The Math of the Wild

Some of these Elk are fitted with radio collars. The data generated through these collars is valuable to mathematicians who study animal movement. This photo is courtesy of the South Dakota Game Fish and Parks.

Around the summer of 2003 in the La Sal Mountains of Utah, mule deer began to turn into zombies.

Or, at least they began to act like zombies. They started losing weight, salivated constantly, and began to walk in listless circles. They grew apathetic and then stopped running from humans.

At first only a few sick animals turned up in annual surveys of harvested deer, but the numbers grew. Testing confirmed the fears of wildlife managers, Chronic Wasting Disease or CWD. The prion disease produces lesions in the brain that change the animals' behavior. “We call them zombie deer,” says Martha Garlick, PhD, SD Mines math professor.

At first CWD shows no symptoms. It progresses over the course of a few years, but once contracted it’s always fatal. CWD is highly contagious and it has ravaged deer and elk populations across the American West. 

Understanding the rate of spread is crucial to stopping any disease. This is where Garlick’s work comes in, she is teamed up with wildlife biologists, mathematicians, and statisticians at Utah State University and Colorado State University. The team is part of a National Science Foundation grant to improve computer models that can help predict how animal populations move. 

“I love math anyway, but, it’s really cool to actually apply this to something real world. It’s exciting to predict things about animal movement that will help wildlife managers who care for these populations.” 

Garlick loves to hike and spend time outdoors but doesn’t spend her days chasing deer and elk in the field, rather she relies on the rich data sets accumulated from years of GPS collars that have been fitted to wild animals. 

She uses GPS tracking records, combined with landscape images to build models of how animals travel across various landscapes. Deer, for example, can move at different rates on rocky slopes than they can in thick trees, or open grasslands, or mazes of cedar brush. Researchers use the animal movement data to assign a number to different landscapes. Animals tend to take the easiest path to resources, like green grass and water, and they are often confined by barriers like a fence, a mountain snowline, or a major river. There are many variables to consider when building the algorithms that can accurately model something so complex. For example, male deer move in different patterns than females, so they require some slightly different math. 

One of Garlick’s favorite parts of the job is seeing students get involved in this research. “It’s fun to get undergraduates excited about this work,” she says. “In math modeling, it’s sometimes difficult to actually make it fit. You try and keep it simple but putting in the details so that it mirrors what’s really going on, this is an exciting challenge.” 

The models Garlick is developing not only have applications in tracking deer and elk in the mountain west but can also be used to predict the movement of harbor seals in Alaska, or the spread of the wolf populations introduced into places like Yellowstone National Park. As the research continues and the models inch closer to predicting reality, the real-world applications of this work will continue to grow.

Last edited 7/18/2018 8:36:52 PM

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