Assessing Compounding Risks
We introduce a new risk-triage platform based on an emerging discipline called multi-sector dynamics (MSD), which seeks to understand and model compounding risks and potential tipping points across interconnected natural and human systems. Tipping points occur when these systems can no longer sustain multiple, co-evolving stresses, such as extreme events, population growth, land degradation, drinkable water shortages, air pollution, aging infrastructure, and increased human demands. MSD researchers use observations and computer models to identify key precursory indicators of such tipping points, providing decision-makers with critical information that can be applied to mitigate risks and boost resilience in natural and managed systems. As risks to natural and managed resources—and to the people and economies that depend upon them—become more complex, interdependent and compounding amid environmental and societal changes, new ways of assessing and understanding these risks are needed. Our new tool provides a computationally efficient way to combine, analyze and visualize data reflecting a wide variety of socio-economic and environmental risks, and to identify regions where individual or combined risks are particularly high.
Our new “risk-triage” computational platform provides decision-makers with an efficient way to assess those risks that matter most to them and identify “hotspots” of compounding risk, which in turn can inform interventions to increase resilience.
Drawing on data that characterize land, water, and energy systems; biodiversity; demographics; environmental equity; and transportation networks; the System for the Triage of Risks from Environmental and Socio-economic Stressors (STRESS) platform developed by researchers at the MIT Joint Program on the Science and Policy of Global Change enables users to assess multiple, co-evolving, compounding hazards within a U.S. geographical region from the national to the county level. Because of its comprehensiveness and precision, this screening-level visualization tool can pinpoint risk “hotspots” that can be subsequently investigated in greater detail. In one demonstration of the platform’s capabilities, the study shows that national and global actions to reduce greenhouse gas emissions could simultaneously reduce risks to land, water, and air quality in the upper Mississippi River basin while increasing economic risks in the lower Basin where poverty and unemployment are already disproportionate. Current STRESS data includes more than 100 risk metrics at the county-level scale, but data collection is ongoing. MIT Joint Program researchers are continuing to develop the STRESS platform as an “open-science tool” that welcomes input from academics, researchers, industry, and the general public.