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Resources

Resources

A repository of data, publications, tools, and other products from project teams, Science Collaborative program, and partners.

Displaying 1 - 10 of 10
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About the project

Through a 2020 catalyst project, staff from the South Carolina Department of Natural Resources worked with ACE Basin NERR and U.S.

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About the project

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

Data |
About this project

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 dataset comprises the data collected and produced as part of the 2016 research project Investigating the Interconnectedness of Climate Change, Nuisance Mosquitoes, and Resilience of Coastal Salt Marsh Systems.

Data |
About this Project

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.

Website |

This 2018 catalyst project streamlined and enhanced mapping and decision support tools to help New Jersey coastal communities prepare for sea level rise and extreme storms.

Website |

This climate adaptation planning toolkit compiles lessons learned by five National Estuarine Research Reserves. It is designed to help communities set goals and identify specific indicators to evaluate progress toward a climate resilient future.

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The Native Olympia Oyster Collaborative is a coastwide network from Baja California to British Columbia to conserve and rebuild West coast native oyster populations.

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Three related datasets were generated by the 2015 - 2019 collaborative research project Evaluating Living Shorelines to Inform Regulatory Decision-Making in South Carolina.

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This code (R and MATLAB) can be used to analyze NERRS System-Wide Monitoring Program time series data.