The 2020-2022 catalyst project Bridging the gap between quadrats and satellites: assessing utility of drone-based imagery to enhance emergent vegetation biomonitoring conducted a regionally coordinated effort, working in salt marshes an
Resources
Resources
A repository of data, publications, tools, and other products from project teams, Science Collaborative program, and partners.
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The 2020-2021 catalyst project Refining Techniques for High-Frequency Monitoring of Chlorophyll in the NERRS brought together twelve biogeochemically diverse reserves to compare results from new YSI in situ sensor technology with ex
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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.
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Thin-layer placement (TLP) is an emergent climate adaptation strategy that mimics natural deposition processes in tidal marshes by adding a small amount of sediment on top of marsh in order to maintain elevation relative to sea level rise.
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This project overview describes a 2017 Science Transfer project in which the southeastern National Estuarine Research Reserves created a region-wide, student-driven program for teachers to further understanding of estuary restoration.
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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.
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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 in which the Old Woman Creek Reserve and partners provided a local demonstration of low-impact development stormwater treatments in Ohio.
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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.