DOI: 10.5061/dryad.h9w0vt4n7
title: Data from: Predicting primate-parasite associations with exponential random graph models

description: Ecological associations between hosts and parasites are influenced by host
 exposure and susceptibility to parasites, and by parasite traits, such as
 transmission mode. Advances in network analysis allow us to answer
 questions about the causes and consequences of traits in ecological
 networks in ways that could not be addressed in the past. We used a
 network-based framework (exponential random graph models, or ERGMs) to
 investigate the biogeographic, phylogenetic, and ecological
 characteristics of hosts and parasites characteristics that affect the
 probability of interactions among nonhuman primates and their parasites.
 Parasites included arthropods, bacteria, fungi, protozoa, viruses, and
 helminths. We investigated existing hypotheses, along with new predictors
 and an expanded host-parasite database that included 213 primate nodes,
 763 parasite nodes, and 2,319 edges among them. Analyses also investigated
 phylogenetic relatedness, sampling effort, and spatial overlap among
 hosts. In addition to supporting some previous findings, our ERGM approach
 demonstrated that more threatened hosts had fewer parasites, and notably,
 that this effect was independent of threatened hosts also having a smaller
 geographic range. Despite having fewer parasites, threatened host species
 shared more parasites with other hosts, consistent with the loss of
 specialist parasites and threats arising from generalist parasites that
 can be maintained in other, non-threatened hosts. Viruses, protozoa, and
 helminths had broader host ranges than bacteria or fungi, and parasites
 that infect non-primates had a higher probability of infecting more
 primate species. The value of the ERGM approach for investigating the
 processes structuring host-parasite networks provided a more complete view
 of the biogeographic, phylogenetic, and ecological traits that influence
 parasite species richness and parasite sharing among hosts. The results
 supported some previous analyses and revealed new associations that
 warrant future research, thus revealing how hosts and parasites interact
 to form ecological networks.
description: We extracted data from the Global Primate Parasite Database
 (parasites.nunn-lab.org), which is part of the Global Mammal Parasite
 Database (Nunn & Altizer 2005; Stephens <em>et
 al</em>. 2017). The version used in this study was downloaded on
 February 25, 2019, and included over 7,900 lines of host-parasite records,
 improving on the ~6,300 records in the previous compilation (Gómez
 <em>et al</em>. 2013). We culled this dataset to include only
 hosts identified at the species level, and parasites identified at the
 species or genus level. For host species, the database generally followed
 a standardized mammalian taxonomy (Wilson & Reeder 2005), though
 for more recently added taxa that were in the database, the species-level
 taxonomy was taken from the authors of the paper and matched to the
 species in the phylogeny, described below. For most parasites, the species
 level could be accurately recorded, but for cases in which species-level
 parasite data were available for a parasite genus on a host, the records
 listed as ‘sp.’ were omitted. This resulted in data for 213 primate hosts
 and 763 parasites, compared to 140 priates and 300 parasites in recent
 work (Gómez <em>et al</em>. 2013).
 <em>Node- and dyad-level variables</em>: We searched
 the literature for data on the host and parasite phenotypes and ecology.
 We included characters that are specific to the nodes (node-level
 attributes), as well as dyad-level attributes, or pair-wise associations
 among nodes. All data are available in the supplementary information
 Appendix S1-4. Continuous variables were z-score transformed before
 analyses.
description: Datasets are saved as .csv files and can be opened with any text
 reader. 'R' code to run analysis is a '.R' file,
 requiring the software 'R' and the associated
 packages.