Once more, kin selection and group selection

Jonathan Birch, Are kin and group selection rivals or friends? Current Biology, Volume 29, ISSUE 11, PR433-R438, June 03, 2019, https://doi.org/10.1016/j.cub.2019.01.065.

Abstract:

Kin selection and group selection were once seen as competing explanatory hypotheses but now tend to be seen as equivalent ways of describing the same basic idea. Yet this ‘equivalence thesis’ seems not to have brought proponents of kin selection and group selection any closer together. This may be because the equivalence thesis merely shows the equivalence of two statistical formalisms without saying anything about causality. W.D. Hamilton was the first to derive an equivalence result of this type. Yet Hamilton was aware of its limitations, and saw that, while illuminating, it papered over some biologically important distinctions. Attending to these distinctions leads to the concept of ‘K-G space’, which helps us see where the biological disagreements between proponents of kin selection and group selection really lie.

Definitions:

Concepts from network theory, such as the ‘clustering coefficient’ and the ‘relative density’ [20], can help us quantify, at any particular moment, the ‘groupiness’ of a social network — the extent to which it contains real, non-arbitrary social groups at that time. If we choose an appropriate measure and take a time-average for the whole population over one generation, we have a rough measure of the extent to which groups are ‘clearly in evidence’. We can define a quantity G that takes the value 1 when social groups are fully discrete and isolated from each other for long periods (as in the Haystacks model) and the value 0 when there is no population structure at all, with more realistic cases in between.

Meanwhile, the extent to which genetic correlation is explained by kinship can be quantified by comparing the locus-specific correlation with respect to the gene of interest to the average correlation across the entire genome, since only kinship can generate correlation at every locus. We can define a quantity K that takes the value 1 when all the correlation is whole-genome correlation and 0 when all the correlation is specific to the locus in question.

K-G space:

These variables lead naturally to the representational device of ‘K-G space’. A population’s place in K-G space depends on the extent to which real groups are clearly in evidence and the extent to which genetic correlation is explained by kinship. As Hamilton himself said in other words, selection in high K, low G populations seems aptly described as ‘kin selection’, whereas selection in high G, low K populations seems aptly described as ‘group selection’. In the high K, high G region we have hybrid cases that are aptly described as ‘kin-group selection’, because assortment is kin-based and groups are clearly in evidence. In these cases, there really is no meaningful debate to be had about which process is at work.

A bit further on:

What is the use of K-G space? It is an unorthodox way of thinking about the relation between kin and group selection, so there had better be some payoff for adopting this unorthodox way of thinking. Otherwise it will just lead to confusion.

The payoff, in my view, is that this representational tool helps us see what is really at stake when proponents of kin selection and group selection debate particular cases, such as the origins of eusociality or the evolution of human cooperation. These are not just non-empirical debates about which mathematical formalism we should use to describe the process. But nor are they black-and-white clashes between vastly different alternatives. They tend to be debates about where the population of interest should be located in K-G space.