Data management strategy to improve global use of ocean acidification data and information

Author Posting. © The Oceanography Society, 2015. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 28, no. 2 (2015): 226-228, doi:10.5670/oceanog.2015.45. Ocean acidification (OA) refe...

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Bibliographic Details
Published in:Oceanography
Main Authors: Garcia, Hernan E., Cosca, Catherine E., Kozyr, Alex, Mayorga, Emilio, Chandler, Cynthia L., Thomas, Robert W., O’Brien, Kevin, Appeltans, Ward, Hankin, Steve, Newton, Jan A., Gutierrez, Angelica, Gattuso, Jean-Pierre, Hansson, Lina, Zweng, Melissa, Pfeil, Benjamin
Format: Article in Journal/Newspaper
Language:English
Published: The Oceanography Society 2015
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Online Access:https://hdl.handle.net/1912/7444
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Summary:Author Posting. © The Oceanography Society, 2015. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 28, no. 2 (2015): 226-228, doi:10.5670/oceanog.2015.45. Ocean acidification (OA) refers to the general decrease in pH of the global ocean as a result of absorbing anthropogenic CO2 emitted in the atmosphere since preindustrial times (Sabine et al., 2004). There is, however, considerable variability in ocean acidification, and many careful measurements need to be made and compared in order to obtain scientifically valid information for the assessment of patterns, trends, and impacts over a range of spatial and temporal scales, and to understand the processes involved. A single country or institution cannot undertake measurements of worldwide coastal and open ocean OA changes; therefore, international cooperation is needed to achieve that goal. The OA data that have been, and are being, collected represent a significant public investment. To this end, it is critically important that researchers (and others) around the world are easily able to find and use reliable OA information that range from observing data (from time-series moorings, process studies, and research cruises), to biological response experiments (e.g., mesocosm), data products, and model output.