NetCDF (Network Common Data Form)
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Gridded abundance maps of marine mammals (sperm whale, short beaked common dolphin, common bottlenose dolphin, Atllantic spotted dolphin) around the Azores. This product was developed with DIVA (Data-Interpolating Variational Analysis). Data was provided by the Azores Fisheries Observation Programme (POPA).
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Gridded abundance map of Caretta caretta around the Azores between 1998 and 2002. This product was developed with DIVA (Data-Interpolating Variational Analysis). Data was provided by the Azores Fisheries Observation Programme (POPA).
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Gridded abundance maps of marine birds from the North Sea. All the bird species of this dataset are indicator species for Descriptor 1 Biodiversity of the MSFD for the North East Atlantic. This product was developed with DIVA (Data-Interpolating Variational Analysis). Data was provided by JNCC (Joint Nature Conservation Committee): Dunn, T. 2012. JNCC seabird distribution and abundance data (all trips) from ESAS database. Data downloaded from OBIS-SEAMAP (http://seamap.env.duke.edu/dataset/427).
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Gridded abundance maps of seal species. This product was developed with DIVA (Data-Interpolating Variational Analysis). Data was provided by JNCC (Joint Nature Conservation Committee): Dunn, T. 2012. JNCC seabird distribution and abundance data (all trips) from ESAS database. Data downloaded from OBIS-SEAMAP (http://seamap.env.duke.edu/dataset/427).
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Gridded abundance map of marine birds around the Azores. This product was developed with DIVA (Data-Interpolating Variational Analysis). Data was provided by the Azores Fisheries Observation Programme (POPA).
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This data product is a series of gridded abundance maps for 40 zooplankton species from 2007 to 2013 in the Baltic Sea, based on a neural network analysis. As input data a combination of EMODnet Biology datasets were used, together with the environmental variables dissolved oxygen, salinity, temperature, chlorophyll concentration bathymetry and the distance from coast. Additionally the position (latitude and longitude) and the year are provided to the neural network. DIVAnd (n-dimensional Data-Interpolating Variational Analysis) and the neural network library Knet were used in this analysis.
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The project aims to produce comprehensive data product of the occurence and absence of (phyto)plankton species. As a basis, data from EMODnet Biology are used. The selection of relevant datasets is optimized in order to find all planktonic species, and exclude all species that are not planktonic. The occurences from EMODnet Biology were complemenented with absence data assuming fixed species lists within each dataset and year. The products are presented as maps of the distribution of the 20 most common species of (phyto)plankton in the Greater Baltic Sea.
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Probability of occurrence of different macroinvertebrate benthic species in the North Sea. This product was created using DIVAnd, an interpolation method that takes into account several environmental variables and physical coastlines.
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Gridded abundance maps representing Dinophysis species, phytoplankton taxon richness and algal toxicity along the French coast. This product was developed with DIVA (Data-Interpolating Variational Analysis). Data was provided by IFREMER (REPHY - réseau de surveillance du phytoplancton. Institut Français pour la Recherche et l'exploitation de la mer, Nantes, France.).
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Gridded abundance maps representing diatoms and dinoflagellates in the North Atlantic and North Sea between 1958 and 2012. Phytoplankton organisms are responsible for about 45% of annual global photosynthesis. They are as such vital for the functioning of marine food webs (considered in MSFD descriptor 4) and are the main drivers of the global biogeochemical cycles. This product was developed with DIVA (Data-Interpolating Variational Analysis) and the scale represents log-transformed abundance. Data was provided by SAHFOS (Continuous Plankton Recorder (CPR) data (phytoplankton) from the Sir Alister Hardy Foundation for Ocean Science (SAHFOS)).