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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 14
Data |
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

Data |

This data resource includes marsh vegetation, water level data and modeling outputs from a project that examined how Piermont Marsh in New York buffers the impacts of storms.

Data |

This data resource includes eDNA sequences, fish species summary tables, and DNA extractions from Wells, Great Bay, Hudson, Apalachicola, South Slough, and Heʻeia National Estuarine Research Reserves.

News |

A project team in South Carolina received a Notable State Documents Award for their 2019 report titled Summary of Living Shoreline Research to Inform Regulatory Decision-Making in South Carolina.

Data |

The collaborative research project, Re-engineering Living Shorelines for High-Energy Coastal Environments, produced four datasets as part of their assessment of living shoreline installations at GTM Reserve in Florida.

Data |
About this resource

Degradation of coastal habitats has led to major declines in oyster reefs and coastal wetlands. Coastal restoration efforts are critical to restoring these habitats, but they often include little to no monitoring and evaluation of success.

Data |

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

Data |

This dataset includes a suite of measures of ecological and physical functions of built sustainable shoreline structures at a set of demonstration sites along the Hudson River.

Data |

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