1. Advancing fishery-independent stock assessments for the Norway lobster (Nephrops norvegicus) with new monitoring technologies
- Author
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Jacopo Aguzzi, Damianos Chatzievangelou, Nathan J. Robinson, Nixon Bahamon, Alan Berry, Marc Carreras, Joan Batista Company, Corrado Costa, Joaquin del Rio Fernandez, Ahmad Falahzadeh, Spyros Fifas, Sascha Flögel, Jordi Grinyó, Jonas Pall Jónasson, Patrik Jonsson, Colm Lordan, Mathieu Lundy, Simone Marini, Michela Martinelli, Ivan Masmitja, Luca Mirimin, Atif Naseer, Joan Navarro, Narcis Palomeras, Giacomo Picardi, Cristina Silva, Sergio Stefanni, Maria Vigo, Yolanda Vila, Adrian Weetman, Jennifer Doyle, Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), European Commission, Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica, Universitat Politècnica de Catalunya. Doctorat en Ciències del Mar, and Universitat Politècnica de Catalunya. SARTI-MAR - Sistemes d'Adquisició Remota de dades i Tractament de la Informació en el Medi Marí
- Subjects
Biomimicking platforms ,Global and Planetary Change ,Norway lobster ,Optoacoustic imaging ,Autonomous networks ,Ocean Engineering ,Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo [Àrees temàtiques de la UPC] ,Aquatic Science ,Oceanography ,Stocks monitoring ,Nephrops norvegicus ,Biological monitoring ,Escamarlà ,UWTV ,Geo-sonars ,Nephrops norvegicus [Norway lobster] ,Fish and Aquacultural Science ,Seguiment biològic ,Enginyeria agroalimentària::Ciències de la terra i de la vida::Zoologia [Àrees temàtiques de la UPC] ,Enginyeria electrònica::Instrumentació i mesura [Àrees temàtiques de la UPC] ,eDNA ,Water Science and Technology - Abstract
18 pages, 8 figures, supplementary material https://www.frontiersin.org/articles/10.3389/fmars.2022.969071/full#supplementary-material, 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, The present research was carried out within the framework of the activities of the Spanish Government through the “Severo Ochoa Centre Excellence” accreditation to ICM-CSIC (CEX2019-000928-S) and the Research Unit Tecnoterra (ICM-CSIC/UPC). Other projects that supported the work were those of the Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 of the Spanish government: BITER-LANDER (PID2020-114732RB-C32); BITER-ECO (PID2020-114732RB-C31); BITER-AUV (PID2020-114732RB-C33); PLOME (PLEC2021-007525/AEI/10.13039/501100011033). Moreover, part of the conceptual development, falls within the framework of EU LIFE Project ECOREST (LIFE20 NAT/ES/001270), which also funded DC. SaF acknowledges the HGF-project (Helmholtz-Future Topic Project) ARCHES (Autonomous Robotic Networks to Help Modern Societies) and HGF POF IV funding for conducting this research. NR was funded by the Spanish Government (Agencia Española de Investigación; AEI) through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)
- Published
- 2022
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