Experiments using ‘DeepVison’ technology to gather real-time information that will reduce pre-catch losses, along with developing the use of fishing closures in nursery areas.
MINOUW partner & Lead scientist:
CIBM (Consorzio per il Centro Interuniversitario di Biologia marina ed Ecologia Applicata), Mario Sbrana
Fishing method and species:
Bottom trawl with 40-mm square mesh or 50-mm diamond mesh cod-ends. Species targeted are European Hake (Merluccius merluccius), Red Mullet (Mullus barbatus), Red Shrimp (Aristemorpha foliacea and Aristeus antennatus), Norway lobster (Nephrops norvegicus), and Deep Water Rose Shrimp (Parapenaeus longirostris).
What is the discards problem?
The Ligurian and Tyrrhenian bottom otter trawl fisheries are characterised by problems that affect most Mediterranean fisheries: multi-specific composition of the catch and the presence of a large number of juveniles of commercial species that are subject to minimum legal size. In particular, the area is characterised by important nurseries of European hake, where the concentration of juveniles is especially high. Mediterranean discards are particularly abundant in cases of low commercial value species.
What activities did the MINOUW project carry out?
- Experimental surveys using the DeepVision system to gather real time information on species and size composition in order to minimize the pre-catch losses/mortality.
- To assess how the use of DeepVision can be beneficial in collecting information on mixed species bottom trawl fisheries.
- To improve the development and implementation of real time fishing closures in nursery areas (e.g. Merluccius merluccius) and essential fish habitats in the Ligurian and Tyrrhenian Seas.
What outcomes were expected?
- Successful use of DeepVision to characterise potential catch composition in a mixed species bottom trawl fishery.
- To promote nursery areas and essential fish habitats protection and real time closures.
- Foster fishers’ involvement in the process of finding solutions to mitigate the impact of the Landings Obligation in their activity.
Deep Vision technology can be considered as a way to improve standard surveys which rely on retaining and physically measuring the catch but (currently) with a cost in time needed to analyse images.