A new study conducted by researchers at the University of Bath proposes a mathematical model that explains the nature of swarming locusts. The model reveals that during swarming, individual locusts interact with at least two neighbors in order to align themselves properly and march in the same direction. This finding is novel, with previous research pointing to flank protection as the sole purpose of this behavior.
The team analyzed the movements of locusts in various group sizes using footage taken by a team of colleagues at The University of Adelaide. Using this data, they studied the interactions of the locusts in these groups and created a mathematical model that represents the collective behavior of these unique insects. Additionally, this model reveals that locusts are sensitive to external environmental changes such as wind conditions, which can disrupt their interactions and decrease the stability of the swarm.
"We can describe the locusts' behavior using quite simple rules and have demonstrated for the first time that locusts have to interact with multiple neighbors in order to swarm in the way they do," Kit Yates, co-author of the study, said in a press release. "We already know that animals, including humans, change their behavior when they are in a crowd, following cues from their peers. In the locust study, we found that small groups of locusts are unstable and tend not to march together - a behavior mimicked in our model."
The team's model could help scientists better understand how locust swarms operate and control them in areas where they are disrupting the surrounding environment, which is currently the case in Argentina, as previously reported by HNGN.
"A better understanding of how individuals behave in these groups could help us develop new strategies of disrupting swarms," said Yates. "Our model could also be applied to other swarming insects such as crickets, which are a major problem in Australia, and even in crowd dynamics of humans."
The findings mark the first time that the dynamics of locust swarming have been represented using a mathematical model.
"Our model helps us to understand how the individual decisions made by each locust using the information available to them can result in the dynamics we observe in the group as a whole," said Louise Dyson, another co-author of the study.
The findings were published in the Nov. 6 issue of Physical Review E.
