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Habitats and biotopes

1063 record(s)
 
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    This layer shows the current known extent and distribution of live hard coral cover in European waters, collated by EMODnet Seabed Habitats. The point and polygon layers were last updated in 2023. Lophelia pertusa and Coral gardens are both on the OSPAR List of threatened and/or declining species and habitats. The purpose was to produce a data product that would provide the best compilation of evidence for the essential ocean variable (EOV) known as Hard coral cover and composition (sub-variable: Live hard coral cover and extent), as defined by the Global Ocean Observing System (GOOS). This data product should be considered a work in progress and is not an official product.

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    This layer shows the current known extent and distribution of macroalgal canopy in European waters, collated by EMODnet Seabed Habitats. The points were added in Sept 2021, and both the points and polygons were updated in 2023. The purpose was to produce a data product that would provide the best compilation of evidence for the essential ocean variable (EOV) known as Macroalgal canopy cover and composition (sub-variable: Areal extent), as defined by the Global Ocean Observing System (GOOS). Kelp and fucoid brown algae are the dominant species that comprise macroalgal forests. This data product should be considered a work in progress and is not an official product.

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    This layer shows the current known extent and distribution of Coralligenous and other calcareous bioconcretions in the Mediterranean, this was collated most recently in 2023 but was originally created in 2021 by EMODnet Seabed Habitats. The purpose was to produce a data product that would provide the best compilation of evidence for this habitat, as described in the "Action Plan for the protection of the coralligenous and other calcareous bio-concretions in the Mediterranean". This data product contains large data gaps and should be viewed as incomplete.

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    This layer shows the current known extent of biogenic substrate in European waters. This product was first produced in 2021 with the aim to add a new class of substrate into the EUSeaMap substrate layer. This was required in order to classify the EUSeaMap broad-scale habitat map according to the 2019 version of the EUNIS habitat classification system, which includes a biogenic substrate category. This layer has been updated in 2023 to feed into an updated version of EUSeaMap.

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    The aim of the National Program for Mapping Biodiversity – Coast is to provide Norwegian managers and planners with maps of the distribution of marine habitats and key areas for species. The kelp was identified in the field using underwater video cameras and GPS and classified according to the routine established in the Norwegian National Program for Mapping Biodiversity – Coast. Kelp forests were defined as moderately dense and dense occurrences of kelp. Areas of kelp forest were modelled using different statistical methods (e.g. GAM, BRT, Maxent) based on point data collected along environmental gradients. These data include only the largest kelp forests.

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    The National Program for Mapping Biodiversity – Coast has had an aim to provide Norwegian managers and planners with maps of the distribution of marine habitats and key areas for species. Maerl beds have not been systematically mapped, but maerl coverage has been recorded whenever maerl has been observed. Maerl has been identified in the field using underwater video cameras and GPS and coverage has been defines into one of four classes (1-single observations, 2-scarce occurrences, 3-Moderately dense, 4-Dense/dominating). For some data, coverage has not been defined, and maerl has only been recorded as a presence. The data has been collected in northern Norway.

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    The aim of the National Program for Mapping Biodiversity – Coast is to provide Norwegian managers and planners with maps of the distribution of marine habitats and key areas for species. Carbonate sand is composed of skeletal fragments from marine organisms, mostly shells, snails, barnacles, sea urchins and calcareous algae, accumulating during the past 10 000 years. Carbonate sand deposits with ongoing production and accumulation were identified through distribution modelling (using statistical methods such as GAM, BRT, Maxent) based on presence–absence data of carbonate sand deposits from grab samples (collected by the Geological Survey of Norway). Depth, wave exposure and ocean current speed were the most important predictors. Polygon areas were derived from the model according to the routine established in the Norwegian National Program for Mapping Biodiversity – Coast.

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    Point data on Saccharina latissima, collected from different sources in the Nordic countries, were used to model the kelp forest distribution by fitting boosted regression trees to the compiled data. The predictors were distance to shore, slope, curvature, aspect, salinity, temperature, light, current speed, sea ice concentration and wave fetch.

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    The project had the aim to map intertidal and subtidal habitats at the Sore Sunnmore area on the West coast of Norway. We collected data points in the intertidal and in the seaweed, kelp and red algae bed in the subtidal. These data were used to model the distribution of different habitats. Habitat data was analysed (using the R package mlogit for Multinomial Logit Models, CRAN - Package mlogit (r-project.org)) against modelled depth, seabed light, salinity, temperature and wave exposure. 30 habitats were modelled, which again was transformed into composite maps, identifying the most dominant habitat/species.

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    Point data on Laminaria hyperborea, collected from different sources in the Nordic countries, were used to model the kelp forest distribution by fitting boosted regression trees to the compiled data. The predictors were distance to shore, slope, curvature, aspect, salinity, temperature, light, current speed, sea ice concentration and wave fetch. The aim of the project was to model the distribution of kelp forests in the Nordic countries in order to identify their ecosystem functions and services, including their role in the carbon cycle.