• Bibtex: @scheffer2012
  • Bibliography: Scheffer, M., Carpenter, S. R., Lenton, T. M., Bascompte, J., Brock, W., Dakos, V., van de Koppel, J., van de Leemput, I. A., Levin, S. A., van Nes, E. H., Pascual, M., & Vandermeer, J. (2012). Anticipating Critical Transitions. Science, 338(6105), 344–348. https://doi.org/10.1126/science.1225244

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Key takeaways

  • If we are better able to identify and understand tipping points in Complex systems, we can use them to induce positive change and prevent collapses of the systems we study.
  • Combining research that tries to understand the architecture of tipping points in complex systems, with indicators that rapid change is underway (early warning signs or Canary in a coal mine)
  • Tipping point

Tipping points in complex systems may imply risks of unwanted collapse, but also opportunities for positive change. Our capacity to navigate such risks and opportunities can be boosted by combining emerging insights from two unconnected fields of research. One line of work is revealing fundamental architectural features that may cause ecological networks, financial markets, and other complex systems to have tipping points. Another field of research is uncovering generic empirical indicators of the proximity to such critical thresholds. Although sudden shifts in complex systems will inevitably continue to surprise us, work at the crossroads of these emerging fields offers new approaches for anticipating critical transitions.

How does a system respond to changing conditions and external events? The heterogeneity of the components and their connectivity. Node similarity and high connectivity increases probability of sudden shifts. High connectivity can increase local resilience to changes in external stressors, but highly connected systems can reach a tipping point once the external pressure is high enough, and cause a Domino effect.

In summary, the same prerequisites that allow recovery from local damage may set a system up for large-scale collapse.

Critical slowing down as an indicator of lower resilience

Critical slowing down occurs when a system recovers more slowly from small stressors. It has been shown to be an indicator that systems change is coming in multiple fields.

Future directions

Most research to date has been in ecology and climate science, but perhaps there are generic indicators that can be applied to other types of systems as well.