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Resources

Resources

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

Displaying 1 - 9 of 9
Factsheet |

This factsheet, written as a resource for a three-year Collaborative Research project, describes measures and proposed management plans for marsh resilience to create a long-term monitoring programs and national-level synthesis efforts.

Project Overview |

This project overview describes a 2017 Collaborative Research project that is piloting and refining DNA-based monitoring protocols that can be applied to specific issues and species of interest in estuarine ecosystems.

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.

Factsheet |

This factsheet describes the process of environmental DNA (eDNA) water sampling in estuarine systems, and provides specific methdology recommendations to facilitate detection of invasive species.

Data |

This data resource includes eDNA sequences, fish species summary tables, and DNA extractions from Wells, Great Bay, Hudson, Apalachicola, South Slough, and Heʻeia National Estuarine Research Reserves.

Report |

This collection of reports summarizes Surface Elevation Table (SET) data at fiften reserves. A technical report analyzing of surface elevation change and a summary for oureach purposes is provided for each reserve.

Data |

This code (R and MATLAB) can be used to analyze NERRS System-Wide Monitoring Program time series data.

Project Overview |

This project overview describes a 2015 Science Transfer project that produced tools, graphical support, and training for research staff at the Mid-Atlantic reserves to better utilize reserve monitoring data.

Webinar Summary |

These slides summarize a webinar given by Thomas Grothues of the Jacques Cousteau Reserve on September 19, 2018 about methods for analyzing trends in SWMP temperature with missing data.