EMODnet BiologyThe EMODnet Biology products include a set of gridded map layers showing the average abundance of marine species for different time windows (seasonal, annual) using geospatial modelling. The spatial modelling tool used to calculate the gridded abundance maps is based on DIVA. DIVA (Data-Interpolating Variational Analysis) is a tool to create gridded data sets from discrete point measurements of the ocean. For the representation of time dynamics, it was decided to produce gridded maps for sliding time windows, e.g. combining one or more years in one gridded map, so that relatively smooth animated GIF presentations can be produced that show the essential change over time. EMODnet Biology’s data products include the Operational Ocean Products and Services (OOPS), harvested by ICES.WFSWMSGEOSERVERWFS2.0.0nonePlease contact VLIZ if you want to use a layerFlanders Marine Institute (VLIZ)EMODnet Biology teamOostendBelgiumbio@emodnet.eu1.0.01.1.02.0.0text/xmlServiceIdentificationServiceProviderOperationsMetadataFeatureTypeListFilter_Capabilitiesapplication/gml+xml; version=3.2resultshitsapplication/gml+xml; version=3.2GML2KMLSHAPE-ZIPapplication/jsonapplication/vnd.google-earth.kml xmlapplication/vnd.google-earth.kml+xmlcsvgml3gml32jsontext/csvtext/xml; subtype=gml/2.1.2text/xml; subtype=gml/3.1.1text/xml; subtype=gml/3.2nonelocalFALSE1000000nonelocalapplication/gml+xml; version=3.2urn:ogc:def:queryLanguage:OGC-WFS::WFSQueryExpressionALLSOMEresultshitsapplication/gml+xml; version=3.2GML2KMLSHAPE-ZIPapplication/jsonapplication/vnd.google-earth.kml xmlapplication/vnd.google-earth.kml+xmlcsvgml3gml32jsontext/csvtext/xml; subtype=gml/2.1.2text/xml; subtype=gml/3.1.1text/xml; subtype=gml/3.2nonelocalapplication/gml+xml; version=3.2ALLSOMETRUETRUETRUETRUETRUETRUEFALSEFALSETRUETRUETRUETRUEFALSETRUEFALSEwfs:Querywfs:StoredQueryhttps://emodnet.ec.europa.eu/geonetwork/srv/api/records/5c100755a4b1337343762cc3a05de8642041cd05/formatters/xmlapplication/vnd.ogc.csw.GetRecordByIdResponse_xmlengengde150065-3c5d-444d-b0ce-8b80ee65afe9Emodnetbio:cti_macroalgae_nw_spainOcean warming is expected to drive quick shifts in marine species distributions modifying coastal communities. Previous research has shown how the southern Bay of Biscay is particularly affected and the canopy-forming subtidal and intertidal macroalgal assemblages are expected to be replaced by turf-forming Mediterranean-like communities with warmer affinities by the end of the century. The effect of temperature on macroalgal communities could be assesed using thermal metrics that can target temperature effects alone. An example is the Community Temperature Index (CTI) which is an abundance-weighted mean of the species’ optimal temperature. It has been previously used to understand the thermal preferences of different organisms such us birds, fish or invertebrates. This product provides the Community Temperature Index (CTI) of macroalgae intertidal communities from NW Spain. The CTI has been calculated for 18 sites along a longitudinal thermal gradient in NW Spain, two intertidal levels (Low and Mid) and two different years (2011 and 2017). Results are stored in a csv file with the coordinates of each site ("decimalLongitude" and "decimalLatitude" columns), their codes ("Site" and "Intertidal_level" columns), the sampling year ("Year" column) and the mean CTI ("CTI column").featurescti_macroalgae_nw_spainurn:ogc:def:crs:EPSG::4326-9.249575 42.235177-2.259167 43.629808Emodnetbio:mediseh_cor_abs_pntCoral absence data from the dataset Coralligenous and mäerl beds distribution along the Mediterranean coasts - Mediterranean Sensitive Habitats (MEDISEH). Information has been derived from three sources: 1) the Action plan for the conservation of the coralligenous and other calcareous bio-concretions in the Mediterranean Sea by the UNEP-MAP-RAC/SPA (2008) 2) the report in the State of knowledge of the geographical distribution of the coralligenous and other calcareous bio-concretions in the Mediterranean by UNEP (2009) 3) projects focussing bioconstructions, their distribution and the driving forces affecting their structure and function A total of 798 scientific documents have been collected, together with 43 shapefiles, 1492 polygons and 641 data points for coralligenous formations, 47 polygons and 124 data points for maërl, and 39 bathymetry maps within the framework of the MEDISEH project. Even though proving information on absence data for both coralligenous and mäerl can be extremely difficult, an attempt has been made and 584 polygons have been included for coralligenous formations and 935 for maërl data. Detailed information for these two habitats is now available on about 15% of the Mediterranean coastal area. Fraschetti, M. Gristina, M. Salomidi, L. Knittweis, M.L. Pace, E. Punzo, A. Belluscio, G. Scarcella, F. Grati, F. De Leo, L. Rizzo, R. Cattaneo-Vietti, P. Povero, A. Cau, C. Piccinetti, V. Valavanis, C. Martin 2013. Coralligenous and mäerl beds distribution along the Mediterranean coasts Mediterranean Sensitive Habitats (MEDISEH) Final Report, DG MARE Specific Contract SI2.600741.biologymacroalgaemarineMediterraneanbiotamedisehmaerlmaërlcoalligenousoutcroppointsvectorabsence datacoralscoalligenous outcropHabitats and biotopesurn:ogc:def:crs:EPSG::43262.69709825515747 39.23693466186524.13495206832886 40.0964660644531Emodnetbio:mediseh_cor_abs_polyCoral absence data (polygons) in the Mediterranean Sea. Data comes from Coralligenous and mäerl beds distribution along the Mediterranean coasts - Mediterranean Sensitive Habitats (MEDISEH). Information has been derived from three sources: 1) the Action plan for the conservation of the coralligenous and other calcareous bio-concretions in the Mediterranean Sea by the UNEP-MAP-RAC/SPA (2008) 2) the report in the State of knowledge of the geographical distribution of the coralligenous and other calcareous bio-concretions in the Mediterranean by UNEP (2009) 3) projects focussing bioconstructions, their distribution and the driving forces affecting their structure and function A total of 798 scientific documents have been collected, together with 43 shapefiles, 1492 polygons and 641 data points for coralligenous formations, 47 polygons and 124 data points for maërl, and 39 bathymetry maps within the framework of the MEDISEH project. Even though proving information on absence data for both coralligenous and mäerl can be extremely difficult, an attempt has been made and 584 polygons have been included for coralligenous formations and 935 for maërl data. Detailed information for these two habitats is now available on about 15% of the Mediterranean coastal area. Fraschetti, M. Gristina, M. Salomidi, L. Knittweis, M.L. Pace, E. Punzo, A. Belluscio, G. Scarcella, F. Grati, F. De Leo, L. Rizzo, R. Cattaneo-Vietti, P. Povero, A. Cau, C. Piccinetti, V. Valavanis, C. Martin 2013. Coralligenous and mäerl beds distribution along the Mediterranean coasts Mediterranean Sensitive Habitats (MEDISEH) Final Report, DG MARE Specific Contract SI2.600741.biologymacroalgaemarineMediterraneanbiotamedisehmaerlmaërlcoalligenousoutcroppolygonvectorHabitats and biotopesurn:ogc:def:crs:EPSG::4326-1.63966238498688 37.052261352539113.4048929214478 42.2407722473145Emodnetbio:mediseh_cymodocea_pntCymodocea nodosa beds distribution (presence points) in the Mediterranean Sea. One of the general objectives of the MEDISEH (Mediterranean Sensitive Habitats) project was to compile historical and current data on seagrass beds. Belluscio A, Panayiotidis P, Gristina M., Knittweis L., Pace M.L.,Telesca L, Criscoli A, Apostolaki ET, Gerakaris V., S. Fraschetti, M. T. Spedicato, G. Lembo, M. Salomidi,R. Mifsud, G. Fabi, F. Badalamenti, G. Garofalo A. Alagna, Ardizzone G.D., Martin C., V. Valavanis 2013. Seagrass beds distribution along the Mediterranean coasts. Mediterranean Sensitive Habitats (MEDISEH) Final Report, DG MARE Specific Contract SI2.600741.MEDMediterraneanCymodocea nodosabiologyplantsangiospermmarineseagrassHabitats and biotopesurn:ogc:def:crs:EPSG::4326-5.22415655182084 31.122976606707735.9138022710002 45.7738989895096Emodnetbio:Species_gridded_abundance_allThis dataproduct consists of a set of gridded map layers showing the average abundance of different species of species groups for different time windows (seasonal, annual or multi-annual as appropriate) using spatial modelling. They cover a wide taxonomic range, from the smallest organisms (e.g. diatoms, flagellates) to the largest ones (e.g. fish, birds, reptiles, mammals), encompassing all trophic levels.fishbirdreptilemammaltrophic levelgriddiatomflagellatedataproductaverageabundancetimeseasonyearSpecies distributionurn:ogc:def:crs:EPSG::4326-180.0 -90.0180.0 90.0Emodnetbio:Species_gridded_abundances_10yearThis dataproduct consists of a set of gridded map layers showing the average abundance of different species of species groups for different time windows (seasonal, annual or multi-annual as appropriate) using spatial modelling. They cover a wide taxonomic range, from the smallest organisms (e.g. diatoms, flagellates) to the largest ones (e.g. fish, birds, reptiles, mammals), encompassing all trophic levels.fishbirdreptilemammaltrophic levelgriddiatomflagellatedataproductaverageabundancetimeseasonyearSpecies distributionurn:ogc:def:crs:EPSG::4326-4.55 49.9511.95 61.95Emodnetbio:Species_gridded_abundances_2yearThis dataproduct consists of a set of gridded map layers showing the average abundance of different species of species groups for different time windows (seasonal, annual or multi-annual as appropriate) using spatial modelling. They cover a wide taxonomic range, from the smallest organisms (e.g. diatoms, flagellates) to the largest ones (e.g. fish, birds, reptiles, mammals), encompassing all trophic levels.fishbirdreptilemammaltrophic levelgriddiatomflagellatedataproductaverageabundancetimeseasonyearSpecies distributionurn:ogc:def:crs:EPSG::4326-31.85 35.95-22.85 40.45Emodnetbio:Species_gridded_abundances_3yearThis dataproduct consists of a set of gridded map layers showing the average abundance of different species of species groups for different time windows (seasonal, annual or multi-annual as appropriate) using spatial modelling. They cover a wide taxonomic range, from the smallest organisms (e.g. diatoms, flagellates) to the largest ones (e.g. fish, birds, reptiles, mammals), encompassing all trophic levels.fishbirdreptilemammaltrophic levelgriddiatomflagellatedataproductaverageabundancetimeseasonyearSpecies distributionurn:ogc:def:crs:EPSG::4326-5.45 41.859.85 51.45Emodnetbio:mediseh_halophila_pntHalophila stipulacea beds distribution (presence points) in the Mediterranean Sea. One of the general objectives of the MEDISEH (Mediterranean Sensitive Habitats) project was to compile historical and current data on seagrass beds. Belluscio A, Panayiotidis P, Gristina M., Knittweis L., Pace M.L.,Telesca L, Criscoli A, Apostolaki ET, Gerakaris V., S. Fraschetti, M. T. Spedicato, G. Lembo, M. Salomidi,R. Mifsud, G. Fabi, F. Badalamenti, G. Garofalo A. Alagna, Ardizzone G.D., Martin C., V. Valavanis 2013. Seagrass beds distribution along the Mediterranean coasts. Mediterranean Sensitive Habitats (MEDISEH) Final Report, DG MARE Specific Contract SI2.600741.MEDMediterraneanHalophila stipulaceabiologyplantsangiospermmarineseagrassHabitats and biotopesurn:ogc:def:crs:EPSG::432610.8352777777777 31.077611763137835.8056323950001 40.4418768180838Emodnetbio:mediseh_maerl_pntMaërl bed occurrences (point distributions) in the Mediterranean Sea. Data comes from from Coralligenous and mäerl beds distribution along the Mediterranean coasts - Mediterranean Sensitive Habitats (MEDISEH). Information has been derived from three sources: 1) the Action plan for the conservation of the coralligenous and other calcareous bio-concretions in the Mediterranean Sea by the UNEP-MAP-RAC/SPA (2008) 2) the report in the State of knowledge of the geographical distribution of the coralligenous and other calcareous bio-concretions in the Mediterranean by UNEP (2009) 3) projects focussing bioconstructions, their distribution and the driving forces affecting their structure and function A total of 798 scientific documents have been collected, together with 43 shapefiles, 1492 polygons and 641 data points for coralligenous formations, 47 polygons and 124 data points for maërl, and 39 bathymetry maps within the framework of the MEDISEH project. Even though proving information on absence data for both coralligenous and mäerl can be extremely difficult, an attempt has been made and 584 polygons have been included for coralligenous formations and 935 for maërl data. Detailed information for these two habitats is now available on about 15% of the Mediterranean coastal area. Fraschetti, M. Gristina, M. Salomidi, L. Knittweis, M.L. Pace, E. Punzo, A. Belluscio, G. Scarcella, F. Grati, F. De Leo, L. Rizzo, R. Cattaneo-Vietti, P. Povero, A. Cau, C. Piccinetti, V. Valavanis, C. Martin 2013. Coralligenous and mäerl beds distribution along the Mediterranean coasts Mediterranean Sensitive Habitats (MEDISEH) Final Report, DG MARE Specific Contract SI2.600741.biologymacroalgaemarineMediterraneanbiotamedisehmaerlmaërlcoalligenousoutcroppointvectordistributionsHabitats and biotopesurn:ogc:def:crs:EPSG::43262.71985194163643 34.675754861000135.834454576 45.6722Emodnetbio:mediseh_maerl_polyMaërl bed occurences (polygons) in the Mediterranean Sea from the dataset Coralligenous and mäerl beds distribution along the Mediterranean coasts - Mediterranean Sensitive Habitats (MEDISEH). Information has been derived from three sources: 1) the Action plan for the conservation of the coralligenous and other calcareous bio-concretions in the Mediterranean Sea by the UNEP-MAP-RAC/SPA (2008) 2) the report in the State of knowledge of the geographical distribution of the coralligenous and other calcareous bio-concretions in the Mediterranean by UNEP (2009) 3) projects focussing bioconstructions, their distribution and the driving forces affecting their structure and function A total of 798 scientific documents have been collected, together with 43 shapefiles, 1492 polygons and 641 data points for coralligenous formations, 47 polygons and 124 data points for maërl, and 39 bathymetry maps within the framework of the MEDISEH project. Even though proving information on absence data for both coralligenous and mäerl can be extremely difficult, an attempt has been made and 584 polygons have been included for coralligenous formations and 935 for maërl data. Detailed information for these two habitats is now available on about 15% of the Mediterranean coastal area. Fraschetti, M. Gristina, M. Salomidi, L. Knittweis, M.L. Pace, E. Punzo, A. Belluscio, G. Scarcella, F. Grati, F. De Leo, L. Rizzo, R. Cattaneo-Vietti, P. Povero, A. Cau, C. Piccinetti, V. Valavanis, C. Martin 2013. Coralligenous and mäerl beds distribution along the Mediterranean coasts Mediterranean Sensitive Habitats (MEDISEH) Final Report, DG MARE Specific Contract SI2.600741.biologymacroalgaemarineMediterraneanbiotamedisehmaerlmaërlcoalligenousoutcroppointvectordistributionsHabitats and biotopesurn:ogc:def:crs:EPSG::43261.35282004937332 33.03188579374135.1032721811811 43.1771104698274Emodnetbio:mediseh_posidonia_modelThis dataset is an output of the “Mediterranean Sensitive Habitats” project (MEDISEH). It shows under a raster form modelled spatial distributions of Posidonia oceanica across the Mediterranean Sea. Posidonia oceanica is endemic to the Mediterranean Sea, where it is the dominant seagrass, covering about 50,000 km2 of coastal to offshore sandy and rocky areas down to depths of about 45 m. P. oceanica is a protected species according to EU legislation (Habitat directive), the Bern and Barcelona Conventions and several national legislations. The raster has a spatial resolution of 0.004166 decimal degrees, and the values are in the [0,1] interval (occurrence probabilities).Mediterranean basincoastalmarineblue carbonmodelbiogenic habitatgridMarine habitat mappingHabitats and biotopesurn:ogc:def:crs:EPSG::4326-5.665799 30.26600236.210833 45.792684Emodnetbio:mediseh_coral_modelThis dataset shows modelled spatial distributions of coralligenous outcrops and maërl beds across the Mediterranean Sea. These bioconstructions are typical Mediterranean underwater seascapes, comprising coralline algal frameworks that grow in dim light conditions. They are the result of the building activities of algal and animal constructors, counterbalanced by physical, as well as biological, eroding processes. Because of their extent, biodiversity and production, coralligenous and maërl habitats rank among the most important ecosystems in the Mediterranean Sea, and they are considered of great significance both for fisheries and carbon regulation.Mediterranean basin2014marinemodelbioconstructionbiogenic habitatcoralligenousmäerlmaerlmarine habitat mappinggridHabitats and biotopesurn:ogc:def:crs:EPSG::4326-5.66618707289344 30.266863558632936.2060849504857 45.7862245358287Emodnetbio:mediseh_maerl_modelThis dataset shows modelled spatial distributions of coralligenous outcrops and maërl beds across the Mediterranean Sea. These bioconstructions are typical Mediterranean underwater seascapes, comprising coralline algal frameworks that grow in dim light conditions. They are the result of the building activities of algal and animal constructors, counterbalanced by physical, as well as biological, eroding processes. Because of their extent, biodiversity and production, coralligenous and maërl habitats rank among the most important ecosystems in the Mediterranean Sea, and they are considered of great significance both for fisheries and carbon regulation.Mediterranean basin2014marinemodelbioconstructionbiogenic habitatcoralligenousmäerlmaerlmarine habitat mappinggridHabitats and biotopesurn:ogc:def:crs:EPSG::4326-5.66618707289347 30.266377455585236.2077482373789 45.7848197508306Emodnetbio:OOPS_errorsShapefile containing the error values of the spatial modelling tool DIVA used to calculate the gridded abundance maps of the six most abundant Copepod species from the CPR for different time windows (seasonal, annual) using geospatial modelling.OOPS_errorsfeaturesError valuesSpatial modellingAbundanceCopepodsNorth Atlanitc OceanNorth Seaurn:ogc:def:crs:EPSG::4326-4.95 48.0511.95 62.05Emodnetbio:OOPS_metadataThis file contains the metadata of the OOPS product and includes for each abundance value stored in the OOPS product file information on the scientific name, start and end year of data collection, season, measurement unit and link to the original netCDF file, generated by DIVAOOPS_metadatafeaturesurn:ogc:def:crs:EPSG::4326-1.0 -1.00.0 0.0Emodnetbio:OOPS_productsShapefile containing a set of gridded map layers showing the average abundance of the six most abundant Copepod species from the CPR for different time windows (seasonal, annual) using geospatial modelling. The spatial modelling tool used to calculate the gridded abundance maps is based on DIVA (Data-Interpolating Variational Analysis).featuresOOPS_productsCopepodsAbundanceSpatial modellingBiotaNorth SeaNorth Atlantic Oceanurn:ogc:def:crs:EPSG::4326-4.95 48.0512.25 60.75Emodnetbio:OOPS_products_vlizOOPS_products_vlizfeaturesurn:ogc:def:crs:EPSG::4326-4.95 48.0511.55 62.05Emodnetbio:OOPS_regionsShapefile containing ICES ecoregions and Western Atlantic Hydrographic regions for the development of ICES operational Oceanographic Products and Services.OOPS_regionsfeaturesMarine regionsAtlantic OceanBoundariesurn:ogc:def:crs:EPSG::4326-77.3202788782475 30.267049551395868.5000001347984 90.0000000001Emodnetbio:OOPS_summariesSummary statistics of the data of the OOPS products, providing an average value and standard deviation of the abundance values of the six most dominant Copepod species per regional sea of the North Atlantic Ocean per year per seson.featuresOOPS_summariesAbundanceCopeodsAtlantic regional seasBiotaurn:ogc:def:crs:EPSG::4326-1.0 -1.00.0 0.0Emodnetbio:mediseh_cor_pntCoralligenous outcrop occurrences (point distributions) in the Mediterranean Sea. Data comes from Coralligenous and mäerl beds distribution along the Mediterranean coasts - Mediterranean Sensitive Habitats (MEDISEH). Information has been derived from three sources: 1) the Action plan for the conservation of the coralligenous and other calcareous bio-concretions in the Mediterranean Sea by the UNEP-MAP-RAC/SPA (2008) 2) the report in the State of knowledge of the geographical distribution of the coralligenous and other calcareous bio-concretions in the Mediterranean by UNEP (2009) 3) projects focussing bioconstructions, their distribution and the driving forces affecting their structure and function A total of 798 scientific documents have been collected, together with 43 shapefiles, 1492 polygons and 641 data points for coralligenous formations, 47 polygons and 124 data points for maërl, and 39 bathymetry maps within the framework of the MEDISEH project. Even though proving information on absence data for both coralligenous and mäerl can be extremely difficult, an attempt has been made and 584 polygons have been included for coralligenous formations and 935 for maërl data. Detailed information for these two habitats is now available on about 15% of the Mediterranean coastal area. Fraschetti, M. Gristina, M. Salomidi, L. Knittweis, M.L. Pace, E. Punzo, A. Belluscio, G. Scarcella, F. Grati, F. De Leo, L. Rizzo, R. Cattaneo-Vietti, P. Povero, A. Cau, C. Piccinetti, V. Valavanis, C. Martin 2013. Coralligenous and mäerl beds distribution along the Mediterranean coasts Mediterranean Sensitive Habitats (MEDISEH) Final Report, DG MARE Specific Contract SI2.600741.biologymacroalgaemarineMediterraneanbiotamedisehmaerlmaërlcoalligenousoutcroppointvectordistributionsHabitats and biotopesurn:ogc:def:crs:EPSG::4326-4.66237856464225 32.802940000097435.8291752043475 45.6636Emodnetbio:mediseh_cor_polyCoralligenous outcrop occurrences (polygons) in the Mediterranean Sea. Data comes from Coralligenous and mäerl beds distribution along the Mediterranean coasts - Mediterranean Sensitive Habitats (MEDISEH). Information has been derived from three sources: 1) the Action plan for the conservation of the coralligenous and other calcareous bio-concretions in the Mediterranean Sea by the UNEP-MAP-RAC/SPA (2008) 2) the report in the State of knowledge of the geographical distribution of the coralligenous and other calcareous bio-concretions in the Mediterranean by UNEP (2009) 3) projects focussing bioconstructions, their distribution and the driving forces affecting their structure and function A total of 798 scientific documents have been collected, together with 43 shapefiles, 1492 polygons and 641 data points for coralligenous formations, 47 polygons and 124 data points for maërl, and 39 bathymetry maps within the framework of the MEDISEH project. Even though proving information on absence data for both coralligenous and mäerl can be extremely difficult, an attempt has been made and 584 polygons have been included for coralligenous formations and 935 for maërl data. Detailed information for these two habitats is now available on about 15% of the Mediterranean coastal area. Fraschetti, M. Gristina, M. Salomidi, L. Knittweis, M.L. Pace, E. Punzo, A. Belluscio, G. Scarcella, F. Grati, F. De Leo, L. Rizzo, R. Cattaneo-Vietti, P. Povero, A. Cau, C. Piccinetti, V. Valavanis, C. Martin 2013. Coralligenous and mäerl beds distribution along the Mediterranean coasts Mediterranean Sensitive Habitats (MEDISEH) Final Report, DG MARE Specific Contract SI2.600741.biologymacroalgaemarineMediterraneanbiotamedisehmaerlmaërlcoalligenousoutcroppointvectordistributionsHabitats and biotopesurn:ogc:def:crs:EPSG::4326-0.654747315096928 33.063335432357335.0962586360078 45.6649931202008Emodnetbio:mediseh_posidonia_absCoastline with real absence information of Posidonia oceanica meadows. One of the general objectives of the MEDISEH (Mediterranean Sensitive Habitats) project was to compile historical and current data on seagrass beds. Belluscio A, Panayiotidis P, Gristina M., Knittweis L., Pace M.L.,Telesca L, Criscoli A, Apostolaki ET, Gerakaris V., S. Fraschetti, M. T. Spedicato, G. Lembo, M. Salomidi,R. Mifsud, G. Fabi, F. Badalamenti, G. Garofalo A. Alagna, Ardizzone G.D., Martin C., V. Valavanis 2013. Seagrass beds distribution along the Mediterranean coasts. Mediterranean Sensitive Habitats (MEDISEH) Final Report, DG MARE Specific Contract SI2.600741.MEDMediterraneanPosidonia oceanicabiologyplantsangiospermmarineseagrassHabitats and biotopesurn:ogc:def:crs:EPSG::4326-5.73955200760205 30.718760236323536.214428897906 45.7857511310799Emodnetbio:mediseh_posidonia_nodataCoastline with unknown distribution of Posidonia oceanica meadows. One of the general objectives of the MEDISEH (Mediterranean Sensitive Habitats) project was to compile historical and current data on seagrass beds. Belluscio A, Panayiotidis P, Gristina M., Knittweis L., Pace M.L.,Telesca L, Criscoli A, Apostolaki ET, Gerakaris V., S. Fraschetti, M. T. Spedicato, G. Lembo, M. Salomidi,R. Mifsud, G. Fabi, F. Badalamenti, G. Garofalo A. Alagna, Ardizzone G.D., Martin C., V. Valavanis 2013. Seagrass beds distribution along the Mediterranean coasts. Mediterranean Sensitive Habitats (MEDISEH) Final Report, DG MARE Specific Contract SI2.600741.MEDMediterraneanPosidonia oceanicabiologyplantsangiospermmarineseagrassHabitats and biotopesurn:ogc:def:crs:EPSG::4326-2.17980035367841 30.266233795459634.6076704462685 45.4766767770067Emodnetbio:mediseh_posidonia_current_pntCurrent Posidonia oceanica meadows distribution (presence points) in the Mediterranean Sea. One of the general objectives of the MEDISEH (Mediterranean Sensitive Habitats) project was to compile historical and current data on seagrass beds. Belluscio A, Panayiotidis P, Gristina M., Knittweis L., Pace M.L.,Telesca L, Criscoli A, Apostolaki ET, Gerakaris V., S. Fraschetti, M. T. Spedicato, G. Lembo, M. Salomidi,R. Mifsud, G. Fabi, F. Badalamenti, G. Garofalo A. Alagna, Ardizzone G.D., Martin C., V. Valavanis 2013. Seagrass beds distribution along the Mediterranean coasts. Mediterranean Sensitive Habitats (MEDISEH) Final Report, DG MARE Specific Contract SI2.600741.MEDMediterraneanPosidonia oceanicabiologyplantsangiospermmarineseagrassHabitats and biotopesurn:ogc:def:crs:EPSG::43263.00340833300004 30.823301591567334.406732706224 45.4707269880164Emodnetbio:mediseh_posidonia_current_shapeCurrent Posidonia oceanica meadows distribution in the Mediterranean Sea. One of the general objectives of the MEDISEH (Mediterranean Sensitive Habitats) project was to compile historical and current data on seagrass beds. Belluscio A, Panayiotidis P, Gristina M., Knittweis L., Pace M.L.,Telesca L, Criscoli A, Apostolaki ET, Gerakaris V., S. Fraschetti, M. T. Spedicato, G. Lembo, M. Salomidi,R. Mifsud, G. Fabi, F. Badalamenti, G. Garofalo A. Alagna, Ardizzone G.D., Martin C., V. Valavanis 2013. Seagrass beds distribution along the Mediterranean coasts. Mediterranean Sensitive Habitats (MEDISEH) Final Report, DG MARE Specific Contract SI2.600741.MEDMediterraneanPosidonia oceanicabiologyplantsangiospermmarineseagrassHabitats and biotopesurn:ogc:def:crs:EPSG::4326-5.18010018812167 32.200467767310334.1001108343815 45.672768501839Emodnetbio:mediseh_posidonia_historical_shapeHistorical Posidonia oceanica meadows distribution in the Mediterranean Sea. One of the general objectives of the MEDISEH (Mediterranean Sensitive Habitats) project was to compile historical and current data on seagrass beds. Belluscio A, Panayiotidis P, Gristina M., Knittweis L., Pace M.L.,Telesca L, Criscoli A, Apostolaki ET, Gerakaris V., S. Fraschetti, M. T. Spedicato, G. Lembo, M. Salomidi,R. Mifsud, G. Fabi, F. Badalamenti, G. Garofalo A. Alagna, Ardizzone G.D., Martin C., V. Valavanis 2013. Seagrass beds distribution along the Mediterranean coasts. Mediterranean Sensitive Habitats (MEDISEH) Final Report, DG MARE Specific Contract SI2.600741.MEDMediterraneanPosidonia oceanicabiologyplantsangiospermmarineseagrassHabitats and biotopesurn:ogc:def:crs:EPSG::4326-5.22508825283165 35.685930374408719.4899290628674 44.3995849910059Emodnetbio:mediseh_posidonia_historical_pntHistorical Posidonia oceanica meadows distribution (presence points) in the Mediterranean Sea. One of the general objectives of the MEDISEH (Mediterranean Sensitive Habitats) project was to compile historical and current data on seagrass beds. Belluscio A, Panayiotidis P, Gristina M., Knittweis L., Pace M.L.,Telesca L, Criscoli A, Apostolaki ET, Gerakaris V., S. Fraschetti, M. T. Spedicato, G. Lembo, M. Salomidi,R. Mifsud, G. Fabi, F. Badalamenti, G. Garofalo A. Alagna, Ardizzone G.D., Martin C., V. Valavanis 2013. Seagrass beds distribution along the Mediterranean coasts. Mediterranean Sensitive Habitats (MEDISEH) Final Report, DG MARE Specific Contract SI2.600741.MEDMediterraneanPosidonia oceanicabiologyplantsangiospermmarineseagrassHabitats and biotopesurn:ogc:def:crs:EPSG::432610.365220939874 31.097545219011535.2761571225822 45.3079002290906Emodnetbio:mediseh_ruppia_c_pntRuppia cirrhosa beds distribution (presence points) in the Mediterranean Sea. One of the general objectives of the MEDISEH (Mediterranean Sensitive Habitats) project was to compile historical and current data on seagrass beds. Belluscio A, Panayiotidis P, Gristina M., Knittweis L., Pace M.L.,Telesca L, Criscoli A, Apostolaki ET, Gerakaris V., S. Fraschetti, M. T. Spedicato, G. Lembo, M. Salomidi,R. Mifsud, G. Fabi, F. Badalamenti, G. Garofalo A. Alagna, Ardizzone G.D., Martin C., V. Valavanis 2013. Seagrass beds distribution along the Mediterranean coasts. Mediterranean Sensitive Habitats (MEDISEH) Final Report, DG MARE Specific Contract SI2.600741.MEDMediterraneanRuppia cirrhosabiologyplantsangiospermmarineseagrassHabitats and biotopesurn:ogc:def:crs:EPSG::43260.726282361917948 31.062084919431133.2970991030128 44.5096141401189Emodnetbio:mediseh_ruppia_m_pntRuppia maritima beds distribution (presence points) in the Mediterranean Sea. One of the general objectives of the MEDISEH (Mediterranean Sensitive Habitats) project was to compile historical and current data on seagrass beds. Belluscio A, Panayiotidis P, Gristina M., Knittweis L., Pace M.L.,Telesca L, Criscoli A, Apostolaki ET, Gerakaris V., S. Fraschetti, M. T. Spedicato, G. Lembo, M. Salomidi,R. Mifsud, G. Fabi, F. Badalamenti, G. Garofalo A. Alagna, Ardizzone G.D., Martin C., V. Valavanis 2013. Seagrass beds distribution along the Mediterranean coasts. Mediterranean Sensitive Habitats (MEDISEH) Final Report, DG MARE Specific Contract SI2.600741.MEDMediterraneanRuppia maritimabiologyplantsangiospermmarineseagrassHabitats and biotopesurn:ogc:def:crs:EPSG::432610.8181016644514 33.257529281298826.05 41.4168266767333Emodnetbio:mediseh_zostera_m_pntZostera marina beds distribution (presence points) in the Mediterranean Sea. One of the general objectives of the MEDISEH (Mediterranean Sensitive Habitats) project was to compile historical and current data on seagrass beds. Belluscio A, Panayiotidis P, Gristina M., Knittweis L., Pace M.L.,Telesca L, Criscoli A, Apostolaki ET, Gerakaris V., S. Fraschetti, M. T. Spedicato, G. Lembo, M. Salomidi,R. Mifsud, G. Fabi, F. Badalamenti, G. Garofalo A. Alagna, Ardizzone G.D., Martin C., V. Valavanis 2013. Seagrass beds distribution along the Mediterranean coasts. Mediterranean Sensitive Habitats (MEDISEH) Final Report, DG MARE Specific Contract SI2.600741.MEDMediterraneanZostera marinabiologyplantsangiospermmarineseagrassHabitats and biotopesurn:ogc:def:crs:EPSG::4326-4.16715370823943 33.077825222093215.357656963319 45.7245106171991Emodnetbio:mediseh_zostera_n_pntZostera noltii beds distribution (presence points) in the Mediterranean Sea. One of the general objectives of the MEDISEH (Mediterranean Sensitive Habitats) project was to compile historical and current data on seagrass beds. Belluscio A, Panayiotidis P, Gristina M., Knittweis L., Pace M.L.,Telesca L, Criscoli A, Apostolaki ET, Gerakaris V., S. Fraschetti, M. T. Spedicato, G. Lembo, M. Salomidi,R. Mifsud, G. Fabi, F. Badalamenti, G. Garofalo A. Alagna, Ardizzone G.D., Martin C., V. Valavanis 2013. Seagrass beds distribution along the Mediterranean coasts. Mediterranean Sensitive Habitats (MEDISEH) Final Report, DG MARE Specific Contract SI2.600741.MEDMediterraneanZostera noltiibiologyplantsangiospermmarineseagrassHabitats and biotopesurn:ogc:def:crs:EPSG::4326-5.42911323637077 31.27682852223735.9138022710002 45.6998542408631Emodnetbio:grey_sealThese grid data were derived from National Parks and Wildlife Service cetacean surveys within the Irish MSFD area and the EEA-10km GRID. The grid shows the current distribution of Grey seal (Halichoreus grypus) in Irish coastal and marine waters. The data were collected for the purposes of 2019 reporting under Article 17 of the EU Habitats Directive.Species distributionSpecies distributionurn:ogc:def:crs:EPSG::4326-10.782374382019 51.3417510986328-5.83586025238037 55.5402717590332Emodnetbio:eb185_benthos_full_matchedThis product is built from two existing EMODnet data products. It uses the EUSeaMap product created by EMODNet Seabed Habitats and the Presence/absence data of macrozoobenthos in the European Seas product created by EMODnet Biology to obtain lists of all macrobenthic species occurring in all EUNIS seabed habitat types. For the purposes of this product the seabed habitat map is summarised on a grid at approx. 500m resolution, with each grid cell assigned to the dominant EUNIS code present within it. Summaries of benthic diversity are created for each grid cell, as well as more synthetic summaries by EUNIS category. The full matched benthos community data was written to file in the derived data folder as benthos_full_matched in parquet format with gzip compression.featureseb185_benthos_full_matchedurn:ogc:def:crs:EPSG::4326-32.28091049194336 28.18761062622070342.83333206176758 79.1833267211914Emodnetbio:eb185_eusm23_totalThis product is built from two existing EMODnet data products. It uses the EUSeaMap product created by EMODNet Seabed Habitats and the Presence/absence data of macrozoobenthos in the European Seas product created by EMODnet Biology to obtain lists of all macrobenthic species occurring in all EUNIS seabed habitat types. For the purposes of this product the seabed habitat map is summarised on a grid at approx. 500m resolution, with each grid cell assigned to the dominant EUNIS code present within it. Summaries of benthic diversity are created for each grid cell, as well as more synthetic summaries by EUNIS category. The full matched benthos community data was written to file in the derived data folder as benthos_full_matched in parquet format with gzip compression.featureseb185_eusm23_totalurn:ogc:def:crs:EPSG::4326-35.97180141999996 23.6804721800000442.99962379300007 81.54050178800009Emodnetbio:calanus_year_abundancefeaturescalanus_yearurn:ogc:def:crs:EPSG::4326-21.0 40.7512.0 66.75Emodnetbio:kuenm_modelsThe number of marine seaweeds outside their natural boundaries has increased in the last decades generating impacts on biodiversity and economy. This makes the development of management tools necessary, where species distribution models (SDMs) play a crucial role. SDMs can help in the early detection of invasions and predict the extent of the potential spread. However, modelling non-native marine species distributions is still challenging in terms of model building, evaluation and selection. This product aims to predict the European distribution of four widespread introduced seaweed species selecting the best model building process.featureskuenm_modelsurn:ogc:def:crs:EPSG::4326-35.95833 15.0416742.875 83.70833Emodnetbio:benthos_europeThe large databases of EMODNET Biology only store confirmed presences of taxon. However, when mapping taxon distribution, it is also important where the taxon did not occur: there is at least as much information in absences as in presences. Inferring absences from presence-only databases is difficult and always involves some guesswork. In this product we have used as much meta-information as possible to guide us in inferring absences. There is important meta-information at two different levels: the level of the data set, and the level of the taxon. Datasets can contain implicit information on absences when they have uniformly searched for the same taxon over a number of sample locations. Normally, if the taxon would have been present there, it would have been recorded. Other datasets, however, are not informative at all about absences. Typical examples are museum collections. The fact that a specimen is found at a particular place confirms that it lived there, but does not give information on any other taxon being present or absent in the same spot. A difficulty is that some datasets have searched for a restricted part of the total community, e.g. only sampled shellfish but no worms. In this case, absence of a shellfish taxon is relevant, but absence of a worm is not. The dataset can only be used to infer absence for the taxa it has targeted. Here we implicitly assume that a dataset inventorying the endomacrobenthos, is targeting all taxa belonging to this functional group. Usually, the distinction can be made on the basis of the metadata. It is also helpful to plot the total number of taxa versus the total number of samples. Incomplete datasets have far less taxa than expected for their size, compared to 'complete' datasets. At the taxon level, taxonomic registers such as WoRMS (WoRMS Editorial Board, 2021) give information on the functional group the taxon belongs to. This information is present for many taxa, but it is most likely incomplete. The size of the register excludes any easy test of completeness of the traits. However, even if incomplete, the register trait data can be used to select the most useful datasets. If one were to use an incomplete register directly to restrict the taxa to be used in mapping, that would cause loss of interesting information. Therefore the present workflow contains additional steps using the identified promising datasets rather than the taxon list based on the register’s traits.featuresbenthos_europeurn:ogc:def:crs:EPSG::4326-10.1070003509521 51.435199737548816.8089694976807 58.0088195800781Emodnetbio:all_diversity_measuresThis product builds on the EMODnet Biology data product Presence/absence data of macrozoobenthos in the European Seas to derive estimates of temporal turnover in benthic communities on a spatial grid across European seas. This product only uses species-level records, and only uses sampling events where the full macrobenthic community was surveyed (i.e. where there are no 'NA' values in the presence/absence dataset for any species). Six time periods are considered, based on data availability: before 1990, 1990-1999, 2000-2004, 2005-2009, 2010-2014, and 2015 and after. A 1 degree grid is used to obtain reasonable numbers of repeat samples per grid cell. The code below could be adapted to set different time periods and/or a different grid resolution. This readme describes the product structure, including the workflow to generate the required derived datasets and the process for turning them into gridded maps of community turnover.all_diversity_measuresfeaturesurn:ogc:def:crs:EPSG::4326-33.0 28.044.0 79.0TRUETRUETRUETRUETRUETRUETRUETRUETRUETRUEFALSETRUEFALSETRUExs:intxs:intxs:longxs:longxs:floatxs:floatxs:doublexs:doublexs:doublexs:doublexs:stringxs:stringxs:stringxs:stringxs:stringxs:doublexs:doublexs:doublexs:doublexs:doublexs:doublexs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:stringxs:booleanxs:booleanxs:booleanxs:doublegml:AbstractGeometryTypexs:doublegml:AbstractGeometryTypexs:stringxs:stringxs:intxs:intxs:stringxs:doublexs:doublexs:stringgml:AbstractGeometryTypexs:doublexs:doublexs:doublexs:doublexs:doublexs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:intxs:intxs:stringxs:stringxs:stringxs:intxs:stringxs:stringxs:stringxs:intxs:doublexs:doublexs:intxs:intxs:doublexs:doublexs:intxs:doublexs:stringxs:intxs:intxs:booleanxs:stringxs:stringxs:stringxs:stringgml:AbstractGeometryTypexs:intgml:AbstractGeometryTypexs:stringxs:stringxs:stringxs:stringgml:AbstractGeometryTypexs:floatxs:stringxs:stringxs:doublexs:stringxs:stringgml:AbstractGeometryTypexs:floatxs:floatxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:doublexs:floatxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:intxs:booleanxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:stringxs:stringxs:floatxs:floatxs:stringgml:AbstractGeometryTypexs:floatxs:stringxs:dateTimexs:dateTimexs:dateTimexs:dateTimexs:dateTimexs:dateTimexs:stringxs:dateTimexs:floatxs:floatxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:stringxs:stringxs:stringxs:stringxs:intxs:stringxs:doublexs:booleanxs:booleanxs:stringxs:stringxs:stringxs:stringxs:stringxs:doublexs:stringxs:stringxs:stringxs:stringgml:AbstractGeometryTypexs:stringxs:stringxs:stringxs:intxs:intxs:intxs:doublexs:doublexs:floatxs:stringxs:stringxs:stringxs:stringxs:intxs:intxs:stringxs:doublexs:stringxs:stringxs:stringxs:booleanxs:stringxs:stringxs:stringxs:stringxs:floatxs:stringxs:longxs:dateTimexs:dateTimexs:stringxs:stringxs:stringxs:dateTimexs:dateTimexs:stringxs:stringxs:stringxs:stringxs:floatxs:stringxs:stringxs:stringxs:stringxs:intgml:AbstractGeometryTypexs:booleanxs:stringxs:stringxs:doublexs:stringxs:stringxs:doublexs:stringxs:stringxs:doublexs:stringxs:stringxs:intxs:intxs:intxs:booleanxs:doublexs:doublexs:stringxs:stringxs:stringxs:stringxs:stringxs:stringgml:AbstractGeometryTypexs:stringxs:doublexs:intxs:doublexs:booleanxs:stringxs:doublexs:intxs:booleanxs:booleanxs:stringxs:stringxs:booleanxs:stringxs:stringxs:doublexs:booleanxs:stringxs:stringxs:stringxs:doublexs:floatxs:stringgml:AbstractGeometryTypexs:stringgml:AbstractGeometryTypexs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:intxs:stringxs:doublexs:doublexs:doublexs:stringxs:stringxs:stringxs:stringxs:stringxs:stringgml:AbstractGeometryTypexs:stringgml:AbstractGeometryTypexs:stringgml:AbstractGeometryTypexs:doublegml:AbstractGeometryTypexs:stringgml:AbstractGeometryTypexs:intxs:stringxs:doublegml:AbstractGeometryTypexs:doublegml:AbstractGeometryTypexs:doublegml:AbstractGeometryTypexs:stringxs:stringxs:booleanxs:stringxs:stringxs:booleanxs:stringxs:stringxs:stringxs:stringxs:doublexs:doublexs:doublexs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:intxs:stringxs:intxs:stringxs:intxs:intxs:stringxs:doublexs:doublexs:doublexs:stringxs:doublexs:floatxs:floatxs:stringxs:booleanxs:stringxs:stringxs:booleanxs:stringxs:stringxs:booleanxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:stringxs:stringxs:stringxs:booleanxs:stringxs:stringxs:stringxs:stringxs:booleanxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:intxs:doublexs:intxs:stringgml:AbstractGeometryTypexs:stringgml:AbstractGeometryTypexs:intxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:booleanxs:booleanxs:stringxs:stringxs:doublexs:stringxs:stringxs:booleanxs:stringxs:booleangml:AbstractGeometryTypexs:booleanxs:booleangml:AbstractGeometryTypexs:booleanxs:stringxs:booleanxs:stringxs:stringxs:booleanxs:stringxs:stringgml:AbstractGeometryTypexs:doublexs:booleangml:AbstractGeometryTypexs:booleangml:AbstractGeometryTypexs:booleangml:AbstractGeometryTypexs:booleanxs:stringxs:stringxs:doublexs:doublexs:stringxs:stringxs:doublexs:stringxs:doublexs:intxs:booleanxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:intxs:stringxs:booleanxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:intxs:stringxs:booleanxs:floatxs:floatxs:booleanxs:floatxs:floatxs:stringxs:stringxs:floatxs:stringxs:booleanxs:stringxs:stringxs:stringxs:stringxs:stringxs:floatxs:stringxs:stringxs:stringxs:intxs:stringxs:stringxs:intxs:stringxs:doublexs:floatxs:stringxs:stringxs:stringxs:stringxs:doublexs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:doublexs:doublexs:stringxs:stringxs:stringxs:doublexs:floatxs:floatxs:longxs:floatxs:floatxs:floatxs:floatxs:floatxs:intxs:floatxs:floatxs:doublexs:stringxs:stringxs:stringxs:doublexs:doublexs:doublexs:longxs:floatxs:floatxs:floatxs:floatxs:floatxs:intxs:floatxs:floatxs:stringgml:AbstractGeometryTypexs:stringgml:AbstractGeometryTypexs:stringgml:AbstractGeometryTypexs:stringxs:stringxs:stringxs:doublexs:intxs:intxs:intxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:doublexs:stringxs:stringxs:doublexs:stringxs:booleanxs:booleanxs:booleanxs:stringxs:stringxs:dateTimexs:stringxs:stringxs:floatxs:stringxs:stringxs:stringxs:floatxs:stringxs:stringxs:stringxs:intgml:AbstractGeometryTypexs:intgml:AbstractGeometryTypexs:intgml:AbstractGeometryTypexs:stringgml:AbstractGeometryTypexs:stringgml:AbstractGeometryTypexs:doublexs:doublexs:booleanxs:booleanxs:booleanxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:stringxs:doublexs:stringxs:intxs:stringxs:longxs:stringxs:stringxs:booleangml:AbstractGeometryTypexs:intxs:doublexs:stringxs:stringxs:stringxs:stringxs:intxs:stringgml:AbstractGeometryTypexs:intxs:stringxs:stringxs:doublexs:stringxs:stringxs:intxs:booleanxs:booleanxs:stringxs:stringxs:intxs:intxs:stringxs:stringxs:stringxs:intxs:booleanxs:stringxs:floatxs:stringxs:doublexs:floatxs:floatxs:stringxs:stringxs:booleanxs:stringxs:stringxs:doublexs:intxs:booleanxs:stringxs:stringxs:stringxs:stringxs:doublexs:stringxs:stringxs:intxs:stringxs:stringxs:doublexs:stringxs:stringxs:stringxs:floatxs:stringxs:booleanxs:stringxs:stringxs:intxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:stringxs:stringxs:stringxs:booleangml:AbstractGeometryTypegml:AbstractGeometryTypexs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:doublexs:stringxs:doublexs:floatxs:floatxs:floatxs:longxs:floatxs:doublexs:floatxs:stringxs:stringxs:floatxs:stringxs:stringxs:stringxs:doublexs:doublexs:doublexs:doublexs:stringxs:stringgml:AbstractGeometryTypexs:stringxs:stringxs:stringxs:doublexs:stringxs:stringxs:doublexs:booleanxs:doublexs:floatxs:intxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:doublexs:doublexs:floatxs:stringxs:doublexs:intxs:booleanxs:doublexs:stringxs:stringxs:stringxs:stringxs:stringxs:intxs:intxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:stringxs:stringxs:booleanxs:stringxs:stringxs:intxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:intxs:stringxs:stringxs:intxs:stringxs:booleanxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:booleanxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:intxs:intxs:stringxs:stringxs:intxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:booleanxs:stringxs:stringxs:stringxs:stringgml:AbstractGeometryTypegml:AbstractGeometryTypexs:doublexs:floatxs:stringxs:stringxs:doublexs:doublexs:floatxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:doublexs:stringxs:stringxs:doublexs:floatxs:booleangml:AbstractGeometryTypegml:AbstractGeometryTypexs:stringgml:AbstractGeometryTypexs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:intxs:stringgml:AbstractGeometryTypegml:AbstractGeometryTypexs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:doublexs:intxs:booleanxs:stringxs:stringxs:intxs:intxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringxs:stringgml:AbstractGeometryTypexs:stringxs:stringxs:stringxs:booleangml:AbstractGeometryTypegml:AbstractGeometryType