Description: The most significant breakthroughs in science are often made as a result of technological developments and innovation. A new capacity to gather more data, measure more precisely or make entirely new observations generally leads to new insights and fundamental understanding. The future of ocean research and exploration therefore lies in robotics: marine robotic systems can be deployed at depths and in environments that are out of direct reach for humans, they can work around the clock, and they can be autonomous, freeing up time and money for other activities. To advance the field of submarine geomorphology, the two types of robots that currently make the biggest difference are Remotely Operated Vehicles (ROVs) and Autonomous Underwater Vehicles (AUVs). Other autonomous or robotic systems are available for marine research (e.g. gliders, autonomous surface vehicles, benthic crawlers etc.), but their application for geomorphological studies is less extensive. This chapter gives an overview of the main characteristics of ROVs and AUVs, their advantages and disadvantages, and their main applications for geomorphological research. In comparison to the other geomorphological methods discussed in this book, however, it has to be made clear that ROVs and AUVs are not so much methods per se, instead they are platforms from which existing and new approaches can be applied.

Description: Highlights • All known observations for Area of Particular Environmental Interest 6 presented. • Assess morphology, sediments, nodules, oceanography, biogeochemistry and ecology. • APEI-6 partially representative of nearby exploration areas yet clear differences. • Present scientific synthesis and management implications for Clarion Clipperton Zone. To protect the range of habitats, species, and ecosystem functions in the Clarion Clipperton Zone (CCZ), a region of interest for deep-sea polymetallic nodule mining in the Pacific, nine Areas of Particular Environmental Interest (APEIs) have been designated by the International Seabed Authority (ISA). The APEIs are remote, rarely visited and poorly understood. Here we present and synthesise all available observations made at APEI-6, the most north eastern APEI in the network, and assess its representativity of mining contract areas in the eastern CCZ. The two studied regions of APEI-6 have a variable morphology, typical of the CCZ, with hills, plains and occasional seamounts. The seafloor is predominantly covered by fine-grained sediments, and includes small but abundant polymetallic nodules, as well as exposed bedrock. The oceanographic parameters investigated appear broadly similar across the region although some differences in deep-water mass separation were evident between APEI-6 and some contract areas. Sediment biogeochemistry is broadly similar across the area in the parameters investigated, except for oxygen penetration depth, which reached 〉2 m at the study sites within APEI-6, deeper than that found at UK1 and GSR contract areas. The ecology of study sites in APEI-6 differs from that reported from UK1 and TOML-D contract areas, with differences in community composition of microbes, macrofauna, xenophyophores and metazoan megafauna. Some species were shared between areas although connectivity appears limited. We show that, from the available information, APEI-6 is partially representative of the exploration areas to the south yet is distinctly different in several key characteristics. As a result, additional APEIs may be warranted and caution may need to be taken in relying on the APEI network alone for conservation, with other management activities required to help mitigate the impacts of mining in the CCZ.

Description: Highlights • AUV geophysical mapping reveals complex patterns of Mn nodule distribution. • Geophysical and image-based data suggest that Mn nodule occurence relates to sediment thickness. • The role of sediment thickness in nodule development requires detailed geochemical investigation. Abstract The relationship between polymetallic nodules (Mn nodules) and deep-sea stratigraphy is relatively poorly studied and the role of sediment thickness in determining nodule occurrence is an active field of research. This study utilizes geophysical observations from three types of autonomous underwater vehicle (AUV) data (multi-beam bathymetry, sub-bottom profiles and underwater photography) in order to assess this relationship. Multi-beam bathymetry was processed with a pattern recognition approach for producing objective geomorphometric classes of the seafloor for examining their relation to sediment thickness and nodule occurence. Sub-bottom profiles were used for extracting sediment thickness along a dense network of tracklines. Close-range AUV-photography data was used for automated counting of polymetallic nodules and their geometric features and it served as ground truth data. It was observed that higher nodule occurence were related to layers with increased sediment thickness. This evidence reveals the role of local seafloor heterogeneity in nodule formation and suggests that unique patterns of local stratigraphy may affect geochemical processes that promote polymetallic nodule development at local scales.

Description: The data provided here were derived using a new ArcGIS-based British Geological Survey (BGS) seabed mapping toolbox that semi-automatically delineated over 500 Lophelia reef 'minimounds' from bathymetry data of the Mingulay Reef Complex. The morphometric and acoustic characteristics of the minimounds were also automatically quantified and captured using this toolbox. Coral presence data were derived from high-definition remotely operated vehicle (ROV) records and high-resolution microbathymetry collected by a ROVmounted multibeam echosounder. With a resolution of 0.35 9 0.35 m, the microbathymetry covers 0.6 km2 in the centre of the study area and allowed identification of individual live coral colonies in acoustic data for the first time. Maximum water depth, maximum rugosity, mean rugosity, bathymetric positioning index and maximum current speed were identified as the environmental variables that contributed most to the prediction of live coral presence. These variables were used to create a predictive map of the likelihood of presence of live cold-water coral colonies in the area of the Mingulay Reef Complex covered by the 2-m resolution data set.