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Resources

Resources

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

Displaying 21 - 30 of 80
Project Overview |

This project overview describes a 2018 Catalyst project led by Grand Bay Reserve that developed standardized tools to quality-check, analyze, and visualize Surface Elevation Table data.

Webinar Summary |

This resource contains the presenter slides, Q&A responses, recording, and presenter bios from the November 2020 webinar Measuring Climate Adaptation Success and Progress: Introduction to the Resilience Metrics Toolkit

Data |

This dataset contains processed Surface Elevation Table data from five reserves along with metadata, R scripts, reports, and figures, illustrating how SET can be processed, analyzed and visualized.

News |

Project Overview |

This project overview describes a 2018 Catalyst project that created the web-based toolkit Resilience Metrics to share lessons learned on successful climate adaptation planning within the National Estuarine Research Reserve System.

Journal Article |

This article, which appeared in Journal of Coastal Research in 2020, discusses the creation and field performance testing of a low-cost do-it-yourself (DIY) wave gauge.

Website |

This 2018 catalyst project streamlined and enhanced mapping and decision support tools to help New Jersey coastal communities prepare for sea level rise and extreme storms.

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.

Report |

This national synthesis report analyzes SET data from 15 National Estuarine Research Reserves across the continental United States, summarizing wetland water level trends over a 19-year period.

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.