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Resources

Resources

A repository of data, publications, tools, and other products from project teams, Science Collaborative program, and partners.

Displaying 1 - 10 of 16
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This toolkit organizes and consolidates content from a combination of literature reviews, SWMP data interpretation, and interviews and exhibit evaluations at multiple reserves into a comprehensive package of resources that is accessible to all education coordinators and exhibit designers in the Reserve System.
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The ability to quickly communicate local environmental changes in the aftermath of hurricanes helps impacted communities better understand storm events and support recovery.

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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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With funding from the NERRS Science Collaborative, scientists from 12 biogeographically diverse Reserves compared fluorescence measurements taken by the YSI EXO TAL sensor to extracted chlorophyll concentrations processed in the lab.

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Standardized protocols for sensor-based chlorophyll monitoring are now available for use by staff around the system to implement high frequency chlorophyll monitoring at their reserves.

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This tool provides an overview of acoustic monitoring in aquatic ecosystems, including sources of sound, metrics for measurement, data collection and analysis, and applications for habitat assessment, stewardship, and education.

Project Overview |

This project overview describes a 2017 Collaborative Research project that is piloting and refining DNA-based monitoring protocols that can be applied to specific issues and species of interest in estuarine ecosystems.

Project Overview |

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.

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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.