Water sample data collected and curated by Ohio State University's Stone Laboratory and others between 2013 and 2024 in Lake Erie. The samples were collected in part of several projects funded by various state (Ohio EPA and Ohio Sea Grant) and federal agencies (US EPA, NSF, NIH, NOAA). The program column describes who or why the samples were collected. The captains program is a partnership between Stone Lab and the Lake Erie Charter Boat Association in which the captains collect water samples and Stone Lab analyzes them (https://ohioseagrant.osu.edu/products/4c0k6/charter-boat-captains-help-monitor-lake-erie-water-quality). The SL Buoy program is a high temporal resolution dataset of grab samples paired with a high temporal resolution sonde data attached to a buoy (https://doi.org/10.1007/s11356-018-2612-z). The HABs Grab were high spatial resolution samples collected on two days during peak blooms of 2018 and 2019 (https://doi.org/10.1016/j.hal.2021.102080). The flow-through program was an attempt to collect water quality data throughout the winter by pumping lake water into the research building at Stone Lab. Programs Stone Lab and UToledo were samples collected by Stone Lab and UT Lake Erie Center from research vessels at routinely monitored locations. Samples were analyzed for chlorophyll a (an indicator of algae biomass), microcystins (a group of toxins produced by cyanobacteria), total phosphorus and nitrogen (indicators of maximum biomass potential), dissolved nitrate, phosphate, and silicate (nutrients available for algae), and total suspended solids (mass of all particulates in the water).

In 2015-2018, the U.S. Geological Survey (USGS) in cooperation with the U.S. Environmental Protection Agency Great Lakes Restoration Initiative investigated the biodegradation of microcystins in source waters and sand filters from drinking-water plants in the Western Lake Erie Basin. Four source waters and three sand filtrate samples were collected from the intakes and sand filters of Lake Erie drinking-water plants and transported to the USGS Ohio Water Microbiology Laboratory, where investigators set up microcosms to enrich for and identify indigenous bacteria capable of degrading microcystins. Quality control samples were set up in the microcosms to check analyses and included positive controls, negative controls, and replicates. Microcystin biodegradation was quantified by the disappearance of the toxin as compared to control cultures in microcosm and microplate experiments, and by the presence of a gene within microcystin-degrading bacteria that encodes for an enzyme involved in the initial steps of biodegradation. Bacteria were isolated from microcosms enriched with microcystin-LR (MC-LR) and MC-LR concentrations were measured over time by ELISA (table 1). Isolates were selected from the microcosm experiments for further growth testing in microplate experiments with various enrichment media and MC-LR over 96 hours (table 2). Biofilm formation potential for the isolates were also measured and data is shown in table 3. Isolate absorbances of ten potential microcystin degraders were incubated in a microplate with MC-LR as the sole carbon source (table 4) and concentrations of MC-LR in microplate wells were measured over time (table 5).

In 2015-2018, the U.S. Geological Survey (USGS) in cooperation with the U.S. Environmental Protection Agency Great Lakes Restoration Initiative investigated the biodegradation of microcystins in source waters and sand filters from drinking-water plants in the Western Lake Erie Basin. Four source waters and three sand filtrate samples were collected from the intakes and sand filters of Lake Erie drinking-water plants and transported to the USGS Ohio Water Microbiology Laboratory, where investigators set up microcosms to enrich for and identify indigenous bacteria capable of degrading microcystins. Quality control samples were set up in the microcosms to check analyses and included positive controls, negative controls, and replicates. Microcystin biodegradation was quantified by the disappearance of the toxin as compared to control cultures in microcosm and microplate experiments, and by the presence of a gene within microcystin-degrading bacteria that encodes for an enzyme involved in the initial steps of biodegradation. Bacteria were isolated from microcosms enriched with microcystin-LR (MC-LR) and MC-LR concentrations were measured over time by ELISA (table 1). Isolates were selected from the microcosm experiments for further growth testing in microplate experiments with various enrichment media and MC-LR over 96 hours (table 2). Biofilm formation potential for the isolates were also measured and data is shown in table 3. Isolate absorbances of ten potential microcystin degraders were incubated in a microplate with MC-LR as the sole carbon source (table 4) and concentrations of MC-LR in microplate wells were measured over time (table 5).

Spatial reconnaissance of fluvial microcystins (MC) concentrations and select water-quality parameters, including nutrients and periphyton biomass, in 75 wadeable streams in the Piedmont region of the southeastern USA during 2014. Data set includes only those data specifically discussed in the associated journal article: Loftin, K.A., Clark, J.M., Journey, C.A., Kolpin, D.W., Van Metre, P.C., and Bradley, P.M., 2016, Spatial and temporal variation in microcystins occurrence in wadeable streams in the southeastern USA: Environmental Toxicology and Chemistry, http://dx.doi.org/10.1002/etc.3391.

Spatial reconnaissance of fluvial microcystins (MC) concentrations and select water-quality parameters, including nutrients and periphyton biomass, in 75 wadeable streams in the Piedmont region of the southeastern USA during 2014. Data set includes only those data specifically discussed in the associated journal article: Loftin, K.A., Clark, J.M., Journey, C.A., Kolpin, D.W., Van Metre, P.C., and Bradley, P.M., 2016, Spatial and temporal variation in microcystins occurrence in wadeable streams in the southeastern USA: Environmental Toxicology and Chemistry, http://dx.doi.org/10.1002/etc.3391.

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 a cyanotoxin, microcystin, in recreational and drinking waters used by the public. Real-time models include easily- or continuously-measured factors that do not require that a sample be collected. Real-time models are presented in two categories: (1) six models with continuous monitor data, and (2) three models with on-site measurements. Real-time models commonly included variables such as phycocyanin, pH, specific conductance, and streamflow or gage height. Many of the real-time factors were averages over time periods antecedent to the time the microcystin sample was collected, including water-quality data compiled from continuous monitors. Comprehensive models use a combination of discrete sample-based measurements and real-time factors. Comprehensive models were useful at some sites with lagged variables (< 2 weeks) for cyanobacterial toxin genes, dissolved nutrients, and (or) N to P ratios. Comprehensive models are presented in three categories: (1) three models with continuous monitor data and lagged comprehensive variables, (2) five models with no continuous monitor data and lagged comprehensive variables, and (3) one model with continuous monitor data and same-day comprehensive variables. Funding for this work was provided by the Ohio Water Development Authority and the U.S. Geological Survey Cooperative Water Program.

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 a cyanotoxin, microcystin, in recreational and drinking waters used by the public. Real-time models include easily- or continuously-measured factors that do not require that a sample be collected. Real-time models are presented in two categories: (1) six models with continuous monitor data, and (2) three models with on-site measurements. Real-time models commonly included variables such as phycocyanin, pH, specific conductance, and streamflow or gage height. Many of the real-time factors were averages over time periods antecedent to the time the microcystin sample was collected, including water-quality data compiled from continuous monitors. Comprehensive models use a combination of discrete sample-based measurements and real-time factors. Comprehensive models were useful at some sites with lagged variables (< 2 weeks) for cyanobacterial toxin genes, dissolved nutrients, and (or) N to P ratios. Comprehensive models are presented in three categories: (1) three models with continuous monitor data and lagged comprehensive variables, (2) five models with no continuous monitor data and lagged comprehensive variables, and (3) one model with continuous monitor data and same-day comprehensive variables. Funding for this work was provided by the Ohio Water Development Authority and the U.S. Geological Survey Cooperative Water Program.

From August 2018 to October 2019, the U.S. Geological Survey collected high-resolution spatial water quality from a total of five shoreline synoptic surveys conducted around the perimeters of Owasco Lake, Seneca Lake, and Skaneateles Lake within the Finger Lakes Region. Water-quality data were collected just below water surface utilizing YSI EXO2 multiparameter sondes and portable nitrate sensors paired with real-time GPS data collection as part of an Advanced HABs Monitoring Program in the Finger Lakes Region. In October 2019, water-quality data collection was paired with discrete phytoplankton grab samples on Owasco Lake and Seneca Lake. Phytoplankton grab samples were collected just below water surface with a peristaltic pump at twelve unique locations on each of the two lakes.

From August 2018 to October 2019, the U.S. Geological Survey collected high-resolution spatial water quality from a total of five shoreline synoptic surveys conducted around the perimeters of Owasco Lake, Seneca Lake, and Skaneateles Lake within the Finger Lakes Region. Water-quality data were collected just below water surface utilizing YSI EXO2 multiparameter sondes and portable nitrate sensors paired with real-time GPS data collection as part of an Advanced HABs Monitoring Program in the Finger Lakes Region. In October 2019, water-quality data collection was paired with discrete phytoplankton grab samples on Owasco Lake and Seneca Lake. Phytoplankton grab samples were collected just below water surface with a peristaltic pump at twelve unique locations on each of the two lakes.

From August 2018 to October 2019, the U.S. Geological Survey collected high-resolution spatial water quality from a total of five shoreline synoptic surveys conducted around the perimeters of Owasco Lake, Seneca Lake, and Skaneateles Lake within the Finger Lakes Region. Water-quality data were collected just below water surface utilizing YSI EXO2 multiparameter sondes and portable nitrate sensors paired with real-time GPS data collection as part of an Advanced HABs Monitoring Program in the Finger Lakes Region. In October 2019, water-quality data collection was paired with discrete phytoplankton grab samples on Owasco Lake and Seneca Lake. Phytoplankton grab samples were collected just below water surface with a peristaltic pump at twelve unique locations on each of the two lakes.