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Synthesis of National Coastal Assessment data for Great Lakes national parks

Sector: Car parking • Location: United States of America

Source: Grants.gov

Project
Archived

The purpose of this agreement is to analyze and interpret (fully and statistically) a large coastal dataset generated by the U.S. Environmental Protection Agency (EPA)�s National Coastal Assessment for the Great Lakes. This Assessment effort was supplemented and made more park-specific through funds from an NPS Great Lakes Restoration Initiative Project (GLRI #89 �Comprehensive Marine Assessm

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The project “Synthesis of National Coastal Assessment data for Great Lakes national parks” is an infrastructure initiative in the Car parking sector, located in United States of America. Taiyo aggregates data on it from Grants.gov.

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archived

Taiyo status

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Description

Description

The purpose of this agreement is to analyze and interpret (fully and statistically) a large coastal dataset generated by the U.S. Environmental Protection Agency (EPA)�s National Coastal Assessment for the Great Lakes. This Assessment effort was supplemented and made more park-specific through funds from an NPS Great Lakes Restoration Initiative Project (GLRI #89 �Comprehensive Marine Assessments�). The proposed analysis of these data will provide unprecedented information on coastal conditions within NPS boundaries, but will also place those conditions into a larger Great Lakes context. Specifically, the project aims to 1) summarize coastal conditions on a park-specific basis, 2) determine whether or not coastal conditions in national park units differ from those of surrounding Great Lakes waters, and 3) conduct additional exploratory analysis of coastal datasets, as time permits. The careful analysis of this dataset will provide important insights for Great Lakes parks to consider in addressing coastal management issues, restoration projects, and research needs. It will also provide insights to EPA about Great Lakes reference conditions, as coastal waters near NPS units are likely among those least impacted by upland pollutants and other stressors.

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Source

Source reliability

High

Data quality score

100%

Source

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URL

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