DOI: 10.5061/dryad.9ghx3ffh9
title: Bipartite network datasets for Permian host-plant--insect herbivory

description: Plant–insect associations have been a significant component of terrestrial
 ecology for over 400 million years. Exploring these interactions in the
 fossil record, through novel perspectives, provides a window into
 understanding evolutionary and ecological forces that shaped these
 interactions. For the past several decades, researchers have documented,
 described and categorized fossil evidence of these interactions. Drawing
 on powerful tools from network science, we propose here a bipartite
 network representation of fossilized plants and their herbivore-induced
 leaf damage to understand late Paleozoic plant–insect interactions at the
 local community level. We focus on four assemblages from north-central
 Texas, but the methods used in this work are general and can be applied to
 any well-preserved fossil flora. Network analysis can address key
 questions in the evolution of insect herbivory that often would be
 difficult to summarize using standard herbivory metrics.
description: <strong>     Network Construction from
 Data</strong>.  We constructed weighted bipartite networks using
 plant–insect associations of four floras from the latest Pennsylvanian to
 middle Permian of north-central Texas, USA (Maccracken and Labandeira,
 2020; Schachat et al., 2014; Schachat et al., 2015; Xu et al., 2017),
 where network nodes were either plant taxa (at the most highly or less
 resolved ranks) or herbivory damage types (DTs) (Labandeira et al., 2007).
 In such a network, edges represent interactions between the two nodes they
 connect, and are present only between nodes of the two different classes
 and not between those of the same class. Therefore, an edge can only be
 present between a DT and a plant taxon in our networks, and each edge
 denotes the presence of a particular DT in the plant taxon to which it is
 connected. The width (or weight) of an edge represents the number of
 occurrences of a given DT in a plant taxon. The width of each node denotes
 their respective number of occurrences. Each network is normalized
 according to its total number of DT occurrences and leaf specimens for
 each node-class. <strong>     Network
 Analysis and Metrics.</strong>  After constructing the
 weighted bipartite networks, we used the packages
 <i>bipartite</i> (Dormann et al., 2008; 2009),
 <i>vegan</i> (Oksanen et al., 2013) and <i>igraph
 </i>(Csardi and Nepusz, 2006) to calculate and display various
 network statistics associated with the network structure at each locality.
 In this analysis, we suggest network measures used for bipartite networks
 in the context of fossil herbivory networks (Table 1). As detailed below,
 we categorize the measures into five groups, depending upon what they
 measure: centrality, co-occurrence, nestedness, robustness, and
 specialization, as well as the level of study. The level of study
 indicates whether the property being quantified pertains to a single node,
 a class of nodes (such as all DTs or all plants in our case), or of the
 entire network. <strong>     Comparison with
 Modern Plant-Herbivore Interaction Networks</strong>.  In order to
 compare our reconstructed networks (Appendices S1, S2) with their modern
 counterparts, data was collected for 41 host plant–herbivore interaction
 networks, representing a variety of habitats and environmental gradients
 (Michalska-Smith and Allesina, 2019; Appendices S3–S8). Although the host
 plant class of nodes is same for both the fossil as well as current
 networks, the herbivory class is represented by DTs in the former, and by
 insect taxa in the latter. The same metrics were calculated that were
 explored for the DT networks of the four Paleozoic floras at whole network
 level and at each node class level. A principal component analysis (PCA)
 was performed of the network metrics obtained at different network levels
 (whole network and node-class levels) using the R package factoextra
 (Kassambara and Mundt, 2020) to document similarities among the localities
 and within different node-classes for the set of modern and fossil
 networks.
description: Use of the datasets are self-explanatory in the structure of the
 datasets.