Managing for resilience: early detection of regime shifts in complex systems

The broad implications of catastrophic regime shifts have prompted the need to find methods that are not only able to detect regime shifts but more importantly, identify them before they occur. Rising variance, skewness, kurtosis, and critical slowing down have all been proposed as indicators of impending regime shifts. However, these approaches typically do not signal a shift until it is well underway. Further, they have primarily been used to evaluate simple systems; hence, additional work is needed to adapt these methods, if possible, to real systems which typically are complex and multivariate. Fisher information is a key method in information theory and affords the ability to characterize the dynamic behavior of systems. In this work, Fisher information is compared to traditional indicators through the assessment of model and real systems and identified as a leading indicator of impending regime shifts. Evidenced by the great deal of activity in this research area, it is understood that such work could lead to better methods for detecting and managing systems that are of significant importance to humans. Thus, we believe the results of this work offer great promise for resilience science and sustainability.