Résumé
Thanks to the availability of the MEDITS survey data, a standardized picture of the occurrence and abundance of demersal Chondrichthyes in the northern Mediterranean has been obtained. During the spring-summer period between 2012 and 2015, 41 Chondrichthyes, including 18 sharks (5 orders and 11 families). 22 batoids (3 orders and 4 families) and 1 chimaera, were detected from several geographical sub-areas (GSAs) established by the General Fisheries Commission for the Mediterranean. Batoids had a preferential distribution on the continental shelf (10-200 m depth). while shark species were more frequent on the slope (200-800 m depth). Only three species, the Carcharhiniformes Galeus melastomus and Scyliorhinus canicida and the Torpediniformes Torpedo matmorata were caught in all GSAs studied. On the continental shelf, the Rajidae family was the most abundant, being represented in primis by Raja clavaia and then by R. miraleius, R. polystigma and R. asterias. The slope was characterized by the prevalence of G. melastomus in all GSAs, followed by S. canictda, E. spinax and Squalus blainville. Areas under higher fishing pressure, such as the Adriatic Sea and the Spanish coast (with the exception of the Balearic Islands), show a low abundance of chondrichthyans, but other areas with a high level of fishing pressure, such as southwestern Sicily, show a high abundance, suggesting that other environmental drivers work together with fishing pressure to shape their distribution. Results of generalized additive models highlighted that depth is one of the most important environmental drivers influencing the distribution of both batoid and shark species, although temperature also showed a significant influence on their distribution. The approach explored in this work shows the possibility of producing maps modelling the distribution of demersal chondrichthyans in the Mediterranean that are useful for the management and conservation of these species at a regional scale. However, because of the vulnerability of these species to fishing exploitation, fishing pressure should be further incorporated in these models in addition to these environmental drivers.