American Society of Naturalists

A membership society whose goal is to advance and to diffuse knowledge of organic evolution and other broad biological principles so as to enhance the conceptual unification of the biological sciences.

Synthesis: “The complexity of social complexity: a quantitative multidimensional approach for studies on social organization”

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Jacob George Holland and Guy Bloch (Nov 2020)

Social complexity evolution is not ladderlike as assumed: quantifying individual social traits provides better direction

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How did complex animal societies evolve from solitary ancestors? Animals such as species of bees, ants, and wasps, live in social groups which determine many aspects of their biology. In some species these associations are loose, but in others individuals are entirely dependant on one another for daily life. Some of these groups resemble a “superorganism”, with incredible coordination between large numbers of specialised individuals. Many social insects are ecologically significant and economically important, further urging the need to understand their biology. The common research approach has assumed that there is a series of neat stages of social complexity that need to be passed in order to reach the highest level, like climbing rungs on a ladder. We propose that, instead, complexity should be measured separately for multiple social traits, such as colony size or the amount of individual specialisation. We focus on bumble bees, which provide a nice example of limitations in the current approach, because their social complexity has been defined quite differently across studies. Moreover, some of their social traits are relatively simple, such as small colonies, and reproduction by females other than the queen (“worker” bees); whereas other traits are socially complex, such as workers which vary greatly in size and perform different roles. Our approach overcomes these limitations and allows us to distinguish between species that are currently defined as having the same level of social complexity, despite substantial variation in some of their social traits. Our approach also makes it easier to understand how different social traits might be linked to specific molecular or behavioural mechanisms that have been important for the evolution of social complexity.


The rapid increase in “big data” of the post-genomic era makes it crucial to appropriately measure the level of social complexity in comparative studies. We argue that commonly used qualitative classifications lump together species showing a broad range of social complexity, and falsely imply that social evolution always progresses along a single linear stepwise trajectory that can be deduced from comparing extant species. To illustrate this point, we compared widely used social complexity measures in "primitively eusocial" bumble bees with “advanced eusocial” stingless bees, honey bees, and attine ants. We find that a single species can have both higher and lower levels of complexity compared to other taxa, depending on the social trait measured. We propose that measuring the complexity of individual social traits switches focus from semantic discussions and offers several directions for progress. Firstly, quantitative social traits can be correlated with molecular, developmental, and physiological processes within and across lineages of social animals. This approach is particularly promising for identifying processes that influence or have been affected by social evolution. Secondly, key social complexity traits can be combined into multidimensional lineage-specific quantitative indices enabling fine scale comparison across species that are currently bundled within the same level of social complexity.