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      The Value of Coastal Wetlands for Flood Damage Reduction in the Northeastern USA

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          Abstract

          As exposure to coastal hazards increases there is growing interest in nature-based solutions for risk reduction. This study uses high-resolution flood and loss models to quantify the impacts of coastal wetlands in the northeastern USA on (i) regional flood damages by Hurricane Sandy and (ii) local annual flood losses in Barnegat Bay in Ocean County, New Jersey. Using an extensive database of property exposure, the regional study shows that wetlands avoided $625 Million in direct flood damages during Hurricane Sandy. The local study combines these models with a database of synthetic storms in Ocean County and estimates a 16% average reduction in annual flood losses by salt marshes with higher reductions at lower elevations. Together, the studies quantify the risk reduction ecosystem services of marsh wetlands. Measuring these benefits in collaboration with the risk modelling industry is crucial for assessing risk accurately and, where appropriate, aligning conservation and risk reduction goals.

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          Most cited references51

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          Future flood losses in major coastal cities

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            Ecosystem-based coastal defence in the face of global change.

            The risk of flood disasters is increasing for many coastal societies owing to global and regional changes in climate conditions, sea-level rise, land subsidence and sediment supply. At the same time, in many locations, conventional coastal engineering solutions such as sea walls are increasingly challenged by these changes and their maintenance may become unsustainable. We argue that flood protection by ecosystem creation and restoration can provide a more sustainable, cost-effective and ecologically sound alternative to conventional coastal engineering and that, in suitable locations, it should be implemented globally and on a large scale.
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              Coastal ecosystem-based management with nonlinear ecological functions and values.

              A common assumption is that ecosystem services respond linearly to changes in habitat size. This assumption leads frequently to an "all or none" choice of either preserving coastal habitats or converting them to human use. However, our survey of wave attenuation data from field studies of mangroves, salt marshes, seagrass beds, nearshore coral reefs, and sand dunes reveals that these relationships are rarely linear. By incorporating nonlinear wave attenuation in estimating coastal protection values of mangroves in Thailand, we show that the optimal land use option may instead be the integration of development and conservation consistent with ecosystem-based management goals. This result suggests that reconciling competing demands on coastal habitats should not always result in stark preservation-versus-conversion choices.
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                Author and article information

                Contributors
                sid.narayan@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                31 August 2017
                31 August 2017
                2017
                : 7
                : 9463
                Affiliations
                [1 ]ISNI 0000 0001 0740 6917, GRID grid.205975.c, Department of Ocean Sciences, , University of California Santa Cruz, ; Santa Cruz, CA USA
                [2 ]The Nature Conservancy, Global Oceans Team, Santa Cruz, CA USA
                [3 ]GRID grid.437659.a, Risk Management Solutions, Inc., ; London, UK
                [4 ]The Nature Conservancy, Gulf of Mexico Program, Punta Gorda, FL USA
                [5 ]Marsh & McLennan Innovation Centre, Guy Carpenter and Company, Dublin, Ireland
                [6 ]GRID grid.478902.0, Wildlife Conservation Society/EY, LLC., ; New York, USA
                Author information
                http://orcid.org/0000-0002-5898-9355
                Article
                9269
                10.1038/s41598-017-09269-z
                5579246
                28860521
                edb3e2ad-4202-4a71-bcdc-10ef71e031d4
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 17 March 2017
                : 1 August 2017
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