Complex systems ranging from ecosystems to financial markets and the climate may have tipping points where a sudden shift to a contrasting regime can occur. As such critical transitions can have dire consequences, being able to anticipate them is important.
Recent work suggests that we may find generic early warning signals to assess whether a system is approaching a tipping point (Scheffer et al 2009). The expectation is that these early-warning signals may work across a range of systems. However, their practical application remains challenging.
In this masterclass, we will:
- present the basic theory of early warning signals,
- demonstrate how we can design experiments to test early warning signals, and
- provide tools for applying early warning signals in time series and spatial datasets.
Four keynote speakers (both experimentalists and theoreticians) will introduce these ideas:
- John Drake (University of Georgia, USA)
- Alan Hastings (University of California at Davis, USA)
- Johan van de Koppel (Royal Netherlands Institute for Sea Research, The Netherlands)
- Vasilis Dakos (Estación Biológica de Doñana, Spain).
Goal of the masterclass is to stimulate participants into using early warnings in their work. For this reason, we are aiming for a crowd of PhD’s, postdocs, or senior researchers regardless of their experience in the topic and their field of expertise. Instead, we encourage interested participants to develop novel ideas of applying early warnings in any system.
We are open to theoretical or experimental ideas in any discipline ranging from ecology to medicine.
During the masterclass, we expect participants to work in groups to further develop their initial ideas into research projects. The best three projects - judged by our keynote speakers - will be supported by SparcS (the SPinoza center for the Advanced Study of Complex Systems).
- KNAW (Royal Netherlands Academy of Arts and Sciences) and
- SparcS (the SPinoza center for the Advanced Study of Complex Systems)
Vasilis Dakos, Egbert van Nes, Marten Scheffer