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.

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.

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.

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.

This project overview describes a 2017 Collaborative Research project where Kachemak Bay Reserve staff and local partners are developing a conceptual model and geospatial layer that can be used to predict specific locations where groundwater discharge and recharge occur.

This project overview describes a 2017 Science Transfer project that developed business resilience tools and training to strengthen a network of south-central Alaska fisheries businesses prepared for climate impacts.

This project overview describes a project led by Elkorn Slough National Estuarine Research Reserve to communicate the results of a recent national synthesis of NERR Sentinel Site data on marsh resilience to sea level rise.

This project overview describes a 2013 Collaborative Research project that refined and piloted the Climate Change Vulnerability Assessment Tool for Coastal Habitats ("CCVATCH").

This project overview describes a 2016 Science Transfer project that extended the reach of a watershed education and training project, Climate Education for a Changing Bay, in Virginia.

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