The GLAHF spatial database is organized in several broad categories below. Summarized, public data can be downloaded from links within each category. For complete information about data sources and processing see the metadata attached to each data layer. Note, the data available for download are in Esri file geodatabase format and most data are available in raster format attributed to the GLAHF 30 m or 1800 m spatial framework.
Data Download Packages
Benthic data have been compiled from various sources including U.S. EPA Great Lakes National Program Office (GLNPO), NOAA Great Lakes Environmental Research Laboratory (GLERL), and targeted lake monitoring activities, such as the Cooperative Science and Monitoring Initiative, Lake Erie Forage Task Group, and the Lake Michigan Mass Balance. The data indices calculated by the GLAHF project include Oligocheata Trophic Index (OTI), Chironomidae Trophic Index (CTI), Shannon index of diversity, Simpson index of diversity, Pielou eveness index, taxa richness, Oligochaetae abundance, Chironomidae abundance, Bivalves abundance, Diporeia abundance, Dressenidae abundance, proportion of Oligochatae, ratio of Oligochaetae / Chironomidae.
Fish species locations, community, and spawning data have been compiled from USGS trawl surveys, Lake Erie cooperative state and provincial sampling, Michigan Dept. of Natural Resources, and the Goodyear Spawning Atlas and additional published spawning locations. Depending on the lake and available data some of the fish species metrics such as, CPUE, taxa richness, and diversity indices.
download link for fish presence database coming soon – coming soon!
Invasive species are a possible threat to the Great Lakes ecosystem. The GLAHF project has been working with collaborators to incorporate known invasives data into the spatial database. USGS and Michigan Tech Research Institute (MTRI) partnered to create data layers showing areas of coastal Phragmites in the Great Lakes Basin. Aquatic invasive species occurrence records are from the Great Lakes Aquatic Nonindigenous Species Information System (GLANSIS), and include occurrences of algae, crustaceans, fishes, mollusks, plants, protozoans, reptiles, and viruses. See benthos, fish, and zooplankton sections for more information about specific invasive species.
Submerged Aquatic Vegetation
MTRI has developed satellite algorithms to interpret locations of submerged aquatic vegetation (predominately Cladophora). The Michigan Dept. of Natural Resources Lake St. Clair Fisheries Research Station collected submerged aquatic vegetation plant surveys and GLAHF interpolated the data to create SAV maps.
To date zooplankton from the Lake Erie Forage Task Group and the Lake Ontario Lower Foodweb Assessment (LOLA) are available. We are waiting to incorporate data from the U.S. EPA Great Lakes National Program Office (GLNPO), and National Coastal Condition Assessment.
download link for zooplankton database – coming soon!
Environmental & Chemical
Water chemistry and physical parameters (sampling)
In the nearshore areas of the Great Lakes we have compiled water chemistry from the U.S. EPA Great Lakes National Program Office (GLNPO) National Coastal Condition Assessment and Nearshore Program (TRIAXUS surveys) and the Ontario Ministry of the Environment and Climate Change Great Lakes Nearshore Index Stations. Offshore water chemistry has been compiled for the water column sampling by the U.S. EPA GLNPO Monitoring, Environment Canada Great Lakes Surveillance Program, and target lake sampling activities such as the Cooperative Science and Monitoring Initiative and the Lake Erie Forage Task Group.
Water chemistry and physical parameters (satellite derived)
Michigan Tech Research Institute (MTRI) have developed satellite algorithms to determine concentrations of chlorophyll-a, suspended minerals, Kd-490, and dissolved organic carbon specific to the open waters of the Great Lakes. Please contact MTRI to obtain satellite derived data.
The bathymetry for the Great Lakes was obtained from NOAA National Centers for Environmental Information. Lake bottom slope and relief were derived from the bathymetry. Combining the bathymetry and relief in classes we created 24 classes of hydrogeoforms based on the concepts in Hammond’s Landforms to identify features on the lake bottom. Known reef locations in the Great Lakes were compiled from various sources including USGS publications and Geographic Names Information System (GNIS).
download lake bottom slope
Shoreline classifications have been compiled from NOAA’s Environmental Sensitivity Index and Environment Canada’s Environment Sensitivity Atlas. Lake Erie and portions of Lake Michigan’s shoreline classification do not exist in geospatial digital form, so the U.S. Army Corps of Engineers (USACEs) shoreline descriptions from the 2012 oblique imagery were also included. USACEs and Environment Canada geomorphology classification includes descriptions of protection, nearshore, and geomorphology. USACEs and NOAA light detection and ranging (LiDAR) for the U.S. coastal areas of the Great Lakes a portions of the northshore of Lake Ontario. Metrics were derived from the LiDAR including contours, slope, relief, and bottom roughness. Shoreline sinuosity was calculated using the shoreline delineation compiled for the Great Lakes Hydrography Dataset. The GLHD shoreline was divided into 1km segments and sinuosity was calculated.
Substrate for the bottom of the Great Lakes in the offshore regions was digitized from peer reviewed publications. In the coastal and nearshore zones, the USACEs shoreline material descriptions (2012) were extended to 30 m of depth and confirmed by researchers across the Great Lakes and benthic sampling data. In Lake Erie, the Lake Erie Habitat Task Group has collected fine scale substrate data from tow, grab sample, and underwater video data to support management decisions for fish habitat. Several other locations included fine scale substrate data such as the Illinois waters of Lake Michigan, and in the nearshore areas of Minnesota, Lake Superior.
In the mid-2000s the Great Lakes Commission convened the Great Lakes Coastal Wetland Consortium (GLCWC) to identify hydrologically connected coastal wetlands across the entire Great Lakes Basin. The final data set identifies the areas and hydrogeomorphic wetland types the coastal wetlands. We have enhance the data set by aggregating the wetlands into 3 major types (open, protected, and delta) and creating data layers that describe the distance and direction to these 3 wetland types. Michigan Tech Research Institute (MTRI) created an updated wetlands and land use data within 10 km of the Great Lakes shoreline, which have also been incorporated into the GLAHF database.
Fish access to Great Lakes
Fish tributary access in the Great Lakes Basin was determine using the National Hydrography Dataset (NHD) Plus Version 2 and the Ontario Integrated Hydrology Dataset (2012). The tributary barriers included the USGS National Anthropogenic Barrier Dataset for the U.S. and the Ontario Ministry of Natural Resources and Forestry dams and barriers. The fish access data set identifies stream segments between the shoreline of the Great Lakes and first major barrier identified.
While developing the Great Lakes Hydrology Dataset (GLHD) we compiled a high-resolution shoreline of the Great Lakes using best available digitized shorelines for the U.S. and Canada.
Watersheds & tributaries
Tributaries are the most dominating link between the landscape and the open waters of the Great Lakes. We have tried to capture this link, consistently, by creating a set of watersheds and interfluves in the Great Lakes Hydrology Dataset (GLHD). Tributaries mouths are identified as pour points in the GLHD and contain attributes of common name and stream order. Data layers were created to calculated distance, direction, and river mouth density to all pour points in the GLHD and to only those pour points of Strahler stream order 5 and greater. Tributaries and land adjacent to the coastal and nearshore areas of the Great Lakes are known to influence the water and aquatic habitats. This is a very dynamic system that GLAHF tried to capture by spatially and mathematically modeling the zone most likely to be impacted by tributary and surface water runoff. The tributary influence data layer is weighted by watershed and interfluve area, decayed by distance and water depth, the layer is then broken into 3 classes based on stream order.
Quaternary and bedrock geology layers were obtained from the U.S. Geological Survey (USGS) and Ontario Ministry of Northern Development and Mines. The datasets were harmonized and aggregated up to common quaternary and bedrock geology classes that cover the entire Great Lakes Basin.
Land use & cover
Land use/cover has been harmonized for the 8 Great Lakes states in the U.S. and the province of Ontario. Data was obtained from USGS National Land Cover Database (NLCD) and Ontario Ministry of Natural Resources and Forestry (OMNRF). The 2 countries collect imagery for land cover at differing temporal scales, we were able to complete harmonized, bi-national land cover composites for 2000/2001 and 2011/2012. In the U.S. the land cover product includes developed imperiousness data layer. Land cover/use data are also available summarized by watershed.
Population & roads
Population census and road locations data are available from the U.S. Census Bureau and Statistics Canada. We harmonized population county and computed density for the 2000/2001 and 2010/2011 censuses. Population census data are also available summarized by watershed. Road locations and type were obtained from the same data sources, since both agencies maintain road information at similar spatial resolutions. Road locations for the entire Great Lakes Basin and road density by watershed available.
The Natural Resources Conservation Service and Agriculture and Agri-Food Canada develop and maintain soils database. We obtained the data and harmonized common classes for the Great Lakes Basin for soil slope, drainage, and rooting depth.
Measurements from buoys on the Great Lakes maintained by NOAA National Data Buoy Center and Department of Fisheries and Oceans Canada were summarized at several temporal scales for wind speed, direction, wave height mean and maximum, dominate wave period, average wave period, mean wave direction, air temperature, and water temperature for each buoys period of record.
Fetch is the unobstructed distance that wind can travel over a lake surface in an essentially constant direction. It is an important characteristic of open water bodies as a longer fetch can result in larger wind-generated waves. Utilizing buoy wind data and accounting for changes over time GLAHF has calculated the effective fetch for the open water and an index of coastal wind exposure called the Relative Exposure Index for the Great Lakes from ice-off season wind data. Fetch and Relative Exposure Index summaries are available annually and as a composite of averaged values from 2006 to 2014.
Offshore circulation hydrodynamic models have been develop at NOAA’s Great Lakes Environmental Research Laboratory (GLERL) as part of the Great Lakes Coastal Forecasting System (GLCFS). The GLAHF database provides summarizes of mean circulation magnitude and direction for the years 2006-2012.
Upwelling is the occurrence of cooler bottom water rising to the surface as warm water is pushed offshore during high winds. This is an important phenomena in the coastal areas of the Great Lakes, which introduces cooler, nutrient rich water to the surface. Using methods established by Plattner, et al. (2006) we have developed an annual index of the number of days upwelling has occurred each year at a fine spatial scale across the Great Lakes for the years 1995-2013.
U.S. Army Corps of Engineers (USACEs) Wave Information Studies have developed wave action models for the nearshore areas of the Great Lakes. We have summarized the hourly model output into annual, monthly, spring, and summer averages for wind speed, wave height, and wave period and have calculated the maximum and coefficient of variation for wave height for the years 1979-2012.
Cumulative degree-days (CDD) are a measure of heat accumulation over an entire season or year. Using the mean daily water temperature we calculated CDD for the surface water (1995-2013) and upper layer for the vertical water (2006-2012) temperature (see Water Temperature below).
Since 1973 ice cover has been interpolated from remotely sensed images. The daily percent ice cover (concentration) is available from 1973-2002 from the NOAA Great Lakes Ice Atlas, and since 2002 the NOAA Great Lakes Environmental Research Laboratory has continued to make observed days of ice available. We have summarized the data into monthly and annual ice cover concentration and an annual ice duration index (in days) for the years 1973-2013.
Spring rate of warming
We generated an index of spring warming to identify areas of potentially higher spring and early summer productivity. This index is the difference between June 1 and March 1 surface water temperatures (NOAA Great Lakes CoastWatch) divided by the number of days during that period to estimate the averaged change in temperature per day and was calculated for each grid cell for the years 1995-2014.
Stratification duration was derived from the NOAA Great Lakes CoastWatch surface temperature product (see Water Temperature below) for the years 1995-2013. Based on Fahnenstiel et al. (2010) recommending mid-year stratification occurring when the surface temperature is greater than or equal to 15 degrees Celsius. Using this threshold, the number of days a given pixel was at our above the threshold was tallied to calculate stratification duration in days for the years 1995-2013
The U.S. Environmental Protection Agency (EPA) Great Lakes National Program Office (GLNPO) samples stations on the Great Lakes multiple times each year since the early 1990s. Part of their sampling effort includes determining the location of the thermocline during the summer (August/September) sampling effort. We have extracted the depth to thermocline for each year by GLNPO sampling station.
Averaged surface water temperature annual, monthly, spring, and summer estimates of surface water temperature were calculated from remote sensing estimated daily data (NOAA Great Lakes CoastWatch) from 1995 to 2013. NOAA’s Great Lakes Coastal Forecasting System hydrodynamic model calculates vertical water temperature using a sigma coordinate system. We summarized these vertical values into 3 depth bins representing the epi- (0-20 m), meta- (20-40 m), and hypo-limnion (> 40m) and provided average temperatures annually, monthly, and for spring and summer for the years 2006-2012.