|Advancing fishery-independent stock assessments for the Norway lobster (Nephrops norvegicus) with new monitoring technologies|Aguzzi, J.; Chatzievangelou, D.; Robinson, N.J.; Bahamon, N.; Berry, A.; Carreras, M.; Company, J.B.; Costa, C.; del Rio Fernandez, J.; Falahzadeh, A.; Fifas, S.; Flögel, S.; Grinyó, J.; Jónasson, J.P.; Jonsson, P.; Lordan, C.; Lundy, M.; Marini, S.; Martinelli, M.; Masmitja, I.; Mirimin, L.; Naseer, A.; Navarro, J.; Palomeras, N.; Picardi, G.; Silva, C.; Stefanni, S.; Vigo, M.; Vila, Y.; Weetman, A.; Doyle, J. (2022). Advancing fishery-independent stock assessments for the Norway lobster (Nephrops norvegicus) with new monitoring technologies. Front. Mar. Sci. 9: 969071. https://dx.doi.org/10.3389/fmars.2022.969071
In: Frontiers in Marine Science. Frontiers Media: Lausanne. ISSN 2296-7745, meer
Nephrops norvegicus; UWTV; stocks monitoring; autonomous networks; biomimicking platforms; optoacoustic imaging; geo-sonars; eDNA
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 AItools 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.