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Resources

Resources

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

Displaying 111 - 120 of 278
Multimedia |

This collection of videos uses a hydrodynamic model to show salinity changes in the Coos estuary in different geographies and seasons.

Project Overview |

This project overview describes a 2017 science transfer project that developed a risk communication training for reserves to build risk communication capacity in four coastal communities.

Project Overview |

This project overview describes a 2018 Catalyst project where researchers from Duke University and the North Carolina and Rookery Bay reserves partnered to develop ecosystem services models for coastal habitats.

Project Overview |

This project overview describes a 2018 catalyst project led by the San Francisco Bay Reserve that brought together key stakeholders and decision makers to advance adaptation planning for a low-lying coastal road at China Camp State Park.

Multimedia |

These multimedia outreach and communication tools were developed by the Kachemak Bay National Estuarine Research Reserve and its partners in support of a project to advance peatland blue carbon projects in the Kenai Lowlands, Alaska.

Tool |

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

Multimedia |

This story map about salmon, groundwater, and people in the Kenai Lowlands, Alaska can help local stakeholders better understand groundwater dynamics.

Multimedia |

These outreach and communications tools, including a one-page factsheet and presentation slides, discuss the Alaska Fisheries Resilience Index.

Tool |

This focus group template is part of a training and facilitation toolkit, developed to help coastal leaders use the Alaska Fisheries Resilience Index to promote coastal resilience.

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.