DOI: 10.5061/dryad.3q11m8g
title: Data from: Biogeographical network analysis of cretaceous terrestrial tetrapods: a phylogeny-based approach

description: Network methods are widely used to represent and analyse biogeography. It
 is difficult, however, to convert occurrence data of fossil vertebrates to
 a biogeographical network, as most species were known from a single
 locality. A new method for creating a biogeographical network that can
 incorporate phylogenetic information is proposed in this study, which
 increases the number of edges in the network of fossil vertebrates and
 enables the application of various network methods. Using ancestral state
 reconstruction via maximum parsimony, the method first estimates the
 biogeographical regions of all internal nodes of a given phylogeny using
 biogeographical information on the terminal taxa. Then, each internal node
 in the phylogenetic tree is converted to an edge in the biogeographical
 network that connects the region(s), if unambiguously estimated, of its
 two descendants. The new method was applied to phylogenetic trees
 generated by a birth-death model. Under all conditions tested, an average
 of &gt;70% of the internal nodes in phylogenetic trees were converted
 into edges. Three network indices—link density, average link weight, and
 endemism index—were evaluated for their usefulness in comparing different
 biogeographical networks. The endemism index reflects the rate of
 dispersal; the other indices reflect nonbiogeographical parameters, the
 number of taxa and regions, which highlights the importance of evaluating
 network indices before applying them to biogeographical studies. Multiple
 Cretaceous biogeographical networks were constructed from the phylogenies
 of ﬁve tetrapod taxa: terrestrial crocodyliforms, terrestrial turtles,
 non-avian dinosaurs, avians, and pterosaurs. The networks of avians and
 pterosaurs showed similar topologies and a strong correlation, and
 unexpectedly high endemism indices. These similarities were probably a
 result of shared taphonomic biases (i.e., the Lagerstätten effect) for
 volant taxa with fragile skeletons. The crocodyliform network was
 partitioned into the Gondwanan and Laurasian continents. The dinosaur
 network was partitioned into three groups of continents: (1) North
 America, Asia, and Australia; (2) Europe and Africa; (3) India,
 Madagascar, and South America. When Early and Late Cretaceous dinosaurs
 were analysed separately, the dinosaur networks were divided into (1)
 North America, Asia, and Australia; and (2) Europe, Africa, India, and
 South America for the Early Cretaceous and (1) North America, Asia, and
 Europe; (2) India, Madagascar, and South America for the Late Cretaceous.
 This partitioning of dinosaur and crocodyliform networks corroborates the
 results of previous biogeographical studies and indicates that the method
 introduced here can retrieve biogeographical signals from a source
 phylogeny when sufficient data are available for most targeted
 biogeographical regions.
description: bdtree
 resultsThe results of
 simulations for testing rate of unusable node and utility of network
 indices. The file includes means and variances of the ratio of unusable
 nodes and the three indices LD, ALW and EI for each q value, number of
 taxa, and number of areas. The number of simulations in which the ALW
 could not be calculated was also recorded in the file.data and
 treePhylogenetic trees, age
 and biogeographical data for terrestrial crocodyliforms, terrestrial
 turtles, non-avian dinosaurs, avians, and pterosaurs that were used to
 construct biogeographical networks.rcode0801Code for R (R Development Core Team 2017) that calculates an adjacency matrix from a phylogenetic tree and the biogeographical regions of all terminal taxa. If age information is provided for all terminal taxa, then this code can conduct time slicing.results of taxa dropping simulationsResults of simulation that test the effect of taxa pruning from a phylogenetic tree on the constructed biogeographical network. These taxa pruning correspond to sampling and taphonomic biases on fossil taxa.Fig. S5An animation of 3D scatter plot of mean ALW.mean ALW bdtree .gifFig. S7An animation of 3D scatter plot of mean EI.mean EI bdtree .gifFig S3An animation of 3D scatter plot of mean LD.mean LD bdtree .gifFig. S1An animation of 3D scatter plot of mean ration of unusable nodes.mean ratio of unusable nodes.gifFig. S6An animation of 3D scatter plot of variance of ALW.var ALW bdtree .gifFig. S8An animation of 3D scatter plot of variance of EI.var EI bdtree .gifFig S4An animation of 3D scatter plot of variance of LD.var LD bdtree .gifFig S2An animation of 3D scatter plot of variance of the ratio of unusable nodes.var of unusable nodes.gif