ALBERT

Description: Development of global ocean observing capacity for the biological EOVs is on the cusp of a step-change. Current capacity to automate data collection and processing and to integrate the resulting data streams with complementary data, openly available as FAIR data, is certain to dramatically increase the amount and quality of information and knowledge available to scientists and decision makers into the future. There is little doubt that scientists will continue to expand their understanding of what lives in the ocean, where it lives and how it is changing. However, whether this expanding information stream will inform policy and management or be incorporated into indicators for national reporting is more uncertain. Coordinated data collection including open sharing of data will help produce the consistent evidence-based messages that are valued by managers. The GOOS Biology and Ecosystems Panel is working with other global initiatives to assist this coordination by defining and implementing Essential Ocean Variables. The biological EOVs have been defined, are being updated following community feedback, and their implementation is underway. In 2019, the coverage and precision of a global ocean observing system capable of addressing key questions for the next decade will be quantified, and its potential to support the goals of the UN Decade of Ocean Science for Sustainable Development identified. Developing a global ocean observing system for biology and ecosystems requires parallel efforts in improving evidence-based monitoring of progress against international agreements and the open data, reporting and governance structures that would facilitate the uptake of improved information by decision makers.

Description: Author Posting. © University of California Press and American Institute of Biological Sciences, 2013. This article is posted here by permission of University of California Press and American Institute of Biological Sciences for personal use, not for redistribution. The definitive version was published in BioScience 63 (2013): 350-361, doi:10.1525/bio.2013.63.5.8.

Description: Humans depend on diverse ocean ecosystems for food, jobs, and sustained well-being, yet many stressors threaten marine life. Extensive research has demonstrated that maintaining biodiversity promotes ocean health and service provision; therefore, monitoring the status and trends of marine biodiversity is important for effective ecosystem management. However, there is no systematic sustained program for evaluating ocean biodiversity. Coordinating existing monitoring and building a proactive marine biodiversity observation network will support efficient, economical resource management and conservation and should be a high priority. A synthesis of expert opinions suggests that, to be most effective, a marine biodiversity observation network should integrate biological levels, from genes to habitats; link biodiversity observations to abiotic environmental variables; site projects to incorporate environmental forcing and biogeography; and monitor adaptively to address emerging issues. We summarize examples illustrating how to leverage existing data and infrastructure to meet these goals.

Description: © The Author(s), 2018]. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Global Ecology and Biogeography 27 (2018): 760-786, doi:10.1111/geb.12729.

Description: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km2 (158 cm2) to 100 km2 (1,000,000,000,000 cm2). BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.

Description: European Research Council and EU, Grant/Award Number: AdG‐250189, PoC‐727440 and ERC‐SyG‐2013‐610028; Natural Environmental Research Council, Grant/Award Number: NE/L002531/1; National Science Foundation, Grant/Award Number: DEB‐1237733, DEB‐1456729, 9714103, 0632263, 0856516, 1432277, DEB‐9705814, BSR‐8811902, DEB 9411973, DEB 0080538, DEB 0218039, DEB 0620910, DEB 0963447, DEB‐1546686, DEB‐129764, OCE 95‐21184, OCE‐ 0099226, OCE 03‐52343, OCE‐0623874, OCE‐1031061, OCE‐1336206 and DEB‐1354563; National Science Foundation (LTER) , Grant/Award Number: DEB‐1235828, DEB‐1440297, DBI‐0620409, DEB‐9910514, DEB‐1237517, OCE‐0417412, OCE‐1026851, OCE‐1236905, OCE‐1637396, DEB 1440409, DEB‐0832652, DEB‐0936498, DEB‐0620652, DEB‐1234162 and DEB‐0823293; Fundação para a Ciência e Tecnologia, Grant/Award Number: POPH/FSE SFRH/BD/90469/2012, SFRH/BD/84030/2012, PTDC/BIA‐BIC/111184/2009; SFRH/BD/80488/2011 and PD/BD/52597/2014; Ciência sem Fronteiras/CAPES, Grant/Award Number: 1091/13‐1; Instituto Milenio de Oceanografía, Grant/Award Number: IC120019; ARC Centre of Excellence, Grant/Award Number: CE0561432; NSERC Canada; CONICYT/FONDECYT, Grant/Award Number: 1160026, ICM PO5‐002, CONICYT/FONDECYT, 11110351, 1151094, 1070808 and 1130511; RSF, Grant/Award Number: 14‐50‐00029; Gordon and Betty Moore Foundation, Grant/Award Number: GBMF4563; Catalan Government; Marie Curie Individual Fellowship, Grant/Award Number: QLK5‐CT2002‐51518 and MERG‐CT‐2004‐022065; CNPq, Grant/Award Number: 306170/2015‐9, 475434/2010‐2, 403809/2012‐6 and 561897/2010; FAPESP (São Paulo Research Foundation), Grant/Award Number: 2015/10714‐6, 2015/06743‐0, 2008/10049‐9, 2013/50714‐0 and 1999/09635‐0 e 2013/50718‐5; EU CLIMOOR, Grant/Award Number: ENV4‐CT97‐0694; VULCAN, Grant/Award Number: EVK2‐CT‐2000‐00094; Spanish, Grant/Award Number: REN2000‐0278/CCI, REN2001‐003/GLO and CGL2016‐79835‐P; Catalan, Grant/Award Number: AGAUR SGR‐2014‐453 and SGR‐2017‐1005; DFG, Grant/Award Number: 120/10‐2; Polar Continental Shelf Program; CENPES – PETROBRAS; FAPERJ, Grant/Award Number: E‐26/110.114/2013; German Academic Exchange Service; sDiv; iDiv; New Zealand Department of Conservation; Wellcome Trust, Grant/Award Number: 105621/Z/14/Z; Smithsonian Atherton Seidell Fund; Botanic Gardens and Parks Authority; Research Council of Norway; Conselleria de Innovació, Hisenda i Economia; Yukon Government Herschel Island‐Qikiqtaruk Territorial Park; UK Natural Environment Research Council ShrubTundra Grant, Grant/Award Number: NE/M016323/1; IPY; Memorial University; ArcticNet. DOI: 10.13039/50110000027. Netherlands Organization for Scientific Research in the Tropics NWO, grant W84‐194. Ciências sem Fronteiras and Coordenação de Pessoal de Nível Superior (CAPES, Brazil), Grant/Award Number: 1091/13‐1. National Science foundation (LTER), Award Number: OCE‐9982105, OCE‐0620276, OCE‐1232779. FCT ‐ SFRH / BPD / 82259 / 2011. U.S. Fish and Wildlife Service/State Wildlife federal grant number T‐15. Australian Research Council Centre of Excellence for Coral Reef Studies (CE140100020). Australian Research Council Future Fellowship FT110100609. M.B., A.J., K.P., J.S. received financial support from internal funds of University of Lódź. NSF DEB 1353139. Catalan Government fellowships (DURSI): 1998FI‐00596, 2001BEAI200208, MECD Post‐doctoral fellowship EX2002‐0022. National Science Foundation Award OPP‐1440435. FONDECYT 1141037 and FONDAP 15150003 (IDEAL). CNPq Grant 306595‐2014‐1

Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Benson, A., Brooks, C. M., Canonico, G., Duffy, E., Muller-Karger, F., Sosik, H. M., Miloslavich, P., & Klein, E.. Integrated observations and informatics improve understanding of changing marine ecosystems. Frontiers in Marine Science, 5, (2018):428, doi:10.3389/fmars.2018.00428.

Description: Marine ecosystems have numerous benefits for human societies around the world and many policy initiatives now seek to maintain the health of these ecosystems. To enable wise decisions, up to date and accurate information on marine species and the state of the environment they live in is required. Moreover, this information needs to be openly accessible to build indicators and conduct timely assessments that decision makers can use. The questions and problems being addressed demand global-scale investigations, transdisciplinary science, and mechanisms to integrate and distribute data that otherwise would appear to be disparate. Essential Ocean Variables (EOVs) and marine Essential Biodiversity Variables (EBVs), conceptualized by the Global Ocean Observing System (GOOS) and the Marine Biodiversity Observation Network (MBON), respectively, guide observation of the ocean. Additionally, significant progress has been made to coordinate efforts between existing programs, such as the GOOS, MBON, and Ocean Biogeographic Information System collaboration agreement. Globally and nationally relevant indicators and assessments require increased sharing of data and analytical methods, sustained long-term and large-scale observations, and resources to dedicated to these tasks. We propose a vision and key tenets as a guiding framework for building a global integrated system for understanding marine biological diversity and processes to address policy and resource management needs. This framework includes: using EOVs and EBVs and implementing the guiding principles of Findable, Accessible, Interoperable, Reusable (FAIR) data and action ecology. In doing so, we can encourage relevant, rapid, and integrative scientific advancement that can be implemented by decision makers to maintain marine ecosystem health.

Description: We thank T.Malone and A. Knap for the invitation to contribute our ideas to this topic. We also thank the two reviewers and editor for their comments, which strengthened our manuscript.

Description: Dataset: HOBO temperatures from eelgrass field surveys

Description: As part of field surveys to measure effects of eelgrass wasting disease, HOBO temperature loggers were deployed from July 2019 to July 2021 at field sites along the west coast of North America to provide a continuous record of in situ temperatures. 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/877355

Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1829890, NSF Division of Ocean Sciences (NSF OCE) OCE-1829922, NSF Division of Ocean Sciences (NSF OCE) OCE-1829921, NSF Division of Ocean Sciences (NSF OCE) OCE-1829992

Description: Dataset: Eelgrass Shoot Density

Description: These data were collected during ecological field surveys of eelgrass (Zostera marina) meadows along the eastern Pacific from southeastern Alaska to southern California. Parameters measured include seagrass morphology, meadow condition (e.g. shoot densities), and incidence and severity of eelgrass wasting disease. Data were collected within the intertidal area of 32 eelgrass meadows distributed in six regions (five-six meadows sampled in the regions of Alaska, British Columbia, Washington, Oregon, California - Bodega Bay, and California - San Diego). Surveys were conducted in between late June and early August in 2019, 2020, and 2021 by teams from six institutions. The influence of disease on seagrass dynamics is not well understood, and these data can further understanding of the environmental drivers of disease by connecting wasting disease with eelgrass condition across a broad geographic gradient. 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/879764

Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1829890, NSF Division of Ocean Sciences (NSF OCE) OCE-1829922, NSF Division of Ocean Sciences (NSF OCE) OCE-1829921, NSF Division of Ocean Sciences (NSF OCE) OCE-1829992

Description: Dataset: Eelgrass Shoot Metrics

Description: These data were collected during ecological field surveys of eelgrass (Zostera marina) meadows along the eastern Pacific from southeastern Alaska to southern California. Parameters measured include seagrass morphology, meadow condition (e.g. shoot densities), and incidence and severity of eelgrass wasting disease. Data were collected within the intertidal area of 32 eelgrass meadows distributed in six regions (five-six meadows sampled in the regions of Alaska, British Columbia, Washington, Oregon, California - Bodega Bay, and California - San Diego). Surveys were conducted in between late June and early August in 2019, 2020, and 2021 by teams from six institutions. The influence of disease on seagrass dynamics is not well understood, and these data can further understanding of the environmental drivers of disease by connecting wasting disease with eelgrass condition across a broad geographic gradient. 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/878857

Description: NSF Division of Ocean Sciences (NSF OCE) OCE-1829890, NSF Division of Ocean Sciences (NSF OCE) OCE-1829922, NSF Division of Ocean Sciences (NSF OCE) OCE-1829921, NSF Division of Ocean Sciences (NSF OCE) OCE-1829992