A wide variety of systems in nature and society – including fisheries, coral reefs, productive farmland, planetary climate, neural activity in the brain, and financial markets – are known to be susceptible to sudden changes leading to drastic re-organization or collapse. A variety of signals based on statistics of time-series data have been proposed that could provide generic warning signals for these so-called critical transitions. In this talk, I will propose a new method for calculating early warning signals that is complementary to existing approaches. The key step is to incorporate other available expert knowledge through the framework of a so-called generalised model. The new approach will be demonstrated through application to three ecological examples, including the simulated collapse of a fishery.
About the speaker
Steven Lade completed his PhD in the Research School of Physics and Engineering in 2010. He uses theoretical tools from mathematics and physics to develop new insights and approaches in systems ranging from the cell biological to the ecological to the psychological. He is currently between postdocs at the Max Planck Institute for the Physics of Complex Systems in Dresden, Germany, and at the Stockholm Resilience Centre in Sweden.