Quantifying resilience and the risk of regime shifts under strong correlated noise.

ABSTRACT: Early warning indicators often suffer from the shortness and coarse-graining of real-world time series. Furthermore, the typically strong and correlated noise contributions in real applications are severe drawbacks for statistical measures. Even under favourable simulation conditions the measures are of limited capacity due to their qualitative nature and sometimes ambiguous trend-to-noise ratio. In order to solve these shortcomings, we analyze the stability of the system via the slope of the deterministic term of a Langevin equation, which is hypothesized to underlie the system dynamics close to the fixed point. The open-source available method is applied to a previously studied seasonal ecological model under noise levels and correlation scenarios commonly observed in real world data. We

SUBMITTER: Heßler M 

PROVIDER: S-EPMC9896148 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature