Description: The data are counts of megafaunal specimens in seabed photographs captured with a Teledyne Gavia autonomous underwater vehicle deployed from the RRS James Cook in May 2019 at a site in UK sector of the Central North Sea (Connelly, 2019), as part of the Strategies for Environmental Monitoring of Marine Carbon Capture and Storage (STEMM-CCS) project. The seabed photographs were captured using a GRAS-14S5M-C camera with a Tamron TAM 23FM08-L lens mounted to the Gavia autonomous underwater vehicle. The camera captured photographs at a temporal frequency of 1.875 frames per second, a resolution of 1280 x 960 pixels, and at a target altitude of 2 m above the seafloor. Overlapping photos were removed. Megafaunal specimens (〉1 cm) in the non-overlapping images were detected using the MAIA machine learning algorithm in BIIGLE. The potential specimens detected using this method were reviewed to remove false positives and classified into morphotypes manually. Counts by morphotype, latitude and longitude (in degrees), camera altitude (m above seafloor) and seabed area (m2) are provided for each photo. The following additional unchecked raw data are also provided: date, time, AUV mission number, and AUV heading, pitch, and roll. Acknowledgements We thank the crew and operators of the RRS James Cook and the Gavia autonomous underwater vehicle. The project was funded by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 654462.

Description: The data consist of hourly observations of sedimentation impacts located approximately 31 m southwest of the drilling location, including measurements of proxies of suspended material in the water column, along with observations of the lamellate desmosponge specimen. Acoustic backscatter (1.9-2.0 MHz) and current speed were measured using a Seaguard RCM DW. A time-lapse camera was also deployed: the Nikon E995 camera was set to F 6.0, ISO 200, exposure 1/60, with photos of 2048 x 1536 pixels. As another estimate of suspended material in the water column, brightness (as mean RGB) was calculated for top corners (256 x 256 pixels) in photos, where the corners were not obscured by fish. Settlement of sediment on the sponge specimen was estimated as brightness of a portion of it (approximately 3600 pixels2) in the images. Movement of the sponge was estimated as the distance between successive xy-positions of the apex of the sponge in images. Mean values (6- and 12-hourly) centred on the hourly data, and sums of distance over 6- and 12-h periods were also calculated.

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: Underwater images are used to explore and monitor ocean habitats, generating huge datasets with unusual data characteristics that preclude traditional data management strategies. Due to the lack of universally adopted data standards, image data collected from the marine environment are increasing in heterogeneity, preventing objective comparison. The extraction of actionable information thus remains challenging, particularly for researchers not directly involved with the image data collection. Standardized formats and procedures are needed to enable sustainable image analysis and processing tools, as are solutions for image publication in long-term repositories to ascertain reuse of data. The FAIR principles (Findable, Accessible, Interoperable, Reusable) provide a framework for such data management goals. We propose the use of image FAIR Digital Objects (iFDOs) and present an infrastructure environment to create and exploit such FAIR digital objects. We show how these iFDOs can be created, validated, managed and stored, and which data associated with imagery should be curated. The goal is to reduce image management overheads while simultaneously creating visibility for image acquisition and publication efforts.

Description: Abyssal seafloor communities cover more than 60% of Earth’s surface. Despite their great size, abyssal plains extend across modest environmental gradients compared to other marine ecosystems. However, little is known about the patterns and processes regulating biodiversity or potentially delimiting biogeographical boundaries at regional scales in the abyss. Improved macroecological understanding of remote abyssal environments is urgent as threats of widespread anthropogenic disturbance grow in the deep ocean. Here, we use a new, basin-scale dataset to show the existence of clear regional zonation in abyssal communities across the 5,000 km span of the Clarion–Clipperton Zone (northeast Pacific), an area targeted for deep-sea mining. We found two pronounced biogeographic provinces, deep and shallow-abyssal, separated by a transition zone between 4,300 and 4,800 m depth. Surprisingly, species richness was maintained across this boundary by phylum-level taxonomic replacements. These regional transitions are probably related to calcium carbonate saturation boundaries as taxa dependent on calcium carbonate structures, such as shelled molluscs, appear restricted to the shallower province. Our results suggest geochemical and climatic forcing on distributions of abyssal populations over large spatial scales and provide a potential paradigm for deep-sea macroecology, opening a new basis for regional-scale biodiversity research and conservation strategies in Earth’s largest biome.

Description: Marine imaging studies have unique constraints on the data collected requiring a tool for defining the biological scope to facilitate data discovery, quality evaluation, sharing and reuse. Defining the ‘target population’ is way of scoping biological sampling or observations by setting the pool of organisms to be observed or sampled. It is used in survey design and planning, to determine statistical inference, and is critical for data interpretation and reuse (both images and derived data). We designed a set of attributes for defining and recording the target population in biological studies using marine photography, incorporating ecological and environmental delineation and marine imaging method constraints. We describe how this definition may be altered and recorded at different phases of a project. The set of attributes records the definition of the target population in a structured metadata format to enhance data FAIRness. It is designed as an extension to the image FAIR Digital Objects metadata standard, and we map terms to other biological data standards where possible. This set of attributes serves a need to update ecological metadata to align with new remotely-sensed data, and can be applied to other remotely-sensed ecological image data.

Description: Underwater images are used to explore and monitor ocean habitats, generating huge datasets with unusual data characteristics that preclude traditional data management strategies. Due to the lack of universally adopted data standards, image data collected from the marine environment are increasing in heterogeneity, preventing objective comparison. The extraction of actionable information thus remains challenging, particularly for researchers not directly involved with the image data collection. Standardized formats and procedures are needed to enable sustainable image analysis and processing tools, as are solutions for image publication in long-term repositories to ascertain reuse of data. The FAIR principles (Findable, Accessible, Interoperable, Reusable) provide a framework for such data management goals. We propose the use of image FAIR Digital Objects (iFDOs) and present an infrastructure environment to create and exploit such FAIR digital objects. We show how these iFDOs can be created, validated, managed and stored, and which data associated with imagery should be curated. The goal is to reduce image management overheads while simultaneously creating visibility for image acquisition and publication efforts.