Skip to main content
Advanced Search

Filters: partyWithName: Ecosystems (X) > partyWithName: U.S. Geological Survey - ScienceBase (X)

Folders: ROOT > ScienceBase Catalog > Upper Midwest Environmental Sciences Center (UMESC) > Upper Midwest Environmental Sciences Center Data > Laurentian Great Lakes > GIS Data ( Show all descendants )

2 results (11ms)   

Location

Folder
ROOT
_ScienceBase Catalog
__Upper Midwest Environmental Sciences Center (UMESC)
___Upper Midwest Environmental Sciences Center Data
____Laurentian Great Lakes
_____GIS Data
View Results as: JSON ATOM CSV
The USGS developed the second in a series of informative spatial distribution datasets of submersed aquatic vegetation (SAV) in Lake Erie. The second dataset was developed by object-based image analysis of high-resolution imagery (US waters < 6 meters deep) collected during peak biomass in 2018 to allow assessments of changes in SAV distribution. Assessing SAV abundance may contribute to inform the long-term impacts of Grass Carp, Common Carp, eutrophication, wind fetch and sedimentation on vegetation communities throughout Lake Erie and the impact these stressors may have on other organisms in the ecosystem. These data may also help inform the deployment of toxic bait deployments targeting Grass Carp. Bait placement...
thumbnail
Observations and subtle shifts of vegetation communities in 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 eastern basin of Lake Erie.


    map background search result map search result map Lake Erie Aquatic Vegetation data Lake Erie Aquatic Vegetation data