The relationship between clustering and networked Turing patterns
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Date
2024-07
Journal Title
Journal ISSN
Volume Title
Publisher
Chaos
Abstract
Networked Turing patterns often manifest as groups of nodes distributed on either side of the homogeneous equilibrium, exhibiting high and
low density. These pattern formations are significantly influenced by network topological characteristics, such as the average degree. However,
the impact of clustering on them remains inadequately understood. Here, we investigate the relationship between clustering and networked
Turing patterns using classical prey–predator models. Our findings reveal that when nodes of high and low density are completely distributed
on both sides of the homogeneous equilibrium, there is a linear decay in Turing patterns as global clustering coefficients increase, given a
fixed node size and average degree; otherwise, this linear decay may not always hold due to the presence of high-density nodes considered as
low-density nodes. This discovery provides a qualitative assessment of how clustering coefficients impact the formation of Turing patterns
and may contribute to understanding why using refuges in ecosystems could enhance the stability of prey–predator systems. The results
link network topological structures with the stability of prey–predator systems, offering new insights into predicting and controlling pattern
formations in real-world systems from a network perspective.
Description
This article is published by Chaos 2024 and is also available at 10.1063/5.0195450
Keywords
Citation
Chaos 34, 073114 (2024)