This dataset provides a raster layer (.img format) with the predicted distribution of the gorgonian Eunicella cavolini (Koch, 1887) on the continental shelf and submarine canyon off Cap de Creus (NW Mediterranean), an area included in a Site of Community Importance (SCI) of the Natura 2000 Network. The algorithm Random Forest (RF) was used to model areas suitable for the development of the species based on a combination of species density data extracted from 60 underwater video transects (80 to 400 m depth) and a set of environmental factors of a geomorphologic, oceanographic and human nature. The RF model predicted the presence of the species (densities of at least 1 col·m-2) in 1,061 ha along the whole modelled area, with 14 ha potentially hosting gorgonian densities above 5 col·m-2 and 4.9 ha with densities exceeding 10 col·m-2. The variability explained by the model was 70.1%, although a cross-validation assessment indicated that the variability explained could be lower, denoting some degree of spatial autocorrelation of the data within the underwater dives. Based on the percentage increase in mean squared error of the model used for predictions, the most important variables determining the likelihood of finding high-density patches of E. cavolini in the study area were average bottom current velocity, depth and rugosity of the seafloor (calculated as TRI, Terrain Ruggedness Index). This study provides relevant information about the spatial distribution of E. cavolini inside a recently declared marine protected area of NW Mediterranean, which could be used by policymakers when formulating specific management measures for the conservation of this species within the SCI.
This dataset is related to the article “Environmental niche, spatial distribution and size structure of shelf-dwelling populations of the gorgonian Eunicella cavolini (Koch, 1887) in NW Mediterranean” submitted to Estuarine, Coastal and Shelf Science by Dominguez-Carrió et al., which contains further information on how the data were obtained and processed.
