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      Incorporating public priorities in the Ocean Health Index: Canada as a case study

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          Abstract

          The Ocean Health Index (OHI) is a framework to assess ocean health by considering many benefits (called ‘goals’) provided by the ocean provides to humans, such as food provision, tourism opportunities, and coastal protection. The OHI framework can be used to assess marine areas at global or regional scales, but how various OHI goals should be weighted to reflect priorities at those scales remains unclear. In this study, we adapted the framework in two ways for application to Canada as a case study. First, we customized the OHI goals to create a national Canadian Ocean Health Index (COHI). In particular, we altered the list of iconic species assessed, added methane clathrates and subsea permafrost as carbon storage habitats, and developed a new goal, 'Aboriginal Needs', to measure access of Aboriginal people to traditional marine hunting and fishing grounds. Second, we evaluated various goal weighting schemes based on preferences elicited from the general public in online surveys. We quantified these public preferences in three ways: using Likert scores, simple ranks from a best-worst choice experiment, and model coefficients from the analysis of elicited choice experiment. The latter provided the clearest statistical discrimination among goals, and we recommend their use because they can more accurately reflect both public opinion and the trade-offs faced by policy-makers. This initial iteration of the COHI can be used as a baseline against which future COHI scores can be compared, and could potentially be used as a management tool to prioritise actions on a national scale and predict public support for these actions given that the goal weights are based on public priorities.

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          Most cited references26

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          Gas hydrates-geological perspective and global change

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            Best--worst scaling: What it can do for health care research and how to do it.

            Statements like "quality of care is more highly valued than waiting time" can neither be supported nor refuted by comparisons of utility parameters from a traditional discrete choice experiment (DCE). Best--worst scaling can overcome this problem because it asks respondents to perform a different choice task. However, whilst the nature of the best--worst task is generally understood, there are a number of issues relating to the design and analysis of a best--worst choice experiment that require further exposition. This paper illustrates how to aggregate and analyse such data and using a quality of life pilot study demonstrates how richer insights can be drawn by the use of best--worst tasks.
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              Assessing ecosystem health.

              D. Rapport (1998)
              Evaluating ecosystem health in relation to the ecological, economic and human health spheres requires integrating human values with biophysical processes, an integration that has been explicitly avoided by conventional science. The field is advancing with the articulation of the linkages between human activity, regional and global environmental change, reduction in ecological services and the consequences for human health, economic opportunity and human communities. Increasing our understanding of these interactions will involve more active collaboration between the ecological, social and health sciences. In this, ecologists will have substantive and catalytic roles.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                24 May 2017
                2017
                : 12
                : 5
                : e0178044
                Affiliations
                [1 ]Institut des Sciences de la Mer, Université du Québec à Rimouski, Rimouski, Québec, Canada
                [2 ]National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara, Santa Barbara, California, United States of America
                [3 ]Department of Biological Sciences, Simon Fraser University, Burnaby, British Columbia, Canada
                [4 ]Département de Biologie, Laval University, Québec, Canada
                [5 ]Hopkins Marine Station, Stanford University, Stanford, California, United States of America
                [6 ]Silwood Park, Imperial College London, Ascot, United Kingdom
                [7 ]Bren School of Environmental Science & Management, University of California, Santa Barbara, Santa Barbara, California, United States of America
                Universidade de Aveiro, PORTUGAL
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: RMD PA BSH JSSL IMC.

                • Data curation: RMD JSSH.

                • Formal analysis: RMD JSSH.

                • Funding acquisition: PA IMC.

                • Investigation: RMD.

                • Methodology: RMD PA BSH JSSL IMC.

                • Project administration: RMD PA BSH JSSL IMC.

                • Resources: RMD PA BSH JSSL IMC.

                • Software: RMD JSSH.

                • Validation: RMD JSSH.

                • Visualization: RMD JSSH.

                • Writing – original draft: RMD.

                • Writing – review & editing: RMD PA BSH JSSL IMC.

                Author information
                http://orcid.org/0000-0001-8832-4189
                Article
                PONE-D-16-49120
                10.1371/journal.pone.0178044
                5443542
                28542394
                da6bdb6d-1efb-4dd2-b58b-ef91f1a45f59
                © 2017 Daigle et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 12 December 2016
                : 7 May 2017
                Page count
                Figures: 8, Tables: 6, Pages: 22
                Funding
                Funding for this study was provided by the Natural Sciences and Engineering Research Council of Canada (NSERC)-funded Canadian Healthy Ocean Network (CHONe; NETGP 468437-14), Quebec-Ocean (Fonds de recherche du Québec – Nature et technologies 186795), and Fisheries and Ocean Canada.
                Categories
                Research Article
                Earth Sciences
                Marine and Aquatic Sciences
                Bodies of Water
                Oceans
                People and places
                Geographical locations
                North America
                Canada
                Earth Sciences
                Glaciology
                Sea Ice
                Biology and Life Sciences
                Ecology
                Biodiversity
                Ecology and Environmental Sciences
                Ecology
                Biodiversity
                Physical Sciences
                Chemistry
                Chemical Compounds
                Methane
                Biology and Life Sciences
                Ecology
                Marine Ecology
                Ecology and Environmental Sciences
                Ecology
                Marine Ecology
                Biology and Life Sciences
                Marine Biology
                Marine Ecology
                Earth Sciences
                Marine and Aquatic Sciences
                Marine Biology
                Marine Ecology
                Biology and Life Sciences
                Agriculture
                Fisheries
                Biology and Life Sciences
                Nutrition
                Diet
                Food
                Medicine and Health Sciences
                Nutrition
                Diet
                Food
                Custom metadata
                All relevant code are available from Zenodo at: https://doi.org/10.5281/zenodo.574902.

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