title: Spatial modeling of environmental vulnerability of marine finfish aquaculture using GIS-based neuro-fuzzy techniques.
abstract: Combining GIS with neuro-fuzzy modeling has the advantage that expert scientific knowledge in coastal aquaculture activities can be incorporated into a geospatial model to classify areas particularly vulnerable to pollutants. Data on the physical environment and its suitability for aquaculture in an Irish fjard, which is host to a number of different aquaculture activities, were derived from a three-dimensional hydrodynamic and GIS models. Subsequent incorporation into environmental vulnerability models, based on neuro-fuzzy techniques, highlighted localities particularly vulnerable to aquaculture development. The models produced an overall classification accuracy of 85.71%, with a Kappa coefficient of agreement of 81%, and were sensitive to different input parameters. A statistical comparison between vulnerability scores and nitrogen concentrations in sediment associated with salmon cages showed good correlation. Neuro-fuzzy techniques within GIS modeling classify vulnerability of coastal regions appropriately and have a role in policy decisions for aquaculture site selection.
authors.affiliation: Institute of Aquaculture, University of Stirling, Stirling FK9 4LA, UK. juralon5@hotmail.com
authors.forename: Juan Moreno
authors.initials: JM
authors.lastname: Navas
authors.forename: Trevor C
authors.initials: TC
authors.lastname: Telfer
authors.forename: Lindsay G
authors.initials: LG
authors.lastname: Ross
mesh_terms: D004784:Environmental Monitoring / Q000379:methods* / Q000706:statistics & numerical data; D005398:Fisheries; D017143:Fuzzy Logic; D040362:Geographic Information Systems; D007494:Ireland; D008386:Marine Biology / Q000379:methods*; D008954:Models, Biological; D009584:Nitrogen / Q000032:analysis
chemical_list: D009584:Nitrogen