AUTHOR=Aguzzi Jacopo , Chatzievangelou Damianos , Robinson Nathan J. , Bahamon Nixon , Berry Alan , Carreras Marc , Company Joan Batista , Costa Corrado , del Rio Fernandez Joaquin , Falahzadeh Ahmad , Fifas Spyros , Flögel Sascha , Grinyó Jordi , Jónasson Jonas Pall , Jonsson Patrik , Lordan Colm , Lundy Mathieu , Marini Simone , Martinelli Michela , Masmitja Ivan , Mirimin Luca , Naseer Atif , Navarro Joan , Palomeras Narcis , Picardi Giacomo , Silva Cristina , Stefanni Sergio , Vigo Maria , Vila Yolanda , Weetman Adrian , Doyle Jennifer TITLE=Advancing fishery-independent stock assessments for the Norway lobster (Nephrops norvegicus) with new monitoring technologies JOURNAL=Frontiers in Marine Science VOLUME=9 YEAR=2022 URL=https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2022.969071 DOI=10.3389/fmars.2022.969071 ISSN=2296-7745 ABSTRACT=

The Norway lobster, Nephrops norvegicus, supports a key European fishery. Stock assessments for this species are mostly based on trawling and UnderWater TeleVision (UWTV) surveys. However, N. norvegicus are burrowing organisms and these survey methods are unable to sample or observe individuals in their burrows. To account for this, UWTV surveys generally assume that “1 burrow system = 1 animal”, due to the territorial behavior of N. norvegicus. Nevertheless, this assumption still requires in-situ validation. Here, we outline how to improve the accuracy of current stock assessments for N. norvegicus with novel ecological monitoring technologies, including: robotic fixed and mobile camera-platforms, telemetry, environmental DNA (eDNA), and Artificial Intelligence (AI). First, we outline the present status and threat for overexploitation in N. norvegicus stocks. Then, we discuss how the burrowing behavior of N. norvegicus biases current stock assessment methods. We propose that state-of-the-art stationary and mobile robotic platforms endowed with innovative sensors and complemented with AI tools could be used to count both animals and burrows systems in-situ, as well as to provide key insights into burrowing behavior. Next, we illustrate how multiparametric monitoring can be incorporated into assessments of physiology and burrowing behavior. Finally, we develop a flowchart for the appropriate treatment of multiparametric biological and environmental data required to improve current stock assessment methods.