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

Lead Research Organisation: UNIVERSITY OF EXETER
Department Name: Biosciences


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.


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Green PA (2022) Fighting force and experience combine to determine contest success in a warlike mammal. in Proceedings of the National Academy of Sciences of the United States of America

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Hart JDA (2023) BISoN: A Bayesian Framework for Inference of Social Networks. in Methods in ecology and evolution

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Johnstone RA (2020) Exploitative leaders incite intergroup warfare in a social mammal. in Proceedings of the National Academy of Sciences of the United States of America

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Sankey DWE (2022) Leaders of war: modelling the evolution of conflict among heterogeneous groups in Philosophical Transactions of the Royal Society B

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Sankey DWE (2022) Leaders of war: modelling the evolution of conflict among heterogeneous groups. in Philosophical transactions of the Royal Society of London. Series B, Biological sciences

Description We have developed new theoretical models to understand the evolution of leadership and collective decision making in the face of intergroup conflict. This work shows that the potential for some individuals to incite conflicts and yet avoid paying the cost of fighting can exacerbate intergroup competition, leading to destructive warfare. We have further explored the potential for heroic leaders to emerge who bear the lion's share of costs involved in group combat. The type of leadership that emerges during evolution depends on the demographic features of the population - group size, migration rate, adult mortality. Our models have revealed these hiterto unknown influences on the nature and intensity of intergroup conflict, with relevance for a wide range of social organisms, including humans.

In addition we have used the long-term dataset on banded mongoose conflicts to investigate the role of key individuals in collective fighting. Our analysis shows that two factors, the number of males per group, and the age of the oldest male in the group, have a disproportionate influence on the probability of winning a violent intergroup battle. The finding that a single individual - the oldest individual - has such a powerful impact on collective fighting performance is surprising and has stimulated further research to understand how a single individual has such a profound effect on the effectiveness of collective behaviour.
Exploitation Route We are hoping to reestablish the field component of the research in Uganda, to test the predictions of our models. However, that has not yet been possible due to covid.

The field component has been restablished and this funding will provide vital pilot data for future investigations of the evolution of warfare, using banded mongooses as a model system.
Sectors Environment

Description The findings concerning the role of females in inciting intergroup conflicts received very wide global media impact (altmetric score 1200). We are currently in negotiations with several film crews who are interested in filming documentaries about this fascinating behaviour, and the implications of our research for the evolutionary study of warfare.
First Year Of Impact 2021
Sector Digital/Communication/Information Technologies (including Software),Education
Impact Types Cultural


Title Data supporting Johnstone, Cant, Cram & Thompson (2020) Exploitative leaders incite intergroup warfare in a social mammal 
Description This data supports the following publication:
Rufus A. Johnstone, Michael A. Cant, Dominic L. Cram & Faye J. Thompson (2020) Exploitative leaders incite intergroup warfare in a social mammal. Proceedings of the National Academy of Sciences.
Please read the "Read Me.txt" file for a full description of the data contained in each data set 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
URL https://figshare.com/articles/dataset/Data_supporting_Johnstone_Cant_Cram_Thompson_2020_Exploitative...
Title Mortality data for a population of banded mongooses (Mungos mungo) in Mweya, Uganda, 2000-2011 
Description This dataset provides details about each time we observed two banded mongoose groups engaging in what ended up being lethal conflict at our field site (Mweya, Uganda) between 2000-2011. The dataset provides information about which group won the contest (measured by which group ran from the location of the fight), which individual died in the battle, whether that individual was in the losing or winning group, and the date. The purpose of this data was to estimate the proportion of mortalities which come from winning groups vs. losing groups. 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
URL https://catalogue.ceh.ac.uk/id/75f2072e-f708-46d8-baff-0c6d02d81ede
Description Collaboration on developing and testing the theory of intergroup conflict 
Organisation University of California, Santa Cruz
Country United States 
Sector Academic/University 
PI Contribution Through our interest in intergroup conflict we have set up a collaboration with Prof Suzanne Alonzo at the University of Santa Cruz, to develop and test new theory about the role of intergroup conflict in social evolution. The theoretical predictions outlined in the grant can be tested using controlled experiments on a model insect system, the dampwood termite Zootermopsis angusticollis, which complements our field research objectives on social mammals and provides a strong test of the generality of the theoretical models we are developing.
Collaborator Contribution Prof Alonzo has provided advice on logistics and marking of animals, and has provided access to her laboratory facilities at the University of Santa Cruz as required.
Impact We are in the process of discussing and developing theoretical models.
Start Year 2019
Description Collaboration to develop AI methods of animal tracking from UAV video 
Organisation University of York
Department Department of Biology
Country United Kingdom 
Sector Academic/University 
PI Contribution UAV video from the banded mongoose research project has been used to train AI algorithms to track individual mongooses in their natural environment.
Collaborator Contribution Dr Franks from York University has developed and adapted objective recognition algorithms and trained these on data from the banded mongoose research project. The aim is to develop new techniques that could be used to track animals in their natural environment against a heterogeneous background.
Impact none yet. The work was delayed by covid.
Start Year 2020
Description Mongoose genetics 
Organisation Liverpool John Moores University
Country United Kingdom 
Sector Academic/University 
PI Contribution We provide all tissue and blood samples for genetic analysis of parentage. We also provide the long term life history database, and collaborate on a range of publications investigating the genetic population structure of our field population.
Collaborator Contribution Developed microsatellite library for analysis of parentage. Currently working on construction of a full genetic pedigree, which will open up new lines of research.
Impact Numerous papers co-authored with HJ Nichols have investigated the genetic structure of the population, reproductive success, and inbreeding.
Start Year 2007