Author
Listed:
- Zion Michael
- Thomas Chouvenc
- Nan-Yao Su
- Sang-Bin Lee
Abstract
Facilitating efficient resource transfer requires building an optimized transportation network which balances cost minimization with benefit maximization. For animals which forage for food located remotely, optimizing their transportation networks is critically related to survival. This process often involves finding and using the shortest route to save time and energy. Subterranean termites forage for wood resources by excavating underground foraging networks for search and transport. Because termites have no prior knowledge of food location during the food searching phase, establishment of a short tunnel between the nest and feeding site is difficult at the beginning of foraging. Thus, finding a short route should logically follow initial food discovery. However, it remains elusive as to how subterranean termites find the shortest route for food transportation. We simulated different scenarios using Coptotermes formosanus by providing different shapes and distances of pre-formed tunnels (straight, detour, and detour + twisting arenas) to food, where food items were located at a fixed distance from the arena entrance. Termites in the straight arena continuously used the pre-formed tunnel, showing negligible branching efforts. However, termites in the detour and detour + twisting arenas followed the pre-formed tunnel only for the initial few hours before excavating many branching tunnels. This branching activity ultimately resulted in termites finding shorter commuting routes than the pre-formed tunnels. In addition, the shortest established routes were widened over time. This study demonstrated that C. formosanus could actively alter tunnel networks to minimize the cost in food transportation by using short and wide tunnels.
Suggested Citation
Zion Michael & Thomas Chouvenc & Nan-Yao Su & Sang-Bin Lee, 2023.
"Finding shortcuts through collective tunnel excavations in a subterranean termite,"
Behavioral Ecology, International Society for Behavioral Ecology, vol. 34(3), pages 354-362.
Handle:
RePEc:oup:beheco:v:34:y:2023:i:3:p:354-362.
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