This factsheet, written as a resource for a three-year Collaborative Research project, describes measures and proposed management plans for marsh resilience to create a long-term monitoring programs and national-level synthesis efforts.

This resource contains the presenter slides, Q&A responses, recording, and presenter bios from the March 2020 webinar Estimating Long-term Phosphorous Retention Capacity of Riverine and Coastal Wetlands.

This protocol is intended to enable wetland managers, conservationists, and other practitioners to monitor and estimate a wetland ’s long-term Total Phosphorus (TP) retention capacity threshold.

This infographic illustrates the role wetlands can play in removing total phosphorus from the water and ultimately help improve water quality and reduce Harmful Algal Blooms in Lake Erie. The infographic describes how the researchers estimated long-term phosphorus retention capacity for different types of wetlands in Ohio and provides suggestions as to how different audiences might be able to contribute to this effort.

In collaboration with several local partners, Old Woman Creek National Estuarine Research Reserve conducted a study aimed at understanding different wetlands' long-term capacity for removing nutrients. Together, they produced this story map that demonstrates the importance of wetland services, explains different types of wetlands and management priorities, and summarizes how the team estimated the long-term phosphorus retention capacities of a variety of wetland types based on samples collected from sites in Ohio, including the Lake Erie watershed.

This code (R and MATLAB) can be used to analyze NERRS System-Wide Monitoring Program time series data.

This project overview describes a 2015 Science Transfer project that produced tools, graphical support, and training for research staff at the Mid-Atlantic reserves to better utilize reserve monitoring data.

These slides summarize a webinar given by Thomas Grothues of the Jacques Cousteau Reserve on September 19, 2018 about methods for analyzing trends in SWMP temperature with missing data.