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Published on: March 12, 2013
An integrative quantifier of multistability in complex systems based on ecological resilience
Chiranjit Mitra1,2, Jürgen Kurths1,2,3,4, Reik V Donner1
1Potsdam Institute for Climate Impact Research, Transdisciplinary Concepts &Methods - Research Domain 4, Potsdam, 14412, Germany.
We introduce integral stability, a new measure for quantifying the stability of multistable systems. This approach offers an early-warning signal for critical transitions in complex systems.
Area of Science:
- Complex Systems Dynamics
- Ecological Resilience Theory
- Climate Tipping Elements
Background:
- Multistable dynamical systems possess multiple stable states, necessitating robust methods to assess their stability.
- Existing stability concepts (local and global) often address different aspects, leading to an incomplete understanding of system behavior.
- Ecological resilience provides a framework for understanding system persistence and recovery.
Purpose of the Study:
- To propose a novel, pragmatic measure of stability for multistable dynamical systems.
- To integrate various stability aspects into a single, comprehensive metric.
- To develop an early-warning signal for approaching tipping points.
Main Methods:
- Development of the 'integral stability' metric.
- Application and validation of integral stability using exemplary systems: damped driven pendulum, Amazonian rainforest model, and Daisyworld model.
- Comparison with existing local and global stability concepts.
Main Results:
- Integral stability effectively quantifies the stability of different states in multistable systems.
- The proposed measure successfully captures the gradual loss of stability preceding a tipping point.
- Demonstrated applicability across diverse systems, including climate models.
Conclusions:
- Integral stability offers a unified and pragmatic approach to quantifying system stability.
- This new metric serves as a potential early-warning signal for critical transitions.
- Integral stability enhances our ability to predict and manage complex system dynamics.
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