Identifying fish populations prone to abrupt shifts via dynamical footprint analysis.

ABSTRACT: Fish population biomass fluctuates through time in ways that may be either gradual or abrupt. While abrupt shifts in fish population productivity have been shown to be common, they are rarely integrated into stock assessment or fishery management, in part because of the difficulty of predicting when abrupt shifts may occur and which stocks are prone to such shifts. In this study, we address the latter challenge by designing a mechanism-agnostic context-specific approach that is based on exploiting the dynamical properties of fish population fluctuations for detecting potential abrupt shifts. We use time series of fish population biomass from three global datasets, first, to classify their shapes into abrupt and nonabrupt (linear, quadratic, or no change) classes, and, second, to predict cl

SUBMITTER: Cano AV 

PROVIDER: S-EPMC12403094 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature