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Vertical walls of submarine canyons represent features of high conservation value that can provide natural areas of protection for vulnerable marine ecosystems under increasing anthropogenic pressure from deep-sea trawling. Wall assemblages are spatially heterogeneous, attributed to the high environmental heterogeneity over short spatial scales that is a typical feature of canyons. Effective management and conservation of these assemblages requires a deeper understanding of the processes that affect faunal distribution patterns. Canyons are recognised as sites of intensified hydrodynamic regimes, with focused internal tides enhancing near-bed currents, turbulent mixing and nepheloid layer production, which influence faunal distribution patterns. Faunal patterns also respond to broad-scale hydrodynamics and gradients in water mass properties (e.g. temperature, salinity, dissolved oxygen concentration). Oscillating internal tidal currents can advect such gradients, both vertically and horizontally along a canyon's walls. Here we take an interdisciplinary approach using biological, hydrodynamic and bathymetry-derived datasets to undertake a high-resolution analysis of a subset of wall assemblages within Whittard Canyon, North-East Atlantic. We investigate if, and to what extent, patterns in diversity and epibenthic assemblages on deep-sea canyon walls can be explained by spatial and temporal variability induced by internal tides. Vertical displacement of water mass properties by the internal tide was calculated from autonomous ocean glider and shipboard CTD observations. Spatial patterns in faunal assemblage structure were determined by cluster analysis and non-metric Multi-Dimensional Scaling plots. Canonical Redundancy Analysis and Generalised Linear Models were then used to explore relationships between faunal diversity and assemblage structure and a variety of environmental variables. Our results support the hypothesis that internal tides influence spatial heterogeneity in wall faunal diversity and assemblages by generating both spatial and temporal gradients in hydrodynamic properties and consequently likely food supply.

The presence of marine litter is of concern in submarine canyons, although research in this area is still in its infancy. A critical synthesis and literature review selecting studies with primary data of benthic marine litter at depths of over 50 m revealed important gaps in the knowledge, with information on the impact of macroplastics in deep-sea environments still scarce. Less than 1% of medium to large submarine canyons mapped have been studied in any measure for marine litter, with over 91% of the canyon studies located in European waters. Imaging techniques are now the main tools used for sampling, overtaking trawling methods despite the continued growth of the latter for marine litter deep-sea research. Enumeration of litter was diverse with over 75% using abundance for quantification. Despite the existence of litter protocols available for deep-sea environments, over 73% of studies did not use any. There was no standardization in the implementation of established classification protocols, which were either not used in full or were customized in part. Fishing-related categories do not feature as a top-level category in the classification hierarchy in any of the protocols, yet over 50% of publications featured fishing materials as a main category, pointing to a more intuitive activity-based categorization of litter instead of a materials-led approach from the established protocols. Furthermore, interactions between litter and the surrounding environment and biota are very much underreported with little or no consensus between how the data are analyzed and expressed. There were no discernible patterns between litter density, composition and broad geographical location of canyons, with individual topographical characteristics, hydrodynamic regimes and anthropogenic activities being determining factors in how submarine canyons are affected by litter. Overall, there is no apparent framework to allow comparison of studies and due to the different methods of identifying, enumerating, quantifying and classifying marine litter, or lack of data on position and morphological setting within the canyon system. The evidence provided within this study highlights a ‘call to action’ for an urgent need to standardize and unify methodologies with new or established protocols to fully understand the impact of marine litter in submarine canyons.

Landscape maps based on multivariate cluster analyses provide an objective and comprehensive view on the (marine) environment. They can hence support decision making regarding sustainable ocean resource handling and protection schemes. Across a large number of scales, input parameters and classification methods, numerous studies categorize the ocean into seascapes, hydro-morphological provinces or clusters. Many of them are regional, however, while only a few are on a basin scale. This study presents an automated cluster analysis of the entire Atlantic seafloor environment, based on eight global datasets and their derivatives: Bathymetry, slope, terrain ruggedness index, topographic position index, sediment thickness, POC flux, salinity, dissolved oxygen, temperature, current velocity, and phytoplankton abundance in surface waters along with seasonal variabilities. As a result, we obtained nine seabed areas (SBAs) that portray the Atlantic seafloor. Some SBAs have a clear geological and geomorphological nature, while others are defined by a mixture of terrain and water body characteristics. The majority of the SBAs, especially those covering the deep ocean areas, are coherent and show little seasonal and hydrographic variation, whereas other, nearshore SBAs, are smaller sized and dominated by high seasonal changes. To demonstrate the potential use of the marine landscape map for marine spatial planning purposes, we mapped out local SBA diversity using the patch richness index developed in landscape ecology. It identifies areas of high landscape diversity, and is a practical way of defining potential areas of interest, e.g. for designation as protected areas, or for further research. Clustering probabilities are highest (100%) in the center of SBA patches and decrease towards the edges (< 98%). On the SBA point cloud which was reduced for probabilities

20 pages, 12 figures, 3 tables, supplementary material https://www.frontiersin.org/articles/10.3389/fmars.2021.556313/full#supplementary-material.-- Data Availability Statement: The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation. Some datasets presented in this article are not readily available because parts of the study are ongoing, and cannot be made public until they have been fully analysed. Requests to access the datasets should be directed to DP, d.m.price@soton.ac.uk and AW, a.wheeler@ucc.ie, Benthic fauna form spatial patterns which are the result of both biotic and abiotic processes, which can be quantified with a range of landscape ecology descriptors. Fine- to medium-scale spatial patterns (200 m2 were created and all organisms were geotagged in order to illustrate their point pattern. The pair correlation function was used to establish whether organisms demonstrated a clustered pattern (CP) at various scales. We further applied a point pattern modelling approach to identify four potential point patterns: complete spatial randomness (CSR), an inhomogeneous pattern influenced by environmental drivers, random clustered point pattern indicating biologically driven clustering and an inhomogeneous clustered point pattern driven by a combination of environmental drivers and biological effects. Reef framework presence and structural complexity determined inhabitant distribution with most organisms showing a departure from CSR. These CPs are likely caused by an affinity to local environmental drivers, growth patterns and restricted dispersion reproductive strategies within the habitat across a range of fine to medium scales. These data provide novel and detailed insights into fine-scale habitat heterogeneity, showing that non-random distributions are apparent and detectable at these fine scales in deep-sea habitats, These data were collected during the Querci expedition, funded by the Marine Institute under the Ship Time Programme of the National Development Plan. DP was funded by the Natural Environmental Research Council (grant number NE/N012070/1) and University of Southampton GSNOCS European Exchange Programme. VH was funded by the NERC CLASS project (grant number NE/R015953/1). AL and VH were supported by the iAtlantic project of the EU H2020 Research and Innovation Programme (grant number 818123). CLI was supported by the H2020 MSC Action HABISS (GA 890815), With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)