Description: The purpose of the InterRidge Global Database of Active Submarine Hydrothermal Vent Fields, hereafter referred to as the "InterRidge Vents Database," is to provide a comprehensive list of active submarine hydrothermal vent fields for use in academic research, education, and marine policy. This dataset includes a data table (flat file) and a map representing the InterRidge Vents Database Version 3.4. Version 3.4 was completed on 25 March 2020 with a total of 721 vent fields, with 666 confirmed or inferred active and 55 inactive (please note: the database is not comprehensive for inactive vent fields). The number of known active vent fields increased by 134 in the past decade since the publication of InterRidge Vents Database Version 2.1 (Beaulieu et al., 2013, doi:10.1002/2013GC004998). The contents of the InterRidge Vents Database were derived principally from the open literature. The database includes a vocabulary of vent field names and information that may be useful in mapping, including position (latitude, longitude), depth, region, tectonic setting, national jurisdiction, and ocean. Additional information includes names of individual vent sites within vent fields, spreading rate for those vent fields at spreading centers, maximum temperature or temperature category (high or low) for confirmed active vent fields, notes on site description and biology for some of the vent fields, year discovered, and references. The data table was exported from the online database at https://vents-data.interridge.org/ on 2020-03-25; several columns were removed with script available at https://github.com/sbeaulieu/vents-Drupal. We also provide a text file with definitions for the column headers in the data table. The map is provided in several formats and shows locations of all vent fields in Version 3.4 (downloaded from the online database on 2019-12-24) with bathymetry from NOAA ETOPO1. The map was created by Jyun-Nai Wu (University of California San Diego). The InterRidge Vents Database is supported by the InterRidge program for international cooperation in ocean floor studies. For Version 3.4, S. Beaulieu was supported by U.S. National Science Foundation awards #1558904 and #1829773.

Description: Microbial symbionts are a common life-history character of marine invertebrates and their developmental stages. Communities of bacteria that associate with the eggs, embryos, and larvae of coastal marine invertebrates tend to be species specific and correlate with aspects of host biology and ecology. The richness of bacteria associated with the developmental stages of coastal marine invertebrates spans four orders of magnitude, from single mutualists to thousands of unique taxa. This understanding stems predominately from the developmental stages of coastal species. If they are broadly representative of marine invertebrates, then we may expect deep-sea species to associate with bacterial communities that are similar in diversity. To test this, we used amplicon sequencing to profile the bacterial communities of invertebrate larvae from multiple taxonomic groups (annelids, molluscs, crustaceans) collected from 2500 to 3670 m in depth in near-bottom waters near hydrothermal vents in 3 different regions of the Pacific Ocean (the East Pacific Rise, the Mariana Back-Arc, and the Pescadero Basin). We find that larvae of deep-sea invertebrates associate with low-diversity bacterial communities (similar to 30 bacterial taxa) that lack specificity between taxonomic groups. The diversity of these communities is estimated to be similar to 7.9 times lower than that of coastal invertebrate larvae, but this result depends on the taxonomic group. Associating with a low-diversity community may imply that deep-sea invertebrate larvae do not have a strong reliance on a microbiome and that the hypothesized lack of symbiotic contributions would differ from expectations for larvae of coastal marine invertebrates.

Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Carrier, T. J., Beaulieu, S. E., Mills, S. W., Mullineaux, L. S., & Reitzel, A. M. Larvae of deep-sea invertebrates harbor low-diversity bacterial communities. Biological Bulletin, 241(1), (2021): 65–76, https://doi.org/10.1086/715669.

Description: Microbial symbionts are a common life-history character of marine invertebrates and their developmental stages. Communities of bacteria that associate with the eggs, embryos, and larvae of coastal marine invertebrates tend to be species specific and correlate with aspects of host biology and ecology. The richness of bacteria associated with the developmental stages of coastal marine invertebrates spans four orders of magnitude, from single mutualists to thousands of unique taxa. This understanding stems predominately from the developmental stages of coastal species. If they are broadly representative of marine invertebrates, then we may expect deep-sea species to associate with bacterial communities that are similar in diversity. To test this, we used amplicon sequencing to profile the bacterial communities of invertebrate larvae from multiple taxonomic groups (annelids, molluscs, crustaceans) collected from 2500 to 3670 m in depth in near-bottom waters near hydrothermal vents in 3 different regions of the Pacific Ocean (the East Pacific Rise, the Mariana Back-Arc, and the Pescadero Basin). We find that larvae of deep-sea invertebrates associate with low-diversity bacterial communities (~30 bacterial taxa) that lack specificity between taxonomic groups. The diversity of these communities is estimated to be ~7.9 times lower than that of coastal invertebrate larvae, but this result depends on the taxonomic group. Associating with a low-diversity community may imply that deep-sea invertebrate larvae do not have a strong reliance on a microbiome and that the hypothesized lack of symbiotic contributions would differ from expectations for larvae of coastal marine invertebrates.

Description: TJC was supported by a National Science Foundation (NSF) Graduate Research Fellowship; SEB, SWM, and LSM were supported by NSF (OCE-0424953, OCE-1028862, and OCE-1829773) and the Dalio Explore Fund; and AMR was supported by the Human Frontier Science Program Award RGY0079/2016.

Description: This data package provides the sampling locations and identifications for macrofauna and larvae collected at the Auka hydrothermal vent field in Pescadero Basin in 2017 and used in a study by Fleming et al. (2022). This data package contains five tables: paired tables for benthic slurps (sampling metadata and specimen counts), paired tables for plankton slurps (sampling metadata and specimen counts), and one table summarizing benthic and plankton specimens with Barcode of Life Data System (BOLD) Barcode Index Numbers (BINs). The paired data tables are partially aligned to Darwin Core event and occurrence tables for future contribution to the Ocean Biodiversity Information System (OBIS). Records for specimens in BOLD are available through the Global Biodiversity Information Facility (GBIF).

Description: Dalio Ocean Initiative and E/V Nautilus/Ocean Exploration Trust

Description: Presented at Data Science Training Camp, Woods Hole, MA, January, 22 - 23, 2020.

Description: With data and software increasingly recognized as scholarly research products, and aiming towards open science and reproducibility, it is imperative for today's oceanographers to learn foundational practices and skills for data management and research computing, as well as practices specific to the ocean sciences. This educational package was developed as a data science training camp for graduate students and professionals in the ocean sciences and implemented at the Woods Hole Oceanographic Institution (WHOI) in 2019 and 2020. Here we provide materials for the 2020 camp which was delivered in-person during two afternoons (total of 8 hours), with two modules per afternoon. We aimed for ~40 participants per camp, with disciplines spanning Earth and life sciences and engineering. Disciplines at each table were mixed on the first afternoon but similar on the second afternoon. Contents of this package include the syllabus and slide presentations for each of the four modules: 1 "Good enough practices in scientific computing," 2 Data management, 3 Software development and research computing, and 4 Best practices in the ocean sciences. The 3rd module is split into two parts. We also include a poster presented at the 2020 Ocean Science Meeting, which has some results from pre- and post-surveys. Funding: The camp was funded by WHOI Academic Programs Office through a Doherty Chair in Education Award, with additional support from WHOI Ocean Informatics Working Group, WHOI Information Services, MBLWHOI Library, the NSF-funded Biological and Chemical Oceanography Data Management Office (BCO-DMO), and an NSF-funded XSEDE Jetstream Education Allocation TG-OCE190011. We also utilized resources from the NSF-funded Pangeo project.

Description: The camp was funded by WHOI Academic Programs Office through a Doherty Chair in Education Award, with additional support from WHOI Ocean Informatics Working Group, WHOI Information Services, MBLWHOI Library, the NSF-funded Biological and Chemical Oceanography Data Management Office (BCO-DMO), and an NSF-funded XSEDE Jetstream Education Allocation TG-OCE190011. We also utilized resources from the NSF-funded Pangeo project.

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: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Smith, L., Cimoli, L., LaScala-Gruenewald, D., Pachiadaki, M., Phillips, B., Pillar, H., Stopa, J., Baumann-Pickering, S., Beaulieu, S., Bell, K., Harden-Davies, H., Gjerde, K., Heimbach, P., Howe, B., Janssen, F., Levin, L., Ruhl, H., Soule, A., Stocks, K., Vardaro, M.F., Wright, D. The Deep Ocean Observing Strategy: addressing global challenges in the deep sea through collaboration. Marine Technology Society Journal, 56(3), (2022): 50–66, https://doi.org/10.4031/mtsj.56.3.11.

Description: The Deep Ocean Observing Strategy (DOOS) is an international, community-driven initiative that facilitates collaboration across disciplines and fields, elevates a diverse cohort of early career researchers into future leaders, and connects scientific advancements to societal needs. DOOS represents a global network of deep-ocean observing, mapping, and modeling experts, focusing community efforts in the support of strong science, policy, and planning for sustainable oceans. Its initiatives work to propose deep-sea Essential Ocean Variables; assess technology development; develop shared best practices, standards, and cross-calibration procedures; and transfer knowledge to policy makers and deep-ocean stakeholders. Several of these efforts align with the vision of the UN Ocean Decade to generate the science we need to create the deep ocean we want. DOOS works toward (1) a healthy and resilient deep ocean by informing science-based conservation actions, including optimizing data delivery, creating habitat and ecological maps of critical areas, and developing regional demonstration projects; (2) a predicted deep ocean by strengthening collaborations within the modeling community, determining needs for interdisciplinary modeling and observing system assessment in the deep ocean; (3) an accessible deep ocean by enhancing open access to innovative low-cost sensors and open-source plans, making deep-ocean data Findable, Accessible, Interoperable, and Reusable, and focusing on capacity development in developing countries; and finally (4) an inspiring and engaging deep ocean by translating science to stakeholders/end users and informing policy and management decisions, including in international waters.

Description: Funding for the DOOS comes from the U.S. National Science Foundation AccelNet program, Award #2114717.

Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Dykman, L. N., Beaulieu, S. E., Mills, S. W., Solow, A. R., & Mullineaux, L. S. Functional traits provide new insight into recovery and succession at deep-sea hydrothermal vents. Ecology, 102(8), (2021): e03418, https://doi.org/10.1002/ecy.3418.

Description: Investigation of communities in extreme environments with unique conditions has the potential to broaden or challenge existing theory as to how biological communities assemble and change through succession. Deep-sea hydrothermal vent ecosystems have strong, parallel gradients of nutrients and environmental stress, and present unusual conditions in early succession, in that both nutrient availability and stressors are high. We analyzed the succession of the invertebrate community at 9°50′ N on the East Pacific Rise for 11 yr following an eruption in 2006 in order to test successional theories developed in other ecosystems. We focused on functional traits including body size, external protection, provision of habitat (foundation species), and trophic mode to understand how the unique nutritional and stress conditions influence community composition. In contrast to established theory, large, fast-growing, structure-forming organisms colonized rapidly at vents, while small, asexually reproducing organisms were not abundant until later in succession. Species in early succession had high external protection, as expected in the harsh thermal and chemical conditions after the eruption. Changes in traits related to feeding ecology and dispersal potential over succession agreed with expectations from other ecosystems. We also tracked functional diversity metrics over time to see how they compared to species diversity. While species diversity peaked at 8 yr post-eruption, functional diversity was continuing to increase at 11 yr. Our results indicate that deep-sea hydrothermal vents have distinct successional dynamics due to the high stress and high nutrient conditions in early succession. These findings highlight the importance of extending theory to new systems and considering function to allow comparison between ecosystems with different species and environmental conditions.

Description: Funding for L. Dykman, L. Mullineaux, and S. Beaulieu was provided by NSF OCE-1829773. The Synthesis Centre of the German Centre for Integrative Biodiversity Research (sDiv) funded the sFDvent working group and database.

Description: This technical manual guides the user through the process of creating a data table for the submission of taxonomic and morphological information for plankton and other particles from images to a repository. Guidance is provided to produce documentation that should accompany the submission of plankton and other particle data to a repository, describes data collection and processing techniques, and outlines the creation of a data file. Field names include scientificName that represents the lowest level taxonomic classification (e.g., genus if not certain of species, family if not certain of genus) and scientificNameID, the unique identifier from a reference database such as the World Register of Marine Species or AlgaeBase. The data table described here includes the field names associatedMedia, scientificName/ scientificNameID for both automated and manual identification, biovolume, area_cross_section, length_representation and width_representation. Additional steps that instruct the user on how to format their data for a submission to the Ocean Biodiversity Information System (OBIS) are also included. Examples of documentation and data files are provided for the user to follow. The documentation requirements and data table format are approved by both NASA’s SeaWiFS Bio-optical Archive and Storage System (SeaBASS) and the National Science Foundation’s Biological and Chemical Oceanography Data Management Office (BCO-DMO).

Description: This report was an outcome of a working group supported by the Ocean Carbon and Biogeochemistry (OCB) project office, which is funded by the US National Science Foundation (OCE1558412) and the National Aeronautics and Space Administration (NNX17AB17G). AN, SB, and CP conceived and drafted the document. IC, IST, JF and HS contributed to the main body of the document as well as the example files. All members of the working group contributed to the content of the document, including the conceptualization of the data table and metadata format. We would also like thank the external reviewers Cecile Rousseaux (NASA GSFC), Susanne Menden-Deuer (URI) Frank Muller-Karger (USF), and Abigail Benson (USGS) for their valuable feedback.

Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Muelbert, J. H., Nidzieko, N. J., Acosta, A. T. R., Beaulieu, S. E., Bernardino, A. F., Boikova, E., Bornman, T. G., Cataletto, B., Deneudt, K., Eliason, E., Kraberg, A., Nakaoka, M., Pugnetti, A., Ragueneau, O., Scharfe, M., Soltwedel, T., Sosik, H. M., Stanisci, A., Stefanova, K., Stephan, P., Stier, A., Wikner, J., & Zingone, A. ILTER - the International Long-Term Ecological Research Network as a platform for global coastal and ocean observation. Frontiers in Marine Science, 6, (2019): 527, doi: 10.3389/fmars.2019.00527.

Description: Understanding the threats to global biodiversity and ecosystem services posed by human impacts on coastal and marine environments requires the establishment and maintenance of ecological observatories that integrate the biological, physical, geological, and biogeochemical aspects of ecosystems. This is crucial to provide scientists and stakeholders with the support and knowledge necessary to quantify environmental change and its impact on the sustainable use of the seas and coasts. In this paper, we explore the potential for the coastal and marine components of the International Long-Term Ecological Research Network (ILTER) to fill this need for integrated global observation, and highlight how ecological observations are necessary to address the challenges posed by climate change and evolving human needs and stressors within the coastal zone. The ILTER is a global network encompassing 44 countries and 700 research sites in a variety of ecosystems across the planet, more than 100 of which are located in coastal and marine environments (ILTER-CMS). While most of the ILTER-CMS were established after the year 2000, in some cases they date back to the early 1900s. At ILTER sites, a broad variety of abiotic and biotic variables are measured, which may feed into other global initiatives. The ILTER community has produced tools to harmonize and compare measurements and methods, allowing for data integration workflows and analyses between and within individual ILTER sites. After a brief historical overview of ILTER, with emphasis on the marine component, we analyze the potential contribution of the ILTER-CMS to global coastal and ocean observation, adopting the “Strength, Weakness, Opportunity and Threats (SWOT)” approach. We also identify ways in which the in situ parameters collected at ILTER sites currently fit within the Essential Ocean Variables framework (as proposed by the Framework for Ocean Observation recommendations) and provide insights on the use of new technology in long-term studies. Final recommendations point at the need to further develop observational activities at LTER sites and improve coordination among them and with external related initiatives in order to maximize their exploitation and address present and future challenges in ocean observations.

Description: JM was supported by a CNPq fellowship (Grant No. 310047/2016-1) and by PELD Estuário da Lagoa dos Patos e Costa Adjacente (CNPq/CAPES/FAPERGS). SB was supported by US NSF (Grant #OCE-1655686). AB was supported by CAPES/CNPq/FAPES grant no. 441243/2016-9 to PELD Coastal Habitats of Espírito Santo as part of the Brazilian LTER program. HS was supported by US NSF (Grant #CCF-1539256 and #OCE-1655686), Simons Foundation (Grant #561126) and US NOAA/CINAR (Cooperative Agreement NA14OAR4320158).