Lake Habitat Survey data collected using the standard Lake Habitat Survey (LHS) methodology by accredited surveyors. LHS is a standard survey of a lake where data is collected in a replicable manner. At 10 ‘Hab-plots’ (Habitat Observation plots) specific details are recorded about lake marginal features. General information about the lake is recorded in the 'sweep-up' section of the survey. The bulk of the surveys were conducted between 2004 and 2009. A total of 99 lakes in England have been surveyed once. This dataset contains summary information of the LHS surveys. The following information has been excluded from the survey data because there is a risk that we might be disclosing personal data: • Surveyor name • Primary use • Litter, dump, landfill (%) • Lake base data – this has been excluded because it was originally taken from an external source. Up-to-date data for UK lakes is available from CEH (Centre for Ecology & Hydrology) through their Lakes Portal (https://eip.ceh.ac.uk/apps/lakes/).

Habitat and ecosystem data used to conduct a baseline survey of coastal habitat in Lake Huron, Georgian Bay, and St. Marys River are included in this dataset. The Lake Huron Survey methodology consists of four general steps; 1) delineating the coastal ecosystem into coastal units based on water flow, ecology, and geology; 2) selecting key habitat types including wetlands, uplands (natural and anthropogenic), tributaries, and inland lakes and ponds, and the measures to assess each habitat type and the entire coastal ecosystem; 3) conducting a spatial analysis and summarizing results; and 4) sharing results.

Habitat and ecosystem data used to conduct a baseline survey of coastal habitat in Lake Superior, Nipigon Bay, and Black Bay are included in this dataset. The Lake Superior Survey methodology consists of four general steps; 1) delineating the coastal ecosystem into coastal units based on water flow, ecology, and geology; 2) selecting key habitat types including wetlands, uplands (natural and anthropogenic), tributaries, and inland lakes and ponds, and the measures to assess each habitat type and the entire coastal ecosystem; 3) conducting a spatial analysis and summarizing results; and 4) sharing results.

Habitat and ecosystem data used to conduct a baseline survey of coastal habitat in Lake Erie, St. Clair River, Lake St. Clair and Detroit River are included in this dataset. The Lake Erie Survey methodology consists of four general steps; 1) delineating the coastal ecosystem into coastal units based on water flow, ecology, and geology; 2) selecting key habitat types including wetlands, uplands (natural and anthropogenic), tributaries, and inland lakes and ponds, and the measures to assess each habitat type and the entire coastal ecosystem; 3) conducting a spatial analysis and summarizing results; and 4) sharing results.

description: A large-scale lake study on Interior Alaska National Wildlife Refuges (NWR) was undertaken from 1984 1986. Six NWRs were surveyed (Innoko, Kanuti, Koyukuk, Nowitna, Tetlin, and Yukon Flats) and lake-specific habitat and fish data were collected from 135 lakes, though a comprehensive report of the findings was never published. This Alaska Fisheries Data Series Report presents these data, allowing public access to this important information. Lake locations, reference and bathymetric maps, lake habitat descriptions, and fisheries data are organized and presented. Lowland lakes were most commonly sampled (74), followed by foothill (31) and oxbow (30) lakes. The highest elevation and deepest sampled lakes were in Tetlin NWR. The highest water quality measurements (conductivity, total alkalinity, total hardness, and pH) came from Yukon Flats NWR lakes. Of the 135 lakes sampled, 102 lakes contained fish. A total of 15 fish species were collected throughout the study, with Tetlin NWR lakes having the highest species diversity (9 species) and Nowitna and Yukon Flats NWRs having the lowest (6 species). Humpback whitefish Coregonus clupeaformis, least cisco C. sardinella, and northern pike Esox lucius had the widest distribution, being present in all six refuges. The highest frequencies of fish occurrence were in oxbow and lowland lakes, lakes with river connections, and lakes with high flood potential. Foothill lakes and lakes without river connections had the lowest probability of fish capture. Koyukuk NWR had the most sampled lakes containing fish (96%) and Yukon Flats NWR had the fewest sampled lakes with fish present (49%). Northern pike was the most ubiquitous species, occurring in 90% of all lakes containing fish. Fish species diversity was highest in lakes with river connections (14 species).; abstract: A large-scale lake study on Interior Alaska National Wildlife Refuges (NWR) was undertaken from 1984 1986. Six NWRs were surveyed (Innoko, Kanuti, Koyukuk, Nowitna, Tetlin, and Yukon Flats) and lake-specific habitat and fish data were collected from 135 lakes, though a comprehensive report of the findings was never published. This Alaska Fisheries Data Series Report presents these data, allowing public access to this important information. Lake locations, reference and bathymetric maps, lake habitat descriptions, and fisheries data are organized and presented. Lowland lakes were most commonly sampled (74), followed by foothill (31) and oxbow (30) lakes. The highest elevation and deepest sampled lakes were in Tetlin NWR. The highest water quality measurements (conductivity, total alkalinity, total hardness, and pH) came from Yukon Flats NWR lakes. Of the 135 lakes sampled, 102 lakes contained fish. A total of 15 fish species were collected throughout the study, with Tetlin NWR lakes having the highest species diversity (9 species) and Nowitna and Yukon Flats NWRs having the lowest (6 species). Humpback whitefish Coregonus clupeaformis, least cisco C. sardinella, and northern pike Esox lucius had the widest distribution, being present in all six refuges. The highest frequencies of fish occurrence were in oxbow and lowland lakes, lakes with river connections, and lakes with high flood potential. Foothill lakes and lakes without river connections had the lowest probability of fish capture. Koyukuk NWR had the most sampled lakes containing fish (96%) and Yukon Flats NWR had the fewest sampled lakes with fish present (49%). Northern pike was the most ubiquitous species, occurring in 90% of all lakes containing fish. Fish species diversity was highest in lakes with river connections (14 species).

Habitat and ecosystem data used to conduct a baseline survey of coastal habitat in Lake Ontario, Niagara River and the St. Lawrence River (up to the Quebec border) are included in this dataset. The Lake Ontario Survey methodology consists of four general steps; 1) delineating the coastal ecosystem into coastal units based on water flow, ecology, and geology; 2) selecting key habitat types including wetlands, uplands (natural and anthropogenic), tributaries, and inland lakes and ponds, and the measures to assess each habitat type and the entire coastal ecosystem; 3) conducting a spatial analysis and summarizing results; and 4) sharing results.

The Aquatic Habitat Inventory contains lake, river and stream survey data collected from the 1950s to the 1990s. These surveys were conducted to acquire basic knowledge of the chemical, physical and biological characteristics of Ontario’s lakes, rivers, and streams to aid in watershed planning, aquatic habitat conservation and fisheries management.

In 2020, with generous funding from the National Lottery Heritage Fund, Ulster Wildlife, National Trust NI, RSPB NI and Woodland Trust NI came together to start building capacity to deliver Nature Recovery Networks in Northern Ireland. As part of the project, habitat networks maps were produced for all terrestrial and intertidal priority habitats, based on the Natural England (Edwards et al., 2020) methodology. The habitat networks comprise vector datasets that map areas of land into different network categories, based on how favourable the land is for restoration to, or creation of the priority habitat, and how effective actions in each area would be at enhancing connectivity of the priority habitat, based on proximity to existing habitat patches. A description of these network categories is provided in Table 1 in the methodology report, available at https://www.ulsterwildlife.org/sites/default/files/2022-10/EnvSys%20NI%20NRN%20mapping%20report.pdf. The habitat network maps do not represent a fully comprehensive depiction of land cover, nor do they provide specific land management options and do not therefore replace the need for an on-site ecological surveys/appraisals. The maps are intended to function as a decision-support tool alongside other pieces of information, both from on-site surveys and data from other sources.

Habitat and ecosystem data used to conduct a baseline survey of coastal habitat in the Canadian Great Lakes in support of the Great Lakes Water Quality Agreement (Annex 7, Habitat and Species). The baseline habitat survey integrates various internal and external data sources that are collected or produced by various government and non-government organizations and integrated into this dataset. The geographic scope of the survey focuses on the coastal margin (from the shoreline to approximately 2 kilometers inland) of the Canadian Great Lakes and connecting channels. The scope of the survey includes metrics for coastal wetland habitat, coastal terrestrial habitat, tributary habitat and habitat protection and restoration.

The National Lakes Assessment (NLA) is a statistical survey of the condition of our nation's lakes, ponds, and reservoirs. It is designed to provide information on the extent of lakes that support healthy biological condition and recreation, estimate how widespread major stressors are that impact lake quality, and provide insight into whether lakes nationwide are getting cleaner. This dataset is an archived (zipped) file comprised of chemical, physical and biological files used in developing the NLA 2017 report. Sampling was conducted in the summer of 2017 at approximately 1000 sites in the conterminous U.S. Sites were selected using a statistical survey (probabilistic) design. The files include water chemistry, profile data, benthic macroinvertebrates, physical habitat, landscape metrics, phytoplankton data, secchi depth, data, tropic status, zooplankton, etc. Users are encouraged to visit the NARS data webpage for updates to data files (e.g., for example updated zooplankton files) and data from other surveys. https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys Citation for the NLA 2017 archived data: U.S. Environmental Protection Agency. National Aquatic Resource Surveys. National Lakes Assessment 2017 Report. Archived Data. (INSERT data and metadata files used). Available from U.S. EPA web page: https://www.epa.gov/national-aquatic-resource-surveys/reports-and-data-national-lakes-assessment-2017. DOI: 10.23719/1529585 EPA encourages users who are publishing subsets of the data (say as part of a journal article publication) to include the above citation. EPA also encourages users of the data to include the following acknowledgement: “The National Lakes Assessment 2017 data were a result of the collective efforts of dedicated field crews, laboratory staff, data management and quality control staff, analysts and many others from EPA, states, tribes, federal agencies, universities, and other organizations. Please contact nars-hq@epa.gov with any questions.” Additional information: NLA is part of the National Aquatic Resource Surveys, an EPA/State/Tribal partnership. The National Aquatic Resource Surveys (NARS) are statistical surveys designed to assess the status of and changes in quality of the nation’s coastal waters, lakes and reservoirs, rivers and streams, and wetlands. Using sample sites selected at random, these surveys provide a snapshot of the overall condition of the nation’s water. Because the surveys use standardized field and lab methods, we can compare results from different parts of the country and between years. Citation information for this dataset can be found in Data.gov's References section.

This dataset provides shapefile outlines of the 881 lakes that had temperature modeled as part of this study. The format is a shapefile for all lakes combined (.shp, .shx, .dbf, and .prj files). A csv file of lake metadata is also included. This dataset is part of a larger data release of lake temperature model inputs and outputs for 881 lakes in the U.S. state of Minnesota (https://doi.org/10.5066/P9PPHJE2).

National Lakes Assessment 2012 Datafiles for Report “National Lakes Assessment 2012: A Collaborative Survey of lakes in the United States”: The National Lakes Assessment (NLA) is a statistical survey of the condition of our nation's lakes, ponds, and reservoirs. It is designed to provide information on the extent of lakes that support healthy biological condition and recreation, estimate how widespread major stressors are that impact lake quality, and provide insight into whether lakes nationwide are getting cleaner.

This dataset is an archived (zipped) file comprised of chemical, physical and biological files used in developing the NLA 2012 report. Sampling was conducted in the summer of 2012 at approximately 1000 sites in the conterminous U.S. Sites were selected using a statistical survey (probabilistic) design. The files include water chemistry, profile data, benthic macroinvertebrates, physical habitat, landscape metrics, phytoplankton data, secchi depth, data, tropic status, zooplankton, etc. Users are encouraged to visit the NARS data webpage for updates to data files (e.g., for example updated zooplankton files) and data from other surveys. https://www.epa.gov/national-aquatic-resource-surveys/data-national-aquatic-resource-surveys

Citation for the NLA 2012 archived data: U.S. Environmental Protection Agency. National Aquatic Resource Surveys. National Lakes Assessment 2012 Report. Archived Data. (INSERT data and metadata files used). Available from U.S. EPA web page: https://www.epa.gov/national-aquatic-resource-surveys/national-results-and-regional-highlights-national-lakes. DOI: 10.23719/1529584

EPA encourages users who are publishing subsets of the data (say as part of a journal article publication) to include the above citation. EPA also encourages users of the data to include the following acknowledgement: “The National Lakes Assessment 2012 data were a result of the collective efforts of dedicated field crews, laboratory staff, data management and quality control staff, analysts and many others from EPA, states, tribes, federal agencies, universities, and other organizations. Please contact nars-hq@epa.gov with any questions.”

Additional information: NLA is part of the National Aquatic Resource Surveys, an EPA/State/Tribal partnership. The National Aquatic Resource Surveys (NARS) are statistical surveys designed to assess the status of and changes in quality of the nation’s coastal waters, lakes and reservoirs, rivers and streams, and wetlands. Using sample sites selected at random, these surveys provide a snapshot of the overall condition of the nation’s water. Because the surveys use standardized field and lab methods, we can compare results from different parts of the country and between years. Citation information for this dataset can be found in Data.gov's References section.

We applied habitat suitability indices and network analysis to identify the lakes most critical to the establishment and spread of zebra mussels (Dreissena polymorpha). We included 225 lakes in the study area Habitat suitability indices were based on known tolerances of water chemical and physical parameters in relationship to zebra mussel growth, survival, and reproduction. We created multiple boater movement networks consisting of lake nodes and connecting roadway edges. Each network represented the potential connectivity of lakes for recreational users depending on the maximum roadway distance boaters were likely to travel. We evaluated three different maximum roadway distances based on boater movement surveys: 95% of boaters traveled within 363 km, 75% traveled within 125 km, and 50% traveled within 51 km. We recorded centrality measures of graph analysis, to help identify lakes critical to the spread of zebra mussels by acting as hubs (i.e., degree score), stepping stones (i.e., betweenness centrality), or cutpoints. We also documented each lake's infestation status as of March 2024.

In 2020, with generous funding from the National Lottery Heritage Fund, Ulster Wildlife, National Trust NI, RSPB NI and Woodland Trust NI came together to start building capacity to deliver Nature Recovery Networks in Northern Ireland. As part of the project, habitat networks maps were produced for all terrestrial and intertidal priority habitats, based on the Natural England (Edwards et al., 2020) methodology. The habitat networks comprise vector datasets that map areas of land into different network categories, based on how favourable the land is for restoration to, or creation of the priority habitat, and how effective actions in each area would be at enhancing connectivity of the priority habitat, based on proximity to existing habitat patches. A description of these network categories is provided in Table 1 in the methodology report, available at https://www.ulsterwildlife.org/sites/default/files/2022-10/EnvSys%20NI%20NRN%20mapping%20report.pdf. The habitat network maps do not represent a fully comprehensive depiction of land cover, nor do they provide specific land management options and do not therefore replace the need for an on-site ecological surveys/appraisals. The maps are intended to function as a decision-support tool alongside other pieces of information, both from on-site surveys and data from other sources.

Visual survey community data for Lake Tanganyika's littoral fish species. Surveys represent underwater visual surveys undertaken at depths of 5 and 10 metres within the littoral habitat. Surveys were undertaken across 21 sites with ten surveys undertaken at each site. Surveys were undertaken within 2016 and 2017. For further information including survey design and site GPS locations see:Doble C. J, Hipperson H, Salzburger W, Horsburgh G, Mwita C, Murrell D. J and Day J. J. (Accepted) Testing the performance of environmental DNA metabarcoding for surveying highly diverse tropical fish communities: A case study from Lake Tanganyika. Environmental DNA

This document contains information about Buckley lake habitat quality. Information recorded includes physical, chemical, temperature, oxygen, obstruction and pollutions, stocking, access, and habitation data. Maps and images are also included.

Lakes (taken from the Ordnance Survey MasterMap Topography layer hydrology/static water) that meet one or more priority habitat criteria.More detailed metadata description to follow.Full metadata can be viewed on data.gov.uk.

Realized thermal niche and habitat use are two conceptualizations of fish habitat based on organismal performance or lake-specific ecology, respectively. Both habitat types were compared for lake trout (Salvelinus namaycush) and brook trout (S. fontinalis) co-occurring in four large (> 500 ha) oligotrophic lakes. Lakes were partitioned into two morphological categories based on possession of a central or non-central deep basin with corresponding differences in adjoining shelf areas. Lake asymmetry in basin location has been shown to strongly influence food web connections based on isolation of basins from shelf areas. Generally, overlap between both habitat types occurred in several comparisons with lake trout, suggesting that thermal habitat is a reasonable proxy for habitat use boundaries though not a full replacement for insights gained from habitat use models. For brook trout, overlap was not as consistent, especially for lakes with non-central basins. In central basin lakes, the..., Data are from one-hour set duration benthic gill-netting depth stratified randomized netting surveys conducted in four large lakes in Algonquin Provincial Park using standard North American large-mesh gillnets. Surveys were conducted during periods of thermal stratification (July-August) in the daytime. Each site was sampled at least three times during a survey. Lake volumes for hypsographic data were derived from digital bathymetric surveys conducted by Harkness Lab staff. ArcGIS software was used to calculate lake volume at 1 metre resolution from the digital bathymetry rasters. Temperature and DO profiles were collected mid-basin in each lake during the netting surveys. , Data and code to replicate the occupancy and overlap analysis and figures are provided in .Rdata files and can be opened in the R Statistical computing language. Analysis code is provided as .R scripts and is commented. .R files can be opened in any R editor, but are best viewed in RStudio. .Rdata files can be opened in any instance of R. Files are provided in a compressed file containing all files to replicate the analysis found in the paper. To recreate the hypsographic figure lake volume data is provided in a .csv file and lake outlines and contours in a .gpkg file. Both of these can be opened in code provided in a .R file which can be used in R or RStudio.

THIS MAP IS NOT AUTHORITATIVE. SEE TERMS OF USE BELOW.This web map was developed by the National Oceanic and Atmospheric Administration’s (NOAA) Office for Coastal Management and is featured in the U.S. Great Lakes Collaborative Benthic Habitat Mapping Common Operating Dashboard in support of the Collaborative Benthic Habitat Mapping in the Nearshore Waters of the Great Lakes Basin Project. This multi-year, multi-agency project is funded through the Great Lakes Restoration Initiative (GLRI) and focuses on new bathymetric data (airborne lidar and vessel based sonar) acquisition, validation, and benthic habitat characterization mapping of the nearshore waters (0-80 meters) in the U.S. Great Lakes. This project also contributes to the regional Lakebed 2030 campaign, which aims to have high-density bathymetric data available for the entirety of the Great Lakes by 2030. This web map contains data layers reflecting the current status of bathy data coverage in the nearshore (0-80 meters) of the U.S. Great Lakes, including acquisition (lidar and multibeam sonar), ground-truthing/validation, and benthic habitat mapping and characterization. Acquisition layers include coverage areas that have been acquired and are available for public use (green) as well as those that have been acquired, but are not yet available or are still in progress (orange). The nearshore water depth layers (0-25 and 25-80 meters) were created using the National Centers for Environmental Information (NCEI) Great Lakes Bathymetry (3-second resolution) grid extracts. The 0 to 25 meter nearshore water depth layer represents areas where bathymetric lidar data acquisition could ideally be conducted, depending on water condition and turbidity. The 25 to 80 meter layer shows locations where acoustic data acquisition can occur. See below for information on additional data layers. All data originally projected in the following coordinate system: EPSG:3175, NAD 1983 Great Lakes and St Lawrence Albers.This map will continue to be updated as new information is made available.Source Data for Bathy Coverage Layers - Acquired/Available:Topobathy and Bathy Lidar (NOAA's Data Access Viewer: https://coast.noaa.gov/dataviewer/#/; U.S. Interagency Elevation Inventory (USIEI): https://coast.noaa.gov/inventory/). Multibeam Sonar (National Centers for Environmental Information (NCEI) Bathymetric Data Viewer: https://www.ncei.noaa.gov/maps/bathymetry/; NOAA's Data Access Viewer: https://coast.noaa.gov/dataviewer/#/; U.S. Interagency Elevation Inventory (USIEI): https://coast.noaa.gov/inventory/; USGS ScienceBaseCatalog: https://www.sciencebase.gov/catalog/item/656e229bd34e7ca10833f950)Source Data for Bathy Coverage Layers - GLRI AOIs (2020-2024):Acquisition: NOAA Office for Coastal ManagementValidation/CMECS Characterizations: NOAA National Centers for Coastal Ocean Science (NCCOS)Source Data for Bathy Coverage Layers - In Progress and Planned:NOAA Office of Coast Survey Plans: https://gis.charttools.noaa.gov/arcgis/rest/services/Hydrographic_Services/Planned_Survey_Areas/MapServer/0NOAA Office for Coastal ManagementSource Data for Nearshore Water Depths:NOAA's National Centers for Environmental Information (NCEI) Great Lakes Bathymetry (3-second resolution) grid extracts: https://www.ncei.noaa.gov/maps/grid-extract/Source Data for Spatial Prioritization Layers:Great Lakes Spatial Priorities Study Results Jun 2021. https://gis.charttools.noaa.gov/arcgis/rest/services/IOCM/GreatLakes_SPS_Results_Jun_2021/MapServerMapping priorities within the proposed Wisconsin Lake Michigan National Marine Sanctuary (2018). https://gis.ngdc.noaa.gov/arcgis/rest/services/nccos/BiogeographicAssessments_WILMPrioritizationResults/MapServerThunder Bay National Marine Sanctuary Spatial Prioritization Results (2020). https://gis.ngdc.noaa.gov/arcgis/rest/services/nccos/BiogeographicAssessments_TBNMSPrioritizationResults/MapServerSource Data for Supplemental Data Layers:International Boundary Commission U.S./Canada Boundary (version 1.3 from 2018): https://www.internationalboundarycommission.org/en/maps-coordinates/coordinates.phpNational Oceanic and Atmospheric Administration (NOAA) HydroHealth 2018 Survey: https://wrecks.nauticalcharts.noaa.gov/arcgis/rest/services/Hydrographic_Services/HydroHealth_2018/ImageServerNational Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas (MPA) Inventory 2023-2024: https://www.fisheries.noaa.gov/inport/item/69506National Oceanic and Atmospheric Administration (NOAA) National Marine Sanctuary Program Boundaries (2021): https://services2.arcgis.com/C8EMgrsFcRFL6LrL/arcgis/rest/services/ONMS_2021_Boundaries/FeatureServerNational Oceanic and Atmospheric Administration (NOAA) U.S. Bathymetry Gap Analysis: https://noaa.maps.arcgis.com/home/item.html?id=4d7d925fc96d47d9ace970dd5040df0aU.S. Environment Protection Agency (EPA) Areas of Concern: https://services.arcgis.com/cJ9YHowT8TU7DUyn/arcgis/rest/services/epa_areas_of_concern_glahf_viewlayer/FeatureServerU.S. Geological Survey (USGS) Great Lakes Subbasins: https://www.sciencebase.gov/catalog/item/530f8a0ee4b0e7e46bd300dd Latest update: February 20, 2025