ALBERT

Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Farrell, U. C., Samawi, R., Anjanappa, S., Klykov, R., Adeboye, O. O., Agic, H., Ahm, A.-S. C., Boag, T. H., Bowyer, F., Brocks, J. J., Brunoir, T. N., Canfield, D. E., Chen, X., Cheng, M., Clarkson, M. O., Cole, D. B., Cordie, D. R., Crockford, P. W., Cui, H., Dahl, T. W., Mouro, L. D., Dewing, K., Dornbos, S. Q., Drabon, N., Dumoulin, J. A., Emmings, J. F., Endriga, C. R., Fraser, T. A., Gaines, R. R., Gaschnig, R. M., Gibson, T. M., Gilleaudeau, G. J., Gill, B. C., Goldberg, K., Guilbaud, R., Halverson, G. P., Hammarlund, E. U., Hantsoo, K. G., Henderson, M. A., Hodgskiss, M. S. W., Horner, Tristan J., Husson, J. M., Johnson, B., Kabanov, P., Brenhin K. C., Kimmig, J., Kipp, M. A., Knoll, A. H., Kreitsmann, T., Kunzmann, M., Kurzweil, F., LeRoy, M. A., Li, C., Lipp, A. G., Loydell, D. K., Lu, X., Macdonald, F. A., Magnall, J. M., Mänd, K., Mehra, A., Melchin, M. J., Miller, A. J., Mills, N. T., Mwinde, C. N., O'Connell, B., Och, L. M., Ossa Ossa, F., Pagès, A., Paiste, K., Partin, C. A., Peters, S. E., Petrov, P., Playter, T. L., Plaza-Torres, S., Porter, Susannah M., Poulton, S. W., Pruss, S. B., Richoz, S., Ritzer, S. R., Rooney, A. D., Sahoo, S. K., Schoepfer, S. D., Sclafani, J. A., Shen, Y., Shorttle, O., Slotznick, S. P., Smith, E. F., Spinks, S., Stockey, R. G., Strauss, J. V., Stüeken, E. E., Tecklenburg, S., Thomson, D., Tosca, N. J., Uhlein, G. J., Vizcaíno, M. N., Wang, H., White, T., Wilby, P. R., Woltz, C. R., Wood, R. A., Xiang, L., Yurchenko, I. A., Zhang, T., Planavsky, N. J., Lau, K. V., Johnston, D. T., Sperling, E. A., The Sedimentary Geochemistry and Paleoenvironments Project. Geobiology. 00, (2021): 1– 12,https://doi.org/10.1111/gbi.12462.

Description: Geobiology explores how Earth's system has changed over the course of geologic history and how living organisms on this planet are impacted by or are indeed causing these changes. For decades, geologists, paleontologists, and geochemists have generated data to investigate these topics. Foundational efforts in sedimentary geochemistry utilized spreadsheets for data storage and analysis, suitable for several thousand samples, but not practical or scalable for larger, more complex datasets. As results have accumulated, researchers have increasingly gravitated toward larger compilations and statistical tools. New data frameworks have become necessary to handle larger sample sets and encourage more sophisticated or even standardized statistical analyses. In this paper, we describe the Sedimentary Geochemistry and Paleoenvironments Project (SGP; Figure 1), which is an open, community-oriented, database-driven research consortium. The goals of SGP are to (1) create a relational database tailored to the needs of the deep-time (millions to billions of years) sedimentary geochemical research community, including assembling and curating published and associated unpublished data; (2) create a website where data can be retrieved in a flexible way; and (3) build a collaborative consortium where researchers are incentivized to contribute data by giving them priority access and the opportunity to work on exciting questions in group papers. Finally, and more idealistically, the goal was to establish a culture of modern data management and data analysis in sedimentary geochemistry. Relative to many other fields, the main emphasis in our field has been on instrument measurement of sedimentary geochemical data rather than data analysis (compared with fields like ecology, for instance, where the post-experiment ANOVA (analysis of variance) is customary). Thus, the longer-term goal was to build a collaborative environment where geobiologists and geologists can work and learn together to assess changes in geochemical signatures through Earth history.

Description: We thank the donors of The American Chemical Society Petroleum Research Fund for partial support of SGP website development (61017-ND2). EAS is funded by National Science Foundation grant (NSF) EAR-1922966. BGS authors (JE, PW) publish with permission of the Executive Director of the British Geological Survey, UKRI.

Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Sequeira, A. M. M., O'Toole, M., Keates, T. R., McDonnell, L. H., Braun, C. D., Hoenner, X., Jaine, F. R. A., Jonsen, I. D., Newman, P., Pye, J., Bograd, S. J., Hays, G. C., Hazen, E. L., Holland, M., Tsontos, V. M., Blight, C., Cagnacci, F., Davidson, S. C., Dettki, H., Duarte, C. M., Dunn, D. C., Eguiluz, V. M., Fedak, M., Gleiss, A. C., Hammerschlag, N., Hindell, M. A., Holland, K., Janekovic, I., McKinzie, M. K., Muelbert, M. M. C., Pattiaratchi, C., Rutz, C., Sims, D. W., Simmons, S. E., Townsend, B., Whoriskey, F., Woodward, B., Costa, D. P., Heupel, M. R., McMahon, C. R., Harcourt, R., & Weise, M. A standardisation framework for bio-logging data to advance ecological research and conservation. Methods in Ecology and Evolution, 12, (2021): 996–1007, https://doi.org/10.1111/2041-210X.13593.

Description: 1. Bio-logging data obtained by tagging animals are key to addressing global conservation challenges. However, the many thousands of existing bio-logging datasets are not easily discoverable, universally comparable, nor readily accessible through existing repositories and across platforms, slowing down ecological research and effective management. A set of universal standards is needed to ensure discoverability, interoperability and effective translation of bio-logging data into research and management recommendations. 2. We propose a standardisation framework adhering to existing data principles (FAIR: Findable, Accessible, Interoperable and Reusable; and TRUST: Transparency, Responsibility, User focus, Sustainability and Technology) and involving the use of simple templates to create a data flow from manufacturers and researchers to compliant repositories, where automated procedures should be in place to prepare data availability into four standardised levels: (a) decoded raw data, (b) curated data, (c) interpolated data and (d) gridded data. Our framework allows for integration of simple tabular arrays (e.g. csv files) and creation of sharable and interoperable network Common Data Form (netCDF) files containing all the needed information for accuracy-of-use, rightful attribution (ensuring data providers keep ownership through the entire process) and data preservation security. 3. We show the standardisation benefits for all stakeholders involved, and illustrate the application of our framework by focusing on marine animals and by providing examples of the workflow across all data levels, including filled templates and code to process data between levels, as well as templates to prepare netCDF files ready for sharing. 4. Adoption of our framework will facilitate collection of Essential Ocean Variables (EOVs) in support of the Global Ocean Observing System (GOOS) and inter-governmental assessments (e.g. the World Ocean Assessment), and will provide a starting point for broader efforts to establish interoperable bio-logging data formats across all fields in animal ecology.

Description: We are thankful to ONR and UWA OI for funding the workshop, and to ARC for DP210103091. A.M.M.S. was funded by a 2020 Pew Fellowship in Marine Conservation, and also supported by AIMS. C.R. was the recipient of a Radcliffe Fellowship at the Radcliffe Institute for Advanced Study, Harvard University.

Description: Dataset: GP16 Soluble and Dissolved Fe and Fe Isotopes

Description: Concentrations of soluble and dissolved iron (Fe) and iron isotope ratios from the U.S. GEOTRACES EPZT cruise (GP16, TN303) on R/V Thomas G. Thompson in the tropical Pacific during November & December 2013. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/818707

Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1234827, NSF Division of Ocean Sciences (NSF OCE) OCE-1713677, NSF Division of Ocean Sciences (NSF OCE) OCE-1434493

Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Davis, G. E., Baumgartner, M. F., Corkeron, P. J., Bell, J., Berchok, C., Bonnell, J. M., Thornton, J. B., Brault, S., Buchanan, G. A., Cholewiak, D. M., Clark, C. W., Delarue, J., Hatch, L. T., Klinck, H., Kraus, S. D., Martin, B., Mellinger, D. K., Moors-Murphy, H., Nieukirk, S., Nowacek, D. P., Parks, S. E., Parry, D., Pegg, N., Read, A. J., Rice, A. N., Risch, D., Scott, A., Soldevilla, M. S., Stafford, K. M., Stanistreet, J. E., Summers, E., Todd, S., & Van Parijs, S. M. Exploring movement patterns and changing distributions of baleen whales in the western North Atlantic using a decade of passive acoustic data. Global Change Biology, (2020): 1-30, doi:10.1111/gcb.15191.

Description: Six baleen whale species are found in the temperate western North Atlantic Ocean, with limited information existing on the distribution and movement patterns for most. There is mounting evidence of distributional shifts in many species, including marine mammals, likely because of climate‐driven changes in ocean temperature and circulation. Previous acoustic studies examined the occurrence of minke (Balaenoptera acutorostrata ) and North Atlantic right whales (NARW; Eubalaena glacialis ). This study assesses the acoustic presence of humpback (Megaptera novaeangliae ), sei (B. borealis ), fin (B. physalus ), and blue whales (B. musculus ) over a decade, based on daily detections of their vocalizations. Data collected from 2004 to 2014 on 281 bottom‐mounted recorders, totaling 35,033 days, were processed using automated detection software and screened for each species' presence. A published study on NARW acoustics revealed significant changes in occurrence patterns between the periods of 2004–2010 and 2011–2014; therefore, these same time periods were examined here. All four species were present from the Southeast United States to Greenland; humpback whales were also present in the Caribbean. All species occurred throughout all regions in the winter, suggesting that baleen whales are widely distributed during these months. Each of the species showed significant changes in acoustic occurrence after 2010. Similar to NARWs, sei whales had higher acoustic occurrence in mid‐Atlantic regions after 2010. Fin, blue, and sei whales were more frequently detected in the northern latitudes of the study area after 2010. Despite this general northward shift, all four species were detected less on the Scotian Shelf area after 2010, matching documented shifts in prey availability in this region. A decade of acoustic observations have shown important distributional changes over the range of baleen whales, mirroring known climatic shifts and identifying new habitats that will require further protection from anthropogenic threats like fixed fishing gear, shipping, and noise pollution.

Description: We thank Chris Pelkie, David Wiley, Michael Thompson, Chris Tessaglia‐Hymes, Eric Matzen, Chris Tremblay, Lance Garrison, Anurag Kumar, John Hildebrand, Lynne Hodge, Russell Charif, Kathleen Dudzinski, and Ann Warde for help with project planning, field work support, and data management. For all the support and advice, thanks to the NEFSC Protected Species Branch, especially the passive acoustics group, Josh Hatch, and Leah Crowe. We thank the field and crew teams on all the ships that helped in the numerous deployments and recoveries. This research was funded and supported by many organizations, specified by projects as follows: data recordings from region 1 were provided by K. Stafford (funding: National Science Foundation #NSF‐ARC 0532611). Region 2 data: D. K. Mellinger and S. Nieukirk, National Oceanic and Atmospheric Administration (NOAA) PMEL contribution #5055 (funding: NOAA and the Office of Naval Research #N00014–03–1–0099, NOAA #NA06OAR4600100, US Navy #N00244‐08‐1‐0029, N00244‐09‐1‐0079, and N00244‐10‐1‐0047). Region 3A data: D. Risch (funding: NOAA and Navy N45 programs). Region 3 data: H. Moors‐Murphy and Fisheries and Oceans Canada (2005–2014 data), and the Whitehead Lab of Dalhousie University (eastern Scotian Shelf data; logistical support by A. Cogswell, J. Bartholette, A. Hartling, and vessel CCGS Hudson crew). Emerald Basin and Roseway Basin Guardbuoy data, deployment, and funding: Akoostix Inc. Region 3 Emerald Bank and Roseway Basin 2004 data: D. K. Mellinger and S. Nieukirk, NOAA PMEL contribution #5055 (funding: NOAA). Region 4 data: S. Parks (funding: NOAA and Cornell University) and E. Summers, S. Todd, J. Bort Thornton, A. N. Rice, and C. W. Clark (funding: Maine Department of Marine Resources, NOAA #NA09NMF4520418, and #NA10NMF4520291). Region 5 data: S. M. Van Parijs, D. Cholewiak, L. Hatch, C. W. Clark, D. Risch, and D. Wiley (funding: National Oceanic Partnership Program (NOPP), NOAA, and Navy N45). Region 6 data: S. M. Van Parijs and D. Cholewiak (funding: Navy N45 and Bureau of Ocean and Energy Management (BOEM) Atlantic Marine Assessment Program for Protected Species [AMAPPS] program). Region 7 data: A. N. Rice, H. Klinck, A. Warde, B. Martin, J. Delarue, and S. Kraus (funding: New York State Department of Environmental Conservation, Massachusetts Clean Energy Center, and BOEM). Region 8 data: G. Buchanan, and K. Dudzinski (funding: New Jersey Department of Environmental Protection and the New Jersey Clean Energy Fund) and A. N. Rice, C. W. Clark, and H. Klinck (funding: Center for Conservation Bioacoustics at Cornell University and BOEM). Region 9 data: J. E. Stanistreet, J. Bell, D. P. Nowacek, A. J. Read, and S. M. Van Parijs (funding: NOAA and US Fleet Forces Command). Region 10 data: L. Garrison, M. Soldevilla, C. W. Clark, R. A. Chariff, A. N. Rice, H. Klinck, J. Bell, D. P. Nowacek, A. J. Read, J. Hildebrand, A. Kumar, L. Hodge, and J. E. Stanistreet (funding: US Fleet Forces Command, BOEM, NOAA, and NOPP). Region 11 data: C. Berchok as part of a collaborative project led by the Fundacion Dominicana de Estudios Marinos, Inc. (Dr. Idelisa Bonnelly de Calventi; funding: The Nature Conservancy [Elianny Dominguez]) and D. Risch (funding: World Wildlife Fund, NOAA, and Dutch Ministry of Economic Affairs).

Description: Dataset: OlyGrowth_Expt_2018_Mortality

Description: Olympia oyster mortality samples from cultures in 50 unique combinations of temperature, salinity, pCO2 at Shannon Point Marine Center in May 2018. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/776293

Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1538626

Description: Dataset: OlyGrowth_Expt_2018_Growth

Description: Olympia oyster growth samples cultured in 50 unique combinations of temperature, salinity, pCO2 at Shannon Point Marine Center in May 2018. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/776281

Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1538626

Description: © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Seyler, L. M., Brazelton, W. J., McLean, C., Putman, L. I., Hyer, A., Kubo, M. D. Y., Hoehler, T., Cardace, D., & Schrenk, M. O. . Carbon assimilation strategies in ultrabasic groundwater: clues from the integrated study of a serpentinization-influenced aquifer. mSystems, 5(2), (2020): e00607-00619, doi: 10.1128/mSystems.00607-19.

Description: Serpentinization is a low-temperature metamorphic process by which ultramafic rock chemically reacts with water. Such reactions provide energy and materials that may be harnessed by chemosynthetic microbial communities at hydrothermal springs and in the subsurface. However, the biogeochemistry mediated by microbial populations that inhabit these environments is understudied and complicated by overlapping biotic and abiotic processes. We applied metagenomics, metatranscriptomics, and untargeted metabolomics techniques to environmental samples taken from the Coast Range Ophiolite Microbial Observatory (CROMO), a subsurface observatory consisting of 12 wells drilled into the ultramafic and serpentinite mélange of the Coast Range Ophiolite in California. Using a combination of DNA and RNA sequence data and mass spectrometry data, we found evidence for several carbon fixation and assimilation strategies, including the Calvin-Benson-Bassham cycle, the reverse tricarboxylic acid cycle, the reductive acetyl coenzyme A (acetyl-CoA) pathway, and methylotrophy, in the microbial communities inhabiting the serpentinite-hosted aquifer. Our data also suggest that the microbial inhabitants of CROMO use products of the serpentinization process, including methane and formate, as carbon sources in a hyperalkaline environment where dissolved inorganic carbon is unavailable.

Description: We thank McLaughlin Reserve, in particular Paul Aigner and Cathy Koehler, for hosting sampling at CROMO and providing access to the wells, A. Daniel Jones and Anthony Schilmiller for their advice regarding metabolite extraction and mass spectrometry, Elizabeth Kujawinski for her guidance in metabolomics data analysis and interpretation, and Julia McGonigle, Christopher Thornton, and Katrina Twing for assistance with metagenomic and computational analyses.

Description: Dataset: Coral Surface Area and Zooxanthellae Counts

Description: This dataset presents coral fragment surface area calculations utilizing two methods (tin foil and Image J) and corresponding zooxanthellae count data. Three coral species were utilized in this experiment: the octocoral, Eunicea flexuosa, and two hard coral species, Acropora cervicornis and Orbicella faveolata. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/880711

Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1924540, NSF Division of Ocean Sciences (NSF OCE) OCE-1923962

Description: Dataset: WAP model SSH and tracer

Description: NetCDF model output of the simulated sea surface height, surface passive tracer concentration. and model grid data from a West Antarctic Peninsula ROMS model. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/831045

Description: NSF Office of Polar Programs (formerly NSF PLR) (NSF OPP) OPP-1643468, NSF Office of Polar Programs (formerly NSF PLR) (NSF OPP) OPP-1643386

Description: Dataset: OlyGrowth_Expt_2018_Chemistry

Description: Daily water chemistry measurements from a larval growth experiment culturing Olympia oysters in 50 unique combinations of temperature, salinity, and pCO2 over up to 17 days of larval life. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/776260

Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1538626