Time-optimized path choice in the termite-hunting ant Megaponera analis

J Exp Biol. 2018 Jul 1;221(Pt 13):jeb174854. doi: 10.1242/jeb.174854.

Abstract

Trail network systems among ants have received a lot of scientific attention because of their various applications in problem solving of networks. Recent studies have shown that ants select the fastest available path when facing different velocities on different substrates, rather than the shortest distance. The progress of decision making by these ants is determined by pheromone-based maintenance of paths, which is a collective decision. However, path optimization through individual decision making remains mostly unexplored. Here, we present the first study of time-optimized path selection via individual decision making by scout ants. Megaponera analis scouts search for termite-foraging sites and lead highly organized raid columns to them. The path of the scout determines the path of the column. Through installation of artificial roads around M. analis nests, we were able to influence the pathway choice of the raids. After road installation, 59% of all recorded raids took place completely or partly on the road, instead of the direct, i.e. distance-optimized, path through grass from the nest to the termites. The raid velocity on the road was more than double that on the grass, and the detour thus saved 34.77±23.01% of the travel time compared with a hypothetical direct path. The pathway choice of the ants was similar to a mathematical model of least time, allowing us to hypothesize the underlying mechanisms regulating the behavior. Our results highlight the importance of individual decision making in the foraging behavior of ants and show a new procedure of pathway optimization.

Keywords: Decision making; Foraging strategy; Optimal foraging; Orientation; Raiding behavior; Social insect.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Ants / physiology*
  • Choice Behavior
  • Decision Making
  • Predatory Behavior*
  • Time Factors