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Resources

Resources

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

Displaying 41 - 50 of 76
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.

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.

Report |

Southern California ’s coastal environments are under intense development pressure. In the Tijuana River Valley, this pressure translates into the fragmentation and loss of coastal wetlands that provide invaluable services, such as water quality protection.

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.