The distribution of deep-sea sponge aggregations in the North Atlantic and implications for their effective spatial management.

Video and image data are regularly used in the field of benthic ecology to document biodiversity. However, their use is subject to a number of challenges, principally the identification of taxa within the images without associated physical specimens. The challenge of applying traditional taxonomic keys to the identification of fauna from images has led to the development of personal, group, or institution level reference image catalogues of operational taxonomic units (OTUs) or morphospecies. Lack of standardisation among these reference catalogues has led to problems with observer bias and the inability to combine datasets across studies. In addition, lack of a common reference standard is stifling efforts in the application of artificial intelligence to taxon identification. Using the North Atlantic deep sea as a case study, we propose a database structure to facilitate standardisation of morphospecies image catalogues between research groups and support future use in multiple front-end applications. We also propose a framework for coordination of international efforts to develop reference guides for the identification of marine species from images. The proposed structure maps to the Darwin Core standard to allow integration with existing databases. We suggest a management framework where high-level taxonomic groups are curated by a regional team, consisting of both end users and taxonomic experts. We identify a mechanism by which overall quality of data within a common reference guide could be raised over the next decade. Finally, we discuss the role of a common reference standard in advancing marine ecology and supporting sustainable use of this ecosystem.

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The distribution of deep-sea sponge aggregations (Porifera) in relation to oceanographic processes in the Faroe-Shetland Channel.

Studies reporting processes that may shape marine benthic communities under the seasonal scale are rare at depths >50 m. In this study, the use of the VENUS multidisciplinary cabled observatory provided 2-month high-resolution data combining quantitative biology and environmental data in Saanich Inlet, a seasonally hypoxic fjord located on Vancouver Island (British Columbia, Canada). An ecological module equipped with a camera acquired a 3 min video clip every half hour during 2 months at 97 m depth in the oxygen fluctuation zone of the fjord. Results highlighted the role of the tidal cycle on species activity rhythms and confirmed the influence of oxygen fluctuations on benthic assemblage structure and species behaviour. However, environmental variables considered only explained a small proportion of the total variance in species data. This study demonstrates how seafloor observatories can be used to study species behaviour and community dynamics in relation to abiotic conditions by providing continuous access to multidisciplinary data. Résumé :Les études sur les processus qui influencent la structure des communautés marines benthiques profondes (>50 m) à des échelles inférieures aux saisons sont rares. Dans cet article, l'utilisation de l'observatoire multidisciplinaire câblé VENUS a fourni 2 mois de données haute fréquence combinant des données quantitatives biologiques et environnementales dans le Saanich Inlet, un fjord hypoxique saisonnier localisé sur l'île de Vancouver (Colombie-Britannique, Canada). Un module écologique a enregistré des séquences vidéo de 3 min toutes les demi-heures pendant 2 mois à 97 m de profondeur dans la zone de fluctuation d'oxygène. Les résultats ont permis de mettre en évidence le rôle des cycles de marées sur l'activité rythmique des espèces et ont confirmé le rôle des variations temporelles des concentrations en oxygène sur la structure des assemblages faunistiques et le comportement des espèces benthiques. Cependant, les variables environnementales considérées expliquent une faible proportion de la variance. Cette étude démontre comment les observatoires sous-marins permettent d'étudier le comportement des espèces et la dynamique des communautés benthiques en relation avec les facteurs abiotiques, en fournissant un accès continu à des données multidisciplinaires.

Predictive modelling of deep-sea species and assemblages with multibeam acoustic datasets as input variables is now a key tool in the provision of maps upon which spatial planning and management of the marine environment can be based. However, with a multitude of methods available, advice is needed on the best methods for the task at hand. In this study, we predictively modelled the distribution and extent of three vulnerable marine ecosystems (VMEs) at the assemblage level ('Lophelia pertusa reef frameworks'; 'Stylasterids and lobose sponges'; and 'Xenophyophore fields') on the eastern flank of Rockall Bank, using three modelling methods: MaxEnt; RandomForests classification with multiple assemblages (gRF); and RandomForests classification with the presence/absence of a single VME (saRF). Performance metrics indicated that MaxEnt performed the best, but all models were considered valid. All three methods broadly agreed with regard to broad patterns in distribution. However, predicted extent presented a variation of up to 35 % between the different methods, and clear differences in predicted distribution were observed. We conclude that the choice of method is likely to influence the results of predicted maps, potentially impacting political decisions about deep-sea VME conservation.

Marine optical imaging has become a major assessment tool in science, policy and public understanding of our seas and oceans. Methodology in this field is developing rapidly, including hardware, software and the ways of their application.