Unravelling southwest Indian Ocean biological productivity and physics: a machine learning approach

The Mozambique channel and Madagascan waters are a region of the southwestern Indian Ocean with complex circulation patterns that play a key role in the distribution of marine species and regulation of local ecosystems [1]. Unsupervised machine learning techniques can help classify the nonlinear interactions of these circulation patterns and determine those impacting biological productivity [2], where local economies are dependent on marine living resources. Although the flows around Madagascar are known to affect the southern Mozambique channel, they may also influence dynamics farther north because of high eddy activity within the channel. The anticyclonic and cyclonic eddies result in warmer and cooler conditions [3], affecting nutrient distributions. This then impacts phytoplankton, zooplankton, fish and higher trophic levels, and the northern part of the channel that is on the annual migration routes of the Indian Ocean tuna stocks [1]. The biological effects of the eddies aren’t fully understood but, in a changing climate, could affect the fisheries on which local populations depend both for food and livelihoods. This project will apply machine learning to long-term satellite and in situ observations to unravel the effects of the mesoscale dynamics around Madagascar and in the Mozambique Channel on biological productivity there. 

For full project details visit the Inspire project page.