Bayesian spatio-temporal approach to identifying fish nurseries by validating persistence areas
2015
Paradinas, Iosu | Conesa, David | Pennino, M. Grazia | Munoz, Facundo | Fernandez, Angel M. | Lopez-Quilez, Antonio | Maria Bellido, Jose | Departament d’Estadística i Investigació Operativa ; Universitat de València = University of Valencia (UV) | Ecosystèmes Marins Exploités (UMR EME) ; Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Montpellier (UM) | Unité de recherche Amélioration, Génétique et Physiologie Forestières (AGPF) ; Institut National de la Recherche Agronomique (INRA) | Centro Oceanográfico de Murcia ; Instituto Español de Oceanografía - Spanish Institute of Oceanography (IEO) ; Consejo Superior de Investigaciones Cientificas [España] = Spanish National Research Council [Spain] (CSIC)-Consejo Superior de Investigaciones Cientificas [España] = Spanish National Research Council [Spain] (CSIC) | Centro Oceanográfico de Murciain ; Instituto Español de Oceanografía - Spanish Institute of Oceanography (IEO) ; Consejo Superior de Investigaciones Cientificas [España] = Spanish National Research Council [Spain] (CSIC)-Consejo Superior de Investigaciones Cientificas [España] = Spanish National Research Council [Spain] (CSIC)
Spatial and temporal closures of fish nursery areas to fishing have recently been recognized as useful tools for efficient fisheries management, as they preserve the reproductive potential of populations and increase the recruitment of target species. In order to identify and locate potential nursery areas for spatio-temporal closures, a solid understanding of species-environment relationships is needed, as well as spatial identification of fish nurseries through the application of robust analyses. One way to achieve knowledge of fish nurseries is to analyse the persistence of recruitment hotspots. In this study, we propose the comparison of different spatio-temporal model structures to assess the persistence of a spatial process. In particular, we apply our approach to a 2-stage Bayesian hierarchical spatio-temporal model that describes both the occurrence and the abundance of European hake Merluccius merluccius recruits in the western Mediterranean Sea. Results clearly show areas of high occurrence and abundance, mainly along the shelf break and the upper slope of the Spanish Mediterranean coast. Understanding the distributional patterns associated with key life stages such as recruitment is essential for appropriate spatial management, including the implementation of Fisheries Restricted Areas and/or Marine Protected Areas that improve the management of fishery resources.
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