Leaders of war: the evolution of collective decision-making in the face of intergroup conflict

Lead Research Organisation: University of Exeter
Department Name: Biosciences

Abstract

Nature abounds with breathtaking examples of collective animal behaviour: bird flocks undulating in the evening light, schools of fish swirling tightly together to avoid predation, ants teeming along intricate trails to explore and exploit their environment. In the last few decades biologists have discovered how simple behavioural decision rules produce these complex group-level behaviours. Similar decision rules have been found to predict the collective movements of humans in crowds and traffic jams, generating huge interdisciplinary interest in the idea that a very wide range of natural phenomena can be explained by simple universal rules - and that these rules are discoverable through research on animal behaviour.

For animals that form stable social groups, the central problem of collective behaviour is how to agree on where to go and what to do, despite conflicting interests and preferences among group members. In many animals this problem is solved through the emergence of leaders - individuals with disproportionate influence on the behaviour and movement of others. For example, in the face of uncertainty about where to find food or how to avoid predation, individual animals may do best to follow the most experienced or best informed members of a group, or those that are most valuable to their own fitness.

Up to now, research on collective decision-making and leadership has focused almost exclusively on single groups in isolation of all others. But there is now widespread evidence that intergroup interactions can exert a powerful influence on within-group behaviour in social animals, and hence the likely patterns of decision-making. For example, given that coordination is vital to group success in combat, we might expect a shift to more rapid, dictatorial decision-making in groups that are fighting compared to groups that are foraging. On the other hand, followers should be extremely choosy about which individuals they follow into battle, given the risks involved, which could favour more even power sharing over such vital decisions. Intergroup conflict is likely to have profound impacts on patterns of leadership and followership and the speed with which groups are able to agree on unified action, but to date almost nothing is known about the nature of these intergroup impacts on collective decision-making.

We will tackle this gap in knowledge by developing new theory to predict how intergroup competition shapes the evolution of leadership and followership in mobile animal groups; and by testing our predictions using drones (unmanned aerial vehicles, or UAVs) on an ideally suited wild mammal system, the banded mongoose. Banded mongooses live in highly territorial groups which engage in frequent violent conflicts with neighbouring groups. Intergroup conflict is more severe in banded mongooses than in meerkats, chimpanzees, or (to our knowledge) any other non-human mammal. Yet there is also great variation in the intensity of intergroup conflict between groups and across the reproductive cycle, and in levels of within-group conflict between the males and females. This variation in inter- and intragroup conflict provides an opportunity to test our theoretical predictions using experiments and natural observations of collective movement before, during, and after intergroup encounters. In the process we will demonstrate how video from UAVs combined with new 'deep learning' artificial intelligence methods can be used to automatically recognise individual animals and track their movements in the wild - opening the door to a host of potential applications in wildlife management and husbandry.

The outcome of the project will be an improved understanding of collective behaviour and intergroup conflict, with broad interdisciplinary implications beyond evolutionary and behavioural ecology, for example, in economics psychology, political science, and computer science.

Planned Impact

Who will benefit from this research?
Our project will target three major beneficiaries beyond the field of academic evolutionary and behavioural ecology.

First, our project will be of interest to researchers and practitioners in psychology, economics, and political science, and among computer scientists.

Second, our project has potential benefits to practitioners in conservation, wildlife management, and animal husbandry. It will result in a step-change in the ability to identify and track animals in natural habitats using UAVs. UAVs are set to revolutionise the monitoring of both wild and domestic animal populations. Our computer vision algorithms could be adapted, for example, to identify sick or lame animals among a herd of cattle or in wild herds.

Third, our project will be of interest to the general public, to primary and secondary educations teachers, and their students. African mammals are intrinsically interesting to the public, and we aim to capitalise on this interest to increase the public understanding of science, as we have done in the past.

How will they benefit?
First, researchers and practitioners in other disciplines will benefit from improved conceptual understanding of how intergroup relationships influence patterns of collective behaviour in natural systems. Our focus on testing evolutionary models can generate insight into why different forms of decision rule evolve in different ecological and social environments, contributing to a potentially predictive theory of collective behaviour. We will take extra steps to engage with workers in these other disciplines by publishing our work in top interdisciplinary journals, presenting scientific seminars in non-biological departments, and attending conferences beyond the traditional scope of evolutionary and behaviour ecology.

Second, we will hold a training workshop to promulgate the use of UAVs and computer vision algorithms to identify and track individuals in their natural habitat. We will also set up a dedicated website to illustrate the power and potential of these new computer vision methods.

Third, both the general public and schools will benefit through education and engagement with scientific research. We will hold a Wild Science Fair event in Queen Elizabeth National Park, Uganda in Year 2 to engage with local schools and community leaders; and participate each year in the Science in the Square outreach event in Falmouth, Cornwall. In addition we will continue to engage with the media, particularly wildlife documentary filmmakers, to promote public understanding of our scientific research.

In addition, the project team including the RCo-I early career researcher will benefit from developing new skills and experience with outreach and engagement with beneficiaries of the research, which will enhance career development.

Publications

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