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Two strategies for optimizing the food encounter rate of termite tunnels simulated by a lattice model

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  • Lee, S.-H.
  • Bardunias, P.
  • Su, N.-Y.

Abstract

The tunneling structure of the Formosan subterranean termite, Coptotermes formosanus Shiraki, was simulated using a lattice model in order to explore a foraging strategy that optimizes food encounter rate. A tunnel was mimicked by algorithms derived from experimental data that determined the movement of a discrete unit of excavation performed by a cadre of termite workers, the tunnel vector cell (TVC). To be consistent with real tunneling behavior, tunnel propagation was terminated when TVCs did not encounter food particles within a given threshold length L1 (primary tunnel) and L2 (secondary tunnel). The simulations revealed that the length ratio between primary and secondary tunnels, γ (=L2/L1), produced a bimodal distribution of food encounter rates. The encounter rate was optimized at two values of γ because of either a searching distance effect (SDE), characterized by long primary tunnels with short branches, or a searching area effect (SAE), that balances tunnel length with branch length to cover a broad area. These two strategies reflect tunnel geometries that subterranean termites may employ in excavating tunnel patterns that optimize the rate of encountering food sources.

Suggested Citation

  • Lee, S.-H. & Bardunias, P. & Su, N.-Y., 2008. "Two strategies for optimizing the food encounter rate of termite tunnels simulated by a lattice model," Ecological Modelling, Elsevier, vol. 213(3), pages 381-388.
    • Handle: RePEc:eee:ecomod:v:213:y:2008:i:3:p:381-388
    DOI: 10.1016/j.ecolmodel.2008.01.004
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    References listed on IDEAS

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    1. G. M. Viswanathan & Sergey V. Buldyrev & Shlomo Havlin & M. G. E. da Luz & E. P. Raposo & H. Eugene Stanley, 1999. "Optimizing the success of random searches," Nature, Nature, vol. 401(6756), pages 911-914, October.
    2. Eric Bonabeau & Guy Theraulza & Jean-Louis Deneubourg & Serge Aron & Scott Camazine, 1997. "Self-Organization in Social Insects," Working Papers 97-04-032, Santa Fe Institute.
    3. P. Kirk Visscher & Scott Camazine, 1999. "Collective decisions and cognition in bees," Nature, Nature, vol. 397(6718), pages 400-400, February.
    4. Pandey, R.B. & Gettrust, J.F., 2006. "Eruptive flow response in a multi-component driven system by an interacting lattice gas simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 368(2), pages 416-424.
    5. Viswanathan, G.M & Afanasyev, V & Buldyrev, Sergey V & Havlin, Shlomo & da Luz, M.G.E & Raposo, E.P & Stanley, H.Eugene, 2001. "Lévy flights search patterns of biological organisms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 295(1), pages 85-88.
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