Condition-Dependent Effects of Tunnel Curvature on Bidirectional Termite Traffic.

Authors

Sang-Hee Lee, Cheol-Min Park, Youngjoo An

Published in

Bio Systems. Pages 105988. Oct 12, 2026. Epub Oct 12, 2026.

Abstract

Subterranean termite tunnels support bidirectional movement between nests and foraging sites, yet the influence of tunnel curvature on traffic performance remains poorly understood. We developed a non-species-specific, individual-based simulation model to examine how total tunnel turning angle, termite number, tunnel width, and wall irregularities affect traffic. A complete factorial design comprising 69,120 simulation runs was evaluated using total flow rate and a composite congestion index. Termite number and tunnel width were the dominant determinants of performance. Increasing termite number increased flow and congestion, whereas wider tunnels reduced congestion. Wall irregularities were weakly associated with flow but strongly associated with increased congestion. Turning angle showed little monotonic association with either response, and including turning-angle terms provided limited improvement in regression-model support. However, curvature-related variation was somewhat greater under high population loading and in narrow tunnels. A turning angle of 90° was the most frequently selected best-tested angle for both flow maximization and congestion minimization, although selected angles were broadly distributed. The two best-tested angles differed in 334 of 384 conditions. Small optimality margins and moderate bootstrap support indicated that many selections were weakly separated and better interpreted as near-optimal ranges than precise optima. Overall, termite number and tunnel width were better-supported determinants, whereas curvature should be interpreted cautiously as a conditional, model-predicted modifier within the tested geometry and behavioral assumptions. The model has not yet been calibrated against empirical termite traffic data, so curvature-related patterns should be regarded as mechanistic simulation predictions rather than species-specific biological optima.

PMID:
42863807
Bibliographic data and abstract were imported from PubMed on 13 Oct 2026.

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