Skip to main content

Resources

Resources

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

Displaying 1 - 10 of 22
Tool |

This factsheet, developed by a 2020 catalyst project, provides a brief overview of CES frameworks and categories to complement the information contained in the factsheet “Expanding and Deepening the Application of Cultural Ecosystem Services in Estuary Stewardship and Management ”.

Tool |

This factsheet, developed by a 2021 catalyst project, summarizes information to strengthen the conceptual foundation and meaningful application of cultural ecosystem services (CES) in the NERRS.

Tool |

This guide is designed to be a resource for current and potential oyster growers that want to understand and maximize the water quality benefits of their aquaculture operations.

Tool |

This decision support tool, developed as part of a 2017 collaborative research project, allows users to select different combinations of tidal range, suspended sediment, ditch density, and sea-level rise variables and visualize predicted outcomes over different time frames.

Tool |

This curriculum was developed as part of a 2018 Science Transfer project to share knowledge and lessons learned about managing conflict in collaborative science.

Tool |

This advisory committee charter, developed for a National Estuarine Research Reserve project to evaluate a thin-layer placement as a strategy for marsh resilience, offers an example for engaging diverse end users in collaborative research.

Tool |

This how-to guide describes how to synthesize salt marsh monitoring data from the National Estuarine Research Reserve System.

Tool |

This how-to guide describes how to integrate plant cover data from two common methods of estimating marsh plant cover.

Tool |

This stakeholder engagement plan outlines an approach to strengthen stakeholder networks and advance blue carbon conversations in the Kenai Lowlands, Alaska.

Tool |

A 2018 catalyst project developed tools for working with SET data including a series of computer codes - R scripts - for processing, quality checking, analyzing and visualizing these complex datasets. The statistical codes re available through GitHub and are explained in a Guide to the SETr Workflow.