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This data set includes WRTDS nutrient flux trend results and the values of daily streamflow trend results displayed in the Quantile-Kendall plots. For 1995-2015 nutrient trends, the method of generalized flow normalization (FNG) was used which explicitly addresses non-stationary streamflow conditions. For 2005-2015 nutrient trends, the WRTDS trend analyses used the method of stationary flow normalization (FNS) because streamflow nonstationarity is difficult to assess over this shorter duration time frame. The 1995-2015 annual nutrient trends were determined for all five nutrient parameters (TP, SRP, TN, NO23, TKN), and monthly trends were evaluated only for SRP. The 2005-2015 annual nutrient trends were determined...
The data document the results of several microbe bioassays performed by the USGS on Phragmites australis plants, including those performed on mature leaves, seedlings, and dead leaf tissues exploration of the literature to find accounts of microbes associated with Phragmites worldwide. For the bioassays, we prepared 162 pure cultures isolated from Phragmites plants in North America along the east coast, Florida, the Gulf of Mexico, and the Great Lakes area, 125 of which were from a previous study, and 38 represent new collections. The DNA sequences used to identify the 37 new collections are included. Microbes were isolated from plants collected from 2015-2018. We performed assays using both North American plant...
This Benthic Invertebrate Community Analysis dataset, a conceptual subgroup of the Lake Erie Ecological Investigations (LEEI) dataset, focuses on the benthic invertebrates sampled at Areas of Concern (AOCs) on Lake Erie. Per the Quality Assurance Project Plan (QAPP), the invertebrate samples were taken from sediments remaining from the sediment analysis. Identification of the invertebrates was completed by the same invertebrate taxonomist for both the 1998-2000 evaluation and 1986-87 historical evaluation (Smith et al. 1994) for increased consistency. Oligochaetes were identified to species if possible, chironomids were identified to genus, as adult specimens are needed for specific identification, and other taxa...
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...
Vegetation change is an important issue facing managers at Isle Royale National Park (ISRO). These data were created using high-resolution imagery collected in the winter of 2017 which was compared to the vegetation map of the National Park published in 2000 (project imagery collected in 1994 and 1996). These data review where vegetation cover type, density, and pattern have changed since imagery collection for the 2000 publication and provide a proposed reason for the change.
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...
Categories: Data Release - Revised;
Types: GeoTIFF,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Chippewa,
Great Lakes,
Holocene,
Lake Huron,
Lake Michigan,
High-resolution digital aerial imagery was collected on August 23 and 24, 2018, with an 80-megapixel Phase One iXU-R 180 natural color aerial camera co-mounted with a Phase One iXU-RS 160 achromatic aerial camera. Software co-registers the simultaneously collected images to create 4-band imagery that can be displayed in either true color (RGB) or color-infrared (CIR) format. The camera system is connected to the plane's positioning and orientation system and precise metadata was generated for each exposure. This imagery was intended to be used as a base layer for object-based image analysis (OBIA) to map aquatic vegetation in western Lake Erie.
High-resolution digital aerial imagery was collected on August 23 and 24, 2018, with an 80-megapixel Phase One iXU-R 180 natural color aerial camera co-mounted with a Phase One iXU-RS 160 achromatic aerial camera. Software co-registers the simultaneously collected images to create 4-band imagery that can be displayed in either true color (RGB) or color-infrared (CIR) format. The camera system is connected to the plane's positioning and orientation system and precise metadata was generated for each exposure. This imagery was intended to be used as a base layer for object-based image analysis (OBIA) to map aquatic vegetation in western Lake Erie.
High-resolution digital aerial imagery was collected on August 23 and 24, 2018, with an 80-megapixel Phase One iXU-R 180 natural color aerial camera co-mounted with a Phase One iXU-RS 160 achromatic aerial camera. Software co-registers the simultaneously collected images to create 4-band imagery that can be displayed in either true color (RGB) or color-infrared (CIR) format. The camera system is connected to the plane's positioning and orientation system and precise metadata was generated for each exposure. This imagery was intended to be used as a base layer for object-based image analysis (OBIA) to map aquatic vegetation in western Lake Erie.
High-resolution digital aerial imagery was collected on August 23 and 24, 2018, with an 80-megapixel Phase One iXU-R 180 natural color aerial camera co-mounted with a Phase One iXU-RS 160 achromatic aerial camera. Software co-registers the simultaneously collected images to create 4-band imagery that can be displayed in either true color (RGB) or color-infrared (CIR) format. The camera system is connected to the plane's positioning and orientation system and precise metadata was generated for each exposure. This imagery was intended to be used as a base layer for object-based image analysis (OBIA) to map aquatic vegetation in western Lake Erie.
High-resolution digital aerial imagery was collected on August 23 and 24, 2018, with an 80-megapixel Phase One iXU-R 180 natural color aerial camera co-mounted with a Phase One iXU-RS 160 achromatic aerial camera. Software co-registers the simultaneously collected images to create 4-band imagery that can be displayed in either true color (RGB) or color-infrared (CIR) format. The camera system is connected to the plane's positioning and orientation system and precise metadata was generated for each exposure. This imagery was intended to be used as a base layer for object-based image analysis (OBIA) to map aquatic vegetation in western Lake Erie.
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...
This data release contains input data used in model development and TIF raster files used to predict the probability of high arsenic (As) and high manganese (Mn) in groundwater within the glacial aquifer system in the northern United States. Input data include measured As and Mn concentrations at groundwater wells, and associated predictor variable data. The probability of high As and high Mn was predicted using boosted regression tree methods using the gbm package in R version 4.0.0. The response variables for individual models were the occurrence of: (1) As >10 µg/L, and (2) Mn >300 µg/L. Water-quality data were compiled from three sources, as described in Wilson and others (2019): a compilation of data from numerous...
Observations and subtle shifts of vegetation communities in western Lake Erie have USGS researchers concerned about the potential for Grass Carp to alter these vegetation communities. Broad-scale surveys of vegetation using remote sensing and GIS mapping, coupled with on-the-ground samples in key locations will permit assessment of the effect Grass Carp may have already had on aquatic vegetation communities and establish baseline conditions for assessing future effects. Existing aerial imagery was used with object-based image analysis to detect and map aquatic vegetation in the western basin of Lake Erie.
Categories: Data;
Types: Citation,
Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Asian Carp,
Emergent Vegetation,
Erie County,
Grass Carp,
Great Lakes,
These data consist of larval fish and water profile data collected with a nearshore to offshore transect approach at 9 transects throughout Lake Huron. Larval fish and their stomach contents were identified, enumerated, and measured (if possible) using a dissecting microscope. These data were used to calculate densities of potential fish prey items (what is available in the environment) and compare that to what the fishes ate for selectivity analysis. Larval fish age estimation based on daily growth rings from otoliths was also conducted. These data are in raw form. The water profile data were collected using a bathythermograph and bin-averaged at the 1 m level. Environmental prey data are available at the following...
We investigated fine-scale genetic patterns of the federally threatened Eastern Massasauga Rattlesnake (Sistrurus catenatus) on a relatively undisturbed island in northern Michigan, USA. This species often persists in habitat islands throughout much of its distribution due to extensive habitat loss and distance-limited dispersal. These data are from 102 individual Eastern Massasauga Rattlesnakes sampled at Bois Blanc Island, Michigan and genotyped at 15 microsatellite loci. Samples were collected as part of a study to examine functional connectivity for the Eastern Massasauga. We found that the entire island population exhibited weak genetic structuring with spatially segregated variation in effective migration...
This raster dataset describes elevation values, in meters (m), in Sleeping Bear Dunes National Lakeshore in 1955. The 1955 DEM was produced from historical aerial imagery acquired on April 1, 1955 at a flying height of 8,500 ft (1:17,000). Structure from motion (SfM) analysis of this imagery produced a 0.88 m DEM, which was edited and resampled to 1 m.
Data provided in this release support the findings in Choquette et al. (2019), utilizing methods for evaluating water-quality and daily-streamflow trends described also in Hirsch and DeCicco (2015 and 2018a) and Hirsch (2018). The trend results and model-input data focus on 10 locations in the Lake Erie watershed that have long-term (20 or more years) water-quality and streamflow monitoring records. The trend results include the years 1987 through 2016 or specified sub-periods during this time frame. The model-input data records spanned the time period 1974 through 2016 although record lengths varied by site, data type, and trend analysis. The water-quality records were provided by the National Center for Water...
This data set represents initial forest communities developed for Isle Royale National Park. LANDIS-II requires an input data layer that contains the ages of each species cohort present within each cell of the landscape. To develop this layer, we matched the composition of forest inventory plots to a map of forest types, and randomly imputed U.S. Department of Agriculture Forest Inventory plots within each matching forest type
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Forest Succession,
Isle Royale National Park,
Lake Superior,
Michigan,
USGS Science Data Catalog (SDC),
High-resolution digital aerial imagery was collected on August 23 and 24, 2018, with an 80-megapixel Phase One iXU-R 180 natural color aerial camera co-mounted with a Phase One iXU-RS 160 achromatic aerial camera. Software co-registers the simultaneously collected images to create 4-band imagery that can be displayed in either true color (RGB) or color-infrared (CIR) format. The camera system is connected to the plane's positioning and orientation system and precise metadata was generated for each exposure. This imagery was intended to be used as a base layer for object-based image analysis (OBIA) to map aquatic vegetation in western Lake Erie.
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