The evolution of complex behaviours is a major challenge in evolutionary and behavioural biology. The current “Omics” revolution in biology opens new opportunities to study this problem in molecular terms, but this requires the development of new statistical and data analyses tools. We propose to start addressing this challenge by focusing of the evolution of social complexity in insects. Research of social insects such as ants, termites, bees and wasps has provided excellent model systems for developing hypotheses and theories on the evolution of social complexity. These include seminal contributions such as the development of kin selection theory, multi-level selection theory, and the influential idea that the evolution of complexity has progressed through a series of major transitions. Currently, the evolution of social complexity in insects relies on qualitative classifications. We argue that this approach suffers from several significant limitations. These include, lumping together species showing a broad range of social complexity, and falsely implying that social evolution always progresses along a single linear stepwise trajectory that can be deduced from comparing extant species (“rungs on a ladder”). We recently showed that a single species can have both higher and lower levels of social complexity compared to other taxa, depending on the social trait measured. This study proposes a new approach which is based on measuring the complexity of individual key social traits.

Goal

Developing statistical and data analyses tools for studying social complexity within an appropriate phylogenetic framework.

Researchers

• Gili Greenbaum
• Guy Bloch

What we did

In progress