Modelling animal social networks: New solutions and future directions

Abstract

Research Highlight: Ross, C. T., McElreath, R., & Redhead, D. (2023). Modelling ani-mal network data in R using STRAND. Journal of Animal Ecology. https://doi. org/10.1111/1365-2656.14021. One of the most important insights in ecology over the pastdecade has been that the social connections among animals affect a wide range ofecological and evolutionary processes. However, despite over 20 years of study efforton this topic, generating knowledge from data on social associations and interactionsremains fraught with problems. Redhead et al. present an R package—STRAND—thatextends the current animal social network analysis toolbox in two ways. First, theyprovide a simple R interfaces to implement generative network models, which arean alternative to regression approaches that draw inference by simulating the data-generating process. Second, they implement these models in a Bayesian framework,allowing uncertainty in the observation process to be carried through to hypothesistesting. STRAND therefore fills an important gap for hypothesis testing using net-work data. However, major challenges remain, and while STRAND represents an im-portant advance, generating robust results continues to require careful study design,considerations in terms of statistical methods and a plurality of approaches.