Allocating Berths on Noah’s Ark
University of Canterbury mathematicians, Professor Mike Steel and Dr
Charles Semple, have won a Marsden grant to develop mathematics that
will help in the conservation of biodiversity.
We are currently witnessing the sixth major extinction in the history
of life on Earth – but this time it is more rapid than any that has
come before. How can we best conserve the species we have left? To be
able to do this effectively, methods must be developed that allow
biodiversity loss to be accurately measured and predicted. Also, given
a limited budget, how can we decide which species should be conserved
to maximise future biodiversity? This is known as the ‘Noah’s Ark
problem’.
Recently, mathematics, statistics and computer science have begun to
play a crucial role in measuring and analysing biodiversity, and in
creating ways to allocate resources to maximise it in the future.
Previously, the team has developed techniques for dealing with the
large sets of DNA data that are used in biodiversity theory. Now, they
will extend this work. The new project has two objectives: First, they
will calculate how we can maximise future biodiversity, given the
extinction risk of each species. Second, they will develop and apply
models to predict how biodiversity might decline under various
extinction scenarios.
The research requires the development of new theories and methods,
rather than simply applying existing ones to new problems. The results
are likely to find a wide application, and the team will work closely
with biologists who wish to use their findings on their own sets of
data, to help solve some of today’s big issues in conservation.
Total Funding: $493,431
Researchers: Professor Mike Steel, Biomathematics
Research Centre, Department of Mathematics and Statistics, University
of Canterbury, Christchurch.
Dr Charles Semple, University of Canterbury
Associates: Professor Vincent Moulton, University of
East Anglia, UK
Dr Elchanan Mossel, UC Berkeley, USA
Dr Arne Mooers, Simon Fraser University, Canada
