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CC BY-NC-ND V4.0, Open Access
Journal article
Complex battlefields favor strong soldiers over large armies in social animal warfare
Proceedings of the National Academy of Sciences - PNAS, Vol.120(37), e2217973120
2023
Abstract
In social animals, success can depend on the outcome of group battles. Theoretical models of warfare predict that group fighting ability is proportional to two key factors: the strength of each soldier in the group and group size. The relative importance of these factors is predicted to vary across environments [F. W. Lanchester, Aircraft in Warfare, the Dawn of the Fourth Arm (1916)]. Here, we provide an empirical validation of the theoretical prediction that open environments should favor superior numbers, whereas complex environments should favor stronger soldiers [R. N. Franks, L. W. Partridge, Anim. Behav. 45 , 197–199 (1993)]. We first demonstrate this pattern using simulated battles between relatively strong and weak soldiers in a computer-driven algorithm. We then validate this result in real animals using an ant model system: In battles in which the number of strong native meat ant Iridomyrmex purpureus workers is constant while the number of weak non-native invasive Argentine ant Linepithema humile workers increases across treatments, fatalities of I. purpureus are lower in complex than in simple arenas. Our results provide controlled experimental evidence that investing in stronger soldiers is more effective in complex environments. This is a significant advance in the empirical study of nonhuman warfare and is important for understanding the competitive balance among native and non-native invasive ant species.
Details
- Title
- Complex battlefields favor strong soldiers over large armies in social animal warfare
- Authors/Creators
- Samuel J. Lymbery - Murdoch University, Centre for Biosecurity and One HealthBruce L. Webber - The University of Western AustraliaRaphael K. Didham - The University of Western Australia
- Publication Details
- Proceedings of the National Academy of Sciences - PNAS, Vol.120(37), e2217973120
- Publisher
- PNAS
- Identifiers
- 991005601870307891
- Copyright
- © 2023 the Author(s).
- Murdoch Affiliation
- Centre for Biosecurity and One Health
- Language
- English
- Resource Type
- Journal article
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