When Imagery and Physical Sampling Work Together: Toward an Integrative Methodology of Deep-Sea Image-Based Megafauna Identification

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