Thin-layer sediment placement (TLP) is a promising management tool for enhancing tidal marsh resilience to rising seas.
Resources
Resources
A repository of data, publications, tools, and other products from project teams, Science Collaborative program, and partners.
Displaying 1 - 10 of 15See Keywords and Reserves
This 2021 article which appeared in Estuaries and Coasts provides a synthesis of native oyster restoration projects conducted from California, USA, to British Columbia, Canada.
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This project overview describes a 2018 Catalyst project led by Grand Bay Reserve that developed standardized tools to quality-check, analyze, and visualize Surface Elevation Table data.
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This project overview describes a 2018 Catalyst project that created an Olympia oyster restoration network to enhance the success of West Coast restoration efforts.
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This project overview describes a 2017 science transfer project that developed a risk communication training for reserves to build risk communication capacity in four coastal communities.
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This project overview describes a project led by Elkorn Slough National Estuarine Research Reserve to communicate the results of a recent national synthesis of NERR Sentinel Site data on marsh resilience to sea level rise.
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This project overview describes a 2011 Collaborative Research project that developed science-based planning tools that decision-makers along the Pacific Coast can use to better site oyster restoration projects.
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This paper, published in Biological Conservation, describes an innovative approach developed by the NERRS to evaluate the ability of tidal marshes to thrive as sea levels rise.
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This project overview describes a 2016 Science Transfer project that is supporting the development of new, innovate visitor displays at the Guana Tolomato Matanzas, Mission-Aransas, and Delaware National Estuarine Research Reserves.
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This project overview describes a 2015 Science Transfer project that produced tools, graphical support, and training for research staff at the Mid-Atlantic reserves to better utilize reserve monitoring data.