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Resources

Resources

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

Displaying 11 - 20 of 24
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.

Data |

These datasets and statistical analysis codes model surge barrier effects on the Hudson River estuary, developed as part of the 2018 catalyst project Assessing the Physical Effects of Storm Surge Barriers on the Harbor and Hudson River Estuary.

Multimedia |

Slides and a video recording are available from a final stakholder meeting for a study that examined the buffering capacity of a shoreline marsh along Hudson River estuary.

Multimedia |

This webinar, conducted June 30, 2020, presents research findings from the 2018-2020 catalyst project Assessing the Physical Effects of Storm Surge Barriers on the Harbor and Hudson River Estuary.

Data |

These datasets contain sediment core samples from dam impoundments on tributaries to the Hudson River and tidal wetland complexes in the Hudson River estuary, collected as part of the 2016-2020 collaborative research project Dams and Sediment on the Hudson (DaSH).

Multimedia |

This project database and interactive storymap catalogs native Olympia Oyster restoration projects on the West Coast.

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.

Multimedia |

This webinar, which originally aired on December 12, 2013, discusses the Tijuana River Reserve's collaborative efforts to develop a vulnerability assessment that informs an adaptation strategy to address sea level rise and riverine flooding.

Data |

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