In the last decades the ecological role of off-shore platforms as a suitable habitat for fish species has been acknowledged in the context of marine conservation and investigated by an increasing number of studies. Fish communities associated with these artificial structures have been analyzed by different approaches such as hydroacoustic surveys, experimental fishing and remotely operated vehicles (ROVs) in many areas of the world. These techniques were generally used separately providing both qualitative and quantitative data at a different level of accuracy.

In the present project, fish diversity associated with Mediterranean gas platforms was studied for the first time by integrating four different methods. More in detail, fishing surveys, video recordings from remotely operated vehicles (ROVs), remote sensing and underwater visual census (UVC) by means of SCUBA divers were employed.

This multi-technique approach allowed for the collection of complementary data and a complete characterization of the fish community. Fish diversity resulted higher than would have been by using each method separately. The use of innovative techniques (ROV, UVC and Remote Sensing) permitted to explore the inner part of the platforms which is typically difficult to study. More in detail, UVC was the most efficient technique to census fish species strictly associated with the pillars. This technique allowed for the censusing of crypto-benthic fish species which represented an important and generally unnoticed component of the biodiversity associated with these structures. These species, which use these artificial structures as a trophic and reproductive substrate, accounted for the 22% of the total species richness. The contemporary application of different techniques to study the platforms fish community allowed also for an evaluation of limits and potentialities of each method also in relation to their costs and scientific outputs. This information can be easily used to formulate investigation protocols also replicable in other areas.

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