Lagrangian dynamical geography of the Gulf of Mexico

P Miron,J Sheinbaum,M J Olascoaga,P Pérez-Brunius,F J Beron-Vera,G Froyland

doi:10.1038/s41598-017-07177-w

Abstract

We construct a Markov-chain representation of the surface-ocean Lagrangian dynamics in a region occupied by the Gulf of Mexico (GoM) and adjacent portions of the Caribbean Sea and North Atlantic using satellite-tracked drifter trajectory data, the largest collection so far considered. From the analysis of the eigenvectors of the transition matrix associated with the chain, we identify almost-invariant attracting sets and their basins of attraction. With this information we decompose the GoM’s geography into weakly dynamically interacting provinces, which constrain the connectivity between distant locations within the GoM. Offshore oil exploration, oil spill contingency planning, and fish larval connectivity assessment are among the many activities that can benefit from the dynamical information carried in the geography constructed here.

Highlights

Over the past few decades a number of satellite-tracked surface drifting buoys have surveyed the Gulf of Mexico (GoM)
Almost-invariant sets form the basis of a Lagrangian dynamical geography, where the boundaries between basins are determined by the Lagrangian circulation itself, instead of arbitrary geographical divisions
Analyzing the eigenvectors of the transition matrix of the chain we identified almost-invariant regions of attraction and their basins of attraction

Summary

Introduction

Over the past few decades a number of satellite-tracked surface drifting buoys have surveyed the Gulf of Mexico (GoM). The number of drifters that have surveyed the GoM is large enough that a global characterization of the GoM’s Lagrangian dynamics can be sought This is possible thanks to probabilistic tools which enable sketching absorbing and almost-invariant sets in the phase space of a nonlinear dynamical system[15,16,17]. Inspection of the eigenvectors of the transition matrix[18] enables localization of regions of the flow where trajectories converge in forward time as well as the regions where those trajectories originate from (i.e., their backward-time basins of attraction), thereby determining the connectivity between separated locations in the flow domain This is conceptually very different than the traditional approach to population connectivity in marine systems, wherein transition matrices are constructed based on ad-hoc partitions of the flow domain into putative spawning and recruitment areas[19]. Our goal in this paper is to construct such a Lagrangian dynamical geography for the GoM, which carries useful information for guiding activities dealing with hampering and/or palliating the effects of an oil spill or a harmful algal bloom or supporting stock assessment efforts and management decisions for fishing regulations, just to cite some examples

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Conclusion