Chapter

Biodiversity Conservation and Phylogenetic Systematics

Volume 14 of the series Topics in Biodiversity and Conservation pp 173-195

Open Access This content is freely available online to anyone, anywhere at any time.

Split Diversity: Measuring and Optimizing Biodiversity Using Phylogenetic Split Networks

  • Olga ChernomorAffiliated withCenter for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of ViennaBioinformatics and Computational Biology, Faculty of Computer Science, University of Vienna
  • , Steffen KlaereAffiliated withDepartment of Statistics, School of Biological Sciences, University of Auckland
  • , Arndt von HaeselerAffiliated withCenter for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of ViennaBioinformatics and Computational Biology, Faculty of Computer Science, University of Vienna
  • , Bui Quang MinhAffiliated withCenter for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna, Medical University of Vienna Email author 

Abstract

About 20 years ago the concepts of phylogenetic diversity and phylogenetic split networks were separately introduced in conservation biology and evolutionary biology, respectively. While it has been widely recognized that biodiversity assessment should better take into account the phylogenetic tree of life, it has also been widely acknowledged that phylogenetic networks are more appropriate for phylogenetic analysis in the presence of hybridization, horizontal gene transfer, or contradicting trees among genomic loci. Here, we aim to combine phylogenetic diversity and networks into one concept, split diversity (SD), which properly measures biodiversity for conflicting phylogenetic signals. Moreover, we reformulate well-known conservation questions under the SD framework and present computational methods to solve these, in general, computationally intractable questions. Notably, integer programming, a technique widely used to solve many real-life problems, serves as a general and efficient strategy that delivers optimal solutions to many biodiversity optimization problems. We finally discuss future directions for the new concept.

Keywords

Biodiversity optimization Phylogenetic diversity Phylogenetic split networks Split diversity Integer programming