Biodiversity conservation using Phylogenetics on a global scale Klaas Hartmann TAFI, University of Tasmania.

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Presentation transcript:

Biodiversity conservation using Phylogenetics on a global scale Klaas Hartmann TAFI, University of Tasmania

Extinction >100,000 extincts per year times background rate 39% of IUCN Red List species are endangered

Charismatic Megafauna

Biodiversity measures Species richness – Species definition unclear – Species distinctiveness not considered Phylogenetic diversity (PD) – Dan Faith and Ross Crozier

The Noah’s Ark Problem Species have a survival probability which can be increased at a cost Objective: maximise future expected PD Some algorithms to produce optimal solutions have been developed K. H. and M. Steel. (2006). Maximimizing phylogenetic diversity in biodiversity conservation: greedy solutions to the Noah's Ark problem. Systematic Biology 55(4), K. H. and M. Steel. Phylogenetic diversity: From combinatorics to ecology. Book chapter for: Reconstructing evolution: New mathematical and computational approaches (eds. O. Gascuel and M. Steel) Oxford University Press T. Gernhard, K. H. and M. Steel. Stochastic properties of generalised Yule models, with biodiversity applications. Journal of Mathematical Biology

NAP with uncertain parameters

Issues Too complex Difficult to integrate with existing approaches

Species Specific Indices An SSI attributes a single value to each species Some are easy to understand Examples – Pendant edge – Fair proportion – Equal splits – Shapley value

SSI vs PD D.W. Redding, K. H., A. Mimoto, D. Bokal, M. Devos and A.O. Mooers. Evolutionarily distinct species capture more phylogenetic diversity than expected. Journal of Theoretical Biology 251,

Bird EDGE 9,787 species The Data: Half of the species have sequence information All have taxonomic information Hundreds of (conflicting) expert trees How do we combine this information???

Bird EDGE approach Species are divided into patches All expert trees for a patch are combined Taxonomic information is used to enforce monophyletic genera where possible The constrained patch trees are run with a modified version of mrBayes 3.1.2

Blue Fern Two rack IBM Blue Gene/L 4096 cores 1 Terabyte RAM 11.2 Teraflops 53kW power consumption One run takes about 5 cpu years

Bird EDGE approach A BEAST skeleton tree is used to provide probability distributions of the root age for each patch EDGE Indices are produced

Acknowledgements Financial contributors: University of Canterbury (NZ) Allan Wilson Centre for Molecular Ecology and Evolution (NZ) Google Inc. (USA) Simon Fraser University (Vancouver) I am gratefully indebted to: Arne Mooers Mike Steel Walter Jetz David Redding Gavin Thomas Tanja Gernhard Too many others to list!