This project overview describes a 2018 Catalyst project that demonstrated the feasibility of including carbon finance in funding strategies that support the conservation and restoration of tidal wetlands in the Pacific Northwest.

This article, which appeared in Global Change Biology, discusses findings from a study that quantified total ecosystem carbon stocks of major tidal wetland types in the Pacific Northwest.

These four case studies give examples of four best practices for conflict management in collaborative science. They were developed as part of the Resilience Dialogues project to share lessons learned about effective collaboration from within the National Estuarine Research Reserve System.

This curriculum was developed as part of a 2018 Science Transfer project to share knowledge and lessons learned about managing conflict in collaborative science.

These tidal wetland carbon stocks and environmental driver data were collected as part of the 2016-2019 collaborative research Pacific Northwest Carbon Stocks and Blue Carbon Database Project.

This needs assessment of conservation policy stakeholders in the Pacific Northwest identified data needs and barriers for potential blue carbon project partners.

This project overview describes a 2018 catalyst project led by the San Francisco Bay Reserve that brought together key stakeholders and decision makers to advance adaptation planning for a low-lying coastal road at China Camp State Park.

This report provides foundational science and social context to inform the development of adaptation options for a low-lying road in China Camp State Park, along San Francisco Bay, CA.

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.

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.