Abstract:
The primary aim of this PhD project was to improve the knowledge about the spatio-temporal dynamics of trawl fishing activities in the Northern and Central Adriatic Sea (GSA17). This area has been recognised as one of the most exploited within the Mediterranean basin and for this reason the assessment of the fishing effort results to be an important element for the implementation of new management strategies. The use of Automatic Identification System (AIS) data, available for vessels with a length overall (LOA) over 15 m, played a key role for the investigation of this topic. Indeed, this system, conceived for navigation security reasons, provides high spatio-temporal resolution information about the fishing vessel distribution and activities. Considering the characteristics of the Adriatic fishing segments, and since the trawl fishery is one of the most negatively impacting fishing techniques, the entire study was focused on the trawl fleet, and in particular on Small and Large Bottom Otter Trawl, Rapido Trawl (a sort of beam trawl) and Mid-Water Pair Trawl. The main aims of this project are:
1. the evaluation of the fishing effort, estimated by using an innovative method considering the fishing tracks of the vessels and the swept area, in order to identify the main fishing grounds and the seasonal behaviour of the different fishing techniques;
2. the catches assessment on a spatial basis, associated with fishing effort and economic value in order to better understand the fishermen behaviours and the efficiency of the selected fishing segments;
3. the estimation of the carbon dioxide (CO2) emissions, by using a bottom-up approach (AIS-based method), and the emissions associated with landing data in order to assess the impact produced to catches commercial species (kg CO2 per kg landing).
Overall, this research project supplied new insights in a context of sustainable fishery management, providing useful information for the monitoring and the assessment of the trawl fishing activities in the Adriatic Sea.
