Assessing the distribution and abundance of both predator and prey (forage) fish species is a cornerstone of ecosystem-based fishery management and supports decision making that considers food-web interactions. In support of binational Great Lakes fishery management, the objectives of this survey were to: provide estimates of densities of key forage and predator species in the western basin of Lake Erie, to assess seasonal and spatial distributions of fishes in tandem with water quality information, and to assess year class strength. A systematic grid sampling approach with 41 stations was sampled via bottom trawl during June (Spring) and September (Autumn), starting in 2013. This data release adds 2024 data to the set for a total of twelve years observation using the same gear and sampling design.

The Lake Erie Ecological Investigations (LEEI) dataset, housed at the Great Lakes Science Center (GLSC) was developed during a reevaluation of Lake Erie Areas of Concern (AOCs) from 1998-2000. These AOCs were recognized as such by the International Joint Commission (IJC) of the United States and Canada due to their severe water pollution problems. The dataset includes data from both the 1998-2000 reevaluation as well as data from other historical evaluations from the 1980’s to mid-1990’s for comparison where available. Data Description: Rivers and harbors of the Great Lakes have been impacted for decades by heavy industrialization, densely populated areas, and agriculture resulting in contamination, eutrophication, and physical degradation of these ecological areas. Focusing on designated AOCs, such as the Detroit, Cuyahoga, and Black Rivers in Michigan and Ohio, USGS scientists and collaborators gathered data in these evaluations to provide evidence of effects on aquatic biota. ...

Blooms of nuisance and toxic cyanobacteria, referred to as cyanobacteria harmful algal blooms (cHABs), occur annually in Lake Erie and pose a threat to human health, affect the quality of life, and significantly degrade the ecosystem. NOAA Great Lakes Environmental Research Laboratory and the Cooperative Institute for Great Lakes Research (CIGLR), University of Michigan, started regular water quality monitoring of the western basin of Lake Erie in 2012. Since that time the monitoring effort has expanded to incorporate additional parameters and sample locations.

Physical, chemical, and biological water quality data were collected during repeated weekly sampling trips to a set of stations before, during, and after HAB events (from May - October). Data for these discrete sampling events include: wind speed, wave height, secchi depth, sample temperature, Conductivity, Temperature and Depth (CTD) Sonde temperature, CTD specific conductivity, CTD beam attenuation, CTD transmission, CTD dissolved oxygen, CTD photosynthetically active radiation, turbidity, particulate microcystin, dissolved microcystin, extracted phycocyanin, extracted chlorophyll-a, total phosphorus, total dissolved phosphorus, soluble reactive phosphorus, ammonia, nitrate + nitrite, urea, particulate organic carbon, particulate organic nitrogen, dissolved organic carbon, colored dissolved organic material absorbance at 400 nm, total suspended solids, and volatile suspended solids. The bulk water quality parameters were analyzed via established techniques and procedures for routine water quality monitoring and analysis (APHA 1992, 1998, 2017).

In 2014, CIGLR deployed moored buoys to collect real-time physical, chemical, and biological water quality data during the summer season. There are now four moored buoys deployed during the open water season in western Lake Erie that collect in situ data for the following parameters, average wind speed, maximum wind speed, air temperature, barometric pressure, depth, water temperature, specific conductivity, pH, turbidity, dissolved oxygen, chlorophyll-a, phycocyanin, dissolved organic matter, nitrate, and phosphate.

Spring (March-July) phosphorus loads, loading targets and discharge for priority Lake Erie tributaries from 2008-2020. Includes both total phosphorus (TP) and soluble reactive phosphorus (SRP) as well as flow-weighted mean concentrations (FWMC) for both. The U.S. and Canada set phosphorus reduction goals (40 percent of 2008 loads) for eight priority tributary watersheds for both total and soluble reactive phosphorus (SRP) during March-July. SRP refers to phosphorus that is in a dissolved state and is of particular interest because it is the easiest form of phosphorus for algae to use to fuel growth. The targets for these tributaries are expressed in terms of the flow weighted mean concentration (FWMC), which is a way to normalize the load for varying flow conditions. This is important because much of the load is delivered during storm events. It means that efforts to reduce the load must also include efforts to reduce the amount of flow (runoff). FWMC also provides an important backstop and relative measure of whether phosphorus control efforts are actually having an impact. For example, in a dry year, the load may be low due to less runoff, but the FWMC will still be high if the proportion of phosphorus in that runoff is high. The calculation of spring load requires high frequency flow and water quality monitoring, which is now in place for all nearshore priority tributaries. Not all tributaries had monitoring in place going back to 2008.

Lake Erie Center for Fresh Waters and Human Health

The Lake Erie Center for Fresh Waters and Human Health is a five-year, multi-institutional effort aimed at understanding the environmental factors and ongoing changes that influence the growth and toxicity of cyanobacterial harmful algal blooms (cHABs) in Lake Erie. The Center will support three research projects. Specifically these projects address the following aims: first, how environmental cues promote or constrain the proliferation of cHAB species in mixed populations; second, how environmental cues influence toxin production by cHAB species; third, how other member of the microbial assemblage influence cHAB growth and toxicity. The Center will provide a Community Engagement Core to lead outreach activities that will inform the general public on the effects of cHABs by efforts that include: (1) a community engaged scholarship training for scientists associated with the Center, (2) community-engaged scholarship training for practitioners or community members associated with the Center, and (3) a stakeholder needs assessment for Great Lakes and environmental health literacy to inform general outreach information needs. A citizen science engagement with charter boat captains will further develop a near real-time database on cHAB severity in Lake Erie, and the Facilities Core will provide metadata that not only serve the three stated research projects, but also yield a database available to all Great Lakes scientists. The outcomes are to involve community stakeholders and researchers in the Great Lakes on issues regarding human health, climate change and awareness of threats to our fresh water resources.

Water quality monitoring data collected in priority tributaries to provide nutrient concentration data to estimate nutrient loads to the waters of the Great Lakes. Data is collected to advance the science to understand and address the complex problem of recurrent toxic and nuisance algae in the Great Lakes. The majority of the data is focused on Lake Erie, the smallest, shallowest of the Great Lakes, and most susceptible to nearshore water quality issues. Water quality monitoring is conducted to establish current nutrient loadings from selected Canadian tributaries; to enhance the knowledge of the factors that affect tributary and nearshore water quality, ecosystem health, and algae growth; to establish binational lake ecosystem objectives, phosphorus objectives, and phosphorous load reduction targets, and to support the development of a binational nearshore assessment and management framework.

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 for the three parameters TP, SRP, and TN. For the water-quality parameter SRP, monitoring data and trend results were available for 6 of the 10 trend sites. Daily streamflow trends were evaluated for the time-period 1987-2016 at 9 of the study sites, applied as clim ...

The dataset include hydroclimate and ambient environmental as the input data and Cyanobacterial HABs Index (CI) calculated from satellite imageries as the output data altogether used to train and validate three data-driven (machine learning) models and their Ensemble Average (AE) to predict HABs cell count in southwest Lake Erie. The data also include HABs volumetric and areal concentrations obtained from literature and used in conjunction with the CI calculated from satellite data to develop statistical regression models for use to convert model predicted CI values (cell counts) to volumetric/areal concentrations of HABs.

This dataset contains a tabular file of phytoplankton abundance and community composition analysis in samples collected from two sites in the Western Lake Erie Basin and one inland lake site in northeast Ohio. Samples were processed by the Ohio Water Microbiology Lab of the U.S. Geological Survey (USGS) and analyzed by BSA Environmental Inc. and during federal fiscal years 2016-2018. The dataset includes phytoplankton taxa (genus and species), division, tally (number of cells counted for each taxa present), density (cells per liter), and total biovolume (cubic micrometers per liter) for each sample collected. These data can be used to assess the community composition of phytoplankton at the sites, identify cyanobacteria species, and determine abundance and biovolume of any known toxin-producing cyanobacteria. The data were part of a larger study, "Predicting microcystin concentration action-level exceedances resulting from cyanobacterial blooms in selected lake sites in Ohio", in which site-specific multiple linear regression models were developed for eight sites in Ohio−six in the Western Lake Erie Basin and two in northeast Ohio on inland reservoirs−to quickly predict action-level exceedances for microcystin, a cyanotoxin commonly found in freshwaters, in recreational and drinking waters used by the public.

This feature class resides within the SOCECON Feature Data Set of the Lake Erie 2022 ESI Geodatabase. It contains vector points representing Navigational/marine human-use resource data for the Lake Erie System and adjacent lands and waters. The study area includes the United States portion of Lake Erie, covering the coastal portions of Ohio, Pennsylvania, and New York from the Michigan/Ohio bo...

A bathymetric layer for Lake Erie. NOAA is engaged in a program to compile Great Lakes bathymetric data and make them readily available to the public, especially to the communities concerned with Great Lakes science, pollution, coastal erosion, response to climate changes, threats to lake ecosystems, and health of the fishing industry. This program is managed by NGDC and it relies on the cooperation of NOAA/Great Lakes Environmental Research Laboratory, NOAA/National Ocean Service, the Canadian Hydrographic Service, other agencies, and academic laboratories. Compilation of new bathymetry for the Great Lakes is an important part of this program, being carried out cooperatively between NOAA (NGDC and GLERL), and the Canadian Hydrographic Service. This new bathymetry provides a more detailed portrayal of lakefloor topography, and reveals some lakefloor features seen for the first time.Date: 2006-11-08

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.

These feature classes reside within the SOCECON Feature Data Set of the Lake Erie 2022 ESI Geodatabase. They contain vector polygons and points representing Resource management human-use resource data for Lake Erie and adjacent lands and waters. The study area includes the United States portion of Lake Erie, covering the coastal portions of Ohio, Pennsylvania, and New York from the Michigan/Oh...

Among the Great Lakes, Lake Erie was the shallowest, with an average depth of ** meters. In comparison, Lake Superior, the deepest of these five lakes, accounted for an average depth of around *** meters.

This dataset contains annual algal bloom indices (duration, extent, intensity, severity) summary statistics (maximum, mean) over the June through October monitoring period for Lake Erie. These data are derived from satellite remote sensing algorithms using European Space Agency's (ESA's) MEdium Resolution Imaging Spectrometer (MERIS) sensor on the Envisat satellite (2002-2012) and ESA's Ocean and Land Colour Instrument (OLCI) sensor on the Sentinel 3A and Sentinel 3B satellites (2016-present). At the end of each monitoring season, data are presented in annual report format including current and historical summary statistics of algal bloom indices, alongside relevant imagery. Citation: Binding, C.E., Pizzolato, L., & Zeng, C. (2021). EOLakeWatch; delivering a comprehensive suite of remote sensing algal bloom indices for enhanced monitoring of Canadian eutrophic lakes. Ecological Indicators, 121, 106999. doi:10.1016/j.ecolind.2020.106999

Winter survey data from Lake Erie collected on USCGC NEAH BAY and CCGS Limnos during 2018 and 2019. access_formats=.htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt acquisition_description=See attached Supplemental File "Study Plan for the U.S. Coast Guard Survey of Lake Erie in Winter 2019". awards_0_award_nid=751268 awards_0_award_number=OCE-1840715 awards_0_data_url=http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1840715 awards_0_funder_name=NSF Division of Ocean Sciences awards_0_funding_acronym=NSF OCE awards_0_funding_source_nid=355 awards_0_program_manager=Henrietta N Edmonds awards_0_program_manager_nid=51517 cdm_data_type=Other comment=Lake Erie Winter Surveys 2018-2019 PI: George Bullerjahn (Bowling Green State University) Co-PIs: Robert Michael McKay (Great Lakes Institute for Environmental Research University of Windsor) Version date: 24 April 2020 Conventions=COARDS, CF-1.6, ACDD-1.3 data_source=extract_data_as_tsv version 2.3 19 Dec 2019 dataset_current_state=Final and no updates defaultDataQuery=&time<now doi=10.26008/1912/bco-dmo.809945.1 Easternmost_Easting=-81.653888 geospatial_lat_max=41.95 geospatial_lat_min=41.519166 geospatial_lat_units=degrees_north geospatial_lon_max=-81.653888 geospatial_lon_min=-83.15 geospatial_lon_units=degrees_east geospatial_vertical_max=10.0 geospatial_vertical_min=1.0 geospatial_vertical_positive=down geospatial_vertical_units=m infoUrl=https://www.bco-dmo.org/dataset/809945 institution=BCO-DMO instruments_0_acronym=TD-700 instruments_0_dataset_instrument_nid=810618 instruments_0_description=The TD-700 Laboratory Fluorometer is a benchtop fluorometer designed to detect fluorescence over the UV to red range. The instrument can measure concentrations of a variety of compounds, including chlorophyll-a and fluorescent dyes, and is thus suitable for a range of applications, including chlorophyll, water quality monitoring and fluorescent tracer studies. Data can be output as concentrations or raw fluorescence measurements. instruments_0_instrument_external_identifier=https://vocab.nerc.ac.uk/collection/L22/current/TOOL0510/ instruments_0_instrument_name=Turner Designs 700 Laboratory Fluorometer instruments_0_instrument_nid=694 instruments_0_supplied_name=TD-700 fluorometer instruments_1_acronym=Stainless Steel Sampling Bottle instruments_1_dataset_instrument_description=Near-surface water is collected using a stainless steel sampling bottle. This approach has been adopted rather than use of Go-Flo bottles to accommodate working in ice. instruments_1_dataset_instrument_nid=810619 instruments_1_description=A stainless steel sampling bottle used for collecting near surface samples (not a GO-FLO bottle) instruments_1_instrument_name=Stainless Steel Sampling Bottle instruments_1_instrument_nid=722 instruments_1_supplied_name=stainless steel sampling bottle keywords_vocabulary=GCMD Science Keywords metadata_source=https://www.bco-dmo.org/api/dataset/809945 Northernmost_Northing=41.95 param_mapping={'809945': {'Lat': 'flag - latitude', 'Sample_Depth': 'flag - depth', 'long': 'flag - longitude', 'ISO_DateTime_UTC': 'flag - time'}} parameter_source=https://www.bco-dmo.org/mapserver/dataset/809945/parameters people_0_affiliation=Bowling Green State University people_0_affiliation_acronym=BGSU people_0_person_name=George S. Bullerjahn people_0_person_nid=51464 people_0_role=Principal Investigator people_0_role_type=originator people_1_affiliation=University of Windsor people_1_person_name=Robert Michael McKay people_1_person_nid=51463 people_1_role=Co-Principal Investigator people_1_role_type=originator people_2_affiliation=Woods Hole Oceanographic Institution people_2_affiliation_acronym=WHOI BCO-DMO people_2_person_name=Shannon Rauch people_2_person_nid=51498 people_2_role=BCO-DMO Data Manager people_2_role_type=related project=Great Lakes Center projects_0_acronym=Great Lakes Center projects_0_description=NSF Award Abstract: The Lake Erie Center for Fresh Waters and Human Health is a five-year, multi-institutional effort aimed at understanding the environmental factors and ongoing changes that influence the growth and toxicity of cyanobacterial harmful algal blooms (cHABs) in Lake Erie. The Center will support three research projects. Specifically these projects address the following aims: first, how environmental cues promote or constrain the proliferation of cHAB species in mixed populations; second, how environmental cues influence toxin production by cHAB species; third, how other member of the microbial assemblage influence cHAB growth and toxicity. The Center will provide a Community Engagement Core to lead outreach activities that will inform the general public on the effects of cHABs by efforts that include: (1) a community engaged scholarship training for scientists associated with the Center, (2) community-engaged scholarship training for practitioners or community members associated with the Center, and (3) a stakeholder needs assessment for Great Lakes and environmental health literacy to inform general outreach information needs. A citizen science engagement with charter boat captains will further develop a near real-time database on cHAB severity in Lake Erie, and the Facilities Core will provide metadata that not only serve the three stated research projects, but also yield a database available to all Great Lakes scientists. The outcomes are to involve community stakeholders and researchers in the Great Lakes on issues regarding human health, climate change and awareness of threats to our fresh water resources. The Center is jointly supported by NSF and by the National Institute for Environmental Health Sciences (NIEHS). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. projects_0_end_date=2023-09 projects_0_geolocation=Laurentian Great Lakes projects_0_name=Lake Erie Center for Fresh Waters and Human Health projects_0_project_nid=751269 projects_0_project_website=https://www.bgsu.edu/great-lakes-center.html projects_0_start_date=2018-10 sourceUrl=(local files) Southernmost_Northing=41.519166 standard_name_vocabulary=CF Standard Name Table v55 subsetVariables=Snow_cover time_coverage_start=2019-02-26T21:15:00Z version=1 Westernmost_Easting=-83.15 xml_source=osprey2erddap.update_xml() v1.5

Lake Erie Ice - Physico-Chemical Data - Winter 2012, 2013, 2016

For additional information see:
Collecting Winter Data on U.S. Coast Guard Icebreakers
Study Plan for the U.S. Coast Guard Survey of Lake Erie in Winter 2011-12
Study Plan for the U.S. Coast Guard Survey of Lake Erie in Winter 2012-13
Study Plan for the Canadian Coast Guard Survey of Lake Erie in Winter 2012-13
Study Plan for the Canadian Coast Guard Survey of Lake Erie in Winter 2016
Study Plan for the US Coast Guard Survey of Lake Erie in Winter 2016.

Blooms of filamentous benthic algae that plagued Lake Erie in the 1950s through 1970s were largely reduced through reductions of phosphorus (P) loading from point sources. Since the mid-1990s, these blooms have returned despite a period of relatively stable external P inputs. While increased loadings of dissolved P have been causally linked to cyanobacterial blooms in some parts of the lake, the impacts of ecosystem changes such as the effect of invasive species on nutrient cycling and availability have not been fully elucidated, leading to uncertainty as to the effectiveness of additional non-point P management actions. Here we use the oxygen isotope ratios (δ18OP) of phosphate in concert with measures of water quality along the northern shore of the east basin of Lake Erie to identify sources and pathways of P cycling and infer potential importance in relation to annual blooms of Cladophora that foul the shorelines of eastern Lake Erie. δ18OP data indicate that potential external source signatures are rapidly overprinted by biological cycling of P by the plankton community and that much of the available phosphate in the nearshore waters is derived from hydrolysis of dissolved organic P compounds. Near the dreissenid-colonized lake bed, δ18OP was persistently and significantly enriched in 18O relative to δ18OP measured in surface waters and was similar to δ18OP of phosphate excreted by dreissenid mussels in incubations. These results implicate dreissenid mussels as key agents in nearshore P cycling and highlight the importance of considering ecosystem changes in the development of nutrient management strategies designed to ameliorate symptoms of eutrophication. For more information and data please visit:https://open.canada.ca/data/en/dataset/4497ebe5-f45e-4b13-9e98-e9edd016fc66 Supplemental Information Phosphorus is the primary nutrient which can cause excessive algal growth in freshwater. In the 1960’s and 70’s excessive nuisance algae, primarily Cladophora, washed up on beaches around the Great Lakes leaving large odiferous piles unaesthetically pleasing to Canadians seeking recreational activities at nearby Great Lake beaches. The first signing of the Great Lakes Water Quality Agreement established a commitment between the US and Canada to address water quality concerns including nuisance algae. One of the primary outcomes of the Great Lakes Water Quality Agreement (GLWQA) was the limiting of phosphorus inputs into the Great Lakes primarily from detergents and thereby decreasing the biomass of Cladophora in the great lakes. However, in the mid-1990s resurgence in Cladophora biomass occurred as well as toxic cyanobacteria blooms. The Great Lakes Nutrient Initiative (GLNI) provides funding to address the complexities of recurring toxic and nuisance algal blooms in the Great Lakes specifically Lake Erie. For more information please visit: https://www.canada.ca/en/environment-climate-change/services/sustainable-development/strategic-environmental-assessment/public-statements/great-lakes-nutrient-initiative.html

This data release contains data and rloadest models used to estimate sediment and nutrient loads in selected New York tributaries to eastern Lake Erie. Load estimates for suspended sediment and nutrients were calculated using rloadest (Lorenz and others, 2013; Runkel and De Cicco, 2017) models. Included are a zip file with input and output files for selected rloadest models for 13 U.S. Geological Survey sites in the eastern Lake Erie Basin. Also included are brief methods and the R-code used to create the models and generate model summaries. Models for total nitrogen, nitrate plus nitrite, total phosphorus, orthophosphate, and suspended sediment were evaluated at each of the 13 sites. Model results that had high bias or non-significant model variables were not considered. In total, 46 rloadest models were created for the 13 sites. Of the 13 sites, rloadest models were created for total phosphorus at 12 sites, total nitrogen at all 13 sites, nitrate plus nitrite at five sites, ammo ...

Climate data from ground-based climate stations obtained from National Climate Data Center and bias corrected climate values from different climate models for different emission scenarios for the entire Western Lake Erie Basin.