Rock ant meandering is actually methodical

Some ants are moving much more methodically than previously thought, a new study shows.

When strolling through an unfamiliar grocery store, you may find yourself methodically walking down each aisle to make sure you find everything you need without crossing the same path twice. Sometimes you deviate from this orderly process when, for example, you see a glowing “Sale” sign across the store or realize you forgot something.

According to the study in the journal isciencesome ants act in a similar way when searching for food and shelter.

The researchers found that when a colony of stone ants is placed in an unfamiliar environment in a laboratory, the ants migrate in a way that isn’t as random as previously thought. The ants follow a systematic meandering pattern combined with random movements – a method with the potential to streamline exploration of their natural environment.

“Until now, researchers in this field assumed that ants are on the wrong track when looking for targets whose location they do not know,” says Stefan Popp, first author of the work and doctoral student in the Ecology and Evolutionary Biology Department at the University of Arizona. “We found that rock ants display a conspicuous, regular meander pattern when exploring the area around their nests.”

In Arizona, these ants nest between or under rocks in areas above 7,000 feet. These slow-moving creatures are only about half the length of a medium-sized grain of rice.

The study finds that the ants’ meandering or zigzagging walking pattern can make their search more efficient than a purely random search. This is because the ants can explore a large area in less time because they rarely cross their own paths.

“These ants don’t make obvious food tracks like many ants we know,” says Popp. “Instead, the colony depends on individual gatherers finding resources, making their search strategy a crucial part of the colony’s success.”

According to the researchers, the meandering evolutionary advantage found in these rock ants could potentially have evolved in other insect and animal species as well. The researchers also say the ants’ movement could one day be used to inform the design of autonomous swarms of robots performing search-and-rescue missions in disaster areas or exploring landscapes on other worlds.

Because it is difficult to track down ants in their natural environment, Popp and his team collected rock ant colonies on and around Mount Lemmon north of Tucson. The team then brought the ants into the lab and placed them in an enclosed arena with a paper floor. The enclosure measured 2 by 3 meters – huge compared to the tiny scurrying ants. After being introduced to a new home, the ants were eager to explore.

“These ants may have been patrolling the area for other competing ants,” says Popp, explaining that there is a selective pressure to discourage other ants from entering their nest. “They may also have been looking for food and new nesting sites.”

The researchers soon noticed the ants’ meandering pattern as they walked around. The question immediately arose: were these patterns just random squiggles, or were the ants moving in a methodical, non-random way?

To answer this question, the researchers set up cameras and used automatic tracking software coupled with manual corrections to trace the individual paths of each marching insect over a five-hour period. The ants’ migrations were then compared to simulated ants walking in a random fashion.

“We investigated whether the direction in which an ant moves somehow depends on the direction in which it moved before,” says co-author Anna Dornhaus, professor in the Department of Ecology and Evolutionary Biology. “These methods helped us to see that the ants’ foraging behavior was not entirely random, as biologists had previously assumed.”

The researchers used statistics to find that the direction an ant turned correlated directly with previous turns.

“Our research has shown that the ants smoothly alternate left and right on a relatively regular length scale of about three body lengths,” says Popp. “For some ants, the meandering search pattern was even more extreme than for others a meandering river in the Amazon basin. That fascinates me and I wonder how the ants ensure that they don’t keep crossing their own paths and still make extreme turns and loops.”

Popp and Dornhaus note that they do not know how this foraging behavior changes over the course of an ant’s life, or whether individual ants are aware of it.

Regardless, the combination of meandering and randomness can be optimal for finding resources in an unfamiliar environment. The systematic approach can keep an ant close to its nest without pacing back and forth on previously explored ground. The added randomness accounts for obstacles that come with an unpredictable, natural environment.

“Until now, it was widely assumed that free-roaming animals were not capable of methodically searching for new resources,” says Popp. “Most previous research on foraging behavior has only focused on situations where the animal already knows where it is going, such as walking back to the nest entrance or walking back to a memorable food source.”

“Based on these results, many animals potentially use complex combinations of random and systematic search that optimize efficiency and robustness in real and complex habitats,” says Dornhaus. “This discovery opens up a whole new perspective on all animal movements.”

The researchers believe their discovery has the potential to unify different fields of science, including biology and robotics. The migrations of these ants may have applications to real-world environments where a fully systematic search would fail if they encountered an obstacle.

“This discovery could potentially lead to applications for roboticists in programming robots to find their way around or to search,” says Dornhaus. “In this way, they can make their algorithms more robust so that they don’t immediately fail as soon as the robot loses its precise position.”

Source: Kylianne Chadwick from the University of Arizona

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