Final Report Summary - EARLYWARNING (Generic Early Warning Signals for Critical Transitions) Sudden shifts in complex systems such as the climate, financial markets, ecosystems and even the human body can be preceded by surprisingly comparable warning signals. Marten Scheffer and colleagues postulated this idea in a Nature publication in 2009 based on mathematical models. In this ERC project Scheffer and colleagues further develop this idea and try to find evidence for these signals in various systems, such as experimental controlled ecosystems, in the climate and in the mood of depressed patients. At first glance, it appears improbable that a climate shift, an epileptic seizure, the collapse of an ecosystem or a sudden transition in a financial system have something in common. However, all these completely different systems obey certain universal laws when they are close to a tipping point. This has to do with a phenomenon that is known in mathematics as ‘Critical Slowing Down’, implying that recovery from small perturbations becomes slow in the vicinity of tipping points. In this project direct evidence for critical slowing down was found in a collapsing population of cyanobacteria (blue-green algae), in the mood of depressed people, in remote-sensing data of tropical forests and in ancient data of the Earth’s climate. This work showed all these very different systems may have universal laws that can be used across scientific disciplines.
