Nested structure acquired through simple evolutionary process

TL;DR

This paper introduces an evolving network model demonstrating that simple evolutionary processes can naturally produce nested structures and heterogeneous connectivity in plant-animal mutualistic networks, offering new insights into their formation.

Contribution

It presents a novel evolutionary network model that explains the emergence of nested structures and connectivity heterogeneity in mutualistic networks, expanding beyond static models.

Findings

Nested structures can be predicted through simple evolutionary processes.

Evolutionary models can replicate real network patterns.

Provides an alternative explanation for network formation.

Abstract

Nested structure, which is non-random, controls cooperation dynamics and biodiversity in plant-animal mutualistic networks. This structural pattern has been explained in a static (non-growth) network models. However, evolutionary processes might also influence the formation of such a structural pattern. We thereby propose an evolving network model for plant-animal interactions and show that non-random patterns such as nested structure and heterogeneous connectivity are both qualitatively and quantitatively predicted through simple evolutionary processes. This finding implies that network models can be simplified by considering evolutionary processes, and also that another explanation exists for the emergence of non-random patterns and might provide more comprehensible insights into the formation of plant-animal mutualistic networks from the evolutionary perspective.