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Resources

Resources

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

Displaying 31 - 40 of 52
Report |

This report summarizes key findings from a 2019 workshop in New York that examined the potential ecological and physical impacts of constructing a surge barrier to protect the New York/New Jersey Harbor.

Thesis or Dissertation |

This Master's thesis examines sediment accumulation in two disparate coastal environments, including the Hudson River Reserve, as part of a larger research project about marsh formation and resilience, sediment movement, and the potential impact of dam removals.

Website |

This website houses the Rapid Assessment Protocol for assessing the physical and ecological performance of nature-based engineered shoreline structures. You can also access additional resources associated with the Hudson River Sustainable Shorelines Project, including demonstration site case studies along the Hudson River.

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.

Report |

This workshop report summarizes the March 2019 scoping session for a collaborative project to assess the potential effects of storm surge barriers on the Hudson River estuary.

Thesis or Dissertation |

This dissertation was written by PhD student working at Hudson River Reserve on a project that assessed the buffering services of a coastal marsh in New York.

Report |

This document summarizes a tool developed by the NERRS to evaluate and compare the ability of tidal marshes to thrive as sea level rises.

Journal Article |

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.

Tool |

This tool is a novel approach to compare the resilience of different marshes to sea level rise.

Data |

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