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Exploring the efficiency of termite food transportation in a sinusoidal-shaped tunnel

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  • Lee, Sang-Hee
  • Park, Cheol-Min
  • Lee, Sang-Bin

Abstract

From an evolutionary perspective, it is inferred that termites evolved to build tunneling patterns in a way that optimizes search and transport efficiency. So far, there have been many studies on search efficiency, but few studies on transport efficiency due to the difficulty of direct observation under the field condition. To overcome the difficulty, we developed an individual-based model to simulate the transport process. The model was characterized by four variables: (1) the frequency of food transfer (PT), (2) the loss of food during transfer (PL), (3) the effect of tunnel curvature (PC), and (4) the number of individuals participating in the transport (N0). We explored the effect of the variables on the efficiency of food transport (E). When the distance between the food site and the nest was short, food transport with PT = 0 was advantageous for high E, whereas for long and narrow tunnels with high traffic jam frequency, transport with PT > 0 could be rather advantageous for the increase of E. Another finding was that PT had the greatest effect on E, followed by PL, and third on PC. N0 had the least impact. In the discussion section, we discussed strategies that termites could take to optimize E with respect to the findings and presented ideas worth exploring experimentally. In addition, we briefly mentioned how the model could be improved to be more realistic.

Suggested Citation

  • Lee, Sang-Hee & Park, Cheol-Min & Lee, Sang-Bin, 2022. "Exploring the efficiency of termite food transportation in a sinusoidal-shaped tunnel," Ecological Modelling, Elsevier, vol. 474(C).
  • Handle: RePEc:eee:ecomod:v:474:y:2022:i:c:s0304380022002770
    DOI: 10.1016/j.ecolmodel.2022.110180
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    References listed on IDEAS

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    1. Ronald L. Iman & Jon C. Helton, 1988. "An Investigation of Uncertainty and Sensitivity Analysis Techniques for Computer Models," Risk Analysis, John Wiley & Sons, vol. 8(1), pages 71-90, March.
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