Quantifying Hierarchical Selection

TL;DR

This paper uses information theory to analyze the emergence of hierarchical structures in evolutionary ecology, demonstrating that groups of species can act as selective units through collective dynamics.

Contribution

It introduces a novel information-theoretic approach to quantify hierarchical selection and provides evidence of high-order structures emerging in the Tangled Nature model.

Findings

Clusters of species act as selective groups

High-order structures acquire information-theoretic agency

Hierarchical selection can emerge from simple adaptation processes

Abstract

At what level does selective pressure effectively act? When considering the reproductive dynamics of interacting and mutating agents, it has long been debated whether selection is better understood by focusing on the individual or if hierarchical selection emerges as a consequence of joint adaptation. Despite longstanding efforts in theoretical ecology there is still no consensus on this fundamental issue, most likely due to the difficulty in obtaining adequate data spanning sufficient number of generations and the lack of adequate tools to quantify the effect of hierarchical selection. Here we capitalise on recent advances in information-theoretic data analysis to advance this state of affairs by investigating the emergence of high-order structures -- such as groups of species -- in the collective dynamics of the Tangled Nature model of evolutionary ecology. Our results show that evolutionary dynamics can lead to clusters of species that act as a selective group, that acquire information-theoretic agency. Overall, our findings provide quantitative evidence supporting the relevance of high-order structures in evolutionary ecology, which can emerge even from relatively simple processes of adaptation and selection.