What makes ants remarkable diggers? It’s all about physics, study finds

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If there’s one thing we know about ants, it’s that they are remarkable diggers, capable of building nests with multiple layers, connected by an intricate network of tunnels. Now, a group of researchers has used X-ray imaging to better understand the process through which ants build their tunnels. And the findings are just incredible.

Granular forces (black lines) at the same location in the soil before (left) and after (right) ant tunneling. Image credit: The researchers

Scientists have long been interested in ants, studying their collective behavior. While a few ants spaced well apart act like individuals, a pack of them close together behave more like a single unit – with solid and liquid properties. They are social insects, capable of organizing themselves in an efficient community to protect their colony. 

José Andrade, an engineer at the California Institute of Technology (Caltech), wanted to further explore tunneling ants after seeing examples of anthill art. These are pieces created by pouring molten metal, plaster, or cement into an ant mound, which flows through the tunnels. The soil is then removed to reveal the definitive structure.

“I saw a picture of one of these next to a person and I thought ‘My goodness, what a fantastic structure.’ And I got to wondering if ants ‘know’ how to dig,” Andrade said in a statement. “We didn’t interview any ants to ask if they know what they’re doing, but we did start with the hypothesis that they dig in a deliberate way.”

Andrade partnered with other colleagues at Caltech. They suspected that the ants poked around the soil, looking for loose grains to remove. Just like us when we play Jenga, taking off loose blocks and leaving the critical pieces. Those blocks are part of a “fore chain” that serves to jam the blocks together to create a stable structure.

A long process

The first step was to breed ants and learn how to work with them. But it was a very long first step that took over a year. There was a lot of trial and error in getting the ants to dig in small cups of soil that would later be loaded into an X-ray imager. This helped determine an optimal cup size and the ideal number of ants per cup. 

“They’re sort of capricious,” Andrade said. “They dig whenever they want to. We would put these ants in a container, and some would start digging right away, and they would make this amazing progress. But others, it would be hours and they wouldn’t dig at all. And some would dig for a while and then would stop and take a break.”

By x-raying the ants as they worked, the researchers were able to create 3-D animations showing their progress. Image credit: The researchers

Once they could finally set everything up, the researchers would take the cups and x-ray them, using a technique that created a 3-D scan of all the tunnels inside. This allowed them to create simulations and show the progress made by ants as they extended their tunnels farther below the surface – identifying a few patterns in their behavior. 

The ants tried to be as efficient as possible. They dug their tunnels along the inside of the cups, as the cup itself would act as part of their tunnels’ structures – meaning less work for them. They also dug the tunnels as straight and as steeply as possible, up to what’s known as the angle of repose. This is the steepest angle a granular material can be piled up before collapsing. 

The researchers also discovered something about the physics of the tunnels. As ants remove grains of soil, they are changing all the physical interactions of particles in and around the tunnel. Those chains rearrange themselves outside of the tunnel, strengthening the existing walls and relieving pressure from the grains at the end of the tunnel where the ants are working. 

But what about their initial hypothesis? Do ants actually know what they are doing? Apparently not. “They didn’t systematically look for soft spots in the sand. Rather, they evolved to dig according to the laws of physics,” Andrade said. Still, the researchers hope to keep studying this, but now with an artificial intelligence approach.

The study was published in the journal PNAS. 

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