Network-based model of the growth of termite nests

TL;DR

This paper introduces a network growth model for termite nests that combines empirical analysis, pruning, and memory effects to predict key network properties, shedding light on their internal transportation efficiency.

Contribution

The study develops a novel model integrating pruning and memory effects to accurately simulate termite nest network growth and properties.

Findings

Model successfully predicts degree distribution and network connectivity.

Pruning strategies relate to different termite genera.

Networks favor fast transportation over defense efficiency.

Abstract

We present a model for the growth of the transportation network inside nests of the social insect subfamily Termitinae (Isoptera, termitidae). These nests consist of large chambers (nodes) connected by tunnels (edges). The model based on the empirical analysis of the real nest networks combined with pruning (edge removal, either random or weighted by betweenness centrality) and a memory effect (preferential growth from the latest added chambers) successfully predicts emergent nest properties (degree distribution, size of the largest connected component, average path lengths, backbone link ratios, and local graph redundancy). The two pruning alternatives can be associated with different genuses in the subfamily. A sensitivity analysis on the pruning and memory parameters indicates that Termitinae networks favor fast internal transportation over efficient defense strategies against ant predators. Our results provide an example of how complex network organization and efficient network properties can be generated from simple building rules based on local interactions and contribute to our understanding of the mechanisms that come into play for the formation of termite networks and of biological transportation networks in general.