Skip to main content
Advanced Search

Filters: Tags: Lake Michigan (X)

156 results (16ms)   

Filters
Date Range
Extensions
Types
Contacts
Categories
Tag Types
Tag Schemes
View Results as: JSON ATOM CSV
thumbnail
This dataset provides results of a targeted bacterial community metagenomic analysis of surface water, groundwater, and sand samples at Jeorse Park on Lake Michigan in East Chicago, Indiana. Seventy-two samples were collected from 6 sites in 2017. Samples were analyzed for the 16S ribosomal RNA (16S rRNA) gene (the S in 16S refers to the rate of sedimentation, in Svedberg units, of the RNA molecule in a centrifugal field), and one sample was excluded because it produced too few reads. The 16S rRNA gene is the most conserved of three rRNA genes (16S, 23S, and 5S) and is considered the most reliable for identification and taxonomic classification of bacterial species (Bouchet and others, 2008). Taxonomic analysis...
thumbnail
These data describe the catch and biological data from 363 bottom-set gill-net lifts distributed throughout Lake Michigan (including main basin and Green Bay) between April and November in 1930–1932. Data collected from the R/V Fulmar were recorded in notebooks and are now archived at the U.S. Geological Survey’s Great Lakes Science Center. Each lift included 1–7 gangs of linen gill nets. Each gang comprised 3–5 panels each having a length of 155 m, a height of 1.5 m, and a (stretch-)mesh size of either 60, 64, 67, 70, or 76 mm. The digitization of the Fulmar data notebooks was started in the late 1990s and finished in this study.
thumbnail
This dataset describes the hydrogeomorphic structure and lake-tributary mixing in three intermediate-sized Lake Michigan rivermouths: Ford River, Manitowoc River, and Pere Marquette River. Data were collected from May to October 2011. Water chemistry variables were measured with a multiparameter sonde along longitudinal, lateral, and vertical transects. Magnesium, boron, and stable water isotope concentrations were also determined from grab water samples at particular depths.
thumbnail
All gillnet data represented here expand upon vessel operations (OP table) data, all of which are collected by the United States Geological Survey, Great Lakes Science Center and its partners. The Gillnet Tables contain data collected from the research vessel deploying various gear used for gillnet data collection. The database uses sample_type to indicate the gear deployed. The tables relating to Gillnet are: GN_Annulus.csv, GN_Catch.csv, GN_Effort.csv, GN_Fish.csv, GN_L, GN_LF.csv, GN_OP.csv, GN_Prey.csv, GN_Stomach.csv, LMMB_Fish_Prey.csv, and LMMB_Invert_Prey.csv Data Quality: Note that the following data release is a snapshot of the database at the time of release. Some data quality checks are still being...
Categories: Data; Tags: Alewife, Bathythermograph, Benthos, Bloater, Cisco, All tags...
thumbnail
This dataset is part of the U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative. These data represent the flowline network in the Green Bay Restoration Assessment (GBRA). It is attributed with the number of disconnections (e.g., road crossings) between the reach and Lake Ontario. 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. These data help identify the condition of hydrologic separation between potential restoration areas and Lake Ontario. Low numbers represent fewer disconnections, such as culverts, between the reach and the water body requiring no flow network modification...
thumbnail
Aging infrastructure is creating a pressing national need to align priorities between civil engineering and other interests. Restoring ecological connectivity of river networks that are fragmented by dams and road crossings has become a prominent objective for environmental managers across the country. A mature decision-support framework and newly available data on the condition of dams throughout the Lake Michigan basin offer unique opportunities to test for potential cost-efficiency gains from sharing the costs of removing decrepit dams between environmental and engineering organizations. At sites where these interests align, genuine win-win scenarios could advance both ecological connectivity and infrastructure...
thumbnail
This dataset contains all the layers associated with U.S. Geological Survey (USGS) Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) initiative for the Upper Peninsula Restoration Assessment (UPRA) which aims to identify and rank coastal areas with the greatest potential for wetland habitat restoration. Each layer has a unique contribution to the identification of restorable wetlands. The 7 parameters (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) and Index Composite directly correlate to areas that are recommended for restoration. The dikes, degree...
thumbnail
These data were collected to support the development of detection and classification algorithms to support Bureau of Ocean Energy Management (BOEM) studies and assessments associated with offshore wind energy production. There are 3 child zip files included in this data release. 01_Codebase.zip contains a codebase for using deep learning to filter images based on the probability of any bird occurrence. It includes instructions and files necessary for training, validating, and testing a machine learning detection algorithm. 02_Imagery.zip contains imagery that were collected using a Partenavia P68 fixed-wing airplane using a PhaseOne iXU-R 180 forward motion compensating 80-megapixel digital frame camera with...
thumbnail
Structure-from-Motion (SfM) point clouds were created from images collected using a remotely piloted unoccupied aerial system over the bluffs of the eastern shore of Lake Michigan in St. Joseph, a urban residential area. The digital imagery was collected with the internal camera of a DJI Phantom 3 PRO for the July 8, 2019 data and DJI Phantom 4 PRO for the July 13, 2021 data that was operated by the University of Toledo. The images cover an extent between the intersection of Lakeshore Dr. with Lakeshore Road to the north, and South Lakeshore Dr. to the south. The images were collected in .jpg format and include Exif metadata with GPS date, time, and latitude and longitude, and other fields. Point clouds were created...
thumbnail
Images were collected using a remotely piloted unoccupied aerial system over the bluffs of the eastern shore of Lake Michigan in Miami Park rural residential area, Allegan County, MI. Images were collected on July 19, 2021, by Richard Becker, University of Toledo, and cover an extent between south of Lakestone Dr. to the north, and south of A St. to the south. Images were collected to monitor active bluff erosion in the area. The images are presented here in zipped files grouped by type of collection, nadir and oblique. The images were collected in JPG format and include Exif metadata with GPS date, time, longitude and latitude, copyright, keywords, and other fields. These files were used in structure-from-motion...
thumbnail
Structure-from-Motion (SfM) point clouds were created from images collected using a remotely piloted unoccupied aerial system over the bluffs of the eastern shore of Lake Michigan in Miami Park rural residential area. The digital imagery was collected with the internal camera of a DJI Phantom 4 PRO PPK that was operated by the University of Toledo, on July 19, 2021. The images cover an extent between south of Lakestone Dr. to the north, and south of A St. to the south. The images were collected in .jpg format and include Exif metadata with GPS date, time, and latitude and longitude, copyright, keywords, and other fields. Point clouds were created from the collected images using SfM photogrammetry software. The point...
thumbnail
The Fox River transports elevated loads of nitrogen and phosphorus to Lake Michigan. The increased concentration of N and P causes eutrophication of the lake, creating hypoxic zones and damaging the lake ecosystem.To decrease loading, best management practices (BMPs) have been implemented in the uplands of the basin. Little work has been done, however, to reduce nutrient concentrations in the river. Rivers are capable of removing nutrients through biotic uptake and sediment burial and are able to remove N through denitrification. Identifying and managing these locations of increased nutrient cycling known as “hot spots” may be another mechanism for nutrient mitigation.Our objective was to identify hot spots of N...
Coastal and estuarian wetlands in the Great Lakes Basin are increasingly impacted by habitat degradation, invasive species, and most recently (late 2010's), increased water levels. These wetlands act as an important buffer between the open lake and the near-shore areas, as key areas for nutrient cycling, as critical nurseries for many species of lake fish, and as habitat for numerous species of concern. Understanding how the cover and composition of these wetlands has changed over time is critical to making informed management decisions. By using both historical documents and imagery, multiple historic maps of wetland coverage were created in GIS to compare over time and to current maps and imagery of these critical...
thumbnail
These data contain observation and null polygons for waterfowl aerial surveys of Lake Michigan collected through the years 2009-2014. Polygons were created adjacent to either side of the flight lines (transects). The right and left offset of the polygons from the flight path, was determined using the average altitude of the plane along the transect and the observation angle through the plane’s window. Observed birds were counted and identified by species. This count data was attributed to the polygon closest to the point along the transect where the observation occurred, and on the side of the plane in which the observation took place. The point data represent counts where each point represents a single species....
thumbnail
This dataset describes the quantity, morphology, concentration and polymer identity of microplastics in surficial benthic sediment of Lake Michigan and Lake Erie. Lake Michigan sediment samples were collected at 20 locations in September, 2013 and Lake Erie sediment samples were collected at 12 locations in September, 2014 while on-board the R.V. Lake Guardian. Sampling and analysis methods are described in the Processing Steps section of the metadata.
Text files containing data regarding attributes of lake trout egg thiamine concentrations from sites in lakes Huron and Michigan collected during 2019-20, sampling site locations and quality assurance quality control values for comparison to previous years (2017-18) lake trout egg thiamine concentrations.
thumbnail
This dataset includes pesticides and pesticide transformation products in 15 tributaries of the Great Lakes. Pesticides were monitored using polar organic chemical integrative samplers (POCIS) to estimate concentrations in water following standard protocols (Alvarez, 2010) in June and July 2016. POCIS extracts were analyzed for 225 chemicals (USGS National Water Quality Laboratory schedule 5437, Sandstrom and others, 2016), for which 129 chemicals also have POCIS uptake rates, allowing calculations of time-weighted mean concentration over the approximately 30 day deployment (Alvarez and others, 2008). Collectively, there were 97 chemicals detected, and time-weighted mean concentrations could be calculated for 95...
thumbnail
This topobathymetric digital elevation model (TBDEM) mosaic represents the topography and bathymetry for the Milwaukee River Estuary in Milwaukee, Wisconsin and adjacent terrestrial and Lake Michigan nearshore coastal areas. The TBDEM was produced in support of modeling and for developing a physical habitat framework to help with understanding the effects from multidirectional currents and seiche effects associated with the mixing of river flows with Lake Michigan backwater. The TBDEM mosaic is built off existing terrestrial, nearshore, and estuary frameworks developed for other areas around the Great Lakes and the Milwaukee River Harbor. Ranging from 2008-2015, land elevations derived from lidar and historic topographic...
thumbnail
This dataset describes the quantity, morphology, and polymer identity of microplastics in the water column and surficial sediments of Milwaukee-Area streams, the Milwaukee Harbor, and Lake Michigan (Wisconsin). Water samples were collected at 10 locations, 2-4 times each, from May to September, 2016. At the 4 shallowest locations, water was collected only at the water surface. At the remaining 6 locations, water was collected at the water surface and at 1-4 depths below the surface. Sediment samples were collected once, in June 2016, at a subset of 9 locations. Sampling and analysis methods are described in the Processing Steps section of the metadata. These data are interpreted in the following journal article:...
thumbnail
All mensuration data represented here expand upon vessel operations (OP table) data, all of which are collected by the United States Geological Survey, Great Lakes Science Center and its partners. The Mensuration Tables contain data collected from the research vessel deploying various gear used for mensuration data collection. The database uses sample_type to indicate the gear deployed. The tables relating to Mensuration are: Mensuration.csv, MS_head_rope_depth.csv, MS_FOOT_ROPE_DEPTH, MS_Primary.csv, MS_Temperature.csv, and MS_Wingspread.csv Data Quality: Note that the following data release is a snapshot of the database at the time of release. Some data quality checks are still being undertaken after the time...
Categories: Data; Tags: Alewife, Bathythermograph, Benthos, Bloater, Cisco, All tags...


map background search result map search result map Optimization at the infrastructure-connectivity nexus: boosting cost-efficiency of restoration using dam condition data for Lake Michigan Metagenomics analysis of groundwater, surface water, and sand samples at Jeorse Park in East Chicago, Indiana, 2017 Great Lakes Research Vessel Operations 1958-2018: Gillnet. (ver. 3.0, April 2019) Great Lakes Research Vessel Operations 1958-2018: Mensuration. (ver. 3.0, April 2019) Microplastics in the water column and sediment in Milwaukee-Area streams, the Milwaukee Harbor, and Lake Michigan, 2016 Great Lakes Restoration Initiative Project 49 Fox River Basin 2016 and 2017 Data Microplastics in the surficial benthic sediment from Lake Michigan and Lake Erie, 2013 and 2014 Hydrogeochemical Mixing data from Lake Michigan Tributaries 2011 1930-1932 Gill net data from Lake Michigan Topobathymetric Digital Elevation Model (TBDEM) of the Milwaukee River Estuary, Milwaukee, Wisconsin and adjacent terrestrial and Lake Michigan nearshore coastal areas Pesticides and pesticide transformation product data from passive samplers deployed in 15 Great Lakes tributaries, 2016 Lake Michigan Sea Duck Survey 2009-2014 Thiamine concentrations in lake trout eggs collected from the Great Lakes in 2019-20 Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Upper Peninsula, U.S. (ver. 2.0, January 2024) Structure-from-Motion photos and derived point clouds from bluffs in Miami Park, MI, July 19, 2021 Structure-from-Motion point clouds from Miami Park surveys, MI, July 19, 2021 Structure-from-Motion point clouds from St. Joseph surveys, MI, July 13, 2021 Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Green Bay, U.S.: Degree Flowlines Code, imagery, and annotations for training a deep learning model to detect wildlife in aerial imagery Structure-from-Motion photos and derived point clouds from bluffs in Miami Park, MI, July 19, 2021 Structure-from-Motion point clouds from Miami Park surveys, MI, July 19, 2021 Structure-from-Motion point clouds from St. Joseph surveys, MI, July 13, 2021 Metagenomics analysis of groundwater, surface water, and sand samples at Jeorse Park in East Chicago, Indiana, 2017 Topobathymetric Digital Elevation Model (TBDEM) of the Milwaukee River Estuary, Milwaukee, Wisconsin and adjacent terrestrial and Lake Michigan nearshore coastal areas Microplastics in the water column and sediment in Milwaukee-Area streams, the Milwaukee Harbor, and Lake Michigan, 2016 Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Upper Peninsula, U.S. (ver. 2.0, January 2024) Hydrogeochemical Mixing data from Lake Michigan Tributaries 2011 Great Lakes Coastal Wetland Restoration Assessment (GLCWRA) Green Bay, U.S.: Degree Flowlines Great Lakes Restoration Initiative Project 49 Fox River Basin 2016 and 2017 Data Optimization at the infrastructure-connectivity nexus: boosting cost-efficiency of restoration using dam condition data for Lake Michigan 1930-1932 Gill net data from Lake Michigan Lake Michigan Sea Duck Survey 2009-2014 Thiamine concentrations in lake trout eggs collected from the Great Lakes in 2019-20 Microplastics in the surficial benthic sediment from Lake Michigan and Lake Erie, 2013 and 2014 Pesticides and pesticide transformation product data from passive samplers deployed in 15 Great Lakes tributaries, 2016 Code, imagery, and annotations for training a deep learning model to detect wildlife in aerial imagery Great Lakes Research Vessel Operations 1958-2018: Gillnet. (ver. 3.0, April 2019) Great Lakes Research Vessel Operations 1958-2018: Mensuration. (ver. 3.0, April 2019)