This tool is a novel approach to compare the resilience of different marshes to sea level rise.
Resources
Resources
A repository of data, publications, tools, and other products from project teams, Science Collaborative program, and partners.
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This code (R and MATLAB) can be used to analyze NERRS System-Wide Monitoring Program time series data.
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This project overview describes the project approach, results, and benefits of a 2016-2020 collaborative research project that increased clarity about marsh habitat change to inform mosquito control and coastal restoration efforts in New Jersey
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This project overview describes a 2016 Integrated Assessment project that is looking at how to create a modernized land use plan for Oregon's Coos Bay Estuary that balances responsible economic development, social interests, and protection of natural resources.
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This project overview describes a 2016 Collaborative Research project that filled information gaps and modeled estuarine circulation and sediment distribution in Oregon's Coos estuary.
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This project overview describes a 2018 Science Transfer project where 13 reserves are sharing their experiences in managing conflict during collaborative research projects and synthesizing lessons learned.
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This project overview describes a 2015 Collaborative Research project that is developing and field-validating rapid assessment protocols for physical and ecological functions of ecologically-enhanced shorelines.
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This project overview describes a 2015 Science Transfer project that developed products to support New York State decision makers considering nature-based shoreline approaches and other natural resilience measures.
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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.
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These slides summarize a webinar given by Thomas Grothues of the Jacques Cousteau Reserve on September 19, 2018 about methods for analyzing trends in SWMP temperature with missing data.