‘ILSM': a package to analyze the interconnection structure of tripartite interaction networks

In natural or human‐disturbed ecosystems, ecological networks often comprise multiple interaction types, which have been increasingly represented by multipartite ecological networks. One important aspect of their network architecture is how different interaction types or subnetworks are interconnected by connector species, here defined as the interconnection structure. Previous studies have proposed various indices of connector species to characterize macro‐scale interconnection patterns and micro‐scale centrality, but the meso‐scale interconnection structures (here defined as interconnection motifs) remain largely unexplored. Furthermore, there is no package available in the R programming language for conducting analyses of various interconnection structures. Within a tripartite network with two interaction subnetworks, we define the forms of interconnection motifs and unique roles within these motifs. Then we introduce the R package ‘ILSM' for analyzing interconnection pattern, interconnection centrality, and interconnection motif for unweighted and weighted networks. Specifically, we derive mathematical expressions for the frequencies of interconnection motifs and species roles within motifs. We describe the main functions in the package and demonstrate their uses with an example pollinator–plant–herbivore network. In addition, we show that interconnection motifs can reveal additional variation beyond interconnection patterns and centrality using empirical tripartite interaction networks. ‘ILSM' will help ecologists understand how different types of interactions are interconnected by shared species using interconnection pattern, centrality, and motif.

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Publication Details

Journal
Ecography
Published
2025-10-10
DOI
https://doi.org/10.1002/ecog.07823
Primary Topic
Plant and animal studies
Type
article
Field-Weighted Citation Impact
0.00

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article

‘ILSM': a package to analyze the interconnection structure of tripartite interaction networks

Yangyang Zhao, Chuan Yan, W. Sun
Ecography
Plant and animal studies
article

‘ILSM': a package to analyze the interconnection structure of tripartite interaction networks

Yangyang Zhao, Chuan Yan, W. Sun
article en

Abstract

In natural or human‐disturbed ecosystems, ecological networks often comprise multiple interaction types, which have been increasingly represented by multipartite ecological networks. One important aspect of their network architecture is how different interaction types or subnetworks are interconnected by connector species, here defined as the interconnection structure. Previous studies have proposed various indices of connector species to characterize macro‐scale interconnection patterns and micro‐scale centrality, but the meso‐scale interconnection structures (here defined as interconnection motifs) remain largely unexplored. Furthermore, there is no package available in the R programming language for conducting analyses of various interconnection structures. Within a tripartite network with two interaction subnetworks, we define the forms of interconnection motifs and unique roles within these motifs. Then we introduce the R package ‘ILSM' for analyzing interconnection pattern, interconnection centrality, and interconnection motif for unweighted and weighted networks. Specifically, we derive mathematical expressions for the frequencies of interconnection motifs and species roles within motifs. We describe the main functions in the package and demonstrate their uses with an example pollinator–plant–herbivore network. In addition, we show that interconnection motifs can reveal additional variation beyond interconnection patterns and centrality using empirical tripartite interaction networks. ‘ILSM' will help ecologists understand how different types of interactions are interconnected by shared species using interconnection pattern, centrality, and motif.

EcographyVol. 2025(11)
Lanzhou University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 77%
Plant and animal studies
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