Behavioral Ecology and Sociobiology

, Volume 63, Issue 8, pp 1167–1179 | Cite as

Path selection and foraging efficiency in Argentine ant transport networks

  • Simon Garnier
  • Aurélie Guérécheau
  • Maud Combe
  • Vincent Fourcassié
  • Guy Theraulaz
Original Paper


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.


Transport 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.


  1. Acosta FJ, Lopez F, Serrano JM (1993) Branching angles of ant trunk trails as an optimization cue. J Theor Biol 160(3):297–310. doi: /10.1006/jtbi.1993.1020 CrossRefGoogle Scholar
  2. Agresti A (2002) Categorical data analysis. Wiley, HobokenCrossRefGoogle Scholar
  3. Anderson C, Mcshea DW (2001) Intermediate-level parts in insect societies: adaptive structures that ants build away from the nest. Insectes Sociaux 48(4):291–301. doi: /10.1007/PL00001781 CrossRefGoogle Scholar
  4. Banavar JR, Damuth J, Maritan A, Rinaldo A (2002) Supply–demand balance and metabolic scaling. Proc Nat Acad Sci 99(16):10506–10509. doi: /10.1073/pnas.162216899 PubMedCrossRefGoogle Scholar
  5. Banavar JR, Maritan A, Rinaldo A (1999) Size and form in efficient transportation networks. Nature 399(6732):130–132. doi: /10.1038/20144 PubMedCrossRefGoogle Scholar
  6. Bebber DP, Hynes J, Darrah PR, Boddy L, Fricker MD (2007) Biological solutions to transport network design. Proc R Soc B: Biol Sci 274(1623):2307–2315. doi: /10.1098/rspb.2007.0459 CrossRefGoogle Scholar
  7. Beckers R, Deneubourg JL, Goss S (1992) Trails and U-turns in the selection of a path by the ant Lasius niger. J Theor Biol 159:397–415. doi: /10.1016/S0022-5193(05) 80686-1 CrossRefGoogle Scholar
  8. Beckers R, Deneubourg JL, Goss S (1993) Modulation of trail laying in the ant Lasius niger (Hymenoptera: Formicidae) and its role in the collective selection of a food source. J Insect Behav 6(6):751–759. doi: /10.1007/BF01201674 CrossRefGoogle Scholar
  9. Bhatkar A, Whitcomb WH (1970) Artificial diet for rearing various species of ants. Florida Entomologist 53(4):229–232CrossRefGoogle Scholar
  10. Buhl J, Gautrais J, Reeves N, Solé RV, Valverde S, Kuntz P, Theraulaz G (2006) Topological patterns in street networks of self-organized urban settlements. Eur Phys J B Condens Matter 49(4):513–522. doi: /10.1140/epjb/e2006-00085-1 CrossRefGoogle Scholar
  11. Buhl J, Gautrais J, Solé RV, Kuntz P, Valverde S, Deneubourg JL, Theraulaz G (2004) Efficiency and robustness in ant networks of galleries. Eur Phys J B Condens Matter 42(1):123–129. doi: /10.1140/epjb/e2004-00364-9 CrossRefGoogle Scholar
  12. Buhl J, Hicks K, Miller E, Persey S, Alinvi O, Sumpter D (2009) Shape and efficiency of wood ant foraging networks. Behav Ecol Sociobiol 63(3):451–460CrossRefGoogle Scholar
  13. Camazine S, Deneubourg JL, Franks NR, Sneyd J, Theraulaz G, Bonabeau E (2001) Self-organization in biological systems. Princeton University Press, PrincetonGoogle Scholar
  14. Cassill D, Tschinkel WR, Vinson SB (2002) Nest complexity, group size and brood rearing in the fire ant, Solenopsis invicta. Insectes Sociaux 49(2):158–163. doi: /10.1007/s00040-002-8296-9 CrossRefGoogle Scholar
  15. Couzin ID, Krause J (2003) Self-organization and collective behavior in vertebrates. Adv Study Behav 32:1–75. doi: /10.1016/S0065-3454(03) 01001-5 CrossRefGoogle Scholar
  16. Darlington JPEC (1997) Comparison of nest structure and caste parameters of sympatric species of Odontotermes (Termitidae, Macrotermitinae) in Kenya. Insectes Sociaux 44(4):393–408. doi: /10.1007/s000400050060 CrossRefGoogle Scholar
  17. Deneubourg JL, Aron S, Goss S, Pasteels JM (1990) The self-organizing exploratory pattern of the Argentine ant. J Insect Behav 3(2):159–168. doi: /10.1007/BF01417909 CrossRefGoogle Scholar
  18. Deneubourg JL, Goss S (1989) Collective patterns and decision making. Ethol Ecol Evol 1(4):295–311Google Scholar
  19. Deneubourg JL, Goss S, Franks NR, Pasteels JM (1989) The blind leading the blind: modeling chemically mediated army ant raid patterns. J Insect Behav 2(5):719–725. doi: /10.1007/BF01065789 CrossRefGoogle Scholar
  20. Detrain C, Deneubourg JL (2006) Self-organized structures in a superorganism: do ants “behave” like molecules? Phys Life Rev 3(3):162–187. doi: /10.1016/j.plrev.2006.07.001 CrossRefGoogle Scholar
  21. Dussutour A, Deneubourg JL, Fourcassié V (2005) Amplification of individual preferences in a social context: the case of wall-following in ants. Proc R Soc B Biol Sci 272:705–714. doi: /10.1098/rspb.2004.2990 CrossRefGoogle Scholar
  22. Dussutour A, Fourcassié V, Helbing D, Deneubourg JL (2004) Optimal traffic organization in ants under crowded conditions. Nature 428(6978):70–73. doi: /10.1038/nature02345 PubMedCrossRefGoogle Scholar
  23. Dussutour A, Nicolis S, Deneubourg JL, Fourcassié V (2006) Collective decisions in ants when foraging under crowded conditions. Behav Ecol Sociobiol 61(1):17–30. doi: /10.1007/s00265-006-0233-x CrossRefGoogle Scholar
  24. Edelstein-Keshet L (1994) Simple models for trail-following behaviour; trunk trails versus individual foragers. J Math Biol 32(4):303–328. doi: /10.1007/BF00160163 CrossRefGoogle Scholar
  25. Edelstein-Keshet L, Watmough J, Ermentrout G (1995) Trail following in ants: individual properties determine population behaviour. Behav Ecol Sociobiol 36(2):119–133. doi: /10.1007/BF00170717 CrossRefGoogle Scholar
  26. Garnier S, Gautrais J, Theraulaz G (2007) The biological principles of swarm intelligence. Swarm Intelligence 1(1):3–31. doi: /10.1007/s11721-007-0004-y CrossRefGoogle Scholar
  27. Gastner MT, Newman MEJ (2006) The spatial structure of networks. Eur Phys J B Condens Matter 49(2):247–252. doi: /10.1140/epjb/e2006-00046-8 CrossRefGoogle Scholar
  28. Gerbier G, Garnier S, Rieu C, Theraulaz G, Fourcassié V (2008) Are ants sensitive to the geometry of tunnel bifurcation? Anim Cogn 11(4):637–642. doi: /10.1007/s10071-008-0153-4 PubMedCrossRefGoogle Scholar
  29. Giraud T, Pedersen JS, Keller L (2002) Evolution of supercolonies: the Argentine ants of southern Europe. Proc Nat Acad Sci 99(9):6075–6079. doi: /10.1073/pnas.092694199 PubMedCrossRefGoogle Scholar
  30. Goss S, Aron S, Deneubourg JL, Pasteels JM (1989) Self-organized shortcuts in the Argentine ant. Naturwissenschaften 76:579–581. doi: /10.1007/BF00462870 CrossRefGoogle Scholar
  31. Jackson DE, Holcombe M, Ratnieks FLW (2004) Trail geometry gives polarity to ant foraging networks. Nature 432(7019):907–909. doi: /10.1038/nature03105 PubMedCrossRefGoogle Scholar
  32. Jeanson R, Deneubourg JL, Grimal A, Theraulaz G (2004) Modulation of individual behavior and collective decision-making during aggregation site selection by the ant Messor barbarus. Behav Ecol Sociobiol 55:388–394. doi: /10.1007/s00265-003-0716-y CrossRefGoogle Scholar
  33. Krause J, Ruxton GD (2002) Living in groups. Oxford University Press, OxfordGoogle Scholar
  34. Mebane WR, Sekhon JS (2001) Genetic Optimization Using Derivatives for R (RGENOUD).
  35. Mikheyev AS, Tschinkel WR (2004) Nest architecture of the ant Formica pallidefulva: structure, costs and rules of excavation. Insectes Sociaux 51(1):30–36. doi: /10.1007/s00040-003-0703-3 CrossRefGoogle Scholar
  36. Nakagaki T, Kobayashi R, Nishiura Y, Ueda T (2004a) Obtaining multiple separate food sources: behavioural intelligence in the Physarum plasmodium. Proc R Soc B: Biol Sci 271(1554):2305–2310. doi: /10.1098/rspb.2004.2856 CrossRefGoogle Scholar
  37. Nakagaki T, Yamada H, Hara M (2004b) Smart network solutions in an amoeboid organism. Biophys Chem 107(1):1–5. doi: /10.1016/S0301-4622(03) 00189-3 PubMedCrossRefGoogle Scholar
  38. Perna A, Jost C, Couturier E, Valverde S, Douady S, Theraulaz G (2008) The structure of gallery networks in the nests of termite Cubitermes spp. revealed by X-ray tomography. Naturwissenschaften 95(9):877–884. doi: /10.1007/s00114-008-0388-6 PubMedCrossRefGoogle Scholar
  39. Schweitzer F, Lao K, Family F (1997) Active random walkers simulate trunk trail formation by ants. Biosystems 41(3):153–166. doi: /10.1016/S0303-2647(96) 01670-X PubMedCrossRefGoogle Scholar
  40. Sekhon JS, Mebane WR (1998) Genetic optimization using derivatives. Polit Anal 7(1):187–210. doi: /10.1093/pan/7.1.187 Google Scholar
  41. Sumpter DJT, Beekman M (2003) From nonlinearity to optimality: pheromone trail foraging by ants. Anim Behav 66(2):273–280. doi: /10.1006/anbe.2003.2224 CrossRefGoogle Scholar
  42. Tschinkel WR (2003) Subterranean ant nests: trace fossils past and future? Palaeogeogr, Palaeoclimatol, Palaeoecol 192(1):321–333. doi: /10.1016/S0031-0182(02) 00690-9 CrossRefGoogle Scholar
  43. Tsutsui ND, Suarez AV, Holway DA, Case TJ (2000) Reduced genetic variation and the success of an invasive species. Proc Nat Acad Sci 97(11):5948–5953. doi: /10.1073/pnas.100110397 PubMedCrossRefGoogle Scholar
  44. Vittori K, Talbot G, Gautrais J, Fourcassié V, Araujo AF, Theraulaz G (2006) Path efficiency of ant foraging trails in an artificial network. J Theor Biol 239:507–515. doi: /10.1016/j.jtbi.2005.08.017 PubMedCrossRefGoogle Scholar
  45. Watmough J, Edelstein-Keshet L (1995) Modelling the formation of trail networks by foraging ants. J Theor Biol 176(3):357–371. doi: /10.1006/jtbi.1995.0205 CrossRefGoogle Scholar
  46. West GB, Brown JH, Enquist BJ (1997) A general model for the origin of allometric scaling laws in biology. Science 276(5309):122–126. doi: /10.1126/science.276.5309.122 PubMedCrossRefGoogle Scholar
  47. West GB, Brown JH, Enquist BJ (1999a) The fourth dimension of life: fractal geometry and allometric scaling of organisms. Science 284(5420):1677–1679. doi: /10.1126/science.284.5420.1677 PubMedCrossRefGoogle Scholar
  48. West GB, Brown JH, Enquist BJ (1999) A general model for the structure and allometry of plant vascular systems. Nature 400(6745):664–667. doi: /10.1038/23251 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Simon Garnier
    • 1
  • Aurélie Guérécheau
    • 1
  • Maud Combe
    • 1
  • Vincent Fourcassié
    • 1
  • Guy Theraulaz
    • 1
  1. 1.Centre de Recherches sur la Cognition AnimaleCNRS–UMR 5169, Université Paul SabatierToulouse cedex 9France

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