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.

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.

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.

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.

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.

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.

Data represents the distribution of seagrass (eelgrass, Zostera marina) in an area on the West coast of Norway. The model can be inquired via e-mail to trine.bekkby@niva.no.