Räumlichen Abgrenzung von Landschaftsschutzgebieten (LSG) im Landkreis Lüchow- Danneberg gemäß zugrunde liegender Verordnung.
Estuaries and coasts are characterized by ecological dynamics that bridge the boundary between habitats, such as fresh and marine water bodies or the open sea and the land. Because of this, these ecosystems harbor ecosystem functions that shaped human history. At the same time, they display distinct dynamics on large and small temporal and spatial scales, impeding their study. Within the framework of the OTC-Genomics project, we compiled a data set describing the community composition as well as abiotic state of an estuary and the coastal region close to it with unprecedented spatio-temporal resolution. We sampled fifteen locations in a weekly to twice weekly rhythm for a year across the Warnow river estuary and the Baltic Sea coast. From those samples, we measured temperature, salinity, and the concentrations of Chlorophyll a, phosphate, nitrate, and nitrite.
Working Area was the central Baltic Sea from Farö Deep to the Southern Gotland Basin encirceled by the south bound latitude 54.188, west bound longitude of 12.081, north bound latitude of 58.001 and in the east bound by longitude 20.652. The distribution and cycling of manganese (Mn) species across the redox boundary in the central Baltic Sea was studied by a team of researchers from the IOW and WHOI with the aim to interrogate possible links between Mn and the nitrogen (N), oxygen (O), and iodine (I) cycles, taking into account the role of Mn(III)-ligand complexes and reactive Mn oxide particles. The role of reactive Mn species in controlling the redox state of stratified waters, using novel in situ instrumentation, high resolution water sampling, and targeted solid-phase characterization was done by normal CTD and pump CTD casts. Profiles of reactive oxygen species (ROS), showed slight variation throughout the day tentatively suggesting other sources than light as a reason. Seven pump CTD casts (EMB_2 to EMB_8) were the first measured in the Baltic Sea. About the Data: The upper pycnocline coincided with a temperature drop of approx. 10 °C from near 15 °C to around 5 °C. The temperature was stable until the second pycnocline from where it rose to approx. 7 °C and stayed stable to close to the seafloor Oxygen profiles resemble each other even though the concentrations are different below the first pycnocline. At stations go27, TF271, go23 and TF260 the concentration decreased to either the detection limit (stations TF271 and go23) or around 20 μmol L- 1 (stations go and TF260). Below the pycnocline several oxygen peaks occurred with concentrations up to 40 μmol L- 1 and an oxygen saturation reaching 10 % at stations. From a depth of 113 m- Oxygen was no longer detectable at any of the stations. Nutrient data from the upper layer are lacking because they were not interesting for redox processes. Ammonium only increased below 100m depth, nitrate was extremely variable between 50m and 140m experiencing maxima of 6µmol L-1. Finally nitrite had up to 0.4 µmol L-1 around 50m depth and many tiny peaks throughout the redoxzone. The detailed structure visible in the data is unique and will generate a much better understanding of microbial processes and trace metal concentrations.
The EMB217 cruise was dedicated to the DFG-Funded project ROBOTRACE (The role of bottom boundary layer turbulence for the exchange of tracer) and was the third in the project. The purpose was to sample the ROBOTRACE stations during a calm summer season. This allows to understand the seasonality of the oxygen transport in the central Baltic Sea. The sampled stations and main transect were on the eastern part of the Gotland Basin (TS1, Fig. 3.1). For the background condition during the cruise, two moorings chains, including ADCP, T, S and oxygen sensors, were deployed along the transect. Short term deployments of oxygen microprofilers, oxygen eddy-covariance and chamber landers were performed along the transect. The transect was sampled several times with a shear microstructure probe (MSS-90L) including a fast response oxygen optode and accompanied by nutrient samples taken with watersamplers mounted on a standard CTD rosette. Besides these main tasks, maintenance of the IOW longterm mooring NE and GODESS were performed and a lagrangian drifter (Jetsam, Univ. Florida) was tested for its use in the Baltic Sea.
The main aim of the BaltVib sampling campaign was to analyse the microbial community composition in pelagic and benthic habitats with special focus on Vibrio spp. bacteria inside and outside of eelgrass meadows (Zostera marina), and selected macroalgae populations (Fucus spp.) in the salinity gradient of shallow coastal waters of the Baltic Sea. The temporal extent of the dataset is 25.07.2021 to 02.09.2021. The geographic extent of the dataset is spanning from 9°52,655 E to 25°00,698 W and 60°06,547 N to 54°00,8666 S. The measurement depth ranges from 0.2 meters to 7 meters. Salinity ranges from 4 to 14. Environmental parameters measured are: conductivity, temperature, pH, Secchi depth, chlorophyll a, dissolved oxygen, ammonium, nitrate, nitrite, phosphate, silicate, grain size, dissolved organic carbon, dissolved nitrogen, particulate organic nitrogen, particulate organic carbon. Vibrio spp. colony forming units were counted using TCBS agar plates. Abundance of Vibrio vulnificus was determined by ddPCR in water and sediment samples as well as in Zostera marina surface biofilm. Cell counts by flow cytometry contain: Synechococcus, Picoeukaryota, Nanoeukaryota, high-nucleic acid bacteria, low-nucleic acid bacteria. Macrophyte abundance was measured for Zostera marina and Fucus spp..
Kleinmaßstäbige Bodenübersichtskarten werden in der Regel aus groß- oder mittelmaßstäbigen Bodenkarten durch räumliche Generalisierung und inhaltliche Aggregierung abgeleitet. Um dabei auch überregional ein vergleichbares Vorgehen zu sichern, ist eine einheitliche pedoregionale Gliederung erforderlich. Der vorliegende Datensatz auf dem Aggregierungsniveau der Bodengroßlandschaften umfasst die 36 wichtigsten bodenkundlich relevanten lithogenetischen Einheiten in Deutschland und basiert im Wesentlichen auf der von Bund und Ländern gemeinsam herausgegebenen Bodenübersichtskarte 1:200.000 (BÜK200) und deren Bodengroßlandschaftsgliederung. Zusätzlich enthaltenen sind die Böden größerer Siedlungs-, Industrie- und Gewerbegebiete (als BGL 13.1) und die Böden der Bergbaufolgelandschaften (als BGL 13.2). Nähere Informationen zu den Bodenregionen und Bodengroßlandschaften der Bundesrepublik Deutschland sind der Bodenkundlichen Kartieranleitung (KA5), Kapitel 6.5 ab Seite 335 zu entnehmen. Die digitale Kartengrafik basiert auf den topographischen Grundlagen des Digitalen Landschaftsmodells 1:250.000 (DLM250) aus dem Jahr 2014 des Bundesamtes für Kartographie und Geodäsie (BKG).
Distribution of community bioturbation potential BPc (log-transformed values) resulting from random forest modeling using BPc as response variable. Bioturbation potential BPc is a metric to quantitatively estimate bioturbation intensity from benthic quantitative data suggested by Solan et al. (2004). Macrozoobenthic data from 1191 sampling stations located in the German part of the Baltic Sea were analyzed (data sources: Leibniz Institute for Baltic Sea Research). Samples have been collected from 1999 to 2015. Sample data were averaged per stations and standardized to the area of 1 m². For modeling R package “Random Forest” (RF, Version 4.6–7, Liaw and Wiener, 2002), based on random forests statistical analysis (Breiman, 2001) is used. Predictors and modeling algorithm as described in Gogina, M., Morys, C., Forster, S., Gräwe, U., Friedland, R., Zettler, M.L. 2017. Towards benthic ecosystem functioning maps: Quantifying bioturbation potential in the German part of the Baltic Sea. Ecological Indicators 73: 574-588. doi.org/10.1016/j.ecolind.2016.10.025Solan, M., Cardinale, B.J., Downing, A.L., Engelhardt, K.A.M., Ruesink, J.L., Srivastava,D.S., 2004. Extinction and ecosystem function in the marine benthos. Science306, 1177–1180.Liaw, A., Wiener, M., 2002. Classification and regression by randomForest. R. News2, 18–22.Breiman, L., 2001. Random forests. Mach. Learn. 45, 5–32.
A marine physical biogeochemical model simulation was performed with the model MOM-ERGOM for the years 1985 to 2014 covering the Baltic Sea. Previously, MOM-ERGOM had been initialized for several decades. The model output has been validated with measurement data of the "IOW Baltic Monitoring and long-term data program" (https://www.io-warnemuende.de/iowdb.html) and from the HELCOM database (http://ocean.ices.dk/helcom/Helcom.aspx). The years 1995 to 2014 are available here. The model simulation was forced by coastDat2 COSMO-CLM data (doi: 10.1594/WDCC/coastDat-2_COSMO-CLM). Riverine phosphorus input of the Warnow River was calculated with the Soil & Water Assessment Tool (SWAT; Bauwe et al., 2019, doi: 10.1016/j.ecohyd.2019.03.003). Phosphorus from the Warnow River has been tagged in the model simulation according to a method by Menésguen et al. (2006, 10.4319/lo.2006.51.1_part_2.0591). Therefore, all phosphorus-containing model variables exist twice in the output: once as regular variables and once as tagged variable. The default phosphorus input by the Warnow River based on real phosphorus release patterns and real atmospheric conditions was used (PhosWaM SWAT case "ist"). The turnover of phosphorus compounds in the Unterwarnow was calculated based on the “Unterwarnow turnover estimation v04” (see final project report of PhosWaM for details).The work was performed within the project PhosWaM funded by the German Federal Ministry of Education and Research (BMBF, FKZ 033W042, https://www.phoswam.de). PhosWaM is one of 15 joint research projects in the funding measured ReWaM of the funding priority NaWaM in BMBF framework program FONA (details in the project description). The simulation was performed at the North-German Supercomputing Alliance (HLRN). The model output data were processed and evaluated on servers provided by the project 'PROSO - Prozesse von Spurenstoffen in der Ostsee' (FKZ 03F0779A).
A marine physical biogeochemical model simulation was performed with the model MOM-ERGOM for the years 1985 to 2014 covering the Baltic Sea. Previously, MOM-ERGOM had been initialized for several decades. The model output has been validated with measurement data of the "IOW Baltic Monitoring and long-term data program" (https://www.io-warnemuende.de/iowdb.html) and from the HELCOM database (http://ocean.ices.dk/helcom/Helcom.aspx). The years 1995 to 2014 are available here. The model simulation was forced by coastDat2 COSMO-CLM data (doi: 10.1594/WDCC/coastDat-2_COSMO-CLM). Riverine phosphorus input of the Warnow River was calculated with the Soil & Water Assessment Tool (SWAT; Bauwe et al., 2019, doi: 10.1016/j.ecohyd.2019.03.003). Phosphorus from the Warnow River has been tagged in the model simulation according to a method by Menésguen et al. (2006, 10.4319/lo.2006.51.1_part_2.0591). Therefore, all phosphorus-containing model variables exist twice in the output: once as regular variables and once as tagged variable. The default phosphorus input by the Warnow River based on real phosphorus release patterns and real atmospheric conditions was used (PhosWaM SWAT case "ist"). The turnover of phosphorus compounds in the Unterwarnow was calculated based on the “Unterwarnow turnover estimation v04” (see final project report of PhosWaM for details).The work was performed within the project PhosWaM funded by the German Federal Ministry of Education and Research (BMBF, FKZ 033W042, https://www.phoswam.de). PhosWaM is one of 15 joint research projects in the funding measured ReWaM of the funding priority NaWaM in BMBF framework program FONA (details in the project description). The simulation was performed at the North-German Supercomputing Alliance (HLRN). The model output data were processed and evaluated on servers provided by the project 'PROSO - Prozesse von Spurenstoffen in der Ostsee' (FKZ 03F0779A).
A marine physical biogeochemical model simulation was performed with the model MOM-ERGOM for the years 1985 to 2014 covering the Baltic Sea. Previously, MOM-ERGOM had been initialized for several decades. The model output has been validated with measurement data of the "IOW Baltic Monitoring and long-term data program" (https://www.io-warnemuende.de/iowdb.html) and from the HELCOM database (http://ocean.ices.dk/helcom/Helcom.aspx). The years 1995 to 2014 are available here. The model simulation was forced by coastDat2 COSMO-CLM data (doi: 10.1594/WDCC/coastDat-2_COSMO-CLM). Riverine phosphorus input of the Warnow River was calculated with the Soil & Water Assessment Tool (SWAT; Bauwe et al., 2019, doi: 10.1016/j.ecohyd.2019.03.003). Phosphorus from the Warnow River has been tagged in the model simulation according to a method by Menésguen et al. (2006, 10.4319/lo.2006.51.1_part_2.0591). Therefore, all phosphorus-containing model variables exist twice in the output: once as regular variables and once as tagged variable. The phosphorus input by the Warnow River based on real phosphorus release patterns and real atmospheric conditions was modified in order to comply with BASP (Baltic Sea Action Plan) targets (PhosWaM SWAT case "15"). The turnover of phosphorus compounds in the Unterwarnow was calculated based on the "Unterwarnow turnover estimation v04" (see final project report of PhosWaM for details).The work was performed within the project PhosWaM funded by the German Federal Ministry of Education and Research (BMBF, FKZ 033W042, https://www.phoswam.de). PhosWaM is one of 15 joint research projects in the funding measured ReWaM of the funding priority NaWaM in BMBF framework program FONA (details in the project description). The simulation was performed at the North-German Supercomputing Alliance (HLRN). The model output data were processed and evaluated on servers provided by the project 'PROSO - Prozesse von Spurenstoffen in der Ostsee' (FKZ 03F0779A).
| Origin | Count |
|---|---|
| Bund | 1 |
| Land | 2 |
| Wissenschaft | 50 |
| Type | Count |
|---|---|
| unbekannt | 52 |
| License | Count |
|---|---|
| geschlossen | 1 |
| offen | 2 |
| unbekannt | 49 |
| Language | Count |
|---|---|
| Deutsch | 6 |
| Englisch | 46 |
| Resource type | Count |
|---|---|
| Archiv | 20 |
| Datei | 1 |
| Dokument | 4 |
| Keine | 1 |
| Webseite | 49 |
| Topic | Count |
|---|---|
| Boden | 25 |
| Lebewesen & Lebensräume | 24 |
| Luft | 3 |
| Mensch & Umwelt | 51 |
| Wasser | 51 |
| Weitere | 52 |