Summary This study evaluates the variation in population abundance overtime of twenty commercial fish species associated with an artificial reef and a reference site. Mean yearly catch rates were computed from data collected monthly from 1988 to 2012 using trammel nets. The log‐transformed ratios of catches obtained at the reef and the reference site were calculated for each species. Statistical methods employed to study the changes in abundance of such fish species were multidimensional scaling (MDS), Min/Max Auto‐correlation Factor Analysis (MAFA), Dynamic Factor Analysis (DFA) and chronological clustering. The time‐series analyses were performed on three groups of species showing similar patterns of temporal cross‐correlation. These time‐series analytical techniques were utilized to identify common trends, the influence of some environmental variables, and changes in group trends. The analyses indicated a decreasing trend in the catch ratio for two species groups (mostly reef‐dwelling species) while the third species group indicated an inverse pattern. Changes in the trends of abundance in some species were likely related to the general deterioration of the artificial reef modules.

The spatial distribution of fish assemblages was investigated through either hydro-acoustic surveys (using a Multibeam Echosounder) or fishing surveys (using trammel nets) carried out at increasing distance from two gas extraction structures in the Adriatic Sea and characterized by different building architecture: one, a four-leg platform; the other a subsea well-site. Both types of surveys were monthly and performed for 1 year starting after installation of the structures. Primary scope of the study was to evaluate whether the combination of the two methodologies could provide a more comprehensive insight into the fish communities associated with artificial structures. The findings showed that associating the Multibeam Echosounder survey with the fishing survey provided complementary information on the spatial distribution and abundance of fish in the water column surrounding the artificial structures. Both methodologies evidenced the presence of a greater abundance and biomass of fish close to the structures in respect to reference sites. In addition, fish abundance and biomass were generally greater in the surroundings of the four-leg platform than at the well-site, a possible consequence of the larger volume of the former.

ABSTRACT:Artificial reefs (ARs) have become popular technological interventions in shallow water environments characterized by soft seabed for a wide number of purposes, from fisheries/environmental protection and enhancement to research and tourism. AR deployment has the potential for causing significant hydrographical and biological changes in the receiving environments and, in turn, ARs are strongly affected by the surrounding area in terms of spatial arrangement and structural integrity as well as colonization by benthic communities and finfish. In this context, ARs require a systematic monitoring program that a multibeam echosounder (MBES) can provide better than other sampling methods such as visual dives and ROV inspections that are not quantitative and often influenced by water visibility and diver experience/skills. In this paper, some subsequent MBES surveys of the Senigallia scientifically-planned AR (Northern Adriatic Sea) are presented and state-of-the art data processing and visualization techniques are used to draw post-reef deployment comparisons and quantify the evolution of the reef in terms of spatial arrangement and bulk volume. These multibeam surveys play a leading part in a general multi-year program, started simultaneously with the AR design and deployment and aimed to map how the reef structure quantitatively changes over time, as well as it affects the sea-bottom morphology and the fishery resource. All the data, surveyed over years making use of different sampling methods such as visual and instrumental echosounding observations and catch rate surveys, gain a mechanistic and predictive understanding of how the Senigallia AR functions ecologically and physically across spatial and temporal scales during its design life.