Have you ever watched an ant wandering around in search of food and wondered whether there is method in its movements? Probably not. But this is exactly what Stefan Popp and Anna Dornhaus, both from the Department of Ecology and Evolutionary Biology at the University of Arizona, did when trying to understand how ants search their environments efficiently.
Most people assume that when ants need to find food that is in an unknown location, their best option would be to search in a random manner. Ants spend much of their lives searching for resources, but they must also stay close to their nest or colony, in case they need to return quickly. If they search randomly, they will be relatively efficient at locating resources, but will run the risk of returning to areas they have already searched. Alternatively, if they search in a non-random pattern, like a spiral or a left-to-right meander, they will not cross their path again but will be thrown by obstacles that obstruct their pathway and may end up deviating in a manner that takes them over territory they have already searched.
In order to find out which patterns rock ants (Temnothorax rugatulus) use when searching for food, the researchers transplanted five entire colonies into the lab, where they could track all ants automatically and under constant conditions. They gave the ants a large (2 x 3 m), empty arena and left them to search around for food for 5 hours. After video recording almost 5 km of ant tracks, which was equivalent to 1,384 individual tracks, they used statistical means to compare the ants’ movements with computer-generated random walk patterns.
“We wanted to make sure that we are not just seeing patterns where there are none,” Popp said. “We then used a simple statistical method of detecting regularity in movement tracks to get a simple answer.”
The results, published in the online journal iScience, showed that the ants used a mixture of distinctly systematic movements, along with random elements. A total of 78 percent of the ants systematically turned the direction of their search roughly every 10 mm. This means that a turn in one direction was usually followed by a turn in the opposite direction after roughly three ant body lengths. The researchers termed this regular movement “meandering.”
“Previously, researchers in the field assumed that ants move in a pure random walk when searching for targets of which they don’t know their location,” said Popp. “We found that rock ants, show a striking, regular meandering pattern when exploring the area around their nests. This means that the ants smoothly alternate left and right turns on a relatively regular length scale of roughly three body lengths.”
The regular meandering movements are also interspersed with random elements. The researchers state that the ant tracks 1) cross themselves less often than random walks would, and 2) sometimes disperse more than random walks. This means that ants cover the search area more efficiently than if their movements were simply random, because they don’t waste time searching areas they have already covered. In addition, their systematic meandering takes them away from the nest rapidly, to areas that have not been searched as thoroughly. Thus, the movement system of the ants is more efficient than if they walked around randomly. Popp says he was most intrigued by the extreme forms the ants’ patterns could take from these simple principles.
“Parts of some tracks look like the curled threads one can pull out of a piece of clothing, and in some it looks like the meandering path meanders itself,” he said, “creating a seemingly fractal structure. It reminds me of some space-filling curves we know from math!”
The new study is the first to find evidence for efficient search through regular meandering in a freely searching animal, the researchers report. It also adds another complex behavior for ants, suggesting that there’s still more to learn.
Popp says he’s most fascinated in questions about the rules in an ant’s mind that allow such complex search patterns to emerge. He notes also that the ants have solved a problem of collective search over the course of evolution in a way that might find application for designing autonomous swarms of search robots or drones for use in disaster areas or unexplored landscapes.
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