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).
Semi-natural grasslands are among the most species-rich habitats in Europe but have sharply declined in spatial extent and biodiversity in recent decades. Within Europe, the grasslands of the Alps and the Carpathians harbour extraordinary plant diversity but their biodiversity varies significantly due to local environmental conditions and management intensities. Thus, there is general agreement that, in order to prevent further grassland biodiversity loss, the protection, enhancement and potential expansion of species-rich grasslands is necessary. Knowledge of the areas suitable for protection, enhancement and potential expansion comes largely from vegetation samples and experimental studies. However, these are unaffordable and unfeasible for systematic evaluation of biodiversity patterns over large areas. Further, existing monitoring programs generally lack information on grassland management regimes and a historical perspective, both of which can strongly influence current biodiversity. Fortunately, the availability of earth observational data over large areas now allows extrapolation of field measurements over time and space with acceptable accuracy. Combining these data with biodiversity datasets and an understanding of the socioeconomic context offers powerful opportunities for reaching conservation targets. The aims of the proposed project are to (1) identify diversity-rich grasslands and their distribution in the Alps and Carpathians; (2) identify diversity-supporting grassland management practices and their change and persistence; (3) identify the areas suitable for expanding the grassland protection network; and (4) propose new protection areas and their management across Alps and Carpathians. By addressing these aims we will cooperate with stakeholders to (i) identify effective methods for extrapolation of vegetation samples across the mountain ranges; (ii) identify the grassland management drivers and legacy effects on grassland diversity; (iii) identify constraints and motivations for biodiversity-supporting management practices (iv) provide scientific background for expanding the protection area network in the Alps and Carpathians. The proposed research provides a great opportunity to strengthen the cooperation, data and knowledge exchange between the researchers and stakeholders across the two largest mountain ranges in Europe: the Alps and the Carpathians.
This dataset contains a compilation of published and new SNW data with corresponding environmental data extracted from CMIP6 that are used in the at depth species level Bayesian regression modelling. Environmental data for G. truncatulinoides comes from 200m depth, all other environmental data is from the sea surface (≤ 20 m).
The Tree Species Germany product provides a map of dominant tree species across Germany for the year 2022 at a spatial resolution of 10 meters. The map depicts the distribution of ten tree species groups derived from multi-temporal optical Sentinel-2 data, radar data from Sentinel-1, and a digital elevation model. The input features explicitly incorporate phenological information to capture seasonal vegetation dynamics relevant for species discrimination. A total of over 80,000 training and test samples were compiled from publicly accessible sources, including urban tree inventories, Google Earth Pro, Google Street View, and field observations. The final classification was generated using an XGBoost machine learning algorithm. The Tree Species Germany product achieves an overall F1-score of 0.89. For the dominant species pine, spruce, beech, and oak, class-wise F1-scores range from 0.76 to 0.98, while F1-scores for other widespread species such as birch, alder, larch, Douglas fir, and fir range from 0.88 to 0.96. The product provides a consistent, high-resolution, and up-to-date representation of tree species distribution across Germany. Its transferable, cost-efficient, and repeatable methodology enables reliable large-scale forest monitoring and offers a valuable basis for assessing spatial patterns and temporal changes in forest composition in the context of ongoing climatic and environmental dynamics.
The data layers provided show current values for seawater temperature, pH, calcite and aragonite saturation (%), oxygen concentration, and particulate organic carbon (POC) flux to the seafloor at different depths (500, 1000, 2000, 3000, and 4000m) at the present day (1951-2000) and changes in these variables expected between 2041-2060 and 2081-2100 under different RCP scenarios. The data layers were generated following the methods described in Levin et al. (2020). In short, in 2019, we obtained the present day and future ocean projections for the different years which were compiled from all available data generated by Earth Systems Models as part of the Coupled Model Inter-comparison Project Phase 5 (CMIP5) to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Three Earth System Models, including GFDL‐ESM‐2G, IPSL‐CM5A‐MR, and MPI‐ESM‐MR were collected and multi-model averages of temperature, pH, O2 , export production at 100-m depth (epc100), carbonate ion concentration (co3), and carbonate ion concentration for seawater in equilibrium with aragonite (co3satarg) and calcite (co3satcalc) were calculated. The epc100 was converted to export POC flux at the seafloor using the Martin curve (Martin et al., 1987) following the equation: POC flux = export production*(depth/export depth)0.858. The export depth was set to 100 m, and the water depth using the ETOPO1 Global Relief Model (Amante and Eakins, 2008). Seafloor aragonite and calcite saturation were computed by dividing co3 by co3satarg and co3satcalc. All variableswere reported as the inter-annual mean projections between 1951-2000, 2041-2060, and 2081-2100. The data for calcite and aragonite saturation can be found in Morato et al. (2020).
Sauropod dinosaurs represent one of the most important components of Mesozoic terrestrial vertebrate faunas, yet their early evolution and diversification in the Jurassic is still poorly understood. Furthermore, most of the pertinent data so far comes from Early and Middle Jurassic rocks in eastern Asia. The only abundant basal sauropod material reported from the Western Hemisphere so far comes from the Middle Jurassic Cañadón Asfalto Formation of Chubut province, Argentina, from where two species, Patagosaurus fariasi and Volkheimeria chubutensis, have been described. Especially the first of these taxa has figured prominently in basal sauropod phylogenies. However, recent research suggests that more sauropods are represented in the original material referred to this species, and intensive fieldwork in the rocks that have yielded these materials has resulted in the recovery of a wealth of new material. Thus, the objective of this project is a revision of the original materials of Patagosaurus as well as an incorporation of new materials. The alpha taxonomy of the sauropods from the Cañadón Asfalto Formation will be established, detailed osteological descriptions of the different taxa provided and their significance for our understanding of early sauropod evolution will be evaluated.
In subsoils, organic matter (SOM) concentrations and microbial densities are much lower than in topsoils and most likely highly heterogeneously distributed. We therefore hypothesize, that the spatial separation between consumers (microorganisms) and their substrates (SOM) is an important limiting factor for carbon turnover in subsoils. Further, we expect microbial activity to occur mainly in few hot spots, such as the rhizosphere or flow paths where fresh substrate inputs are rapidly mineralized. In a first step, the spatial distribution of enzyme and microbial activities in top- and subsoils will be determined in order to identify hot spots and relate this to apparent 14C age, SOM composition, microbial community composition and soil properties, as determined by the other projects within the research unit. In a further step it will be determined, if microbial activity and SOM turnover is limited by substrate availability in spatially distinct soil microsites. By relating this data to root distribution and preferential flow paths we will contribute to the understanding of stabilizing and destabilizing processes of subsoil organic matter. As it is unclear, at which spatial scale these differentiating processes are effective, the analysis of spatial variability will cover the dm to the mm scale. As spatial segregation between consumers and substrates will depend on the pore and aggregate architecture of the soil, the role of the physical integrity of these structures on SOM turnover will also be investigated in laboratory experiments.
In many plant species, FLOWERING LOCUS T and related proteins are the mobile signal that communicates information on photoperiod from the leaves to the shoots, where the transition to flowering is realized. FT expression is tightly controlled at the transcriptional level so that it is restricted to leaves, occurs only in appropriate photoperiods, and integrates ambient temperature and developmental cues, as well as information on biotic and abiotic stress. We previously established that FT transcription in the model plant Arabidopsis thaliana requires proximal promoter cis-elements and a distal enhancer, both evolutionary conserved among Brassicacea species. In addition, FT transcription is blocked prior vernalization in biannual accessions and vernalization-dependency of FT is controlled through a CArG-box located in the first intron that binds the transcriptional repressor FLOWERING LOCUS C (FLC). Chromatin-mediated repression by the Polycomb Group (PcG) pathway is required for photoperiod-dependent FT regulation and participates in FT expression level modulation in response to other cues.In this project, I propose to explore the available sequence data from the 1001 genome project in Arabidopsis to evaluate how often changes in regulatory cis-elements at FT have occurred and how these translate into an adaptive value. Allele-specific FT expression pattern will be measured in F1 hybrids of different accessions in response to varying environmental conditions. FT alleles that show cis-regulatory variation will be further analyzed to pinpoint the causal regulatory changes and study their effect in more detail. The allotetrapolyploid species Brassica napus is a hybrid of two Brassiceae species belonging to the A- and C-type genome, which are in turn mesopolyploid due to a genome triplication that occurred ca. 10x106 years ago. We will determine allele-specific expression of FT paralogs from both genomes of a collection of B. napus accessions. The plants will be grown in the field in changing environmental conditions to maximize the chance to detect expression variation of the paralogs. We will compare the contribution of the founder genomes to the regulation of flowering time and asses variation in this contribution. A particular focus will be to study the impact of chromatin-mediated repression on allele selection in B. napus.
We are currently facing the urgent need to improve our understanding of carbon cycling in subsoils, because the organic carbon pool below 30 cm depth is considerably larger than that in the topsoil and a substantial part of the subsoil C pool appears to be much less recalcitrant than expected over the last decades. Therefore, small changes in environmental conditions could change not only carbon cycling in topsoils, but also in subsoils. While organic matter stabilization mechanisms and factors controlling its turnover are well understood in topsoils, the underlying mechanisms are not valid in subsoils due to depth dependent differences regarding (1) amounts and composition of C-pools and C-inputs, (2) aeration, moisture and temperature regimes, (3) relevance of specific soil organic carbon (SOC) stabilisation mechanisms and (4) spatial heterogeneity of physico-chemical and biological parameters. Due to very low C concentrations and high spatio-temporal variability of properties and processes, the investigation of subsoil phenomena and processes poses major methodological, instrumental and analytical challenges. This project will face these challenges with a transdisciplinary team of soil scientists applying innovative approaches and considering the magnitude, chemical and isotopic composition and 14C-content of all relevant C-flux components and C-fractions. Taking also the spatial and temporal variability into account, will allow us to understand the four-dimensional changes of C-cycling in this environment. The nine closely interlinked subprojects coordinated by the central project will combine field C-flux measurements with detailed analyses of subsoil properties and in-situ experiments at a central field site on a sandy soil near Hannover. The field measurements are supplemented by laboratory studies for the determination of factors controlling C stabilization and C turnover. Ultimately, the results generated by the subprojects and the data synthesized in the coordinating project will greatly enhance our knowledge and conceptual understanding of the processes and controlling factors of subsoil carbon turnover as a prerequisite for numerical modelling of C-dynamics in subsoils.
Since 1999, the Geologic Survey of Baden-Württemberg publishes a statewide geological map series 1 : 50 000 "Karte der mineralischen Rohstoffe 1 : 50 000 (KMR 50)". On it, the distribution of near-surface mineral raw material prospects and occurrences (mainly) and deposits (subordinate) is shown. This continuously completed and updated map currently covers around 60% of the federal state. It is the base for the regional associations in the task of mineral planning. The prospects and occurrences are classified according to different raw material groups (e.g. raw material for crushed stone (limestone, igneous rocks, metamorphic rocks, sand and gravel), raw materials for cement, dimension stone, high purity limestone, gypsum ...). Their spatial delineation is based on various group-specific criteria such as minimum workable thickness, minimum resources, ratio overburden/workable thickness, and so on. It is assumed that they contain deposits as a whole or in parts. In the vast majority of cases, the data is not sufficient for the immediate planning of mining projects, but it does facilitate the selection of exploration areas. The name of each area (e.g. L 6926-3) consists of three parts. L = roman rnumeral fo 50, 6926 = sheet number of the topographic map 1 : 50 000, 3 = number of the area/mineral occurrence shown on this sheet. Co-occurring land-use conflicts, e.g. water protection areas and nature conservation areas, forestry and agriculture, are not taken into account in the processing of KMR 50. Their assessment is the task of land use planning, the licensing authorities and the companies interested in mining. The data is stored in the statewide raw material area database "olan-db" of the LGRB.
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