Early warnings for multi-stage transitions in dynamics on networks

Author:

MacLaren Neil G.1ORCID,Kundu Prosenjit1ORCID,Masuda Naoki12ORCID

Affiliation:

1. Department of Mathematics, State University of New York at Buffalo, Buffalo, NY 14260-2900, USA

2. Computational and Data-Enabled Science and Engineering Program, State University of New York at Buffalo, Buffalo, NY 14260-5030, USA

Abstract

Successfully anticipating sudden major changes in complex systems is a practical concern. Such complex systems often form a heterogeneous network, which may show multi-stage transitions in which some nodes experience a regime shift earlier than others as an environment gradually changes. Here we investigate early warning signals for networked systems undergoing a multi-stage transition. We found that knowledge of both the ongoing multi-stage transition and network structure enables us to calculate effective early warning signals for multi-stage transitions. Furthermore, we found that small subsets of nodes could anticipate transitions as well as or even better than using all the nodes. Even if we fix the network and dynamical system, no single best subset of nodes provides good early warning signals, and a good choice of sentinel nodes depends on the tipping direction and the current stage of the dynamics within a multi-stage transition, which we systematically characterize.

Funder

Air Force Office of Scientific Research

Sumitomo Foundation

Japan Science and Technology Agency

National Science Foundation

Publisher

The Royal Society

Subject

Biomedical Engineering,Biochemistry,Biomaterials,Bioengineering,Biophysics,Biotechnology

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