Data for Effects of habitat structure and individual variation in a simulated acoustic communication network

Advances in technology are making it possible to characterize whole communication networks, which has important implications for the understanding of animal communication and social behaviour. An important next step is to experimentally manipulate variables that impact network structure, but such studies are still rare. There are multiple sources of variation that, while known to impact individual communication interactions and on signal evolution more broadly, have received limited attention for their effects on animal communication networks. To generate ideas and predictions for future experimental work, I used a computer simulation of competitive interactions in an acoustic communication network to test the effects of 1) variation in vegetation level in the habitat, leading to variation in the excess attenuation of acoustic signals, and 2) individual variation in signal characteristics, specifically the presence of a ‘behavioural outlier’ with either especially loud signals, especially long duration signals or especially sensitive hearing. I tested the effects of these variables on measures of both individual behaviour and communication network structure. In general, increasing vegetation levels led to decreased network connectivity and greater network modularity, but in a few cases network connectivity actually increased because vegetation reduced high levels of background noise. Behavioural outliers had limited impact at the network level, but did affect multiple aspects of individual behaviour. These effects were strongest on individuals nearest to the behavioural outliers but also extended to many other nearby individuals in the network. Many of the results depended on group size, indicating potential feedbacks between space use, individual variation and communication network structure. Future experimental studies of communication networks should therefore aim to measure heterogeneity in environmental factors that affect signal transmission and how spatial positioning interacts with individual communication variation to drive interactions in the network.