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Lagrangian betweenness as a measure of bottlenecks in dynamical systems with oceanographic examples

Authors :
Simons Foundation
Agencia Estatal de Investigación (España)
Ministerio de Economía y Competitividad (España)
Ser-Giacomi, Enrico
Baudena, Alberto
Rossi, Vincent
Follows, Mick
Clayton, Sophie
Vasile, Ruggero
López, Cristóbal
Hernández-García, Emilio
Simons Foundation
Agencia Estatal de Investigación (España)
Ministerio de Economía y Competitividad (España)
Ser-Giacomi, Enrico
Baudena, Alberto
Rossi, Vincent
Follows, Mick
Clayton, Sophie
Vasile, Ruggero
López, Cristóbal
Hernández-García, Emilio
Publication Year :
2021

Abstract

The study of connectivity patterns in networks has brought novel insights across diverse fields ranging from neurosciences to epidemic spreading or climate. In this context, betweenness centrality has demonstrated to be a very effective measure to identify nodes that act as focus of congestion, or bottlenecks, in the network. However, there is not a way to define betweenness outside the network framework. By analytically linking dynamical systems and network theory, we provide a trajectory-based formulation of betweenness, called Lagrangian betweenness, as a function of Lyapunov exponents. This extends the concept of betweenness beyond the context of network theory relating hyperbolic points and heteroclinic connections in any dynamical system to the structural bottlenecks of the network associated with it. Using modeled and observational velocity fields, we show that such bottlenecks are present and surprisingly persistent in the oceanic circulation across different spatio-temporal scales and we illustrate the role of these areas in driving fluid transport over vast oceanic regions. Analyzing plankton abundance data from the Kuroshio region of the Pacific Ocean, we find significant spatial correlations between measures of diversity and betweenness, suggesting promise for ecological applications.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1333182861
Document Type :
Electronic Resource