Measuring community similarity with phylogenetic networks.
Environmental drivers of biodiversity can be identified by relating patterns of community similarity to ecological factors. Community variation has traditionally been assessed by considering changes in species composition and more recently by incorporating phylogenetic information to account for the relative similarity of taxa. Here, we describe how an important class of measures including Bray-Curtis, Canberra, and UniFrac can be extended to allow community variation to be computed on a phylogenetic network. We focus on phylogenetic split systems, networks that are produced by the widely used median network and neighbor-net methods, which can represent incongruence in the evolutionary history of a set of taxa. Calculating β diversity over a split system provides a measure of community similarity averaged over uncertainty or conflict in the available phylogenetic signal. Our freely available software, Network Diversity, provides 11 qualitative (presence-absence, unweighted) and 14 quantitative (weighted) network-based measures of community similarity that model different aspects of community richness and evenness. We demonstrate the broad applicability of network-based diversity approaches by applying them to three distinct data sets: pneumococcal isolates from distinct geographic regions, human mitochondrial DNA data from the Indonesian island of Nias, and proteorhodopsin sequences from the Sargasso and Mediterranean Seas. Our results show that major expected patterns of variation for these data sets are recovered using network-based measures, which indicates that these patterns are robust to phylogenetic uncertainty and conflict. Nonetheless, network-based measures of community similarity can differ substantially from measures ignoring phylogenetic relationships or from tree-based measures when incongruent signals are present in the underlying data. Network-based measures provide a methodology for assessing the robustness of β-diversity results in light of incongruent phylogenetic signal and allow β diversity to be calculated over widely used network structures such as median networks.
Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada. donovan.parks@gmail.com
Donovan H
DH
Parks
Robert G
RG
Beiko
D044822:Biodiversity; D058448:Biota; D004272:DNA, Mitochondrial / Q000235:genetics; D014644:Genetic Variation; D005828:Genetics, Population / Q000379:methods; D006801:Humans; D007214:Indonesia; D008962:Models, Theoretical; D058885:Multilocus Sequence Typing; D010802:Phylogeny; D012243:Rhodopsin / Q000235:genetics; D025604:Rhodopsins, Microbial; D012984:Software; D013296:Streptococcus pneumoniae / Q000235:genetics
D004272:DNA, Mitochondrial; D025604:Rhodopsins, Microbial; C413548:proteorhodopsin; D012243:Rhodopsin