In conservation biology it is a central problem to measure, predict, and preserve biodiversity as species face extinction. One popular approach to this is to measure the diversity of a collection of species in terms of the evolutionary diversity spanned by those species on the `tree of life', a measure that is commonly referred to as phylogenetic diversity. Building on this approach, there has been much interest in setting up a framework that will enable conservation biologists to also take other important aspects into account, such as dependencies between certain species or budgetary constraints. We have developed algorithms that efficiently identify collections of species with high diversity in the presence of reticulate evolution [1] or relative to a collection of gene trees [2]. We have also extended these approaches to take into account geographical constraints, work that commenced in [3].


  1. Spillner,A., Nguyen,E., Moulton, V., Computing phylogenetic diversity for split systems,  IEEE/ACM Computational Biology and Bioinformatics, 5, 2008, 235-244
  2. Bordewich, M., Semple, C., Spillner, A., Optimizing phylogenetic diversity across two trees. , Isaac Newton Institute Preprint Series. NI07068-PLG (2007).
  3. Moulton, V., Semple,C., Steel, M., Optimizing phylogenetic diversity under constraints,  Journal of Theoretical Biology, 246, 2007, 186-194.