The collective movement of animals in a group is a fascinating topic of research for many scientists. Understanding these collective behaviors can sometimes inspire the development of strategies to promote positive social change, as well as technologies that mimic nature.
Many studies describe flow behavior as a self-regulated process, in which individuals in a group constantly adapt their direction and speed to eventually achieve a “collective” motion. However, this perspective does not take into account the hierarchical structure demonstrated by many animal groups and the potential benefits of having a “leader” leading the way.
Luis Gómez-Nava, Richard Boone, Fernando Peruani, and three researchers at Université Côte d’Azur, University of Toulouse, and CY Cergy Paris University recently used theory physics to examine the collective behavior of flocks of young sheep. Their findings, published in nature physicsIt is shown that by alternating between the role of leader and follower, the flock eventually achieves a form of “collective intelligence”.
“In most social animal systems, collective locomotion is not a continuous process, but takes place in loops: the phases of communal locomotion are interrupted, for example, for resting or feeding,” Perwani told Phys.org. However, most studies of group movement, including empirical and theoretical studies, take into account groups that, from start to finish, remain in motion. Moreover, it is often assumed that grouping behavior requires individuals to continually negotiate direction. Travel. “
A major goal of recent work by Perwani and colleagues has been to investigate the collective motion of an animal system in a way that explicitly considers the temporal aspect of the observed self-organizing process, specifically that phases of collective motion have a beginning and an end. . In addition, the team wished to adopt an alternative, holistic perspective, which views animal group movement as a set of “collective phases”.
“From this perspective, questions related to the mechanisms of information exchange and consensus decision-making take on a new dimension,” Birwani explained.
In their experiment, Perwani and colleagues closely studied the spontaneous behavior of small groups of sheep over varying periods of time. They analyzed the tracks of individual herd members and calculated the animals’ general spatial arrangement and orientation, while also evaluating correlations between the speed at which individual animals moved.
“We first showed that none of the existing swarm models, or their extensions, are consistent with our observations,” said Perwani. “Next, we analyzed how information travels through the group, identified an interaction network consistent with the data, and investigated what information is transmitted through this network.”
Interestingly, Birwani and his colleagues found that the interaction network representing herd behavior they observed was highly hierarchical. In addition, they explained, the only information that is disseminated through this network is that of the sheep’s status within the group.
Using their findings, the researchers built a collective animal movement model that focuses on two key cognitive processes. These processes are the selection of the leader who will lead the herd for a specific period of time and the mechanism underlying herd mobility.
“Importantly, each phase of the collective action possesses a temporal leader,” explained Perwani, “We investigated the mathematical properties of the resulting model to determine the advantages of the unblocked collective strategy. I believe the main contribution is the following: Animals, through the use of a hierarchical interaction network To move together for a period of time gives full control of the group to the Temporal Leader, but there is also a quick turnover of the Temporal Leaders.”
Essentially, the researchers’ findings indicate that while navigating flocks, sheep alternate between the role of leader and follower. Thus the leaders only lead the pack for a certain amount of time, before control of the pack is transferred to another sheep.
“If the temporal leader has knowledge relevant to the group (for example, the way out of a maze or the location of a food source), then the temporal leader will be able to direct the group efficiently,” Perwani said. “This way, all members of the group benefit from this knowledge, It should be noted that this only works if all individuals follow the temporal leader without questioning.”
The results compiled by Berwani and colleagues have shed some new light on the dynamics that underlie the collective movement of flocks of young sheep. To investigate the generalizability of these findings, further experiments need to be performed with larger herds and different animals.
“We wondered: If there is a temporary leader at every moment, how does the group share and process information that each member of the group might have? Can the group do information clustering to improve its ability to accurately navigate to a remote location? In short, does the group display collective intelligence?” Perwani said. “We demonstrated that by regularly changing the temporal leader, the group is able to demonstrate information aggregation and collective intelligence.”
Overall, recent work by this team of researchers highlights the possibility that some naturally occurring collective animal strategies can benefit from hierarchical and democratic organizational schemes. In the future, their observations could inspire new studies that look at the physics and biology that underpin these intriguing collective animal behaviours.
“We are now investigating mass movement using groups of different agents,” Perwani added. “Specifically, we are comparing the spontaneous behavior of groups of lambs, young sheep, and adult sheep, to investigate whether sheep learn to follow temporal leaders and act as one over time. We are also looking at how groups behave in complex environments such as mazes or yards with patches. Different dietary choices can lead to conflicts of interest within group members. More generally, we investigate how groups distribute and process information, using several tools of statistical mechanics.”
Luis Gómez-Nava et al, Intermittent collective locomotion in sheep results from alternating leader-follower roles, nature physics (2022). DOI: 10.1038/s41567-022-01769-8
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