Life as a Categorical Information-Handling System: An Evolutionary Information-Theoretic Model of the Holobiont

TL;DR

This paper introduces a categorical information-theoretic model of living systems and evolution, unifying various evolutionary processes and organizational levels through information measures and category theory.

Contribution

It presents a novel categorical framework for modeling evolutionary dynamics and information processing in living systems, including holobionts, extending classical models.

Findings

Evolutionary change can be expressed as Jeffreys divergence.

Categorical models unify simple and complex evolutionary scenarios.

Information measures distinguish different types of evolutionary transformations.

Abstract

Living systems can be understood as organized entities that capture, transform, and reproduce information. Classical gene-centered models explain adaptation through frequency changes driven by differential fitness, yet they often overlook the higher-order organization and causal closure that characterize living systems. Here we revisit several evolutionary frameworks, from the replicator equation to group selection and holobiont dynamics, and show that evolutionary change in population frequencies can be expressed as a Jeffreys divergence. Building on this foundation, we introduce a categorical model of Information Handlers (IH), entities capable of self-maintenance, mutation, and combination. This abstract architecture illustrates the usefulness of category theory for framing evolutionary processes that range from very simple to highly complex. The same categorical scheme can represent basic allele-frequency change as well as more elaborate scenarios involving reproductive interactions, symbiosis, and other organizational layers. A key feature of the framework is that different levels of evolutionary change can be summarized through a measure that quantifies the information generated, thereby distinguishing diverse types of evolutionary transformation such as individual and sexual selection, mate choice, or even holobiont selection. Finally, we show that the informational partition associated with host-microbiome pairings in holobionts generalizes the information-theoretic structure previously developed for non-random mating, revealing a common underlying architecture across biological scales.