This document provides guidance to those wishing to use the Climate Change Vulnerability Assessment Tool for Coastal Habitats ("CCVATCH") - a decision support tool which guides users through a series of questions to calculate numerical climate vulnerability scores for ecological habitats.
Resources
Resources
A repository of data, publications, tools, and other products from project teams, Science Collaborative program, and partners.
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This project overview describes a 2013 Collaborative Research project that refined and piloted the Climate Change Vulnerability Assessment Tool for Coastal Habitats ("CCVATCH").
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This project overview describes a 2012 Collaborative Research project that worked to enhance resilience on Maryland's Deal Island by building a stakeholder network and integrating research to understand how different management practices will impact marsh and community resilience.
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This document summarizes a tool developed by the NERRS to evaluate and compare the ability of tidal marshes to thrive as sea level rises.
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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 tool is a novel approach to compare the resilience of different marshes to sea level rise.
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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 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 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.