University of Minnesota Alumni Association



Protecting Elders from Scams

Research done by the Understanding America Survey at the University of Southern California shows that only 39 percent of Americans over the age of 60 have a durable power of attorney, a legal document naming a trusted person to manage finances if they can’t do it themselves. That can leave an elderly person vulnerable to a host of financial disasters, including unintentional money management mistakes, fraud, and scams.

To prevent these misfortunes, U of M and Stanford researchers have released the Thinking Ahead Roadmap. Funded by AARP, this free toolkit offers instructions to help people select someone they trust to make financial decisions for them, if necessary.

“Problems with financial decision-making can appear many years before a dementia diagnosis,” says the toolkit’s lead author, Marti DeLiema, a gerontologist at the School of Social Work. “Even cognitively healthy older adults may show declines in their financial decision-making abilities.”

Available both online or in print, the Roadmap includes a financial inventory that users can download and fill out. The toolkit offers prompts elders can use to overcome common issues, such as adult children who don’t want to acknowledge that their parents are getting older or who are uncomfortable talking about money.

The Thinking Ahead Roadmap can be viewed and downloaded at

Woodpecker Science

The fiercely territorial red-headed woodpecker has been on the decline in many parts of the United States. Thankfully, the population of these “flying checkerboards” is thriving at the University of Minnesota’s Cedar Creek Ecosystem Science Reserve, a biological field station north of the Twin Cities in East Bethel, Minnesota, which has one of the largest tracts of oak savanna in the state.

To learn more about woodpecker habitats, U of M College of Food, Agricultural and Natural Resource Sciences researcher Elena West leads a team of volunteers to study them. First, West attaches a small tracking device to a woodpecker’s leg, a delicate and complicated task that involves peanuts and a wire box. If she’s successful—not a given due to the birds’ intelligence and feisty nature— her team is able to follow their movements to better understand habitats and migration patterns; red-headed woodpeckers are facultative migrants, so they migrate in some years and stay in place in others.

West also gathers information about the birds’ nesting ecology and behaviors by examining videos from trail cameras placed in the reserve. These images are then posted on the Woodpecker Cavity Cam on Zooniverse, a citizen science platform where volunteers can assist researchers as they work.

Interested in joining these efforts? Check out

Algorithms and the Environment

From helping us choose the next binge-worthy TV series to preventing us from backing into a parked car, algorithms have become integral to modern life. Now, researchers are using these machine-learning tools to make environmental predictions.

A team of researchers from the U of M, the University of Pittsburgh, and the U.S. Geological Survey used algorithms to more accurately predict river and stream temperatures, even when there was a dearth of available data to analyze. They say these predictions can now be used to determine a host of environmental factors, including the suitability of aquatic habitats, evaporation rates, greenhouse gas exchange, and the efficiency of thermoelectric energy production.

Researchers say that being able to accurately predict water temperature and streamflow will help with a range of decisions on waterways, including for resource managers, who use the data to determine when and how much water to release from reservoirs to downstream rivers.

“These knowledge-guided machine learning techniques are fundamentally more powerful than standard machine learning approaches and traditional mechanistic models used by the scientific community to address environmental problems,” says U of M computer scientist Vipin Kumar, whose lab in the College of Science and Engineering develops such technologies.

This study was originally published in the 2021 Society for Industrial and Applied Mathematics (SIAM) International Conference on Data Mining proceedings.

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