Tipping points and early warning signals in complex ecosystems (2017–2020)
Many ecosystems possess tipping points that can lock it into an undesirable state once transgressed. Since the locations of tipping points are often unknown, recent theory has sought metrics that provide an early warning of collapse. These methods are difficult to apply because they require long time series which are usually lacking. We create a new theory of early warning that harnesses the wealth of spatial data available on system state, connectivity and environmental stress. We then create tools to infer the risk of ecosystem collapse. We use the Great Barrier Reef as a testbed because it has both long time series (standard approach) and rich spatial data (new approach). Intriguingly, it also appears to exhibit some early warning signs.