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The Scientific World Journal
Volume 2012 (2012), Article ID 450685, 23 pages
http://dx.doi.org/10.1100/2012/450685
Research Article

An Adaptive Framework for Selecting Environmental Monitoring Protocols to Support Ocean Renewable Energy Development

1Graduate School of Oceanography, University of Rhode Island, South Ferry Road, Narragansett, RI 02882, USA
2Coastal Resources Center and Rhode Island Sea Grant, University of Rhode Island, Narragansett, RI 02882, USA
3Rhode Island Coastal Resources Management Council, South Kingstown, RI 02879, USA
4College of the Environmental and Life Sciences, University of Rhode Island, Kingston, RI 02881, USA
5College of Engineering, University of Rhode Island, Narragansett, RI 02882, USA

Received 17 August 2012; Accepted 23 September 2012

Academic Editors: A. Azzellino and J. P. Kofoed

Copyright © 2012 Emily J. Shumchenia et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [3 citations]

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  • Huan-Ming Chuang, Chien-Ku Lin, Da-Ren Chen, and You-Shyang Chen, “Evolving MCDM Applications Using Hybrid Expert-Based ISM and DEMATEL Models: An Example of Sustainable Ecotourism,” The Scientific World Journal, vol. 2013, pp. 1–18, 2013. View at Publisher · View at Google Scholar
  • Juliane Steinhardt, Paul G. Butler, Michael L. Carroll, and John Hartley, “The Application of Long-Lived Bivalve Sclerochronology in Environmental Baseline Monitoring,” Frontiers in Marine Science, vol. 3, 2016. View at Publisher · View at Google Scholar
  • Hannah L. Linder, and John K. Horne, “Evaluating statistical models to measure environmental change: A tidal turbine case study,” Ecological Indicators, vol. 84, pp. 765–792, 2018. View at Publisher · View at Google Scholar