ALBERT

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: Trait-based approaches that complement taxonomic-based studies have increased in popularity among the scientific community over the last decades. The collection of biological and ecological characteristics of species (i.e., traits) provides insight into species and ecosystem vulnerability to environmental and anthropogenic changes, as well as ecosystem functioning. While most of the available trait databases to date contain essential information to understand the functional diversity of a taxonomic group or functional group based on size, the FUN Azores trait database has an ecosystem-based approach that provides a comprehensive assessment of diverse fauna (meio-, macro-, and megafauna) from benthic and pelagic environments in the Azores Marine Park; including ridges, seamounts, and hydrothermal vents. We used a collaborative approach involving 30 researchers with different expertise to develop the trait database; which contains compiled data on 14 traits representing morphological, behavioral, and life history characteristics for 1210 species, across 10 phyla.

Description: The Central and South Atlantic represents a vast ocean area and is home to a diverse range of ecosystems and species. Nevertheless, and similar to the rest of the global south, the area is comparatively understudied yet exposed to increasing levels of multisectoral pressures. To counteract this, the level of scientific exploration in the Central and South Atlantic has increased in recent years and will likely continue to do so within the context of the United Nations (UN) Decade of Ocean Science for Sustainable Development. Here, we compile the literature to investigate the distribution of previous scientific exploration of offshore (30 m+) ecosystems in the Central and South Atlantic, both within and beyond national jurisdiction, allowing us to synthesise overall patterns of biodiversity. Furthermore, through the lens of sustainable management, we have reviewed the existing anthropogenic activities and associated management measures relevant to the region. Through this exercise, we have identified key knowledge gaps and undersampled regions that represent priority areas for future research and commented on how these may be best incorporated into, or enhanced through, future management measures such as those in discussion at the UN Biodiversity Beyond National Jurisdiction negotiations. This review represents a comprehensive summary for scientists and managers alike looking to understand the key topographical, biological, and legislative features of the Central and South Atlantic.

Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Chapman, A. S. A., Beaulieu, S. E., Colaco, A., Gebruk, A. V., Hilario, A., Kihara, T. C., Ramirez-Llodra, E., Sarrazin, J., Tunnicliffe, V., Amon, D. J., Baker, M. C., Boschen-Rose, R. E., Chen, C., Cooper, I. J., Copley, J. T., Corbari, L., Cordes, E. E., Cuvelier, D., Duperron, S., Du Preez, C., Gollner, S., Horton, T., Hourdez, S., Krylova, E. M., Linse, K., LokaBharathi, P. A., Marsh, L., Matabos, M., Mills, S. W., Mullineaux, L. S., Rapp, H. T., Reid, W. D. K., Rybakova (Goroslavskaya), E., Thomas, T. R. A., Southgate, S. J., Stohr, S., Turner, P. J., Watanabe, H. K., Yasuhara, M., & Bates, A. E. sFDvent: a global trait database for deep-sea hydrothermal-vent fauna. Global Ecology and Biogeography, 28(11), (2019): 1538-1551, doi: 10.1111/geb.12975.

Description: Motivation Traits are increasingly being used to quantify global biodiversity patterns, with trait databases growing in size and number, across diverse taxa. Despite growing interest in a trait‐based approach to the biodiversity of the deep sea, where the impacts of human activities (including seabed mining) accelerate, there is no single repository for species traits for deep‐sea chemosynthesis‐based ecosystems, including hydrothermal vents. Using an international, collaborative approach, we have compiled the first global‐scale trait database for deep‐sea hydrothermal‐vent fauna – sFDvent (sDiv‐funded trait database for the Functional Diversity of vents). We formed a funded working group to select traits appropriate to: (a) capture the performance of vent species and their influence on ecosystem processes, and (b) compare trait‐based diversity in different ecosystems. Forty contributors, representing expertise across most known hydrothermal‐vent systems and taxa, scored species traits using online collaborative tools and shared workspaces. Here, we characterise the sFDvent database, describe our approach, and evaluate its scope. Finally, we compare the sFDvent database to similar databases from shallow‐marine and terrestrial ecosystems to highlight how the sFDvent database can inform cross‐ecosystem comparisons. We also make the sFDvent database publicly available online by assigning a persistent, unique DOI. Main types of variable contained Six hundred and forty‐six vent species names, associated location information (33 regions), and scores for 13 traits (in categories: community structure, generalist/specialist, geographic distribution, habitat use, life history, mobility, species associations, symbiont, and trophic structure). Contributor IDs, certainty scores, and references are also provided. Spatial location and grain Global coverage (grain size: ocean basin), spanning eight ocean basins, including vents on 12 mid‐ocean ridges and 6 back‐arc spreading centres. Time period and grain sFDvent includes information on deep‐sea vent species, and associated taxonomic updates, since they were first discovered in 1977. Time is not recorded. The database will be updated every 5 years. Major taxa and level of measurement Deep‐sea hydrothermal‐vent fauna with species‐level identification present or in progress. Software format .csv and MS Excel (.xlsx).

Description: We would like to thank the following experts, who are not authors on this publication but made contributions to the sFDvent database: Anna Metaxas, Alexander Mironov, Jianwen Qiu (seep species contributions, to be added to a future version of the database) and Anders Warén. We would also like to thank Robert Cooke for his advice, time, and assistance in processing the raw data contributions to the sFDvent database using R. Thanks also to members of iDiv and its synthesis centre – sDiv – for much‐valued advice, support, and assistance during working‐group meetings: Doreen Brückner, Jes Hines, Borja Jiménez‐Alfaro, Ingolf Kühn and Marten Winter. We would also like to thank the following supporters of the database who contributed indirectly via early design meetings or members of their research groups: Malcolm Clark, Charles Fisher, Adrian Glover, Ashley Rowden and Cindy Lee Van Dover. Finally, thanks to the families of sFDvent working group members for their support while they were participating in meetings at iDiv in Germany. Financial support for sFDvent working group meetings was gratefully received from sDiv, the Synthesis Centre of iDiv (DFG FZT 118). ASAC was a PhD candidate funded by the SPITFIRE Doctoral Training Partnership (supported by the Natural Environmental Research Council, grant number: NE/L002531/1) and the University of Southampton at the time of submission. ASAC also thanks Dominic, Lesley, Lettice and Simon Chapman for their support throughout this project. AEB and VT are sponsored through the Canada Research Chair Programme. SEB received support from National Science Foundation Division of Environmental Biology Award #1558904 and The Joint Initiative Awards Fund from the Andrew W. Mellon Foundation. AC is supported by Program Investigador (IF/00029/2014/CP1230/CT0002) from Fundação para a Ciência e a Tecnologia (FCT). This study also had the support of Fundação para a Ciência e a Tecnologia, through the strategic project UID/MAR/04292/2013 granted to marine environmental sciences centre. Data compiled by AVG and EG were supported by Russian science foundation Grant 14‐50‐00095. AH was supported by the grant BPD/UI88/5805/2017 awarded by CESAM (UID/AMB/50017), which is financed by FCT/Ministério da Educação through national funds and co‐funded by fundo Europeu de desenvolvimento regional, within the PT2020 Partnership Agreement and Compete 2020. ERLL was partially supported by the MarMine project (247626/O30). JS was supported by Ifremer. Data on vent fauna from the East Scotia Ridge, Mid‐Cayman Spreading Centre, and Southwest Indian Ridge were obtained by UK natural environment research council Grants NE/D01249X/1, NE/F017774/1 and NE/H012087/1, respectively. REBR's contribution was supported by a Postdoctoral Fellowship at the University of Victoria, funded by the Canadian Healthy Oceans Network II Strategic Research Program (CHONe II). DC is supported by a post‐doctoral scholarship (SFRH/BPD/110278/2015) from FCT. HTR was supported by the Research Council of Norway through project number 70184227 and the KG Jebsen Centre for Deep Sea Research (University of Bergen). MY was partially supported by grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (project codes: HKU 17306014, HKU 17311316).

Description: Until the 1980s, the deep sea was generally considered to be a particularly stable environment, free from major temporal variations (Sanders, 1968). Studies in the abyssal northeast Atlantic by Billett et al. (1983), and subsequently Lampitt (1985) discovered seasonal pulses of surface primary production-derived particulate organic matter (phytodetritus), and hence carbon, at abyssal depths. These early observations were subsequently extended to the central oceanic region of the NE Atlantic (Pfannkuche, 1993; Thiel et al., 1989), and prompted the establishment of more concerted time series studies in the Porcupine Abyssal Plain area. Today, the Porcupine Abyssal Plain Sustained Observatory (PAP–SO) is a multidisciplinary open-ocean time series site in the NE Atlantic (48°50′N 16°30′W, 4850 m water depth; Fig. 1), focused on the study of connections between the surface and deep ocean. In situ measurements of climatically and environmentally relevant variables have been made for more than 30 years. This represents an exceptionally long time series - a recent compilation of biological time series data, across terrestrial, freshwater, and marine realms, indicates an average duration of only 13-years (Dornelas et al., 2018). Long-term time series in the deep sea are rare, particularly those collecting data from surface to seabed. The PAP-SO is one of two abyssal long-term time series sites globally (Smith et al. 2015), the other being a thirty-year time series at Station M in the northeastern Pacific Ocean (34°50′N, 123°00′W, ~4000 m water depth), maintained by the Monterey Bay Aquarium Research Institute (Smith et al., 2020). This ‘sibling’ abyssal time series site also aims to understand the connections between the surface ocean and the seabed, using many similar techniques (Smith et al., 2017), facilitating comparisons between the two sites (e.g. Durden et al., 2019; Durden et al., 2020a; Laguionie-Marchais et al., 2013; Smith et al., 2009). Another source of extended comparison is the 21 year time series Long-Term Ecological Research Observatory HAUSGARTEN, Frontiers in Arctic Marine Monitoring (FRAM) in the Fram Strait between the North Atlantic and the central Arctic Ocean (78.5°N–80°N, 05°W–11°E, 250–5500 m water depth), maintained by the Alfred Wegener Institute for Polar and Marine Research (Soltwedel et al., 2016; Soltwedel et al., 2005). Much of our understanding of temporal variation in the deep sea, and connections between the surface ocean and the seabed have been derived from research conducted at these observatories.

Description: We provide an overview of the World Amphipoda Database (WAD), a global species \ndatabase that is part of the World Register of Marine Species (WoRMS). Launched in 2013, the database \ncontains entries for over 10,500 accepted species names. Edited currently by 31 amphipod taxonomists, \nfollowing WoRMS priorities, the WAD has at least one editor per major group. All accepted species \nare checked by the editors, as is the authorship available for all of the names. The higher classification \nis documented for every species and a type species is recorded for every genus name. This constitutes \nfive of the 13 priorities for completion, set by WoRMS. In 2015, five LifeWatch grants were allocated \nfor WAD activities. These included a general training workshop in 2016, together with data input for \nthe superfamily Lysianassoidea and for a number of non-marine groups. Philanthropy grants in 2019 \nand 2021 covered more important gaps across the whole group. Further work remains to complete the \nlinking of unaccepted names, original descriptions, and environmental information. Once these tasks are \ncompleted, the database will be considered complete for 8 of the 13 priorities, and efforts will continue \nto input new taxa annually and focus on the remaining priorities, particularly the input of type localities. \nWe give an overview of the current status of the order Amphipoda, providing counts of the number of \ngenera and species within each family belonging to the six suborders currently recognized.