carbon cycling, and soil-water interactions.
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 comprises hydrochemical and soil data collected along the first 1.3 km downstream of the White Main spring in northern Bavaria, Germany, from March 2023 to April 2024. Stream water samples were analyzed for in-situ parameters (discharge, water temperature [°C], pH [-], redox potential [mV], electrical conductivity [µS/cm], Table Y1), and laboratory-measured parameters, including major ions and trace metals [mmol/L] (Table Y3), alkalinity [mmol/L], , dissolved inorganic and organic carbon (DIC, DOC [mmol/L]) and their stable isotope ratios (δ13CDIC/DOC ‰-VPDB). In addition, calculated partial pressure of CO2 (pCO2, [µatm]) and carbon dioxide fluxes (FCO2, [mmol/m2 d]), are provided for the stream water samples (Table Y2). The dataset also contains laboratory measurements related to soil-derived natural organic matter from acid and base soil extracts, including zeta potential ([mV], Table X1), particle size distribution ([%], Table X2), ultraviolet-visible absorbance (UV-VIS, Table X3), and fluorescence measurements (Table X4). UV-VIS (Table X5) and fluorescence measurements (Table X6) were additionally done for stream water samples. The datasets were collected to characterize hydrochemistry, carbon concentrations, carbon dioxide dynamics, and soil-derived organic matter properties in a granitic headwater stream and to provide a basis for reuse in studies of headwater biogeochemistry, carbon cycling, and soil-water interactions.
This dataset comprises hydrochemical and soil data collected along the first 1.3 km downstream of the White Main spring in northern Bavaria, Germany, from March 2023 to April 2024. Stream water samples were analyzed for in-situ parameters (discharge, water temperature [°C], pH [-], redox potential [mV], electrical conductivity [µS/cm], Table Y1), and laboratory-measured parameters, including major ions and trace metals [mmol/L] (Table Y3), alkalinity [mmol/L], , dissolved inorganic and organic carbon (DIC, DOC [mmol/L]) and their stable isotope ratios (δ13CDIC/DOC ‰-VPDB). In addition, calculated partial pressure of CO2 (pCO2, [µatm]) and carbon dioxide fluxes (FCO2, [mmol/m2 d]), are provided for the stream water samples (Table Y2). The dataset also contains laboratory measurements related to soil-derived natural organic matter from acid and base soil extracts, including zeta potential ([mV], Table X1), particle size distribution ([%], Table X2), ultraviolet-visible absorbance (UV-VIS, Table X3), and fluorescence measurements (Table X4). UV-VIS (Table X5) and fluorescence measurements (Table X6) were additionally done for stream water samples. The datasets were collected to characterize hydrochemistry, carbon concentrations, carbon dioxide dynamics, and soil-derived organic matter properties in a granitic headwater stream and to provide a basis for reuse in studies of headwater biogeochemistry, carbon cycling, and soil-water interactions.
# Faszination Nächtlicher Vogelzug A web component for visualizing migratory bird detections on an interactive map. Built with React, MapLibre GL, and the BirdWeather GraphQL API. Designed for embedding into CMS platforms like Contao. ## Tech Stack - **React 19** + **TypeScript** (Vite) - **MapLibre GL** -- WebGL map rendering (Stadia Maps dark theme) - **Supercluster** -- per-species spatial clustering - **Apollo Client 4** -- GraphQL data fetching with caching - **GraphQL Code Generation** -- type-safe queries from BirdWeather schema - **SunCalc** -- astronomical day/night calculations - **Tailwind CSS 4** + **Ant Design 6** -- UI - **Vitest** -- testing ## Features - **Interactive map** with color-coded detection clusters per species - **Timeline animation** with autoplay, step controls, and throttled slider - **Night-only mode** that compresses inactive daytime hours using SunCalc sunrise/sunset calculations - **Day/night overlay** showing the terminator (day/night boundary) as a real-time GeoJSON polygon - **Species search** with autocomplete and availability checking per map viewport - **Supplementary layers** (light pollution, noise mapping via WMS) - **Web component** (`<zug-birdnet>`) for CMS embedding without routing ## Project Structure ``` src/ main.tsx Web component registration App.tsx Root component, species selection state api/ fragments.ts GraphQL fragments (DetectionItem, SpeciesItem) queries.ts GraphQL queries (detections, species, search) useDetections.ts Detection fetch hook with prefetching components/ DatesProvider.tsx Time state context (date range, animation, night mode) MapProvider.tsx MapLibre GL instance context SpeciesDropdown.tsx Species selection with search autocomplete Timeline.tsx Date picker, animation slider, playback controls LayersDropdown.tsx Toggle info layers (light pollution, noise) InfoPopup.tsx Map info marker popups map/ Map.tsx MapLibre GL initialization and rendering clusterUtils.ts Per-species Supercluster index creation colorUtils.ts MapLibre paint expression builder mapStyles.ts Map layer definitions usePersistentColors.ts Stable color assignment per species infopoints.ts Static info marker data lib/ apollo-client.ts Apollo Client with cache type policies buildAvailableSpeciesQuery.ts Dynamic aliased query generation getDayPolygon.ts Day/night terminator polygon calculation getTranslatedSpeciesName.ts i18n species name lookup isNotNull.ts, hasNonNullProp.ts Type guard utilities throttle.ts Throttle utility gql/ Auto-generated GraphQL types (do not edit) ``` ## Architecture Three React context providers compose the application: ``` ApolloProvider GraphQL caching and data fetching DatesProvider Date range, animation state, night-only time segments MapProvider MapLibre GL map instance App Species selection, filtered detections, color mapping ``` **Data flow:** Apollo fetches detections for the current bounding box and date range. Detections are filtered client-side by the visualisation time window (controlled by the timeline slider). Each species gets its own Supercluster index for independent color-coded clustering. Cluster features are rendered via MapLibre GL layers with dynamic `match` paint expressions. **GraphQL:** Queries and fragments are defined in `src/api/` and typed via `@graphql-codegen/client-preset`. Run `npm run codegen` after schema changes to regenerate `src/gql/`. ## Development ```sh npm install npm run dev ``` The dev server uses a self-signed SSL certificate via `@vitejs/plugin-basic-ssl`. Accept the browser warning on first visit. Other commands: ```sh npm run build # Production build npm run test # Run tests npm run lint # ESLint npm run codegen # Regenerate GraphQL types ``` ## Build & Integration Run `npm run build` to produce the `dist/` folder. The build outputs stable filenames (no hashes) and splits vendor dependencies into separate chunks for caching: ``` dist/ index.html assets/ index.css App styles (Tailwind + Ant Design) index.js Application code, React, Supercluster, dayjs, SunCalc maplibre.js MapLibre GL antd.js Ant Design + icons apollo.js Apollo Client + graphql ``` Only `index.js` changes on application updates. Vendor chunks are cache-stable between deploys. To embed the web component, include the built CSS and JS, then use the custom element: ```html <link rel="stylesheet" href="/assets/index.css"> <script type="module" src="/assets/index.js"></script> <zug-birdnet></zug-birdnet> ``` No routing. The component is self-contained and can be placed anywhere on the page. Third-party CMS integration (e.g., Contao) only needs to include the built assets and the custom element tag. ## Configuration App-level settings are in `src/config.ts`: | Option | Default | Description | |---|---|---| | `SHOW_DEMO_INFOPOINTS` | `false` | Show static info markers on the map (demo/development only) |
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
Enhanced mineral dissolution in the benthic environment is currently discussed as a potential technique for ocean alkalinity enhancement (OAE) to reduce atmospheric carbon dioxide (CO2) levels. This study explores how biogeochemical processes affect the dissolution of alkaline minerals in surface sediments during laboratory incubation experiments. These involved introducing dunite and calcite to organic-rich sediments from the Baltic Sea under controlled conditions in an anoxic to hypoxic environment. The sediment cores were incubated with Baltic Sea bottom water. Eight sediment cores were positioned vertically in a rack. Since the sediment surface was slightly oxidized by the bottom water (∼125 μmol l−1 upon recovery), the cores were left plugged on the top for 13 days to settle after recovery until the sediment surface was anoxic. To achieve chemical conditions that are expected in the natural system, 500l of retrieved sea water were degassed via bubbling with pure dinitrogen gas in batches of 100 l. Afterwards, between 50 and 60 l were transferred into an evacuated gas tight bag. After the transfer, pH and total alkalinity (TA) were measured to determine the dissolved inorganic carbon (DIC) of the water. Afterwards the DIC was increased via adding pure CO2 until a CO2 partial pressure (pCO2 ) of ∼2,300–∼3,300 μatm was established mimicking conditions prevailing in Boknis Eck during summer. Stirring heads were installed on the cores. To prevent the development of oxic conditions, it was ensured that as little gas phase as possible was left in the cores. Elimination of pelagic autotrophs, heterotrophs, and suspended particles was achieved by flushing the cores with modified bottom water for 2 days with a flow rate of 1.5 mml min−1. Afterwards, a continuous throughflow of 700 μl min−1 from the reservoir of modified bottom water was applied, leading to a residence time of ∼2.1 days inside the cores. For the experimental incubations, six cores received additions of alkaline materials, three with calcite (Cal1 - Cal3) and three cores with dunite (Dun1 - Dun3), leading to three replicates per treatment. Two control cores remained untreated (C1, C2). The amount of added substrate was based on the rain rate of particulate organic carbon observed in Boknis Eck (0.5 mmol cm−2 a−). The incubation lasted for 25 days. The volume of water in each core was determined at the end of the experiment via measuring the height of the water column after removing the stirring heads. At the end of the experiments, the bottom water was removed via suction and the cores were sliced for pore water analysis. The pore waters were recovered by centrifuging each respective sediment layer in 50 ml falcon tubes at 3000 rpm for 10 minutes. Afterwards, the supernatant water was transferred to polyethylene (PE) vials in an Ar-filled glove bag to minimize contact with oxygen. All samples were filtered through a 0.2 µm cellulose membrane filter and refrigerated in 25 ml ZinsserTM scintillation vials. TA samples (1 ml) were titrated with 0.02N HCl. For H2S, an aliquot of pore water was diluted. A 5 ml aliquot was frozen directly after the sampling procedure for later nutrient analysis. Nutrient measurements were performed either via manual photometric measurement (NH4) or using a Seal – AnalyticalTM QuAAtro autoanalyzer (PO43-). Samples for TA were analyzed directly after sampling by titration of 1 ml of bottom/pore water with 0.02N HCl. Titration was ended when a stable purple color appeared. During titration, the sample was degassed by continuous bubbling with nitrogen to remove any generated CO2 and H2S. The acid was standardized using an IAPSO seawater standard. Acidified sub-samples (30 μl suprapure HNO3- + 3 ml sample) were prepared for analyses of major and trace elements (Si, Na, K, Li, B, Mg, Ca, Sr, Mn, Ni and Fe) by inductively coupled plasma optical emission spectroscopy (ICP-OES, Varian 720-ES). For H2S, an aliquot of pore water was diluted with appropriate amounts of oxygen-free artificial seawater and the H2S was fixed by immediate addition of zinc acetate gelatin solution
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.
The study investigates the chemical and physical characteristics of porewater and soil samples from peatlands across 64 sites in Germany, Poland, Estonia, Scotland, Sweden, and Georgia sampled between 1997 and 2017. The sites covers oceanic (Cfb, Cfc) and continental (Dfb, Dfc) climate zones and include both minerotrophic fens and ombrotrophic bogs. Fens were further classified into poor and rich types based on acidity and floristic composition, with rich fens characterized by higher pH and calcium concentrations due to mineral-rich groundwater inputs. The study also distinguishes between natural sites with stable near-surface water tables and rewetted sites previously subjected to drainage and agricultural use.
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