Prediction of benthic biotopes on a Norwegian offshore bank using a combination of multivariate analysis and GIS classification

Abstract

Abstract Mortensen, P. B., Dolan, M., and Buhl-Mortensen, L. 2009. Prediction of benthic biotopes on a Norwegian offshore bank using a combination of multivariate analysis and GIS classification. – ICES Journal of Marine Science, 66: 2026–2032. This study is part of the multidisciplinary seabed mapping programme MAREANO (Marine AREAdatabase for NOrwegian coast and sea areas). The mapping programme includes acquisition of multibeam bathymetry and acoustic backscatter data together with a comprehensive, integrated biological and geological sampling programme. The equipment used includes underwater video, boxcorer, grab, hyperbenthic sled, and beam trawl. The Tromsøflaket offshore bank was used as a case-study area to develop suitable methods for mapping habitats and biotopes. A procedure for producing maps of predicted biotopes is described that combined information on the distribution of biological communities with environmental factors and indicators. Detrended correspondence analysis (DCA) was used to relate bottom environment [including multiscale physical descriptors of the seabed derived from multibeam echosounder (MBES) data] and faunal distribution to find the best physical biotope descriptors. DCA of 252 video samples (sequences 200 m long) revealed six groups of locations representing different biotopes. These were characterized by different compositions of species, substrata, depths, and values for terrain parameters. Prediction of biotope distribution was performed using a supervised GIS classification with the MBES-derived physical seabed descriptors with the strongest explanatory ability (depth, backscatter, and broad-scale bathymetric position index) identified by the DCA. The species diversity of the identified biotopes was described from the content of the bottom samples. For future MAREANO cruises, an important task will be to ground-truth predictions of habitat and biotopes and to test the reliability of these predictions in the wider MAREANO area.