This collection of K-12 lesson plans, compiled by the Native Olympia Oyster Collaborative, features science, math, engineering, writing, art, and multidisciplinary lessons that invite students to explore various aspects of West coast native oysters.

This summary brochure describes thin-layer placement (TLP) as a strategy for marsh resilience, and National Estuarine Research Reserve System research and recommendations for TLP use.

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.

These coastal hazard risk communication workshop materials can be used to help facilitate trainings for coastal decision makers.

This project database and interactive storymap catalogs native Olympia Oyster restoration projects on the West Coast.

The Native Olympia Oyster Collaborative is a coastwide network from Baja California to British Columbia to conserve and rebuild West coast native oyster populations.

This webinar was originally presented on February 20, 2020 as part of the Restoration Webinar Series, hosted by the National Oceanic and Atmospheric Administration and U.S. Fish & Wildlife Service's National Conservation Training Center. Presenters: Kerstin Wasson, Beth Watson, and Kenny Raposa

These video modules introduce the conceputs and vocabulary of estuary ecology using American Sign Language. Five videos are available for the following topics: Watersheds, Water Quality, Water Quality Monitoring, Estuary Values, and Sea Level Rise.

The Credit for Going Green project team developed a toolkit to help partners share project results within their organizations and throughout their professional networks. These resources can be used to develop presentations, web content, newsletter articles, or social media posts about the project.

This guide outlines a structured process to engage experts and develop timely, science-based solutions to environmental problems. The FAST process provides an iterative, weight-of-evidence approach for these experts to reach general agreement around technical recommendations.