This report describes the findings of a 2011 Collaborative Research project that investigated the Matanzas Basin's vulnerability to sea level rise in Florida and identified potential adaptation strategies.
Resources
Resources
A repository of data, publications, tools, and other products from project teams, Science Collaborative program, and partners.
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This game developed as part of the 2011 Collaborative Research project "Planning for Florida's Rising Tides" introduces participants to sea level rise adaptation strategies and provides an understanding of the participants' preferences for different strategies.
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This pre-survey is part of a role-play game developed as part of a 2011 Collaborative Research project on sea level rise adaptation in Florida. Each player is assigned a different stakeholder role and fills out this pre-survey before starting the game, which serves as a foundation for helping participants understand each others' perceptions of sea level rise adaptation strategies.
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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 2011 Collaborative Research project that piloted an approach for stakeholder-driven planning that communities in Florida can use to prepare for sea level rise.
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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 project overview describes a 2016 Science Transfer project that extended the reach of a watershed education and training project, Climate Education for a Changing Bay, in Virginia.
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This code (R and MATLAB) can be used to analyze NERRS System-Wide Monitoring Program time series data.