Turning the clock back on Arctic ecosystem computer modeling

This week, scientists from the University of Alaska Fairbanks are presenting their work alongside thousands of colleagues from around the world at the 2023 American Geophysical Union fall meeting. Some of their discoveries are featured here. You can also find out more about UAF at AGU by searching for #UAFxAGU on social media platforms.

a portrait of a smiling woman with long brown hair
Courtesy of Institute of Arctic Biology
Hannah Mevenkamp

Most ecosystem computer modeling that seeks to forecast the effects of climate change starts with the date of 1900, before industrialization’s fingerprints begin to be seen in the global environment.

But graduate student Hannah Mevenkamp’s ecosystem modeling starts much earlier. For her research with Arctic ecosystems at the University of Alaska Fairbanks, she turns the clock back 15,000 years and runs her models beginning with the Pleistocene Era’s ice age — a time when woolly mammoths still roamed the Earth and humans first began appearing in Alaska.

She’s testing this increased timeline because some of the permafrost that exists today in the Arctic — a region that is feeling the effects of climate change more acutely than any other place on the globe — was created under conditions from the last ice age. At that time, according to the U.S. Geological Survey, glaciers covered 25% of the Earth’s surface.

“The history that something has gone through can change its future behavior, and I am testing to see if that holds true for permafrost. If this is the case, then it might mean we need to set the clock back for ecosystem modeling in the Arctic,” said Mevenkamp.

The crux of Mevenkamp’s research seeks to determine whether there is value in telling the computer model that an ice age has occurred. Preliminary results indicate that setting the timeline back 15,000 years may have significant effects for modeling.

“Arctic soils have a really long memory,” Mevenkamp said. “At least in high-latitude areas, it might be beneficial to run climate models that go further back.”