Minnegram

A river with rocks and grass at the edge. Pine trees in the distance.

Highlighting Minnesota Water Resource Center's research and education.

Minnegram is a quarterly publication of the University of Minnesota Water Resources Center and is sponsored by the University of Minnesota College of Food, Agricultural and Natural Resource Science, University of Minnesota Extension, the USGS-USDI National Institutes for Water Resources, and the Agricultural Experiment Station.

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Recent Minnegram News

Protecting Minnesota's Waters: The important role of our Aquatic Invasive Species Detector volunteers – and how to maintain high engagement.

September 2, 2026

Minnesota's AIS Detectors are deeply committed stewards eager to protect local ecosystems. By expanding training locations and volunteer opportunities, building stronger links to local research and management initiatives, and supporting lake association engagement, the AIS Detector program can keep its passionate volunteer base energized for years to come.


Managing the invisible infrastructure behind Minnesota’s water

July 31, 2026

Behind the scenes, the University of Minnesota’s Water Resources Center and its partners are a big reason why Minnesota is a national leader in water management. 


Researchers are learning what Minnesotans think about lake water quality

June 20, 2026

Director of the Water Resources Center, Bonnie Keeler, speaks about a water quality study being conducted at 17 different lakes across Minnesota.


Go with the flow: Hydrodynamic resilience to invasive mussels

June 8, 2026

Water Resources Science, masters student Jasper Goldstein, investigated how turbulence in water flow negatively affects zebra mussels.


Aquatic invasive species prevention: leveraging big data to inform infestation risk

March 12, 2026

Graduate research assistant, Jeremiah Shrovnal, joined researchers from Minnesota Cooperative Fish and Wildlife Research Unit (MNCFWRU) and the Minnesota Aquatic Invasive Species Research Center (MAISRC), along with collaborators at the USGS Upper Midwest Environmental Sciences Center, to leverage the power of machine learning and large international data sets to generate species distribution models.