Predicting system crashes in nature and society
Thursday, February 2, 2012 - 17:00
in Earth & Climate
The world can deliver sudden and nasty shocks. Economies can crash, fisheries can collapse, and climates can pass tipping points. Providing early warning of such changes currently requires the collection of enormous and often prohibitive amounts of data. A new method developed by Steven Lade from the Max-Planck-Institute for the Physics of Complex Systems in Germany and Thilo Gross from the University of Bristol in the UK could change this. In a paper published in the open-access journal PLoS Computational Biology on February 2, the researchers present a mathematical methodology that uses easily obtainable information to greater effect and can therefore reduce the amount of additional data that needs to be collected.