How to measure group selection in real-world populations

TL;DR

This paper explores how to empirically measure group selection in natural populations by analyzing Simpson's Paradox in bacterial biofilms, addressing the gap between theoretical models and real-world complexity.

Contribution

It introduces a framework for detecting group selection effects in natural populations through local and global frequency comparisons, focusing on practical measurement challenges.

Findings

Simpson's Paradox can indicate group selection in natural populations.

A simple bacterial biofilm model demonstrates the principle.

Measurement challenges in real-world settings are discussed.

Abstract

Multilevel selection and the evolution of cooperation are fundamental to the formation of higher-level organisation and the evolution of biocomplexity, but such notions are controversial and poorly understood in natural populations. The theoretic principles of group selection are well developed in idealised models where a population is neatly divided into multiple semi-isolated sub-populations. But since such models can be explained by individual selection given the localised frequency-dependent effects involved, some argue that the group selection concepts offered are, even in the idealised case, redundant and that in natural conditions where groups are not well-defined that a group selection framework is entirely inapplicable. This does not necessarily mean, however, that a natural population is not subject to some interesting localised frequency-dependent effects -- but how could we formally quantify this under realistic conditions? Here we focus on the presence of a Simpson's Paradox where, although the local proportion of cooperators decreases at all locations, the global proportion of cooperators increases. We illustrate this principle in a simple individual-based model of bacterial biofilm growth and discuss various complicating factors in moving from theory to practice of measuring group selection.