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 - 7 of 7
Data |

These data encompass the nearshore fish surveys conducted by the Kachemak Bay Reserve as part of a 2020 catalyst project that expanded research collaborations and completed proof of concept activities to catalyze future research on the mechanisms of paralytic shellfish toxin transfer from forage fish to upper trophic populations.

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.

Data |
About this Project

Thin-layer placement (TLP) is an emergent climate adaptation strategy that mimics natural deposition processes in tidal marshes by adding a small amount of sediment on top of marsh in order to maintain elevation relative to sea level rise.

Collections |
This collection features blue carbon work completed by project teams from 2010-2019. The collection includes a detailed management brief narrative, an infographic showing the progress of blue carbon work across the U.S., and a webinar recording from a panel discussion on March 17, 2020.
Collections |
This collection features climate resilience and adaptation work completed by project teams from 2015-2018. The collection includes a detailed management brief narrative, an infographic showing how the interconnected nature of the NERRS facilitates collective learning and accelerated action, and a webinar recording from a panel discussion on September 9, 2019.
Collections |
This collection features living shorelines work completed by project teams from 2015-2019. The collection includes a detailed management brief narrative, an infographic showing different shoreline stabilization strategies and how they vary across locations in order to suit the conditions present, and a webinar recording from a panel discussion on April 11, 2019.
Data |

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