New research models model critical conditions of climate collapse in ecological and biological systems

As humans continue to cause environmental damage through climate change, predicting tipping points becomes more crucial than ever. Around the world, humanity and nature are facing rising temperatures, drought, wildfires, hurricanes, rising sea levels and much more.

Ying-Cheng Lai, Regents Professor of Electrical Engineering in the Ira A. Fulton Schools of Engineering at Arizona State University, leads projects studying the impact of tariff-induced shifts on the natural environment. Rate-induced tipping quantifies the rate at which a system changes to reach a tipping point, or the critical moment at which major damage to the ecosystem occurs, such as the extinction of vital species.

Lai and his colleagues’ latest efforts analyzed the impact of rate-induced tipping on organisms that depend on each other for survival, such as photosynthetic cells and the corals that depend on them in a reef. Using mathematical models, researchers found that to avoid environmental disasters, a system should halt its rate of change as much as possible, rather than simply slow it down.

The team’s research led to the article titled “Tipping-Induced Rates in Large-Dimensional Complex Ecological Networks,” published in the Proceedings of the National Academy of Sciences.

A new frontier for research into fare-induced tipping

While tipping point research is a well-established field, Lai and his colleagues, who for this project included Fulton Schools electrical engineering postdoctoral fellow Shirin Panahi; Younghae Do, professor of mathematics at Kyungpook National University of South Korea; and Alan Hastings, distinguished professor emeritus specializing in theoretical ecology at the University of California, Davis, took a new approach to examining the progression of a system’s state rates to determine when a system will collapse.

They found that previous research in the field focused specifically on certain points in phase space, which relies on the spatial location of system states and their associated rates, rather than observing the complete picture of all accessible points in the state space of the underlying system. .

Lai and his team sought to determine the probability of a rate-induced tilt in the entire state space, then used the corresponding data to develop a mathematical theory that could be applied generally to systems ecological and biological domains.

Environmental impact assessment

An ecological example of research applications involves analyzing the effect of rates of environmental degradation caused by climate change on corals and their zooxanthellae, which are microscopic organisms that live in corals and provide them with food by photosynthesis.

As oceans warm due to absorbing more carbon from human-caused emissions, scientists can use rate-induced tipping research to determine when warmer water will cause irreversible damage to oceans. corals. An example of system collapse is when heat stress causes zooxanthellae to separate from host corals and leaves corals in a vulnerable state, often evidenced by coral bleaching.

Because corals support a variety of reef life, coral bleaching has significant upstream impacts on ecosystems, including human populations that rely on the fish that live in reefs for food.

“When the rate of change of parameters exceeds a certain critical value, a system can collapse, in the sense of mass extinction in a relatively short period of time,” explains Lai. “The main conclusion is that even a slow change in parameters can suddenly lead to a system collapse with catastrophic consequences.”

Beyond climate change, the research can also be applied to biological systems, for example to estimate the rate of change that results in a cell’s inability to perform its genetically determined function.

Change the course of future events

Ultimately, Lai wants to prepare humanity to avoid future disasters or mitigate their effects through his research on rate-induced swings. His future projects in the field aim to deepen his current knowledge.

Lai plans to use research findings on rate-induced tipping to create machine learning models that can identify systemic calamities for more specific applications. For example, he hopes to create a model to predict the potential collapse of the Atlantic Southern Overturning Circulation, a current system carrying warm and cold water across the ocean that keeps the climate mild in Western Europe .

The movement of currents slows as oceans warm, and the machine learning model would build on Lai’s established research to determine when Western Europe should prepare for severe climate change from declining currents.