Reporter 450, 3 April 2000

Maths comes to the rescue of marine life

Mathematics based on chaos theory applied to satellite observations is helping in the fight against global warming - and in the survival of fish stocks in the world’s oceans.

Eye on the oceans: Professor John Brindley is mapping plankton distribution

Biologists and chemists are concerned to arrest a decline in the levels of plankton, micro-organisms essential to the future of the planet.

University mathematician John Brindley is building models to assess data collected by satellite, enabling him to map patterns of plankton growth in oceans across the world. The hope is these ‘non-linear’ models will identify areas of plankton deficiency and point to ways of enhancing stocks of these vital organisms.

Plankton shortages pose several grave environmental threats. As well as providing essential nutrition for fish, plankton also help to reduce the effects of global warming by contributing oxygen and removing carbon from the atmosphere. Their environmental role is greater than all the rain forests and other green places of the landmass put together.

"Theoretical modelling of plankton population dynamics is essential to our understanding of the physical processes involved," said Professor Brindley. "We are also able to map the consequences of plankton deficiencies for the oceans and the environment."

Professor Brindley says there are regions where conditions are optimal for plankton, but there are, nonetheless, deficiencies. Scientists believe the introduction of trace elements, such as iron, might encourage plankton growth. Professor Brindley’s mathematical models are being used to identify how much of these elements might be required.

He said: "Practical experiments were carried out in 1994 and 1996 when regions near Galapagos were seeded with soluble iron. The first failed but the second, involving a slightly different amount, succeeded. This is what appealed to me as the subject for mathematical modelling; the threshold phenomenon, the small difference explaining the failure of one experiment and the success of the other."

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