This 2021 article which appeared in Ecological Engineering explores the potential for large-scale breakwaters to preserve fringing marsh vegetation in high wave energy environments.
This 2021 article which appeared in Ecological Engineering explores the potential for large-scale breakwaters to preserve fringing marsh vegetation in high wave energy environments.
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.
This article, which appeared in Journal of Coastal Research in 2020, discusses the creation and field performance testing of a low-cost do-it-yourself (DIY) wave gauge.
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.
This project overview describes a 2012 Collaborative Research project that assessed the ability and cost-effectiveness of marsh restoration designs to remove nitrogen pollution from stormwater runoff.
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.
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.
This project overview describes a Collaborative Research project that evaluated several coastal restoration designs at the Weeks Bay National Estuarine Research Reserve.
This project overview describes a 2015 Science Transfer project where the four Northeast reserves used CCVATCH to conduct vulnerability assessments of coastal habitats in their reserves.
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.