The Great Lakes Initiative Toxicity Data Clearinghouse is a central location for information on criteria, toxicity data, exposure parameters and other supporting documents used in developing water quality standards in the Great Lakes Watershed.

In the Great Lakes basin, there are numerous organizations undertaking scientific monitoring and research efforts with the goal of identifying threats and evaluating management strategies that will protect and restore the Great Lakes ecosystem. Coordination among all these stakeholders is a challenge, and having a centralized location where researchers and managers can identify relevant scientific activities and access fundamental information about these activities is crucial for efficient management. The Science in the Great Lakes (SiGL) Mapper was a map-based discovery tool that spatially displayed basin-wide multidisciplinary monitoring and research activities conducted by both USGS and partners from all five Great Lakes. It was designed to help Great Lakes researchers and managers strategically plan, implement, and analyze monitoring and restoration activities by providing easy access to historical and on-going project metadata while allowing them to identify gaps (spatially and topically) that have been underrepresented in previous efforts or need further study. SiGL provided a user-friendly and efficient way to explore Great Lakes projects and data through robust search options while also providing a critical spatial perspective through its interactive mapping interface.

This dataset is part of the U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative. This data represents the location of dikes within the Lake Ontario Restoration Assessment (LORA) study area. The GLCWRA initiative identifies coastal wetland areas that have the greatest habitat restoration potential. The data model uses seven parameters to identify and rank wetland restoration areas, resulting in a composite index raster that can be used by ecological managers and planners to assist with the selection of wetland restoration sites. The parameters are Parameter 0: Mask, Parameter 1: Hydroperiod, Parameter 2: Wetland Soils, Parameter 3: Flowlines, Parameter 4: Conservation and Recreation Lands, Parameter 5: Impervious Surfaces, and Parameter 6: Land Use (represents developed areas without impervious surfaces but high societal value). The ancillary data include dikes, degree flowlines, study area and culverts. These data layers are put through an ecological model, which results in a composite restoration index of ranked restoration areas.

This dataset is part of the U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative. This data represents the location of dikes within the Lake Ontario Restoration Assessment (LORA) study area. The GLCWRA initiative identifies coastal wetland areas that have the greatest habitat restoration potential. The data model uses seven parameters to identify and rank wetland restoration areas, resulting in a composite index raster that can be used by ecological managers and planners to assist with the selection of wetland restoration sites. The parameters are Parameter 0: Mask, Parameter 1: Hydroperiod, Parameter 2: Wetland Soils, Parameter 3: Flowlines, Parameter 4: Conservation and Recreation Lands, Parameter 5: Impervious Surfaces, and Parameter 6: Land Use (represents developed areas without impervious surfaces but high societal value). The ancillary data include dikes, degree flowlines, study area and culverts. These data layers are put through an ecological model, which results in a composite restoration index of ranked restoration areas.

The Great Lakes Environmental Database (GLENDA) houses environmental data collected by EPA Great Lakes National Program Office (GLNPO) programs that sample water, aquatic life, sediments, and air to assess the health of the Great Lakes ecosystem. GLENDA is available to the public on the EPA Central Data Exchange (CDX). A CDX account is required, which anyone may create. GLENDA offers “Ready to Download Data Files” prepared by GLNPO or a “Query Data” interface that allows users to select from predefined parameters to create a customized query. Query results can be downloaded in .csv format. GLNPO programs providing data in GLENDA include the Great Lakes Water Quality Survey and Great Lakes Biology Monitoring Program (1983-present, biannual monitoring throughout the Great Lakes to assess water quality, chemical, nutrient, and physical parameters, and biota such as plankton and benthic invertebrates), the Great Lakes Fish Monitoring and Surveillance Program (1977-present, annual analysis of top predator fish composites to assess historic and emerging persistent, bioaccumulative, or toxic chemical contaminants), the Cooperative Science and Monitoring Initiative (2002-present, intensive water quality and biology sampling of one lake per year focusing on key challenges and data gaps), the Great Lakes Integrated Atmospheric Deposition Network (1990-present, monitoring Great Lakes air and precipitation for persistent toxic chemicals), the Lake Michigan Mass Balance Study (1993-1996, analyzed the atmosphere, tributaries, sediments, water column, and biota of Lake Michigan for nutrients, atrazine, PCBs, trans-nonachlor, and mercury modelling), and the Great Lakes Legacy Act (1996-present, evaluations of sediment contamination in Areas of Concern). GLENDA is updated frequently with new data.

The Great Lakes Environmental Database (GLENDA) houses environmental data collected by EPA Great Lakes National Program Office (GLNPO) programs that sample water, aquatic life, sediments, and air to assess the health of the Great Lakes ecosystem. GLENDA is available to the public on the EPA Central Data Exchange (CDX). A CDX account is required, which anyone may create. GLENDA offers “Ready to Download Data Files” prepared by GLNPO or a “Query Data” interface that allows users to select from predefined parameters to create a customized query. Query results can be downloaded in .csv format. GLNPO programs providing data in GLENDA include the Great Lakes Water Quality Survey and Great Lakes Biology Monitoring Program (1983-present, biannual monitoring throughout the Great Lakes to assess water quality, chemical, nutrient, and physical parameters, and biota such as plankton and benthic invertebrates), the Great Lakes Fish Monitoring and Surveillance Program (1977-present, annual analysis of top predator fish composites to assess historic and emerging persistent, bioaccumulative, or toxic chemical contaminants), the Cooperative Science and Monitoring Initiative (2002-present, intensive water quality and biology sampling of one lake per year focusing on key challenges and data gaps), the Great Lakes Integrated Atmospheric Deposition Network (1990-present, monitoring Great Lakes air and precipitation for persistent toxic chemicals), the Lake Michigan Mass Balance Study (1993-1996, analyzed the atmosphere, tributaries, sediments, water column, and biota of Lake Michigan for nutrients, atrazine, PCBs, trans-nonachlor, and mercury modelling), and the Great Lakes Legacy Act (1996-present, evaluations of sediment contamination in Areas of Concern). GLENDA is updated frequently with new data.

This dataset is part of the U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative. The degree flowlines dataset was created to indicate how many culverts each flowline passes through within the Lake Ontario Restoration Assessment (LORA) study area. The more road crossings on a flowline the more disconnected that area is from the lake and the less suitable it will be for restoration. The GLCWRA initiative identifies coastal wetland areas that have the greatest habitat restoration potential. The data model uses seven parameters to identify and rank wetland restoration areas, resulting in a composite index raster that can be used by ecological managers and planners to assist with the selection of wetland restoration sites. The parameters are Parameter 0: Mask, Parameter 1: Hydroperiod, Parameter 2: Wetland Soils, Parameter 3: Flowlines, Parameter 4: Conservation and Recreation Lands, Parameter 5: Impervious Surfaces, and Parameter 6: Land Use (represents developed areas without impervious surfaces but high societal value). The ancillary data include dikes, degree flowlines, study area and culverts. These data layers are put through an ecological model, which results in a composite restoration index of ranked restoration areas.

This dataset is part of the U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative. The GLCWRA initiative uses principles of geodesign to identify coastal wetland areas that have the greatest potential for habitat restoration. The data model uses the following seven primary parameters to identify and rank wetland restoration areas. The parameters are Parameter 0: Mask, Parameter 1: Hydroperiod, Parameter 2: Wetland Soils, Parameter 3: Flowlines, Parameter 4: Conservation and Recreation Lands, Parameter 5: Impervious Surfaces, and Parameter 6: Land Use (represents developed areas without impervious surfaces but high societal value).The ancillary data include dikes, degree flowlines, study area and culverts. The resulting composite index raster can be used by ecological managers and planners to assist with the identification and selection of wetland for restoration initiatives.