Rate of recovery from perturbations as a means to forecast future stability of living systems

Ghadami, Amin; Gourgou, Eleni; Epureanu, Bogdan I.

doi:10.1038/s41598-018-27573-0

Cited by 18 publications

(16 citation statements)

References 60 publications

(51 reference statements)

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“…Another approach considers the scaling of critical slowing down as a bifurcation is approached [14]; however, this requires a controlled setting whereby changes in the bifurcation parameter can be measured. Finally, promising studies in large perturbation theory [44,45] demonstrate how information on the bifurcation type and distance can be obtained by carefully monitoring a system's recovery trajectory following a perturbation. This again requires a controlled environment, and a system whereby large perturbations are feasible.…”

Section: Discussionmentioning

confidence: 99%

Detecting and distinguishing tipping points using spectral early warning signals

Bury

Bauch

Anand

2020

J. R. Soc. Interface.

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Theory and observation tell us that many complex systems exhibit tipping points—thresholds involving an abrupt and irreversible transition to a contrasting dynamical regime. Such events are commonly referred to as critical transitions. Current research seeks to develop early warning signals (EWS) of critical transitions that could help prevent undesirable events such as ecosystem collapse. However, conventional EWS do not indicate the type of transition, since they are based on the generic phenomena of critical slowing down. For instance, they may fail to distinguish the onset of oscillations (e.g. Hopf bifurcation) from a transition to a distant attractor (e.g. Fold bifurcation). Moreover, conventional EWS are less reliable in systems with density-dependent noise. Other EWS based on the power spectrum (spectral EWS) have been proposed, but they rely upon spectral reddening, which does not occur prior to critical transitions with an oscillatory component. Here, we use Ornstein–Uhlenbeck theory to derive analytic approximations for EWS prior to each type of local bifurcation, thereby creating new spectral EWS that provide greater sensitivity to transition proximity; higher robustness to density-dependent noise and bifurcation type; and clues to the type of approaching transition. We demonstrate the advantage of applying these spectral EWS in concert with conventional EWS using a population model, and show that they provide a characteristic signal prior to two different Hopf bifurcations in data from a predator–prey chemostat experiment. The ability to better infer and differentiate the nature of upcoming transitions in complex systems will help humanity manage critical transitions in the Anthropocene Era.

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Section: Discussionmentioning

confidence: 99%

Detecting and distinguishing tipping points using spectral early warning signals

Bury

Bauch

Anand

2020

J. R. Soc. Interface.

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“…Non-linear dynamics have been extensively studied and mathematical approaches such as algorithms have been utilized to measure effects of small perturbations in ecological time-series and forecast future changes in systems based on these previous alterations (Bar-Joseph et al, 2003; Ghadami et al, 2018). These approaches allow for prediction of unobserved points in time, yet also suggest that these same systems may exhibit non-linear kinetics (Hoffman and Galle, 2018).…”

Section: Extension To the Physical Sciencesmentioning

confidence: 99%

Etiopathogenesis of Suicide: A Conceptual Analysis of Risk and Prevention Within a Comprehensive, Deterministic Model

Lennon

2019

Front. Psychol.

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Suicide is a rising global health concern receiving disproportionate attention in comparison to other health conditions. In spite of substantial technological and scientific advancements, suicide research has continued to move slowly in terms of clinical translation due to the complexity of neural mechanisms, and subjective experiences that seem to underpin this complex human behavior. This paper analyzes the concepts of risk and prevention in the context of suicide in an attempt to bridge the large methodological and theoretical gaps between the biological, psychological, and sociological dimensions. This paper aims to accomplish the following objectives: (1) operationalize the concepts of suicide risk and prevention as they relate to current knowledge and capabilities; (2) synthesize and integrate suicide research across biological, psychological, and sociological dimensions; (3) discuss limitations of each dimension in isolation; (4) suggest a model of etiopathogenesis that incorporates extant literature and bridges unnecessary gaps between dimensions; and (5) suggest future directions for multidimensional research through the inclusion of principles from the physical sciences. Ultimately, this paper provides a basis for a comprehensive model of suicide within a deterministic, chaotic system.

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“…In order to test whether a system undergoes slowing down, one would ideally investigate its response to perturbations from time to time, although such an approach may not be feasible in practice [23], [27]. As an alternative, the footprints of slowing down in dynamical systems can be investigated via trends in the statistical moments of time-series data as the transition is approached, known as early warning signals (EWSs) [22]- [24], [28].…”

Section: Introductionmentioning

confidence: 99%

Stability and Resilience of Transportation Systems: Is a Traffic Jam About to Occur?

Ghadami

Doering

Drake

et al. 2022

IEEE Trans. Intell. Transport. Syst.

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Measurement of traffic flow stability and resilience is a critical step toward evaluating the performance of transportation systems and implementing appropriate management strategies. Quantifying changes in the stability and resilience of transportation systems, however, is hampered by the complexity of real traffic dynamics and the diversity of infrastructures. Here, we demonstrate that changes in traffic flow stability and resilience are signaled by generic features, known as early warning signals in the theory of critical slowing down, observed before traffic instabilities occur. This finding is incorporated in an operational data-driven algorithm to evaluate the risk of traffic jams on highways. Theoretical findings and tests on simulated and empirical case studies support the premise of this approach and identify candidate statistical measures that are sensitive to changes in the stability and resilience of transportation systems. Our use of universal measures advances the monitoring capability, prediction and control of complex transportation systems.

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Rate of recovery from perturbations as a means to forecast future stability of living systems

Cited by 18 publications

References 60 publications

Detecting and distinguishing tipping points using spectral early warning signals

Detecting and distinguishing tipping points using spectral early warning signals

Etiopathogenesis of Suicide: A Conceptual Analysis of Risk and Prevention Within a Comprehensive, Deterministic Model

Stability and Resilience of Transportation Systems: Is a Traffic Jam About to Occur?

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