Scientists from China and the United Kingdom are pioneering a technique to predict when an ecosystem is likely to collapse, which may have the potential for foretelling crises in agriculture, fisheries or even social systems.

Researchers from the Nanjing Institute of Geography and Limnology, the Chinese Academy of Sciences and the University of Southampton completed the project and recently published it in the scientific journal Nature.

They've applied a mathematical model to a real-world situation, Erhai Lake in China's Yunnan province, to help prove a theory that suggests that an ecosystem "flickers", or fluctuates dramatically between healthy and unhealthy states, shortly before its eventual collapse.

"We chose Erhai Lake for this study because we had a great deal of background information from previous studies and also knew that there were recent problems with water quality from 2000 onward that we could study in the context of critical transitions," Professor John Dearing, head of Geography at the University of Southampton, told China Daily.

"We've worked at Erhai Lake since about 2001," he said. "We wanted to prove that this ‘flickering' occurs just ahead of a dramatic change in a system — be it a social, ecological or climatic one — and that this method could potentially be used to predict future critical changes in other impacted systems in the world around us."

Wang Rong, a PhD from NIGLAS, led a team and extracted core samples from sediment at the bottom of Erhai Lake and charted the levels and variation of fossilized algae, or diatoms, over a 125-year period.

Analysis of the core sample data showed the algae communities remained relatively stable up until about 30 years before the lake's collapse into a turbid or polluted state.

However, the core samples for the last three decades showed much fluctuation, indicating there had been numerous dramatic changes in the types and concentrations of algae present in the water — evidence of the ‘flickering' before the lake's final definitive change of state.

"By using the algae as a measure of the lake's health, we have shown that its eco-system ‘wobbled' before making a critical transition — in this instance, to a turbid state," Wang said.

"Dramatic swings can be seen in other data, suggesting large external impacts on the lake over a long time period — for example, pollution from fertilizers, sewage from fields and changes in water levels — caused the system to switch back and forth rapidly between alternate states," Wang added.

"The most difficult thing was confirming the critical transition in a statistically robust way," Dearing said. "The happiest moment was when we realized that the ‘flickering' happened even when we changed the underlying assumptions about sediment dates and other analyses."

The researchers hope the method could be applied to other regions and landscapes. "We are planning to use the method in the UK on lakes that have become polluted," Dearing said.

"We have already started to look with our co-authors on the paper at other lakes in the Yangtze basin and Yunnan," Dearing added.