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Resources

Resources

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

Displaying 71 - 80 of 98
Tool |

This Excel spreadsheet, developed by a 2011 Collaborative Research project team, allows you to evaluate the appropriateness of one or more sites for Olympia oyster restoration.

Report |

This report discusses environmental conditions and sites that support sustainable Olympia oyster populations in central California.

Report |

Oysters are the tiny superheroes of coastal environments. They enhance water quality, create habitat, and protect shorelines from storms and erosion. Along the Pacific Coast, native oysters are in decline, due in part to sedimentation, inadequate protection, and unsustainable harvests.

Project Overview |

This project overview describes a 2011 Collaborative Research project that developed a science-based framework for stakeholders to use in making decisions about water resource management in the Rookery Bay Estuary.

Project Overview |

This project overview describes a 2011 Collaborative Research project that developed science-based planning tools that decision-makers along the Pacific Coast can use to better site oyster restoration projects.

Project Overview |

This project overview describes a 2012 Collaborative Research project that worked to enhance resilience on Maryland's Deal Island by building a stakeholder network and integrating research to understand how different management practices will impact marsh and community resilience.

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.