Tipping points and early warning signals in complex ecosystems

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This project aims to create a theory of early warning that uses spatial data available on system state, connectivity and environmental stress, and to create tools to infer the risk of ecosystem collapse. Many ecosystems have irreversible tipping points. Since their locations are often unknown, metrics may provide an early warning of collapse but are difficult to apply because they need long time series which are usually lacking. This project will use the Great Barrier Reef as a testbed because it has both long time series (standard approach) and rich spatial data (new approach), and exhibits early warning signs. We will use these tools to gauge whether symptoms on the Great Barrier Reef predict local collapse and to develop intervention plans.