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Research about Great Lakes basin

Source-linked reports with geographic coverage including Great Lakes basin.

7 recordsLinked to original sources
USGS2026

On the importance of ichthyoplankton monitoring for invasive grass carp control in the Laurentian Great Lakes

Grass carp ( Ctenopharyngodon idella ) is an invasive herbivore observed in small numbers in the Laurentian Great Lakes since the 1980 s with records from all lakes except Lake Superior. Identification of diploid, age-1 + grass carp from the Sandusky River, a Lake Erie tributary, in 2012, prompted targeted efforts to evaluate the status of grass carp reproduction in the Lake Erie Basin. In 2014, researchers from the U.S. Geological Survey and University of Toledo began surveys to assess grass carp spawning in the Great Lakes, with the first fertilized eggs discovered in 2015 in the Sandusky River. Eight Great Lakes tributaries in the United States have been surveyed for evidence of grass carp spawning, identifying three confirmed spawning tributaries (Sandusky, Maumee, and Huron Rivers in Ohio). Initial work identified specific flow and temperature conditions that likely stimulate spawning. Egg and larval drift modeling estimated spawning locations based on egg development and flow characteristics, which helped removal crews locate and target spawning fish in the Sandusky River and later, the Maumee River. The research synthesized herein demonstrates the value of ichthyoplankton research to inform control of emerging invasive species and could inform management of other invasive carps with similar reproductive life histories, should they enter the Great Lakes.

Michigan, Ohio↗
USGS2025

Leveraging invasive mussel contaminant survey data for stepwise prioritization of chemicals of potential concern in the Great Lakes basin

Historical and ongoing anthropogenic activities coupled with advancements in analytical techniques have led to the detection of large numbers of contaminants in the Laurentian Great Lakes. Consequently, identifying and prioritizing chemicals likely to cause ecological harm represents a challenge for natural resource managers. Previous prioritization efforts have focused on contaminants in sediment, water, and passive samplers, which may not be representative of compounds that bioaccumulate in aquatic organisms. Consequently, this study adopted a stepwise method to prioritize chemicals of potential concern detected in dreissenid mussels from samples collected across the Great Lakes from 2009–2018. The stepwise method considered environmental fate, detection frequency, and exceedance of toxicity quotients based on ecotoxicological effect concentrations. Overall, 153 compounds out of 267 analyzed were detected in dreissenid mussels, 47 of which had water quality effect concentrations, 56 had apical effect concentrations (Tier 1 ECOTOX or apical screening), 17 had nonapical effect concentrations (Tier 2 ECOTOX, Cytotoxic Burst, and ToxCast) and 33 had estimated effect concentrations (quantitative structure-activity relationship, estimated screening, and pharmacological potency). Of the compounds with water quality effect concentrations, nine were designated as high priority, including the herbicide atrazine and five polycyclic aromatic hydrocarbons that were previously identified as potentially hazardous within other matrices. Similar contaminants were identified as high priority in a related study of native unionid mussels in the Great Lakes. A total of 27 compounds were low priority, suggesting that these contaminants do not warrant further action based on this dataset. Overall, these findings will facilitate the development of management strategies to mitigate the effects of contaminants on aquatic organisms within the Great Lakes.

Great Lakes basin↗
USGS2021

Machine learning predictions of mean ages of shallow well samples in the Great Lakes Basin, USA

The travel time or “age” of groundwater affects catchment responses to hydrologic changes , geochemical reactions, and time lags between management actions and responses at down-gradient streams and wells. Use of atmospheric tracers has facilitated the characterization of groundwater ages, but most wells lack such measurements. This study applied machine learning to predict ages in wells across a large region around the Great Lakes Basin using well, chemistry, and landscape characteristics. For a dataset of age tracers in 961 samples, the travel time from the land surface to the sample location was estimated for each sample using parametric functions. The mean travel times were then modeled using a gradient boosting machine (GBM) algorithm with cross validation tuning of model metaparameters. The GBM approach was able to closely match estimated ages for the training data (RMSE = 0.26 natural-log scale years) and provided a reasonable match to testing data (RMSE = 0.84). Of the variables tested, well characteristics (e.g. depth), land use, hydrologic indicators (e.g. topographic wetness index), and water chemistry (e.g. nitrate, fluoride, and pH), substantially affected the predictions of age. GBM prediction was applied to 14,335 groundwater samples with median sample depth of 5.4 m, indicating for the Great Lakes Basin a broad distribution of ages among wells with a median of 32.9 years. Lag times of decades are likely for these wells to respond to changing solute fluxes near land surface. While depth variables most strongly affected predicted mean ages, chemical constituents exhibited smooth trends with age, consistent with prevailing conceptual models of evolving sources and geochemistry flowpaths. The results provide proof of concept for use of readily available variables of well, landscape, and chemical characteristics to improve groundwater age estimates across large regions.

Great Lakes basin↗
USGS2019

Predicting the occurrence of chemicals of emerging concern in surface water and sediment across the U.S. portion of the Great Lakes Basin

Chemicals of emerging concern (CECs) are introduced into the aquatic environment via various sources, posing a potential risk to aquatic organisms. Previous studies have identified relationships between the presence of CECs in water and broad-scale watershed characteristics. However, relationships between the presence of CECs and source-related watershed characteristics have not been explored across the Great Lakes basin. Boosted regression tree (BRT) analyses were used to develop predictive models of CEC occurrence in water and sediment throughout 24 U.S. tributaries to the Great Lakes. Models were based on the distribution of both broad-scale and source-related watershed characteristics. Twenty-one upstream watershed characteristics, including land cover, number of permitted point sources, and distance to point sources were used to develop models predicting the probability of CEC occurrence in surface water and bottom sediment. Total accuracy of BRT models ranged from 66% to 94% for both matrices. All 21 watershed characteristics were important predictor variables in at least one surface-water model; twenty were important in at least one bottom-sediment model. Among the model variables, developed land use and distance to point sources were important predictors of the presence of CEC classes in both water and sediment. Although limitations exist, BRT models are one tool available for assessing vulnerability of fisheries and aquatic resources to CEC occurrences.

Great Lakes basin↗
USGS1998

Great Lakes

The Great Lakes region, as defined here, includes the Great Lakes and their drainage basins in Minnesota, Wisconsin, Illinois, Indiana, Ohio, Pennsylvania, and New York. The region also includes the portions of Minnesota, Wisconsin, and the 21 northernmost counties of Illinois that lie in the Mississippi River drainage basin, outside the floodplain of the river. The region spans about 9º of latitude and 20º of longitude and lies roughly halfway between the equator and the North Pole in a lowland corridor that extends from the Gulf of Mexico to the Arctic Ocean. The Great Lakes are the most prominent natural feature of the region (Fig. 1). They have a combined surface area of about 245,000 square kilometers and are among the largest, deepest lakes in the world. They are the largest single aggregation of fresh water on the planet (excluding the polar ice caps) and are the only glacial feature on Earth visible from the surface of the moon (The Nature Conservancy 1994a). The Great Lakes moderate the region’s climate, which presently ranges from subarctic in the north to humid continental warm in the south (Fig. 2), reflecting the movement of major weather masses from the north and south (U.S. Department of the Interior 1970; Eichenlaub 1979). The lakes act as heat sinks in summer and heat sources in winter and are major reservoirs that help humidify much of the region. They also create local precipitation belts in areas where air masses are pushed across the lakes by prevailing winds, pick up moisture from the lake surface, and then drop that moisture over land on the other side of the lake. The mean annual frost-free period—a general measure of the growing-season length for plants and some cold-blooded animals—varies from 60 days at higher elevations in the north to 160 days in lakeshore areas in the south. The climate influences the general distribution of wild plants and animals in the region and also influences the activities and distribution of the human population. The wild plants and animals and the natural systems that support them in the Great Lakes region are valuable resources of considerable local, regional, and national interest. They are also, in part, transboundary resources that we share with our Canadian neighbors to the north. The way these resources are changing over time is inadequately known and is a cause for concern for resource users and for those charged with managing and protecting these unique and valuable resources. This chapter describes the wild plants and animals and the systems that support them in the Great Lakes region; addresses their condition; and points out the gaps in our knowledge about them that, if filled, would aid in their conservation and appropriate use.

Illinois, Indiana, Minnesota, New York, Ohio, Penn↗
USGS1991

Hydrogeologic information in the Great Lakes basin, United States, and application of a geographic information system to public supply wells and hazardous-waste sites

A computerized data base has been established to facilitate analysis and interpretation of potential for ground-water contamination in the Great Lakes basin. The computerized data base is being used in conjunction with a geogrpahic information system (GIS). Locations of public-supply wells were obtained from Federal and State agencies and stored in the system. Well locations are displayed using the Albers equal-area projection. A GIS was used to create a map of public-supply wells and a map of combined waste sites and public-supply wells. A comprehensive bibliography of 1,114 references, published during the period 1960-86, pertaining to hydrogeologic studies in the Great Lakes basin and geographic information systems, has been compiled using a relational data-base program. Where possible, references are indexed by State and county to assist in determining areas where additional study is necessary.

Great Lakes basin↗