Movements in swarms are widespread in nature and play a crucial role in the survival of many animal species. A well -known example of this is desert grasshoppers that move through Africa in large collectives and sometimes destroy entire harvests. Unlike previously thought, the insects do not only follow their neighbors passively, but act for active cognitive processes to move together.
The swarms of desertshill lymph (Schistocerca Gregaria) are impressive natural phenomena that have gained dubious celebrity as a biblical plague. Billion -unable young animals join together to form a collective and march together over huge areas in North Africa. The insects seem to act like a single organism, since their movements and molting rhythms are perfectly coordinated. It is special that the swarm works without a recognizable guide or hierarchy within the group; Rather, his behavior is based on the interactions of the individuals. During their runs, the grasshoppers eat whole harvests, the local agriculture damage and threaten the livelihood of the population there. In order to keep such insect plagues under control and predict swarm movements, it is crucial to understand how grasshoppers coordinate their movement in the swarm.
How does the swarm behavior arise?
How exactly such swarms arise and according to which rules the animals move has not yet been fully clarified. For decades, collective movements have been described by principles from theoretical physics based on “self-driven particles”. The individual animals are viewed as particles that align their position and direction of movement. The central prediction of this traditional model was previously confirmed in laboratory experiments with large grasshopper groups. It says that with the increasing density of the animals there is a spontaneous transition from disordered too highly aligned movements. Researchers assumed that individuals passively follow their neighbors in a crush as soon as the density of the swarm increases.
Researchers led by Sercan Sayin from the University of Konstanz and the Max Planck Institute for Behavioral Biology have now found out with grasshoppers using a combination of field and laboratory research as well as virtual reality experiments that the behavior pattern behind the collective movement of grasshoppers cannot be explained by the classic model. “As is known, it is difficult to recognize the mechanisms of interaction in mobile animal groups,” explains senior author Iain Couzin from the University of Konstanz. “The individuals influence each other and are also influenced by the behavior of the others, in a complex interplay.”
Swarm research in three -dimensional VR
To overcome this challenge, the team used an immersive, three -dimensional, virtual reality. The grasshoppers ran on a high -speed ball with movement compensation, which gave them a feeling of natural mobility. At the same time, through virtual panoramic projection, they saw the realistic simulation of a “holographic” swarm with which they could interact. “This approach enabled us to check hypotheses about the behavior of the swarms in a way that would not be possible in natural raves,” explains Sayin.
In contradiction to previous assumptions, the research team found no evidence that grasshoppers align their position and direction of movement to their neighbors. The movements of the individual grasshoppers could not be explained by the classic models. For example, grasshoppers were placed in an experiment between two virtual grasshoppers, both of which moved in the same direction. According to common theory, the grasshopper should have followed this movement. But instead of running with the electricity, the animals crawled headally towards one of the two groups.
Collective behavior newly thought
In order to interpret the movements, the research team developed a simple, cognitive model based on principles of neurobiology. “We have found that all of our experimental key results can explain,” reports Sayin. The basis of this new theory are the neuronal circuits that animals use for spatial navigation – also called the “ring attractor”. In this model, the animals only look at the position of their neighboring conspecifics, but not their body or movement direction. The decisions about their movements then arise in a dynamic process in which the neuronal information about the position of the animals competes or combined. Finally, a common consensus is achieved, which determines the direction in which you move.
According to the researchers, their results represent an important progress in swarm research. The new knowledge about the swarm behavior of grasshoppers could help develop more effective strategies to contain grasshoppers, in particular by predicting their movements. The findings could also be helpful for other animal species as well as robotics and artificial intelligence, for example by benefiting robotic swarms and self -driving vehicles from algorithms that have been inspired by the highly efficient cognitive strategies of grasshoppers.
Source: Sercan Sayin (University of Konstanz, Max Planck Institute for Behavioral Biology, Constance) et al., Science, Doi: 10.1126/science.adq7832