Resources
Resources
A repository of data, publications, tools, and other products from project teams, Science Collaborative program, and partners.
Displaying 1 - 10 of 26See Keywords and Reserves
Designation of essential fish habitat requires a detailed understanding of how species-specific vital rates vary across habitats and biogeographical regions.
See Keywords and Reserves
Through a 2020 catalyst project, staff from the South Carolina Department of Natural Resources worked with ACE Basin NERR and U.S.
See Keywords and Reserves
Through a 2020 catalyst project, staff from the South Carolina Department of Natural Resources worked with ACE Basin NERR and U.S.
See Keywords and Reserves
Monitoring plays a central role in detecting climate and anthropogenic stressors and associated changes in wetlands. There is a need for wetland monitoring programs to bridge the gap between ground-based surveys, which can miss important spatial heterogeneity and cause wetland disturbance, a
See Keywords and Reserves
This instructional and informational webinar features background information on the 2020 science transfer Storm Stories project, how end-user feedback was incorporated, the tools and products that have been developed through the project, and how reserves can access resources.
See Keywords and Reserves
This web resources includes a compilation of lesson plans for grades K - 12 about coastal and estuarine ecology that are intended to complement programs that involve schools in local wetland restoration projects.
See Keywords and Reserves
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.
See Keywords and Reserves
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.
See Keywords and Reserves
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.