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.
Resources
Resources
A repository of data, publications, tools, and other products from project teams, Science Collaborative program, and partners.
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This 2019 report describes the findings of a University of Michigan SEAS Master's project which provides insights for KBNERR regarding current ecosystem services valued in Kachemak Bay using a socio-cultural, place-based, ecosystem services framework.
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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.
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Oysters are the tiny superheroes of coastal environments. They enhance water quality, create habitat, and protect shorelines from storms and erosion. Along the Pacific Coast, native oysters are in decline, due in part to sedimentation, inadequate protection, and unsustainable harvests.
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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 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.