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Track Blooms from the Source | Ohio Sea Grant

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Track Blooms from the Source

These projects aim to improve existing technologies and develop new methods to track algal blooms from start to finish, ensuring a healthy environment

Projects in this focus area aim to improve use of existing technologies, as well as develop new methods to detect, prevent and mitigate harmful algal blooms and their impacts. This will help to ensure drinking water safety and a healthy environment for lakeshore residents by connecting many of the potential causes and effects of harmful algal blooms, from the runoff that fuels them to the toxins that contaminate water supplies, to what makes them produce toxins in the first place.

Projects

Exploring What Produces a Potent Algal Toxin in Northern Ohio Lakes

Principal Investigator

Justin Chaffin, The Ohio State University


Project Summary

Scientists know that potent algal toxins called saxitoxins, or STXs, are present in Ohio, but very little is known about what triggers their production. In 2016, the Ohio Environmental Protection Agency found that the cyanobacteria that may produce STXs are in 65% of Ohio’s lakes. Previous data collected by the Ohio EPA suggested that autumn conditions in lakes could be sparking the production of saxitoxins and a “sxtA” gene that indicates their presence.

Researchers studied the environmental factors associated with STX-producing cyanobacteria in Ohio’s lakes to help predict when and where the toxins emerge. They collected data from several inland lakes that are also part of public water systems. They also trained water treatment plant operators to collect samples of pre-treatment water and send them to Stone Lab for analysis of nutrients, algae, cyanotoxins — including STXs — and toxin genes.

The team looked for potential drivers of STX production through monthly laboratory experiments with water collected from the lakes during August, September and October. Researchers studied the effect of increased temperature, nutrient concentrations and light levels on the presence of saxitoxins. They confirmed that cyanobacteria in phytoplankton can produce saxitoxins and release them into Ohio lakes but couldn’t conclude why this occurs.

Despite this uncertainty, the project successfully compared different methods of analyzing the presence of saxitoxins, as previously no single method was known to work well for all toxin analogues. The team investigated the ELISA method previously used by the Ohio EPA as well as a costly liquid chromatography-mass spectrometry test and a receptor-binding assay that measures sample toxicity. Ultimately, the study found that ELISA is a reliable method to measure total saxitoxins. Future analysis of the presence of saxitoxin will help managers make more informed decisions to remove the toxins from water.

The Bottom Line

Harmful algal blooms on Ohio’s lakes can produce saxitoxins, or STXs, which can have potent neurological effects. Researchers confirmed that cyanobacteria in phytoplankton can produce these toxins and found a reliable method to measure their presence. Insights will help public water systems remove these toxins.

How Does Phosphorus Runoff Move Through Rivers and Streams?

Principal Investigator

Jim Hood, The Ohio State University


Project Summary

Scientists know that phosphorus loading from the agriculture-heavy Maumee River watershed is the main cause of harmful algal blooms in Lake Erie’s Western Basin. What’s less known, however, is what effect rivers and streams have on phosphorus as it moves through the watershed. This is a critical knowledge gap: Researchers don’t know whether rivers have a net positive, negative or neutral effect on how phosphorus enters western Lake Erie.

Using a combination of data analysis and on-site surveys, researchers quantified how stream dynamics affect phosphorus runoff in the region. First, they calculated phosphorus mass balances — how much phosphorus was gained or lost — for large river sections using water monitoring data. Preliminary results found that two river reaches upstream of Defiance, Ohio, gained total phosphorus, while the rest on the lower Maumee River lost phosphorus. The team is still working to improve these estimates with more data and modeling, and final results will help to show whether parts of the Maumee River are net sources or sinks of nutrients, primarily phosphorus.

Meanwhile, researchers conducted on-site measurements of phosphorus cycling components during periods of both high flow and low flow in the Maumee watershed. The surveys showed that sediment in the rivers within the watershed is on average more likely to be a phosphorus sink, though it can also be a source. The research is still ongoing and will provide insight into how phosphorus cycling affects nutrient runoff in streams and rivers. Results will help inform management decisions on how to reduce phosphorus runoff to Lake Erie.

The project also resulted in the development of an adapted SWAT — soil and water assessment tool — model to quantify instream phosphorus transformations and determine whether the stream bed is a phosphorus source or sink under different flow and land management conditions. Improvements to the model will help decision-makers understand phosphorus time lags and possible management levers needed to achieve water quality targets. The team also collaborated with Great Lakes Restoration Initiative researchers to test the model in Wisconsin.

The Bottom Line

The effect rivers and streams have on phosphorus runoff as it moves into Lake Erie is a critical knowledge gap. Ongoing research is using data modeling and on-site surveying to quantify how phosphorus moves through the Maumee River watershed. Results will inform decision-makers about whether streams are a source or sink for phosphorus and how to reduce nutrient runoff.

Discovering How Blooms Can Contaminate Groundwater

Principal Investigator

Ganming Liu, Bowling Green State University


Project Summary

While many studies of HABs in the Great Lakes focus on surface water issues, very few investigate the potential for algal toxins to contaminate groundwater. Yet surface water and groundwater interactions do present risks to water wells and human health. To address this significant knowledge gap, researchers studied whether Lake Erie blooms can contaminate groundwater resources and what conditions might facilitate this.

Through a collaboration with The Ohio State University’s Stone Laboratory, researchers collected samples of untreated well water on South Bass Island to look for levels of the algal toxin microcystin. They also designed and conducted flow tank experiments to simulate the toxin’s transport from Lake Erie to water wells. Analysis found that coastal water pumping in these wells reverses groundwater flow and can indeed result in microcystin contamination moving from lake water into water wells.

Researchers further developed a state-of-the-art 3D hydrological model for the entire South Bass Island that simulated microcystin transport processes both above and below ground. Based on the simulation’s results, researchers suggest that wells at high pumping rates located within 100 meters of the shoreline should be regularly monitored and tested during and after HAB events. While wells located beyond 100 meters seem safe, certain conditions such as fractures, higher lake levels and severe bloom events could worsen the contamination risk.

This research has highlighted the ability of this modeling tool to assess the risk of residents’ exposure to algal toxins and can help decision-makers identify and evaluate contamination sources. Such modeling can also aid Ohio managers and officials in replacing well systems along the coast to protect public health.

The Bottom Line

The potential for harmful algal blooms to contaminate groundwater is a significant knowledge gap in Great Lakes research. Researchers used field sampling, lab experiments and a new 3D hydrological model to conclude that the algal toxin microcystin can contaminate water wells. In the future, this modeling tool could provide governmental agencies the ability to evaluate the risk of residents’ exposure to cyanotoxins and other contaminants in their groundwater.

Improving How Satellites Are Used for Harmful Algal Bloom Monitoring

Principal Investigator

Kaiguang Zhao, The Ohio State University


Project Summary

Satellites help scientists monitor harmful algal blooms (HABs) in Ohio each year, yet challenges and limitations abound. Images of blooms do little to inform science and policy until they’re rigorously converted into reliable water quality information. What’s more, no satellites have been designed to specifically monitor water quality on inland lakes. To improve HAB monitoring, researchers sought to improve how existing satellites are used to track water quality over time and across large areas.

The team focused on three aspects of monitoring: satellite data, on-site data and models that relate the two. First, they identified three suitable satellites — two from the European Space Agency and one from NASA and the U.S. Geological Survey — and combined them to leverage strengths and mitigate weaknesses. Next, they compiled publicly available on-site water quality measurements from numerous federal agency databases and The Ohio State University’s Stone Lab. Researchers then created models with new, state-of-the art machine-learning techniques and found intricate relationships between satellite signals and water quality parameters.

The project achieved several successful results. For one, the team’s new satellite-based approaches are significantly more accurate — by a factor of 2 to 20 — than the cyanobacteria index (CI) method currently used for routine monitoring of algal blooms. The researchers’ methods use artificial intelligence to estimate water quality and can complement the existing CI framework. In addition to providing direct benefits to Ohio water quality monitoring, the spatial tools have broad applications in dozens of disciplines. In Australia, two research groups used the tools to measure water quality in local waterbodies. Meanwhile, researchers around the world have already used the team’s tool for analyzing satellite data over time to answer questions in fields such as finance, climate science, political science, epidemiology and cardiology, among others.

The Bottom Line

Researchers developed new tools to monitor harmful algal blooms using satellites. The team’s approaches, which leverage artificial intelligence, are accurate and can complement existing bloom monitoring in Ohio. Notably, the tools are already being used by researchers around the world in a wide range of disciplines.

Evaluation of a Low-Cost In Situ Water Quality Monitoring Network to Assess Physical and Biological Changes in Ohio’s Recreational and Drinking Water Sources

Principal Investigator

Darren Bade, Kent State University


Project Summary

On-site equipment, such as sensors on buoys or other platforms, has been increasingly employed to monitor water quality and harmful algal blooms. Researchers selected monitoring systems developed by three companies to examine in the lab and at three locations in Sandusky Bay to provide side-by-side comparisons in field settings. Finding a surprising lack of congruency among the sensors, the researchers are investigating the reasons, including whether the sensors may need higher frequency of cleaning and servicing due to biofouling. They are sharing their experiences, including design ideas on how to best deploy the sensors to keep them positioned correctly during rough water, with the manufacturers. Another facet of the project involves analyzing a way that the data from sensors like this could be used to generate an automated warning of an impending harmful algal bloom based on ecological theory.

Quantifying the Role of Sediment in Phosphorus Exports From Drainage Networks: Sources, Recency and DRP Interactions

Principal Investigator

Jim Hood, The Ohio State University


Project Summary

The primary cause of Lake Erie’s harmful algal blooms is dissolved reactive phosphorus loading from the Maumee River basin during high flow events between March and July. Researchers are addressing knowledge gaps associated with how sediment composition, source and age influence instream phosphorus cycling. This is relevant to our understanding of what happens to phosphorus as it travels downstream toward Lake Erie. In studies of Black Creek, preliminary data suggests that during low flow, streambed sediment was a phosphorus sink. During high flow events, suspended sediment was a phosphorus sink, with phosphorus binding rates being shaped more strongly by seasonality than discharge. Sediment in transit during different periods of a storm event may be coming from different locations. This information will be useful in evaluating the potential effect of management actions on phosphorus export to downstream habitats such as Lake Erie.

Evaluating the Interactive Effects of Dissolved Organic Matter and Nutrients on Cyanobacteria and Their Toxins

Principal Investigator

Craig Williamson, Miami University


Project Summary

To determine the contributors to cyanobacterial growth, researchers are studying dissolved organic matter in runoff from agriculture fields and wetlands. They tested the effects of this organic matter and inorganic nutrients on natural phytoplankton communities from Maumee Bay, Sandusky Bay and Grand Lake St. Marys. To date, they have found that dissolved organic matter significantly increases the concentration of the cyanobacteria pigment, phycocyanin, which is used to indicate cyanobacteria density. The effect on the cyanobacteria toxin, microcystin, varied by source water, with no change in Maumee and Sandusky Bay waters but a large increase in Grand Lake St. Marys water, and including nutrients amplified that result. Adding dissolved organic matter from manure leachate significantly increased microcystin concentrations in Sandusky Bay and Grand Lake samples. The results of this study will help determine to what extent and how dissolved organic matter should be included in nutrient reduction strategies and implications for monitoring harmful algal blooms with high frequency sensors.