The research team developed a vegetation-resolving three-dimensional surge-wave model to simulate storm impacts on Piermont Marsh and the adjacent Village. The model incorporated locally collected data on plant distribution and structure, as well as observed and simulated wind and water level data from the Hudson River. By modeling the impacts of Superstorm Sandy, they found that marsh vegetation with predominantly invasive common reed, Phragmites australis, reduced 66% of the wave energy, but less than 1% of the flood, at the Village. The marsh vegetation also significantly prevented transport of debris from the southeastern corner of the marsh. If managers were to replace Phragmites with the shorter, native cattail, Typha angustifolia , simulations of Sandy, which occurred in October, suggest that Piermont Marsh’s wave and debris buffering capacity would be preserved. However, had Sandy occurred in May/June when Typha is much shorter and sparser, the marsh would have been unable to buffer the wave and debris as effectively. The Piermont Marsh Coastal GeoTool allows Village of officials and resource managers to explore how homes and buildings would be impacted under marsh management and sea-level rise scenarios.

One of the few pristine, mangrove-forested estuaries in the country, Florida’s Rookery Bay Estuary is a critical breeding ground for the fisheries that underpin the region’s economy. Balancing the freshwater needs of the estuary with those of local communities is increasingly challenging as population growth and sea level rise tax freshwater resources. Decision-makers need information about freshwater requirements of the estuary and the perspectives of water users to effectively manage water resources.

This project provided support for local governments to obtain necessary information to modernize and revise the Coos Bay estuary management plan. Through an integrative assessment, the project team leveraged knowledge from community members, synthesized and compiled existing information, and applied a triple bottom line lens (economic, social, and environmental) to portray current conditions and uses in the estuary, and generate options and recommendations for local governments to improve their estuarine and shoreland management. This integrated assessment project was funded by NOAA through the National Estuarine Research Reserve System Science Collaborative to evaluate options for action. It did not produce any new data.

This project conducted field research at six shoreline sites in the Guana Tolomato Matanzas National Estuarine Research Reserve in northeast Florida. At each of the six study sites, the project team installed experimental living shoreline treatments. Between November 2015 and June 2019, several physical and biological variables were routinely monitored to evaluate the performance of the living shoreline installations, including: (1) ecological response variables for the adjacent marsh (2) data about the oysters and invertebrates that colonized the new living shoreline structures, and (3) hydrodynamic measurements around the new structures.

In this project, National Estuarine Research Reserves in North and South Carolina worked to improve local understanding of climate change effects on southeastern salt marsh and provide decision makers with the information and skills they need to address these vulnerabilities. North Carolina Reserve staff members were trained in the Climate Change Vulnerability Assessment Tool for Coastal Habitats (CCVATCH) by their colleagues from North Inlet-Winyah Bay Reserve. This decision support tool incorporates existing information on climate change impacts with knowledge of local conditions to help users develop vulnerability scores for specific areas. The project team used CCVATCH to conduct habitat vulnerability assessments for seven estuaries in North and South Carolina, summarized regional findings to help managers in the Southeast improve salt marsh resilience, and developed guidance and outreach products. This science transfer project was funded by NOAA through the National Estuarine Research Reserve System Science Collaborative to promote the use of science. It did not produce any new data.

Southern California’s coastal environments are under intense development pressure. In the Tijuana River Valley, this pressure translates into the fragmentation and loss of coastal wetlands that provide invaluable services, such as water quality protection. Conserving and restoring these wetlands has become a priority for regional coastal managers, scientists, and environmental organizations. However, despite a wealth of knowledge about these coastal systems, decision-makers lack essential information to transform wetland recovery and management priorities into action.

This project will provide research staff members from the mid-Atlantic reserves with targeted tools, graphical support, and training to facilitate the use of reserve monitoring data. The project team will focus on deciphering trends in water quality parameters, which are related to management issues such as storm surge mitigation. Through workshops and the development of statistical applications, this project will increase capacity to distill monitoring data into a format that resource managers can use. The project team will share their approach and project outputs with the larger reserve system, and collectively, these efforts will demonstrate the value of the reserve monitoring program. This science transfer project was funded by NOAA through the National Estuarine Research Reserve System Science Collaborative to promote the use of science. It did not produce any new data.

The project team produces educational outreach materials for audiences throughout Grand Bay. The materials will raise awareness of the positive and negative effects of land-use change for the general public, community organizations, and decisionmakers within the region. The materials will educate audiences about the ways to preserve and protect Grand Bay from waterborne pathogens and excess nutrients. The team will use science-based information to reinforce the importance of reducing stormwater contamination, improving wastewater management, and implementing land-use planning that takes water resources into account. This science transfer project was funded by NOAA through the National Estuarine Research Reserve System Science Collaborative to promote the use of science. It did not produce any new data.

This project will 1) quantify pathogens, nutrients, and sediment delivery to the Rachel Carson Reserve; 2) create predictive models for shellfish and recreational waters in the North Carolina Reserve by using this information, along with decades of historical data; 3) engage stakeholders and end users to prioritize management options; and 4) engage coastal decision makers, community members, K-12 students, and teachers in hands-on education on stormwater runoff and its impacts.

From 2010 to 2018, the National Estuarine Research Reserve System’s Science Collaborative supported the Hudson River Sustainable Shorelines Project, which engages a regional research team to quantify the ecological functions and physical stresses on the full range of Hudson River, New York shorelines. This research is the basis for development of information and tools to identify the best settings and approaches for sustainable shoreline protection in the Hudson River Estuary. Work has included the establishment of a sustainable shoreline demonstration network of seven sites with varying modes of construction distributed along the Hudson. The most recent project-- the focus of this InPort entry-- expanded that effort by working closely with regulators, engineers, and land managers to 1) develop and field-validate a rapid assessment protocol manual for physical and ecological functions of ecologically enhanced shorelines and 2) train local land managers in the protocols. This work helps to solidify confidence in the suitability of novel shoreline techniques in the Hudson River Estuary and has enabled local managers to track performance into the future. The project also produced a dataset comprised of a suite of measures of ecological and physical functions of built sustainable shorelines along the Hudson River.