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Sanchez-Carnero N.,University of La Coruna | Rodriguez-Perez D.,Spanish University for Distance Education (UNED) | Counago E.,Kartenn | Acena S.,University of La Coruna | Freire J.,University of La Coruna
Estuarine, Coastal and Shelf Science | Year: 2012

An acoustic method, a vertically oriented Sidescan Sonar (SSSv), is used to detect and map Posidonia oceanica meadows in the bay of Agua Amarga (SE of the Mediterranean coast of Spain). Sidescan sonar, among other active hydroacoustic techniques, has shown its ability to detect, map and monitor seagrass based on its acoustic backscatter; however, some limitations linked to its power based approach have been reported in the literature. Our method is based on the SSSv measurement of canopy height distribution, making the most use of the SSSv acoustic data and using existing algorithms as statistical mapping methods. The results show a spatially coherent and statistically consistent classification. The comparison with groundtruthing is difficult due to the steep variations in the seafloor cover found in the area of interest, nevertheless the validation is successful (proving low-order discrimination) in a zone with a large range of depth variations (0-25 m). © 2012 Elsevier Ltd. Source


Sanchez-Carnero N.,University of Vigo | Rodriguez-Perez D.,Spanish University for Distance Education (UNED) | Counago E.,Kartenn | Le Barzik F.,Kartenn | Freire J.,Kartenn
Ocean and Coastal Management | Year: 2016

Habitat suitability (HS) of target species is assessed in the coastal region of Seno de Corcubión, including Os Miñarzos Marine Protected Area (MPA) in west Galicia, NW of Spain. Current MPA was outlined using local environmental knowledge (LEK). Our objective is to test whether maximization of HS of 12 species would select the same MPA as fishers' LEK. A detailed capture database and 13 layers summarizing ecogeographic variables (derived from bathymetry, satellite data and sea bottom classification map) have been used and several Ecological Niche Factor Analysis (ENFA) Species Distribution Models (SDM) have been tested to find the best HS prediction (according to a nonparametric index due to Boyce). Our SDM results show that the LEK defined MPA (comprising 20% of the total area) is over 70% more suitable than the rest of the region for all species but one (European seabass, only 40%). We conclude that stakeholders LEK methodology correctly identifies local species habitats, and that SDM, and in particular ENFA models, can be used to validate and keep track of the MPA boundaries. © 2016 Elsevier Ltd. Source

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