Details of Award
NERC Reference : NE/S009914/1
Leaders of war: the evolution of collective decision-making in the face of intergroup conflict
Grant Award
- Principal Investigator:
- Professor MA Cant, University of Exeter, Biosciences
- Co-Investigator:
- Professor RA Johnstone, University of Cambridge, Zoology
- Co-Investigator:
- Dr DW Franks, University of York, Biology
- Co-Investigator:
- Professor DP Croft, University of Exeter, Psychology
- Grant held at:
- University of Exeter, Biosciences
- Science Area:
- Terrestrial
- Overall Classification:
- Panel C
- ENRIs:
- Biodiversity
- Environmental Risks and Hazards
- Global Change
- Natural Resource Management
- Science Topics:
- Animal behaviour
- Social behaviour
- Behavioural Ecology
- Altruism
- Behavioural modelling
- Competition
- Cooperative behaviour
- Evolutionary biology
- Population Ecology
- Population Genetics/Evolution
- Social behaviour
- 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.
- NERC Reference:
- NE/S009914/1
- Grant Stage:
- Completed
- Scheme:
- Standard Grant FEC
- Grant Status:
- Closed
- Programme:
- Standard Grant
This grant award has a total value of £647,771
FDAB - Financial Details (Award breakdown by headings)
| DI - Other Costs | Indirect - Indirect Costs | DA - Investigators | DA - Estate Costs | DI - Staff | DI - T&S | DA - Other Directly Allocated |
|---|---|---|---|---|---|---|
| £164,073 | £162,564 | £79,928 | £58,966 | £141,891 | £32,358 | £7,990 |
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