Bograd Steven

No Thumbnail Available
Last Name
Bograd
First Name
Steven
ORCID

Filters

2019 - 2019 1 2020 - 2021 4
3 2
5
Reset filters

Settings

Search Results

Now showing 1 - 5 of 5
  • Article
    A standardisation framework for bio-logging data to advance ecological research and conservation
    (Wiley, 2021-03-15) Sequeira, Ana M. M. ; O'Toole, Malcolm ; Keates, Theresa R. ; McDonnell, Laura H. ; Braun, Camrin D. ; Hoenner, Xavier ; Jaine, Fabrice R. A. ; Jonsen, Ian ; Newman, Peggy ; Pye, Jonathan ; Bograd, Steven ; Hays, Graeme ; Hazen, Elliott L. ; Holland, Melinda ; Tsontos, Vardis ; Blight, Clint ; Cagnacci, Francesca ; Davidson, Sarah C. ; Dettki, Holger ; Duarte, Carlos M. ; Dunn, Daniel C. ; Eguíluz, Víctor M. ; Fedak, Michael ; Gleiss, Adrian C. ; Hammerschlag, Neil ; Hindell, Mark ; Holland, Kim ; Janekovic, Ivica ; McKinzie, Megan K. ; Muelbert, Monica M. C. ; Pattiaratchi, Charitha ; Rutz, Christian ; Sims, David W. ; Simmons, Samantha E. ; Townsend, Brendal ; Whoriskey, Frederick G. ; Woodward, Bill ; Costa, Daniel P. ; Heupel, Michelle R. ; McMahon, Clive R. ; Harcourt, Robert ; Weise, Michael
    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.
  • Dataset
    Physical indicators of winter climate variability (coastal upwelling, sea level, precipitation) influenced by the winter North Pacific High (CalBenJI project)
    (Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu, 2021-12-27) Black, Bryan ; Bograd, Steven ; Garcia Reyes, Marisol ; Sydeman, William
    Physical indicators of winter climate variability (coastal upwelling, sea level, precipitation) influenced by the winter North Pacific High. 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/686578
  • Dataset
    Path analysis, run in Stata v. 11.1, for direct/indirect effects of upwelling on seabirds; data were collected at Dassen and Robben Islands, Malgas Island and in Lamberts Bay, South Africa
    (Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu, 2019-08-05) Black, Bryan ; Bograd, Steven ; Garcia Reyes, Marisol ; Sydeman, William
    Path analysis, run in Stata v. 11.1, for direct/indirect effects of upwelling on seabirds; data were collected at Dassen and Robben Islands, Malgas Island and in Lamberts Bay, South Africa. 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/679946
  • Dataset
    Monthly Regional Cumulative Upwelling Index (Ekman transport) for California and Benguela Ecosystems from 1979-2014
    (Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu, 2021-12-27) Black, Bryan ; Bograd, Steven ; Garcia Reyes, Marisol ; Sydeman, William
    Monthly Regional Cumulative Upwelling Index (Ekman transport) for California and Benguela Ecosystems from 1979-2014/ 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/674979
  • Article
    Seasonal-to-interannual prediction of North American coastal marine ecosystems: forecast methods, mechanisms of predictability, and priority developments
    (Elsevier, 2020-02-20) Jacox, Michael ; Alexander, Michael A. ; Siedlecki, Samantha A. ; Chen, Ke ; Kwon, Young-Oh ; Brodie, Stephanie ; Ortiz, Ivonne ; Tommasi, Desiree ; Widlansky, Matthew J. ; Barrie, Daniel ; Capotondi, Antonietta ; Cheng, Wei ; Di Lorenzo, Emanuele ; Edwards, Christopher ; Fiechter, Jerome ; Fratantoni, Paula S. ; Hazen, Elliott L. ; Hermann, Albert J. ; Kumar, Arun ; Miller, Arthur J. ; Pirhalla, Douglas ; Pozo Buil, Mercedes ; Ray, Sulagna ; Sheridan, Scott ; Subramanian, Aneesh C. ; Thompson, Philip ; Thorne, Lesley ; Annamalai, Hariharasubramanian ; Aydin, Kerim ; Bograd, Steven ; Griffis, Roger B. ; Kearney, Kelly ; Kim, Hyemi ; Mariotti, Annarita ; Merrifield, Mark ; Rykaczewski, Ryan R.
    Marine ecosystem forecasting is an area of active research and rapid development. Promise has been shown for skillful prediction of physical, biogeochemical, and ecological variables on a range of timescales, suggesting potential for forecasts to aid in the management of living marine resources and coastal communities. However, the mechanisms underlying forecast skill in marine ecosystems are often poorly understood, and many forecasts, especially for biological variables, rely on empirical statistical relationships developed from historical observations. Here, we review statistical and dynamical marine ecosystem forecasting methods and highlight examples of their application along U.S. coastlines for seasonal-to-interannual (1–24 month) prediction of properties ranging from coastal sea level to marine top predator distributions. We then describe known mechanisms governing marine ecosystem predictability and how they have been used in forecasts to date. These mechanisms include physical atmospheric and oceanic processes, biogeochemical and ecological responses to physical forcing, and intrinsic characteristics of species themselves. In reviewing the state of the knowledge on forecasting techniques and mechanisms underlying marine ecosystem predictability, we aim to facilitate forecast development and uptake by (i) identifying methods and processes that can be exploited for development of skillful regional forecasts, (ii) informing priorities for forecast development and verification, and (iii) improving understanding of conditional forecast skill (i.e., a priori knowledge of whether a forecast is likely to be skillful). While we focus primarily on coastal marine ecosystems surrounding North America (and the U.S. in particular), we detail forecast methods, physical and biological mechanisms, and priority developments that are globally relevant.