Entropy-based early detection of critical transitions in spatial vegetation fields.

ABSTRACT: In semiarid regions, vegetated ecosystems can display abrupt and unexpected changes, i.e., transitions to different states, due to drifting or time-varying parameters, with severe consequences for the ecosystem and the communities depending on it. Despite intensive research, the early identification of an approaching critical point from observations is still an open challenge. Many data analysis techniques have been proposed, but their performance depends on the system and on the characteristics of the observed data (the resolution, the level of noise, the existence of unobserved variables, etc.). Here, we propose an entropy-based approach to identify an upcoming transition in spatiotemporal data. We apply this approach to observational vegetation data and simulations from two models of ve

SUBMITTER: Tirabassi G 

PROVIDER: S-EPMC9910486 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature