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Autonomous networks for fishery monitoring across marine and inland waters to track exploited stocks of anadromous and catadromous species

Authors :
Aguzzi, Jacopo
Gavrilović, Ana
Chatzievangelou, Damianos
Iveša, Neven
Castellicchio, Antonio
Cukrov, Neven
Costa, Corrado
Francescangeli, Marco
Stefanni, Sergio
Mirimin, Luca
Marini, Simone
Aguzzi, Jacopo
Gavrilović, Ana
Chatzievangelou, Damianos
Iveša, Neven
Castellicchio, Antonio
Cukrov, Neven
Costa, Corrado
Francescangeli, Marco
Stefanni, Sergio
Mirimin, Luca
Marini, Simone
Publication Year :
2022

Abstract

Coordinated systems composed by fixed and mobile robotic platforms are used for the ecological monitoring of megafauna across ecological gradients (oceanographic, geomorphological and substrate characteristics across the bathymetry of the slope and through water column layers) continuously at a high temporal frequency. None of these platforms is branching into estuarine and river areas, providing the coupling of ecological gradients that encompass marine and inland waters. Here, we propose a conceptual scheme to bring forward that integration, by establishing the principles of a network of fixed platforms working not only with HD imaging but also with advanced optoacoustic tools that works in turbid waters. This sensor dotation may be expanded by tools for augmented species presence detection beyond the HD and optoacoustic imaging, such as Passive Acoustic Monitoring and omics approaches (eDNA). Detection by acoustic and molecular markers can be cross-validated against libraries of images. The use of land-docked crawlers may allow stepping-stone observations between patches to spatially scale local data, extending the ecological representativeness of local observations. Those infrastructures may be of a special relevance for legally prescribed monitoring of endangered European eel (Anguilla anguilla), but also for other species, including anadromous Salmo salar in increasingly impacted coastal-river areas

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1395213976
Document Type :
Electronic Resource