This data set includes qPCR data for the microcystin producing planktothrix (mcyApla) gene and the microcystin producing cyanobacteria (Hep) gene for samples collected from Grand Lake St. Marys and downstream waterways in 2023.

This data set includes qPCR data for the microcystin producing planktothrix (mcyApla) gene and the microcystin producing cyanobacteria (Hep) gene for samples collected from Grand Lake St. Marys and downstream waterways in 2022.

This data set includes qPCR data for the microcystin producing planktothrix (mcyApla) gene and the microcystin producing cyanobacteria (Hep) gene for samples collected from Grand Lake St. Marys and downstream waterways in 2024.

This data set includes flow cytometry data for planktothrix in samples collected from Gran Lake St. Marys and downstream waterways in 2025

This data set includes flow cytometry data for planktothrix in samples collected from Grand Lake St. Marys and downstream waterways in 2024.

This Dataset includes the spatial and temporal quantification of planktothrix cyanobacteria filaments within the canal and river system of St. Mary's, OH for the year 2023.

This Dataset includes the spatial and temporal quantification of planktothrix cyanobacteria filaments within the canal and river system of St. Mary's, OH for the year 2022.

qPCR and RT-qPCR. This dataset is associated with the following publication: Lu, J., I. Struewing, L. Wymer, D. Tettenhorst, J. Shoemaker, and J. Allen. Use of qPCR and RT-qPCR for monitoring variations of microcystin producers and as an early warning system to predict toxin production in an Ohio inland lake. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 170: 115262, (2020).

(1) qPCR and RT-qPCR for cyanotoxin producing genes, and (2) some water quality parameters. This dataset is associated with the following publication: Duan, X., C. Zhang, I. Struewing, X. Li, H. Allen, and J. Lu. Cyanotoxin-encoding genes as powerful predictors of cyanotoxin production during harmful cyanobacterial blooms in an inland freshwater lake: Evaluating a novel early-warning system. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 830: 154568, (2022).

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).