The ability to quickly communicate local environmental changes in the aftermath of hurricanes helps impacted communities better understand storm events and support recovery.
Resources
Resources
A repository of data, publications, tools, and other products from project teams, Science Collaborative program, and partners.
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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
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This guide is designed to be a resource for current and potential oyster growers that want to understand and maximize the water quality benefits of their aquaculture operations.
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This decision support tool, developed as part of a 2017 collaborative research project, allows users to select different combinations of tidal range, suspended sediment, ditch density, and sea-level rise variables and visualize predicted outcomes over different time frames.
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This curriculum was developed as part of a 2018 Science Transfer project to share knowledge and lessons learned about managing conflict in collaborative science.
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This advisory committee charter, developed for a National Estuarine Research Reserve project to evaluate a thin-layer placement as a strategy for marsh resilience, offers an example for engaging diverse end users in collaborative research.
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This how-to guide describes how to synthesize salt marsh monitoring data from the National Estuarine Research Reserve System.
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This how-to guide describes how to integrate plant cover data from two common methods of estimating marsh plant cover.
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This stakeholder engagement plan outlines an approach to strengthen stakeholder networks and advance blue carbon conversations in the Kenai Lowlands, Alaska.
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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.