Data for: Collective signalling is shaped by feedbacks between signaller variation, receiver perception, and acoustic environment in a simulated communication network

Communication takes place within a network of multiple signallers and
receivers. Social network analysis provides tools to quantify how an
individual’s social positioning affects group dynamics, and the subsequent
biological consequences. However, network analysis is rarely applied to
animal communication, likely due to the logistical difficulties of
monitoring natural communication networks. We generated a simulated
communication network to investigate how variation in individual
communication behaviours generates network effects, and how this
communication network’s structure feeds back to affect future signalling
interactions. We simulated competitive acoustic signalling interactions
among chorusing individuals and varied several parameters related to
communication and chorus size to examine their effects on calling output
and social connections. Larger choruses had higher noise levels, and this
reduced network density and altered the relationships between individual
traits and communication network position. Hearing sensitivity interacted
with chorus size to affect both individuals’ positions in the network and
the acoustic output of the chorus. Physical proximity to competitors
influenced signalling, but a distinctive communication network structure
emerged when signal active space was limited. Our model raises novel
predictions about communication networks that could be tested
experimentally, and identifies aspects of information processing in
complex environments that remain to be investigated.