Quantifying natural capital along the Portuguese continental shelf

This study was published by authors from a range of universities and research institutes. The lead author is a representative of the Department of Biology of Universidade de Aveiro, a Portuguese university.

Researchers were aiming to complete a marine biological valuation for the Portuguese continental shelf, in line with the Marine Biological Valuation protocol to support the European Marine Strategy Framework Directive (MSFD) environmental status assessment and national marine spatial planning approaches. In order to achieve this, the authors used methodology previously applied to terrestrial systems, compiled a database of information on ecosystem components and their spatial overlap with current and proposed protected areas. To feed into this, the authors required information on benthic habitats and the environmental factors such as oceanographic conditions and local hydrodynamics which may impact these habitats.

EMODnet provided broad-scale predictive habitat maps for the Portuguese continental shelf study area. Data on substrate and biological zone were selected as attributes to be overlaid with the users maps depicting “Biological Value.” As the habitat data were classified according to the EUNIS system, this provided a common and comparable European reference set of habitat types, as well as providing environmental data affecting habitat type within the data layer. The ease of access and suitable format of the data therefore provided a solution that was both time and cost effective to the users. The resultant maps describe and identify areas of particular value, which were in line with the expected and previously determined patterns of physical and biological oceanographic conditions.

This study highlights the value of currently unprotected sites and identifies areas to be considered for the potential designation of future marine protected areas.  The work also demonstrates the use of biological valuation maps as a tool to compile and analyse spatial biological datasets. The authors also discussed the potential use of this tool in making spatially-appropriate decisions in marine planning, such as in the allocation of areas for human activities.