Path selection and foraging efficiency in Argentine ant transport networks
We experimentally investigated both individual and collective behavior of the Argentine ant Linepithema humile as they crossed symmetrical and asymmetrical bifurcations in gallery networks. Ants preferentially followed the branch that deviated the least from their current direction and their probability to perform a U-turn after a bifurcation increased with the turning angle at the bifurcation. At the collective level, colonies were better able to find the shortest path that linked the nest to a food source in a polarized network where bifurcations were symmetrical from one direction and asymmetrical from the other than in a network where all bifurcations were symmetrical. We constructed a model of individual behavior and showed that an individual’s preference for the least deviating path will be amplified via the ants’ mass recruitment mechanism thus explaining the difference found between polarized and non-polarized networks. The foraging efficiency measured in the simulations was three times higher in polarized than in non-polarized networks after only 15 min. We conclude that measures of transport network efficiency must incorporate both the structural properties of the network and the behavior of the network users.
KeywordsTransport networks Argentine ant Linepithema humile Path selection Bifurcation geometry Foraging efficiency
We thank the members of the EMCC workgroup in Toulouse for helpful and inspiring discussions. We also thank Jérôme Buhl and Iain Couzin for English proofreading. Simon Garnier is supported by a research grant from the French Ministry of Education, Research and Technology.
- Camazine S, Deneubourg JL, Franks NR, Sneyd J, Theraulaz G, Bonabeau E (2001) Self-organization in biological systems. Princeton University Press, PrincetonGoogle Scholar
- Deneubourg JL, Goss S (1989) Collective patterns and decision making. Ethol Ecol Evol 1(4):295–311Google Scholar
- Krause J, Ruxton GD (2002) Living in groups. Oxford University Press, OxfordGoogle Scholar
- Mebane WR, Sekhon JS (2001) Genetic Optimization Using Derivatives for R (RGENOUD). http://sekhon.berkeley.edu/rgenoud/.