Directionality measures in evolutionary ecological networks: Insights from the Tangled Nature model

TL;DR

This paper explores how network analysis metrics like entropy, diversity, and clustering can reveal the directionality and stability of evolutionary trends in ecological systems, using the Tangled Nature model as a case study.

Contribution

It introduces a network-based approach to quantify evolutionary directionality and stability in ecological models, specifically applying it to the Tangled Nature model.

Findings

Network entropy correlates with system stability.

Species diversity indicates evolutionary trends.

Clustering coefficient reflects system directionality.

Abstract

The myriad microscopic interactions among the individual organisms that constitute an ecological system collectively give rise, at the macroscopic scale, to evolutionary trends. The ability to detect the directionality of such trends is crucial for understanding and managing the dynamics of natural systems. Nevertheless, identifying the key observable quantities that capture such directional behaviour poses a major challenge. In this study, we propose that translating ecological data into a network framework is a valuable strategy to measure system stability and evolution. We examine the Tangled Nature model as a test case, evaluating network entropy, species diversity, and the clustering coefficient as metrics of network stability and directionality.