There has been much talk about tipping points over the past few years, and about the warning signals that may precede them. You could be forgiven for thinking that the forecasting of epidemics and stock-market crashes is just around the corner. But no one has yet managed to use the theory on early warning signals to predict a natural catastrophe.
The rewards of bridging the gap between the real world and mathematical conceptualizations of catastrophic shifts would be vast. Climate scientists might be able to foresee major shifts in the ocean currents with a rise in global temperatures; ecologists could potentially stave off pest outbreaks; and policies might be implemented to avert the collapse of fisheries1. (A report out this week from the World Economic Forum outlines other risks facing the world2). But for such applications to emerge, researchers should resist the lure of general rules. We must instead use all the available data to develop tools to study the specific properties of real systems.
Tipping points: From patterns to predictions
Carl Boettiger & Alan Hastings
Nature 493, 157–158 (10 January 2013) http://dx.doi.org/10.1038/493157a
Via Complexity Digest