Protocol to record multiple interaction types in small social groups of birds.

Here, we present a protocol for collecting data on multiple interaction types in small, stable groups of Arabian babblers (Argya squamiceps). We describe the procedure of habituation, the recording of social interactions, and how to classify the interaction types. Additionally, we provide code for testing, comparing, and visualizing data. The high-resolution data collection is time demanding and requires several data tests before forming the final protocol. The collected data can then be used for multiplex social network analysis. For complete details on the use and execution of this protocol, please refer to Dragic et al. (2021).

Multilayer social networks reveal the social complexity of a cooperatively breeding bird.

The social environment of individuals affects various evolutionary and ecological processes. Their social environment is affected by individual and environmental traits. We assessed the effects of these traits on nodes and dyads in six layers of networks of Arabian babblers, representing different interaction types. Additionally, we tested how traits affect social niches in the multilayer networks using the t-distributed stochastic neighbor embedding (tSNE) dimensionality reduction algorithm. The effect of group size and season was similar across network layers, but individual traits had different effects on different layers. Additionally, we documented assortativity with respect to individual traits in the dominance display and allopreening networks. The joint analysis of all six layers revealed that most traits did not affect individuals' social niches. However, older individuals occupied fewer social niches than younger ones. Our results suggest that multilayer social networks are an important tool for understanding the complex social systems of cooperative breeders and intragroup interactions.