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

This dataset ‘Example_Interaction_Data’ comprises the empirical interaction data used in the ILSM R package for analyzing tripartite ecological network structure. The dataset contains quantitative interaction matrices from 49 distinct tripartite networks, systematically organized into two major ecological system types: 31 Pollinator-Plant-Herbivore networks and 18 Plant-Herbivore-Parasitoid networks.
This dataset ‘ILSM_Function‘ supports the ILSM R package for analyzing interconnection structures in tripartite ecological networks. The package provides computational functions to quantify 48 interconnection motifs, species roles, and network-level patterns in tripartite interaction systems. Key functionalities include motif frequency analysis using matrix-based algorithms, connector species role assessment, interconnection centrality metrics, and null model generation for statistical testing. The tools handle both binary and weighted networks, supporting the analysis of ecological sy..., , # Data from: 'ILSM': A package to analyze the interconnection structure of tripartite interaction networks

In this example of the softnote, we collected two types of tripartite ecological network: 

Plant-herbivore-parasitoid (PHP) and pollinator-plant-herbivore (PPH) networks are two kinds of commonly studied tripartite networks, with antagonistic-antagonistic interactions and mutualistic-antagonistic subnetworks, respectively. They also have different connector nodes, herbivores in PHP networks, and plants in PPH networks.

## Description of the data and file structure

The \"Example Interaction Data.Zip\" contains the interaction network data for all examples, and \"ILSM_Function.zip\" contains the source function code for the R package. 

### Files and variables

#### File: Example_Interaction_Data.zip

**Description:** Data for example analyses: 31 Pollinator-Plant-Herbivore networks and 18 Plant-Herbivore-Parasitoid networks.

## Data Structure and ...,