Sound discrimination of two sympatric, threatened fish species allows for their in situ mapping. Issue 8 (6th May 2021) - Picciulin, Marta; Bolgan, Marta; Facca, Chiara; Fiorin, Riccardo; Riccato, Federico; Malavasi, Stefano
Abstract: Human impacts on marine ecosystems are increasing and the number of fish species listed in the Red List is constantly growing. In the Mediterranean Sea, seven of the 10 bony fishes defined as Threatened by the IUCN are known to be vocal, including the target species of this study: the shi drum ( Umbrina cirrosa Linnaeus, 1758) and the brown meagre ( Sciaena umbra Linnaeus, 1758). As a result, non‐invasive passive acoustic monitoring (PAM) can be used to pinpoint their distribution at sea. However, for PAM to be effective, reliable acoustic discrimination is required because the sounds they emit during reproduction are remarkably similar (i.e. short broadband pulsed sounds). The shi drum and the brown meagre are closely related, elusive, vocal sciaenids, partially overlapping in their ecological niche. During summer 2019, three PAM surveys were conducted along the tidal inlets of the Venice lagoon (Italy). Here, the calls of both species have been recognized according to their temporal features: shi drum sounds were made up of a lower number of longer pulses with a different envelope, repeated at a lower rate than those of the brown meagre. Further, shi drum and brown meagre sounds of different origins (aquaculture and semi‐natural conditions) were analysed and compared with those collected during the survey of the study area in order to validate the field collected data. Call discrimination allowed for a fine‐scale species mapping, showing a partially overlapping distribution of the two species along the inlets. This is the first case in which two sciaenids have been documented to share their reproductive habitat in the Mediterranean Sea. This study demonstrates that it is feasible to acoustically monitor the target species even in those parts of the Mediterranean Sea where they co‐exist. This, in its turn, could provide managers with the required data for effective conservation measures to be implemented.