Biodiversity conservation using Phylogenetics on a
global scale
Klaas Hartmann
TAFI, University of Tasmania
Extinction
• >100,000 extincts per year
• 100-1000 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), 644-651.
• 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, 606-615.
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!