Multi‐level framework to assess social variation in response to ecological and social factors: modeled with coral gobies

Abstract

Understanding variation in social organization that lacks a strong phylogenetic signal represents a key focus of research in behavioural ecology. Accordingly, we established a framework that identifies whether a range of ecological and social factors are affecting the social maintenance of taxa across multiple categories of social variation (ranging from large to fine‐scale): 1) forms of sociality, 2) degree of sociality, 3) social plasticity and 4) hierarchy maintenance. Each category of variation can then be assessed in combination to provide an outlook for social maintenance in light of predictor factors. We modelled this framework by quantifying each category over time, space and disturbance regime using multiple species of coral‐dwelling gobies, genus Gobiodon. Gobies are an interesting model system as they vary in social structure, have within‐group cooperation, and form mutualisms with coral hosts, which are vulnerable to climatic disturbances. We found that gobies varied in forms of sociality – from being more solitary or pair‐forming in high disturbance regimes, versus group‐forming in moderate disturbance regimes at some locations. Only low or moderate degrees of sociality were observed in gobies, with location or disturbance regime affecting some species. The size of coral hosts influenced the social plasticity of gobies, which was affected by climatic disturbances. Gobies did not exhibit direct changes to hierarchy maintenance, as location and disturbance regime did not affect their size‐based hierarchies. Lastly, by combining the four categories of variation, we found a high loss of sociality in coral‐dwelling gobies due to environmental disturbances, which likely affects overall goby survival as group‐forming can improve survival and fitness. By using our structured framework, we identified which categories of social variation were influenced by ecological factors like location and disturbance. This framework therefore provides an excellent tool for predicting future responses of animal societies to environmental stressors.