Brains have seizures, ecosystems collapse, economies crash — and it sure would be great if we could predict when. Despite the complexity of these seemingly disparate events, recent research suggests that tipping points are foreseeable.
A study published online February 2 in PLoS Computational Biology offers a way to discern when a complex system such as a fishery may be teetering towards collapse. The new work uses mathematical indicators to help researchers understand systems when there’s not enough data to build the kind of complex supercomputer simulations that are typically used to study things like climate change. And other recent studies have turned up even more mathematical red flags that a system is approaching a point of no return.
“At one end, there’s the brute force approach,” says study coauthor Steven Lade of the Max Planck Institute for the Physics of Complex Systems in Dresden, Germany. “You make a very detailed model of the system, try and add everything that’s going on, and run it into the future.”
But scientists often don’t know enough of the details to make such simulations accurate. “The more specific you can be, the better, but you shouldn’t be specific about the things you don’t know about,” says Marten Scheffer of Wageningen University in the Netherlands.