A SMCE approach to individual site selection and management of aquaculture areas  

Aquaculture is a growing industry worldwide and, according to FAO estimates, its annual production has already overtaken fish catches. Marine aquaculture accounts for a very important fraction of the total production of seafood and is progressively becoming a key component  of a sustainable food supply. The selection of sites/areas allocated to aquaculture plays a key role in supporting the sustainable development of aquafarming within the framework of the Ecosystem Approach to Aquaculture, EAA. To this regard, the identification of Allocated Zone to Aquaculture (AZA), the selection of individual sites and the design of aquaculture management areas are three complex and key issues in the implementation of EAA, which has to be dealt with within the framework of a comprehensive spatial planning. In this paper we propose a general methodology based on Spatial Multi Criteria Evaluation (SMCE), for supporting the identification of AZA, individual site selection and design of shellfish Aquaculture Management Areas (AMAs). SMCE combines the wide range of tools made available by GIS software with Multi Criteria Evaluation techniques, which allows one to obtain a suitability map by overlaying a set of spatially explicit information layers concerning constraints and criteria. This methodology has been recently applied to the identification of fish farming AZA at a regional scale . We applied SMCE to two case studies focusing on individual site selection and AMA design: CS1) selection of seabass/seabream farming sites along the Algerian coastline; CS2) design of an off-shore shellfish AMA along the Adriatic coastline. In both applications we identify constraints on the basis of a spatial analysis of potential conflicts of use with other activities, such as tourism and fishery, presence of MPAs and sensitive habitats, i.e. seagrass meadows. A core set of criteria concerning both biomass production and environmental impact were mapped by combining data from satellite and operational oceanography with simulation models. In CS1, biomass yield and fish farm Zones of Effect, in terms of potentially harmful organic enrichment of surface sediment, were mapped using FiCIM, Fish Cage Integrated Model , using as forcings, SST satellite data and hydrodynamic currents from freely available output of operational oceanographic models. In CS2, time to reach the market size and dry weight at harvest were mapped for both Mediterranean mussel and Pacific Oyster by means of two literature ecophysiological models forced by spatial time series of SST and Chlorophyll a from satellite. The results of these two test cases show that SMCE, supported by satellite data and models, is a flexible methodology for site selection also at local scale, which can be applied also in data poor areas. SMCE will be further tested in the context of the EU funded H2020 project"Aquaspace" ( http://aquaspace-h2020.eu/).