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Researchers take to tech to study toxic cyanobacteria with $1.47M NASA grant

Study will help predict & manage harmful blooms in Northeastern lakes.

With support from a $1.47 million grant from the National Aeronautics and Space Administration (NASA), an interdisciplinary team of researchers from the Cary Institute of Ecosystem Studies, Dartmouth, and the University of New Hampshire are developing high-tech tools to monitor cyanobacteria in lakes, predict impending blooms, and identify factors that are degrading water quality.  

Throughout the Northeast, water quality in lakes is declining due to development, increased population density, and climate change. One of the most persistent symptoms of reduced water quality is the presence of cyanobacteria, often referred to as blue-green algae. Blooms disrupt recreation and can produce toxins that are harmful to fish and people. 

Under the three-year grant, the research team will explore how population growth, land use, climate change, and lake-specific factors have affected water quality in approximately 2,000 lakes in New York, Vermont, New Hampshire, and Maine. To identify patterns and understand relationships between these complex systems, the team will bring together multiple data types collected via satellite, drone, and mobile app.

Cyanobacteria. CC Midge Elliassen
Cyanobacterial bloom on Lake Sunapee, New Hampshire. Credit: Midge Eliassen

Kathleen Weathers, an ecosystem ecologist at the Cary Institute of Ecosystem Studies and co-principal investigator on the study explains, “NASA funding will allow us to tap into the power of both remote sensing and citizen science to better understand, predict, and manage cyanobacterial blooms, which are becoming a real problem in Northeast lakes. Citizens, scientists, lake associations, and management agencies are eager to find solutions.”

David Lutz, an environmental scientist at Dartmouth and the study’s principal investigator notes, “There has been a great deal of research focusing on cyanobacterial blooms in the Midwest and southern states, where nutrient pollution is abundant due to runoff from fertilizer applied to agricultural fields. Much less is known about blooms taking place in the Northeast, where clear-water lakes with lower nutrient concentrations are very valuable, especially as recreational locations and vacation home sites that stimulate nearby economies,” explains Lutz.

Cyanobacteria drone. CC by Michael Palace
The 'Hexcopter', piloted by Michael Palace, Research Associate Professor at the University of New Hampshire, will be flown over lakes to monitor cyanobacteria. Credit: Michael Palace


In this study, remotely-sensed information will come from two sources: satellites and an unmanned aerial system, or drone. The team will mine satellite data on weather conditions and lake water temperature to better understand the influence that these factors have on water quality and cyanobacterial blooms. These long-term data sets will allow the researchers to identify trends spanning several decades.

Closer-to-earth, on a shorter-term scale, a drone equipped with hyperspectral sensors will estimate water clarity and identify cyanobacterial blooms. The drone will be flown four times a year around three focal lakes: Lake Sunapee (New Hampshire), Lake Auburn (Maine), and Great Pond (Maine). These data, which will also include information on lake watersheds, will be coupled with satellite data.

Remotely-sensed information, while increasingly reliable, needs to be verified with on-the-ground sampling. ‘Lake Observer’, a mobile app designed by members of the Global Lake Ecological Observatory Network (GLEON), co-directed by Cary’s Kathleen Weathers, will empower citizen scientists to record data on lakes in their communities. Water quality observations, such as the presence or absence of cyanobacterial blooms, will provide vital insights.

“The Lake Sunapee Protective Association (LSPA) staff, members, and residents around Lake Sunapee have been integrally involved in the research planning and are already enthusiastically contributing to this work as citizen scientists. In addition to LSPA, we’ll be working with other lake associations and management groups throughout the study region to generate citizen interest in sampling lakes with Lake Observer. These data will help us ground-truth information that we collect via drone and satellite imagery,” Weathers says.

“This work highlights the ways that we are merging empirical ‘boats in the water’ sampling techniques and new technologies. By coupling remotely-sense data and physical sampling, and melding this information with local knowledge, this project will allow us to extend the spatial and temporal extent of cyanobacterial bloom predictions.”

Ultimately, the team will develop a method to monitor cyanobacterial blooms in real-time, providing invaluable context for freshwater management.

The Cary Institute of Ecosystem Studies is one of the world's leading independent environmental research organizations. Areas of expertise include disease ecology, forest and freshwater health, climate change, urban ecology, and invasive species. Since 1983, Cary Institute scientists have produced the unbiased research needed to inform effective management and policy decisions.

The Hexcopter

Sensors on the drone being used in this study can resolve frequency bands finer than those resolved by satellites. The result: a clearer picture of what is actually happening on and around lakes.

Consider the resolution of a photograph. A high-resolution image will contain more pixels per square inch than a low-resolution image. A higher concentration of pixels increases the clarity of the photograph, making it appear detailed and defined. The same is true for images produced by satellites and aerial instruments such as those attached to drones.

In this case, the drone detects finer wavelengths, resulting in an image with more 'pixels' than a satellite. This means that information about nearshore development, land use in the watershed surrounding lakes, and cyanobacterial blooms on lake surfaces collected by the drone will be more accurate. 

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