Transfer entropy analysis reveals interaction dynamics between termite castes

Termites exhibit complex social structures characterized by distinct castes, each playing specialized roles within the colony. This study explores the interaction dynamics between the worker and soldier castes of Reticulitermes lucifugus using a transfer entropy framework. Inter-individual interactions were investigated across three caste pairings (worker with worker, soldier with soldier, and worker with soldier), enabling direct comparison of interaction dynamics. A computer vision pipeline tracked movements, and two variables, occupied area and speed, were analyzed as proxies for interaction. Transfer entropy quantified the amount, direction, and timing of information transfer. Sampling resolution and time lags were systematically varied to map temporal scales of influence. The working assumption was that higher transfer entropy values reflect a higher level of interaction between individuals. First, in the temporal-resolution analysis of speed, worker–worker pairs showed the highest total transfer entropy, and mixed pairs exhibited directional asymmetry, with higher information flow from soldiers to workers than vice versa. Second, in the time-lag analysis, total transfer entropy for occupied area was higher in worker–worker pairs (1.04 bits), compared with soldier–soldier (0.67 bits) and mixed (0.68 bits) pairs. The same pattern held for speed, with worker–worker pairs reaching 0.25 bits, whereas soldier–soldier and mixed pairs reached 0.20 bits. Overall, results indicate caste-specific interaction dynamics, with worker-worker pairs exhibiting a higher level of interaction. These insights advance understanding of termite social organization and suggest applications in pest management, with broader implications for swarm intelligence and bio-inspired engineering. • Termite societies rely on caste-based roles and complex communication strategies. • Transfer entropy revealed termites' caste-specific interaction dynamics. • Temporal scales and information flow directionality were investigated. • Worker-worker pairs showed the highest total transfer entropy. • Findings support improved pest control strategies and swarm robotics design.