Imagery has become a key tool for assessing deep-sea megafaunal biodiversity, historically based on physical sampling using fishing gears. Image datasets provide quantitative and repeatable estimates, small-scale spatial patterns and habitat descriptions. However, taxon identification from images is challenging and often relies on morphotypes without considering a taxonomic framework. Taxon identification is particularly challenging in regions where the fauna is poorly known and/or highly diverse. Furthermore, the efficiency of imagery and physical sampling may vary among habitat types. Here, we compared biodiversity metrics (alpha and gamma diversity, composition) based on physical sampling (dredging and trawling) and towed-camera still images (1) along the upper continental slope of Papua New Guinea (sedimented slope with wood-falls, a canyon and cold seeps), and (2) on the outer slopes of the volcanic islands of Mayotte, dominated by hard bottoms. The comparison was done on selected taxa (Pisces, Crustacea, Echinoidea, and Asteroidea), which are good candidates for identification from images. Taxonomic identification ranks obtained for the images varied among these taxa (e.g., family/order for fishes, genus for echinoderms). At these ranks, imagery provided a higher taxonomic richness for hard-bottom and complex habitats, partially explained by the poor performance of trawling on these rough substrates. For the same reason, the gamma diversity of Pisces and Crustacea was also higher from images, but no difference was observed for echinoderms. On soft bottoms, physical sampling provided higher alpha and gamma diversity for fishes and crustaceans, but these differences tended to decrease for crustaceans identified to the species/morphospecies level from images. Physical sampling and imagery were selective against some taxa (e.g., according to size or behavior), therefore providing different facets of biodiversity. In addition, specimens collected at a larger scale facilitated megafauna identification from images. Based on this complementary approach, we propose a robust methodology for image-based faunal identification relying on a taxonomic framework, from collaborative work with taxonomists. An original outcome of this collaborative work is the creation of identification keys dedicated specifically to in situ images and which take into account the state of the taxonomic knowledge for the explored sites.

BENTHEDI, BIOMAGLO, BIOPAPUA, MADEEP, MAINBAZA, MIRIKY, Restricted, Restricted, PAPUA NIUGINI

Seamounts are vulnerable ecosystems targeted by fishing and potentially by future mineral exploitation. Their abundance, widespread distribution, and heterogeneity of faunal and abiotic components require integrated studies at multiscale to describe spatial patterns and identify environmental drivers needed by conservation plans. There is also a lack of knowledge on seamount benthic ecosystems in some regions, such as the Indian Ocean. These gaps, in the context of Marine Protected Areas establishment in the region, have motivated the present study focusing on the Mozambique Channel Eparses islands and flat top seamounts, along a 10-degree latitude gradient. These structures are characterized by complex volcanic and carbonate geomorphologies at multiscale and are distributed along a highly dynamic turbulent ocean circulation area with large anticyclonic eddies. For the first time, we analysed, from seabed image transects obtained by towed-camera on four seamounts, and two volcanic islands - Bassas da India and Mayotte - external slopes, and from multiscale environmental data, how benthic communities respond to this high habitat heterogeneity at regional, and local scales. This study reveals high discrepancies of benthic megafauna richness, density, and beta diversity among seamounts and among slopes of the same islands. Moreover, at similar latitude, seamounts display higher densities than island slopes. The highest densities found on a seamount of the Glorieuses archipelago are explained by strong currents and flat homogeneous geomorphology. Except on this seamount, the beta diversity is high, despite the quite limited depth range explored (84–734 m) and is the highest on island slopes and Hall Bank, driven by the diversity and hardness of the substrate. Beta diversity is mainly due to taxa turnover, with high contribution of the habitat-forming sponges and cnidarians, together with a few mobile taxa. We identified from biogeographic network analysis 12 dominant faunal assemblages, displaying a patchy distribution, with variability in composition both among and within sites. Currents and primary productivity explain ~15% of the observed assemblage structure along the channel, while geomorphology (km scale), topography (60–500 m scale) and substrate (60-m units) explain together 24% of the faunal spatial patterns. Analysis of spatial structures along island slopes detected some small (100–200 m), medium (~1 km) and large scale (~2–6 km) megabenthic community structures, partly explained by topography, substrate, depth, and slope. Despite limited taxonomic identifications for this poorly sampled area, this study reveals an outstanding heterogeneity of megabenthic assemblages at multispatial scales in the Mozambique Channel seamounts and island slopes, in response to the complex hydrography and geology of the area. Further characterization of environmental drivers with greater focus at local scales including hydro­ graphic variables are therefore needed to improve predictions of suitable habitats of vulnerable marine ecosystems.

BIOMAGLO, Restricted, Restricted