Study: ants create stable tunnels in nests, much like humans play Jenga

Ants are prodigious diggers, building elaborate nests with several layers connected by an intricate network of tunnels, sometimes reaching depths of 25 feet. Today, a team of scientists from Caltech used X-ray imaging to capture the process of tunneling ants. Scientists have found that ants have evolved to intuitively detect which grain particles they can remove while maintaining structural stability, much like removing individual blocks in a game of Jenga. The team described their work in a new article published in the Proceedings of the National Academy of Sciences.

Scientists interested in collective behavior have been studying ants for decades. This is because, as a group, ants act as a form of granular medium. A few well-spaced ants behave like individual ants. But pack enough of them against each other and they act more as a single unit, exhibiting both solid and liquid properties. You can pour fire ants from a teapot, for example, or the ants can link together to build towers or floating rafts. Ants can be tiny creatures with tiny brains, but these social insects are able to collectively organize themselves into a highly effective community to ensure the survival of the colony.

Several years ago, behavioral biologist Guy Theraulaz of the Institute for Advanced Study in Toulouse, France, and several colleagues combined laboratory experiments with Argentine ants and computer modeling to identify three simple rules governing tunnel behavior. ants. Namely: (1) the ants collected the grains at a constant rate (about 2 grains per minute); (2) ants preferentially deposit their grains near other grains to form pillars; and (3) ants generally choose grains marked with a chemical pheromone after being handled by other ants. Theraulaz et al. built a computer simulation based on these three rules and found that after a week, their virtual ants built a structure that looked a lot like real ant nests. They concluded that these rules emerge from local interactions between individual ants, without the need for central coordination.

More recently, a 2020 article revealed that the social dynamics of how the division of labor emerges in an ant colony is similar to how political polarization develops in human social networks. Ants are also good at regulating their own flow of traffic. A 2018 study by Daniel Goldman’s group at Georgia Tech looked at how fire ants optimize their tunneling efforts without causing traffic jams. As we reported at the time, the group concluded that when an ant encounters a tunnel that other ants are already working in, it retreats to find another tunnel. And only a small fraction of the colony digs at any given time: 30 percent of them do 70 percent of the work.

David Hu’s biolocomotion group at Georgia Tech also studied fire ants. In 2019, he and his colleagues reported that fire ants can actively detect changes in forces acting on their floating raft. Ants recognize different fluid flow conditions and can adapt their behavior accordingly to preserve the stability of the raft. A paddle moving through the water of the river will create a series of swirling vortices (known as vortex loss), causing the ant rafts to rotate. These vortices can also exert additional forces on the raft, sufficient to break it. The changes in the centrifugal and shear forces acting on the raft are quite small, perhaps 2-3% of the normal force of gravity. Yet somehow ants can sense these little changes with their bodies.

This last article focuses on Western harvester ants (Pogonomyrmex occidentalis), selected for their prolific digging ability with millimeter-scale soil grains. Co-author José Andrade, Mechanical Engineer at Caltech, was inspired to explore tunnel ants after seeing examples of anthill art. Pieces are created by pouring some kind of molten metal, plaster or cement into an anthill, which passes through all the tunnels and eventually hardens. Then the surrounding soil is removed to reveal the final complex structure. Andrade was so impressed that he began to wonder if the ants really “knew” how to dig these structures.

Andrade partnered with Caltech’s biological engineer Joe Parker on the project; Parker’s research focuses on the ecological relationships of ants with other species. “We didn’t interview any ants to ask them if they know what they’re doing, but we started with the assumption that they are digging on purpose,” Andrade said. “We speculated that maybe ants were playing Jenga. “

In other words, the researchers suspected that the ants were rummaging in the ground looking for loose grains to remove, in the same way that people look for loose blocks to remove from a Jenga tower, leaving critical load-bearing parts in place. These blocks are part of what is called a “chain of force” which serves to wedge the blocks (or granular soil particles, in the case of an anthill) together to create a stable structure.

For their experiments, Andrade and his colleagues mixed 500 ml of Quikrete soil with 20 ml of water and placed the mixture in several small cups of soil. The size of the wells was chosen based on the ease with which they could be placed inside a CT scanner. Through trial and error, starting with an ant and gradually increasing the number, the researchers determined the number of ants needed to achieve the optimal excavation rate: 15.

The team ran four-minute half-resolution scans every 10 minutes as the ants dug tunnels to monitor their progress. From the resulting 3D images, they created a “digital avatar” for each particle in the sample, capturing the shape, position and orientation of each grain, which can significantly influence the distribution of forces in the particles. soil samples. The researchers were also able to determine the order in which each grain was removed by the ants by comparing images taken at different points in time.

Ants weren’t always cooperative when it came to diligently digging their tunnels. “They are kind of temperamental,” Andrade said. “They dig when they want. We would put these ants in a container, and some would start digging right away, and they would make amazing progress. But others – it would take hours and they wouldn’t dig at all. And some would dig for a while, then stop and take a break. “

Andrade and Parker noticed some emerging trends in their analysis. For example, ants usually burrowed along the inner edges of the cups, an effective strategy, as the sides of the cups could be part of the tunnel structure, sparing the ants a bit of effort. Ants also favored straight lines for their tunnels, a tactic that maximizes efficiency. And the ants tended to dig their tunnels as steeply as possible. The steepest possible limit in a granular medium such as soil is called the “angle of repose”; exceed this angle and the structure will collapse. Either way, ants can detect this critical threshold, making sure their tunnels never go beyond the angle of repose.

As for the underlying physics, the team found that when ants removed grains of soil to dig their tunnels, the chains of force acting on the structure rearranged from a random distribution to form a sort coating around the outside of a tunnel. This redistribution of forces strengthens the existing walls of the tunnel and relieves the pressure exerted by the kernels at the end of the tunnel, making it easier for ants to remove these kernels to expand the tunnel even further.

“It’s a mystery both in engineering and in ant ecology how ants build these structures that persist for decades,” Parker said. “It turns out that by removing the kernels in this pattern that we have observed, the ants benefit from these chains of circumferential force as they dig.” The ants tap on individual grains to assess the mechanical forces exerted on them.

Parker sees it as a sort of behavioral algorithm. “This algorithm does not exist in a single ant,” he said. “It’s this emerging colony behavior of all these worker bees acting like a superorganism. The way this behavioral program spreads through the tiny brains of all of these ants is a wonder of the natural world for which we have no explanation. . “

DOI: PNAS, 2021. 10.1073 / pnas.2102267118 (About DOIs).