Wood samples from Douglas fir trees were taken using an increment borer. From each tree two opposing increment cores were taken at breast height. The sampled trees stood in an area of ~50x50 meters. Total ring width was measured and digitized. The resulting two radii measurements of each tree were visually synchronized and averaged to form a tree-ring series. Additionally, metadata were collected such as tree height, circumference and provenance (coastal, interior). The tree-ring data were used to investigate the resilience, resistance and recovery of the Douglas fir trees to severe drought events and to perform climate sensitivity analysis. This tree-ring dataset was part of a sampling campaign to assess the growth potential of Douglas fir trees until the year 2100. Annual tree growth variability until 2100 was modeled for Germany (including the river basins draining to Germany) with a spatial resolution of 12x12 km using regional climate projections ensemble.
Die Amtliche Basiskarte 1:5 000 (ABK5) ist eine Übersichtskarte, die eine Verbindung zwischen der großmaßstäbigen Liegenschaftskarte und der Topographischen Karte 1:25000 (TK25) herstellt. Wesentliche Inhalte: Gebäude, Gebäudenutzung, Straßen, Wege, Bodennutzung, Böschungen und Beschriftungen. Sie wird aus dem Amtlichen Liegenschaftskataster-Informationssystem (ALKIS®) abgeleitet. ALKIS® beinhaltet ein bundeseinheitliches, objektbasiertes Datenmodell indem die raumbezogenen (Karten-) und nicht raumbezogenen (Buch-) Daten systematisch verbunden und redundanzfrei gepflegt werden. Die Datenhaltung erfolgt mit Metadaten und Historienführung. Ausgabe: farbig, grau
This data set contains current and critical metal concentrations and its exceedances in topsoils, as well as data related to the current and critical metal inputs to and outputs from soils (uptake, accumulation and leaching) and the resulting exceedances of critical metal inputs. This data set has been compiled by the European Topic Centre on Urban, Land and Soil Systems (ETC/ULS) in the context of a study on metal and nutrient dynamics where the fate and dynamics of the most abundant heavy metals and nutrients in agricultural soils were investigated. The purpose of this study was to investigate the impacts of agricultural intensification in Europe, and to understand its environmental impact. Metal concentrations in soils were used from two consecutive Europe-wide geochemical surveys, sampled in 1998 (FOREGS survey) and 2009 (GEMAS survey). For land use, the 2010 Eurostat data were used. The metals included in this data set are cadmium (Cd), copper (Cu), lead (Pb) and zinc (Zn). The results on the fate of Nitrogen (N) and Phosphorus (P) are included in a separate dataset. Cu and Zn are minor nutrients but at high inputs, they may cause adverse impacts on soil biodiversity, whereas Cd and Pb are toxic metals that may lead to soil degradation, by both affecting soil biodiversity and food quality. Metal budgets based on spatially explicit input and output data were calculated using the INTEGRATOR model; approximately 40,000 so-called NCUs as unique combinations of soil type, administrative region, slope class and altitude class were used. Available critical limits for food, water and soil organisms, from different existing regulations and studies, were converted to soil property-dependent critical metal concentrations (soil-based quality standards), which were then used to calculate critical metal inputs. The results allow for the first time to identifying spatial hot spots for critical environmental impact of soil pollution for the four most abundant heavy metals. It thus informs policy processes important for planning and guiding sustainable agriculture and soil management. The work is methodologically novel, as it applies endpoint risk to thresholds in soils, and thus guides future impact studies. Updates with more recent land use and soil data are now possible. The description of the included model results and the reference report is provided under "lineage". The data set is provided as SHP and also in a GDB, the latter including as well the N and P concentrations. An Excel file "Metadata heavy metals nutrients.xlsx" with the attribute metadata is provided with the data set.
Die Elementkarte stellt die räumliche Verteilung der klassifizierten Gehalte des 50. Perzentils von Niob (in mg/kg) innerhalb der 184 geochemischen Gesteinseinheiten in Bayern dar. In die Auswertung gehen dabei nur die Daten der ersten (von maximal drei) Lithologien einer geochemischen Gesteinseinheit ein. Für Informationen im Hinblick auf die Auswertung der Daten sowie auf die kartenmäßige Darstellung wird auf die Metadaten der digitalen Lithogeochemischen Karte 1:25 000 von Bayern (dLGK25) verwiesen.
Die Elementkarte stellt die räumliche Verteilung der klassifizierten Gehalte des 90. Perzentils von Niob (in mg/kg) innerhalb der 184 geochemischen Gesteinseinheiten in Bayern dar. In die Auswertung gehen dabei nur die Daten der ersten (von maximal drei) Lithologien einer geochemischen Gesteinseinheit ein. Für Informationen im Hinblick auf die Auswertung der Daten sowie auf die kartenmäßige Darstellung wird auf die Metadaten der digitalen Lithogeochemischen Karte 1:25 000 von Bayern (dLGK25) verwiesen.
Die WebGIS-Anwendung "Naturschutzfachdaten" stellt Informationen zu verschiedenen Naturschutzfachthemen bereit. Datenbasis sind die in den Bestandteilen des Fachinformationssystem Naturschutz zusammengeführten und geprüften Datenbestände. Die Anwendung enthält Geoinformationen zu den Schutzgebieten nach Naturschutzrecht des Landes Brandenburg, den Schutzgebieten NATURA 2000 nach EU-Recht, zu Biotopen, geschützten Biotopen (nach §30 BNatSchG, §18 BbgNatSchAG), Lebensräumen nach der europäischen FFH-Richtlinie, Bewirtschaftungserlassen für die FFH-Gebiete, Daten der Naturräumlichen Gliederung sowie Artendaten. Zu den FFH- und SPA-Gebieten können die Standarddatenbögen aufgerufen werden. Bitte beachten Sie, dass die Schutzgebiete nur bis zu einem Maßstab von 1:9.000 angezeigt werden. Die Daten selbst wurden im Maßstab 1:10.000 erfasst. So sollen Fehlinterpretationen z.B. im Zusammenhang mit den Orthofotos ausgeschlossen werden, da die Daten selbst eine höhere Genauigkeit nicht liefern können. Mit dem Aufruf der Anwendung Naturschutzfachdaten erkennen Sie die Nutzungsbedingungen an. Der Kartendienst ist kostenfrei. Es wird ausdrücklich darauf hingewiesen, dass die zugrunde liegenden Daten lediglich der Übersicht dienen und keine Rechtsverbindlichkeit besitzen. Bitte beachten Sie die Hinweise in den Metadaten der gekoppelten Daten.
GISCO (Geographic Information System of the COmmission) is responsible for meeting the European Commission's geographical information needs at three levels: the European Union, its member countries, and its regions. In addition to creating statistical and other thematic maps, GISCO manages a database of geographical information, and provides related services to the Commission. Its database contains core geographical data covering the whole of Europe, such as administrative boundaries, and thematic geospatial information, such as population grid data. Some data are available for download by the general public and may be used for non-commercial purposes. For further details and information about any forthcoming new or updated datasets, see http://ec.europa.eu/eurostat/web/gisco/geodata. This metadata refers to the whole content of GISCO reference database extracted in May 2021, which contains both public datasets (also available for the general public through http://ec.europa.eu/eurostat/web/gisco/geodata) and datasets to be used only internally by the EEA (typically, but not only, GISCO datasets at 1:100k). The database is provided in as a single GDB and also as individual GPKG file per feature, with datasets at scales from 1:60M to 1:100K, with reference years spanning until 2021 (e.g. NUTS 2021). Additional information and metadata is provided with the dataset in the folder docs. The database manual, a file with the content of the database, a glossary, and a document with the naming conventions are included in this folder. The document GISCO-ConditionsOfUse.pdf provided with the dataset gives information on the copyrighted data sources, the mandatory acknowledgement clauses and re-dissemination rights. The license conditions for EuroGeographic datasets in GISCO are provided in a standalone document "LicenseConditions_EuroGeographics.pdf". The main updates with respect to the previous version of the full database in the SDI (from June 2020) are the addition of the following datasets: - Coastline boundaries, 2020 (COAS_2020) (N.B.: An update is expected soon) - Degree of Urbanisation, 2020 (DGURBA_2020) - Exclusive Economic Zones, 2020 (EEZ_2020) - FAO Fishing Areas, 2020 (FAO_FISH_2020) - Healthcare services (HEALTH) - LAU Historical Census data (LAU_CENS_1961-2011) - Local Administrative Units, 2017 (LAU_2017), 2019 (LAU_2019) and 2020 (LAU_2020) - LUCAS, 2018 (LUCAS_2018) - Metropolitan Regions, 2021 (MREG_2021) - Postal Codes, 2020 (PCODE_2020) (N.B.: DE is to be updated soon) When available, the model specifications of these new layers are also provided with the database (under the folder docs). NOTE: This metadata file is only for internal EEA purposes and in no case replaces the official metadata provided by Eurostat. For specific GISCO datasets included in this version there are individual EEA metadata files in the SDI: NUTS_2021, MREG_2021 and CNTR_2020. For public products, continuous updates are being published in the public website of GISCO: https://ec.europa.eu/eurostat/web/gisco/geodata. The original metadata files from Eurostat for the different GISCO datasets are available via ECAS login through the Eurostat metadata portal on https://webgate.ec.europa.eu/inspire-sdi/srv/eng/catalog.search#/home For more information about the full database or any of its datasets, please contact the SDI Team (sdi@eea.europa.eu).
European air quality information reported by EEA member countries, including all EU Member States, as well as EEA cooperating and other reporting countries. The EEA’s air quality database consists of a multi-annual time series of air quality measurement data and calculated statistics for a number of air pollutants. It also contains meta-information on the monitoring networks involved, their stations and measurements, air quality modelling techniques, as well as air quality zones, assessment regimes, compliance attainments and air quality plans and programmes reported by the EU Member States and European Economic Area countries.
Periods of extreme geomagnetic change such as geomagnetic excursions have frequently occurred throughout geological time. Characterizing their behaviour is essential for a full understanding of the geodynamo and the interaction of Earths magnetic field and the space environment. We propose to model the global behaviour of Earths magnetic field between 10 and 50 ka using palaeomagnetic data. During this time the geomagnetic field showed significant variability in direction and intensity, including two well documented excursions: Laschamp and Mono Lake. No model currently exists that spans the total length of this time period, yet this period could provide great insights into the geodynamo. The ultimate goal of the project is to synthesize the results from our empirical modelling with those from numerical dynamo simulations, so that a deeper physical understanding of geodynamo processes can be gained. We will compile all sedimentary and volcanic palaeomagnetic data coupled with geochronological data spanning this period. This data will be added to a community available database along with all rock magnetic and sedimentological metadata. This will allow a detailed assessment of the data used in the modelling. Low quality palaeomagnetic data and erroneous age models may distort geomagnetic field structures generated by our new model and it is a key objective of this study to assess the fidelity of the palaeomagnetic and chronological data included in the modeling. Using this data we will construct a temporally continuous global spherical harmonic geomagnetic field model through a regularized least squares inversion of the data using spherical harmonics in space and cubic B splines in time. This model will enable assessment of the geomagnetic at the core-mantle boundary, the Earths surface and at elevated altitudes. Our key scientific objective is to determine where excursions fit into the spectrum of geomagnetic field variations and how the geodynamo processes that generate excursions differ from those that produce secular variation and reversals.
Frame: The project is part of the GLP (Global land project) fast track action (http://bbs2008.wikidot.com) Decreasing uncertainty in predicting biome boundary shifts which aims at improving the simulation of biome boundary shifts at large spatial scales, working group Migration . The long-term goal is to improve existing vegetation models or to develop new models that are reliable and robust and can be included in Earth System models for studying biosphere-atmosphere feedbacks. Rationale: Because of the nature of terrestrial plant population and community dynamics and dispersal, and the pace of climate change, predicting the future distribution of plant species is challenging. Many coupled GCM's assume simply that the boundaries between major terrestrial biomes are either static, or adjusted non-mechanistically to follow the change of climate without time lags. In some DGVM's, a non-mechanistic treatment of biome boundaries is employed with assumed delays. Recent model simulations with both explicit seed dispersal and population and community dynamics suggest that range shifts of forest biomes will be both complex and extremely delayed (several millennia delay for centennial warming). Research topics: the effect of plant population processes and dispersal on migration, the effect of spatial heterogeneity (e.g. fragmentation or barriers) on dispersal and migration, methods to incorporate these effects into large scale models like such as DGVM's, the lags due to species migration and their effects on feedbacks to the earth system. Methods: Starting from the forest landscape model TreeMig which describes tree species migration by explicitly simulating seed dispersal on a grid of 1km wide cells, we develop numerical approaches to describe migration across heterogenous grid cells. These approaches are either aggregated models of within-cell migration speed, e.g. derived from meta-modelling, or simulating spread in a subset of smaller cells within each grid cell and then extrapolating to the larger cell. We test our methods with simulations on south-north transects in Siberia and assess the effect of species migration on the feedbacks to the earth system.
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