Catastrophes can result from “tipping point” transitions of complex environmental systems. Such quickly eroding conditions can change weather and climate patterns, shift ocean currents or speed up melting of large ice sheets. Researchers are finding ways to predict when stable systems are about to become unstable. Fulton Schools Professor Ying-Cheng Lai, a physicist, and his research collaborators came up with a way to produce data to forecast when the stability of some kinds of systems would begin to collapse. Other researchers have since developed a machine learning algorithm to predict when systems are about to dramatically change behavior. That progress promises ways to foresee widespread alterations in Earth’s ecosystems and the planet’s climate.