A complex network theory approach to oceanic and atmospheric transport phenomena

Doctoral thesis 2015. Doctoral Program of Physics (Universitat de les Illes Balears).[EN] The last two decades have seen important advances in the Lagrangian description of transport and mixing in fluid flows driven by concepts from dynamical systems theory, and nowadays several approaches have been developed. Some of such techniques focus on geometric objects - lines, surfaces - separating fluid regions with different properties while others have focussed on computing stretching-like fields in the fluid domain, such as different types of Lyapunov exponents or other Lagrangian descriptors. Finally, there is a line of research focussing on the moving fluid regions themselves, the so-called set-oriented methods. On the other hand many real-world systems can be studied by using the Network paradigm and in the last years Network Theory approaches have been successfully used for geophysical systems in the context of climate networks in which the connections among the different locations represent statistical relationships between climatic time series from these locations, inferred from correlations and other statistical methods. In this thesis we propose a new paradigm linking the network formalism with transport and mixing phenomena in geophysical flows. We analyze directly the network describing the material fluid flow among different locations, which we call flow network. Among other characteristics this network is directed, weighted, spatially embedded and time-dependent. We illustrate the general ideas with an exemplary network derived from a realistic simulation of the surface flow in the Mediterranean sea. We use network-theory tools to analyze them and gain insights into transport processes from a general point of view. We quantitatively relate dispersion and mixing characteristics, classically quantified by Lyapunov exponents, to the degree of the network nodes. A family of network entropies is defined from the network adjacency matrix, and related to the statistics of stretching in the fluid, in particular to the Lyapunov exponent field. We use a network community detection algorithm, Infomap, to partition the network into coherent regions, i.e. areas internally well mixed, but with little fluid interchange between them. We find interesting applications of this approach to marine biology of the Mediterranean Sea. Oceanic dispersal and connectivity have been identified indeed as crucial factors for structuring marine populations and designing Marine Protected Areas (MPAs). Larvae of different pelagic durations and seasons could be modeled as passive tracers advected in a simulated oceanic surface flow from which a flow network is constructed. By ap- plying the Infomap algorithm we extract hydrodynamical provinces from the network that result to be delimited by frontiers which match multi-scale oceanographic features. By examining the repeated occurrence of such boundaries, we identify the spatial scales and geographic structures that would control larval dispersal across the entire seascape. Based on these hydrodynamical units, we study novel connectivity metrics for existing MPAs.We also define node-by-node proxies measuring local larval retention and exchange. From the analysis of such measures we confirm that retention processes are favored along the coastlines while they are weak in the open ocean due to specific oceanographic conditions. Although these proxies were often studied separately in the literature, we demonstrated that they are inter-related under certain conditions and that their integrated analysis leads to a better understanding of metapopulation dynamics, informing both genetic and demographic connectivities. We also consider paths in weighted and directed temporal networks, introducing tools to compute sets of paths of high probability. We quantify the relative importance of the most probable path between two nodes with respect to the whole set of paths, and to a subset of highly probable paths which incorporate most of the connection probability. These concepts are used to provide alternative definitions of betweenness centrality. We apply these tools to the temporal flow network describing surface currents in the Mediterranean sea. Despite the full transport dynamics is described by a very large number of paths we find that, for realistic time scales, only a very small subset of high probability paths (or even a single most probable one) is enough to characterize global connectivity properties of the network. Finally we apply the same analysis to the atmospheric blocking of eastern Europe and western Russia in summer 2010. We compute the most probable paths followed by fluid particles which reveal the Omega-block skeleton of the event. A hierarchy of sets of highly probable paths is introduced to describe transport pathways when the most probable path alone is not representative enough. These sets of paths have the shape of narrow coherent tubes flowing close to the most probable one. Thus, as for the case of Mediterranean Sea, even when the most probable path is not very significant in terms of its probability, it still identifies the geometry of the transport pathwaysI acknowledge also financial support from FEDER and MINECO (Spain) through the ESCOLA (CTM2012- 39025-C02-01) and INTENSE@COSYP (FIS2012-30634) projects, and from European Commission Marie-Curie ITN program (FP7-320 PEOPLE-2011- ITN) through the LINC project (no. 289447).Peer reviewe

Information Recovery In Behavioral Networks

In the context of agent based modeling and network theory, we focus on the problem of recovering behavior-related choice information from origin-destination type data, a topic also known under the name of network tomography. As a basis for predicting agents' choices we emphasize the connection between adaptive intelligent behavior, causal entropy maximization and self-organized behavior in an open dynamic system. We cast this problem in the form of binary and weighted networks and suggest information theoretic entropy-driven methods to recover estimates of the unknown behavioral flow parameters. Our objective is to recover the unknown behavioral values across the ensemble analytically, without explicitly sampling the configuration space. In order to do so, we consider the Cressie-Read family of entropic functionals, enlarging the set of estimators commonly employed to make optimal use of the available information. More specifically, we explicitly work out two cases of particular interest: Shannon functional and the likelihood functional. We then employ them for the analysis of both univariate and bivariate data sets, comparing their accuracy in reproducing the observed trends.Comment: 14 pages, 6 figures, 4 table

Most probable paths in temporal weighted networks: An application to ocean transport

We consider paths in weighted and directed temporal networks, introducing tools to compute sets of paths of high probability. We quantify the relative importance of the most probable path between two nodes with respect to the whole set of paths, and to a subset of highly probable paths which incorporate most of the connection probability. These concepts are used to provide alternative definitions of betweenness centrality. We apply our formalism to a transport network describing surface flow in the Mediterranean sea. Despite the full transport dynamics is described by a very large number of paths we find that, for realistic time scales, only a very small subset of high probability paths (or even a single most probable one) is enough to characterize global connectivity properties of the network

Hydrodynamic provinces and oceanic connectivity from a transport network help designing marine reserves

Oceanic dispersal and connectivity have been identified as crucial factors for structuring marine populations and designing Marine Protected Areas (MPAs). Focusing on larval dispersal by ocean currents, we propose an approach coupling Lagrangian transport and new tools from Network Theory to characterize marine connectivity in the Mediterranean basin. Larvae of different pelagic durations and seasons are modeled as passive tracers advected in a simulated oceanic surface flow from which a network of connected areas is constructed. Hydrodynamical provinces extracted from this network are delimited by frontiers which match multi-scale oceanographic features. By examining the repeated occurrence of such boundaries, we identify the spatial scales and geographic structures that would control larval dispersal across the entire seascape. Based on these hydrodynamical units, we study novel connectivity metrics for existing reserves. Our results are discussed in the context of ocean biogeography and MPAs design, having ecological and managerial implications

Lagrangian Flow Network approach to an open flow model

Concepts and tools from network theory, the so-called Lagrangian Flow Network framework, have been successfully used to obtain a coarse-grained description of transport by closed fluid flows. Here we explore the application of this methodology to open chaotic flows, and check it with numerical results for a model open flow, namely a jet with a localized wave perturbation. We find that network nodes with high values of out-degree and of finite-time entropy in the forward-in-time direction identify the location of the chaotic saddle and its stable manifold, whereas nodes with high in-degree and backwards finite-time entropy highlight the location of the saddle and its unstable manifold. The cyclic clustering coefficient, associated to the presence of periodic orbits, takes non-vanishing values at the location of the saddle itself.Comment: 7 pages, 3 figures. To appear in European Physical Journal Special Topics, Topical Issue on "Recent Advances in Nonlinear Dynamics and Complex Structures: Fundamentals and Applications

Dominant transport pathways in an atmospheric blocking event

A Lagrangian flow network is constructed for the atmospheric blocking of eastern Europe and western Russia in summer 2010. We compute the most probable paths followed by fluid particles which reveal the {\it Omega}-block skeleton of the event. A hierarchy of sets of highly probable paths is introduced to describe transport pathways when the most probable path alone is not representative enough. These sets of paths have the shape of narrow coherent tubes flowing close to the most probable one. Thus, even when the most probable path is not very significant in terms of its probability, it still identifies the geometry of the transport pathways.Comment: Appendix added with path calculations for a simple kinematic model flo

Flow networks: A characterization of geophysical fluid transport

We represent transport between different regions of a fluid domain by flow networks, constructed from the discrete representation of the Perron-Frobenius or transfer operator associated to the fluid advection dynamics. The procedure is useful to analyze fluid dynamics in geophysical contexts, as illustrated by the construction of a flow network associated to the surface circulation in the Mediterranean sea. We use network-theory tools to analyze the flow network and gain insights into transport processes. In particular we quantitatively relate dispersion and mixing characteristics, classically quantified by Lyapunov exponents, to the degree of the network nodes. A family of network entropies is defined from the network adjacency matrix, and related to the statistics of stretching in the fluid, in particular to the Lyapunov exponent field. Finally we use a network community detection algorithm, Infomap, to partition the Mediterranean network into coherent regions, i.e. areas internally well mixed, but with little fluid interchange between them.Comment: 16 pages, 15 figures. v2: published versio

Loop Current Transport and Dispersal Dynamics in the Gulf of Mexico

Transport, connectivity, and dispersal both within and outside of the Gulf of Mexico impact important processes such as biological and pollutant dispersal. The Loop Current is a key flow feature within the Gulf of Mexico that affects transport. This research pairs Network Theory and Lagrangian oceanographic modeling (Lagrangian Flow Networks, LFN) to study the connectivity within the Gulf as a function of the Loop Current state. Surface-following particles are used to simulate Lagrangian transport over the observational record using a HYCOM ocean model reanalysis simulation coupled with the LFN particle tracking model computed on TACC supercomputers. The particle simulations are used to determine regions of connectivity, or hydrodynamic provinces, as a function of the Loop Current state, using machine learning. These provinces inform us about biological and pollutant transport variability, such as larval connectivity and harmful algal blooms

Accounting for ocean connectivity and hydroclimate in fish recruitment fluctuations within transboundary metapopulations

International audienceMarine resources stewardships are progressively becoming more receptive to an effective incorporation of both ecosystem and environmental complexities into the analytical frameworks of fisheries assessment. Understanding and predicting marine fish production for spatially and demographically complex populations in changing environmental conditions is however still a difficult task. Indeed, fisheries assessment is mostly based on deterministic models that lack realistic parameterizations of the intricate biological and physical processes shaping recruitment, a cornerstone in population dynamics. We use here a large metapopulation of a harvested fish, the European hake (Merluccius merluccius), managed across transnational boundaries in the northwestern Mediterranean, to model fish recruitment dynamics in terms of physics-dependent drivers related to dispersal and survival. The connectivity among nearby subpopulations is evaluated by simulating multi-annual Lagrangian indices of larval retention, imports, and self-recruitment. Along with a proxy of the regional hydroclimate influencing early life stages survival, we then statistically determine the relative contribution of dispersal and hydroclimate for recruitment across contiguous management units. We show that inter-annual variability of recruitment is well reproduced by hydroclimatic influences and synthetic connectivity estimates. Self-recruitment (i.e., the ratio of retained locally produced larvae to the total number of incoming larvae) is the most powerful metric as it integrates the roles of retained local recruits and immigrants from surrounding subpopulations and is able to capture circulation patterns affecting recruitment at the scale of management units. We also reveal that the climatic impact on recruitment is spatially structured at regional scale due to contrasting biophysical processes not related to dispersal. Self-recruitment calculated for each management unit explains between 19% and 32.9% of the variance of recruitment variability, that is much larger than the one explained by spawning stock biomass alone, supporting an increase of consideration of connectivity processes into stocks assessment. By acknowledging the structural and ecological complexity of marine populations, this study provides the scientific basis to link spatial management and temporal assessment within large marine metapopulations. Our results suggest that fisheries management could be improved by combining information of physical oceanography (from observing systems and operational models), opening new opportunities such as the development of short-term projections and dynamic spatial management

Strings in AdS_4 x CP^3: finite size spectrum vs. Bethe Ansatz

We compute the first curvature corrections to the spectrum of light-cone gauge type IIA string theory that arise in the expansion of $AdS_4\times \mathbb{CP}^3$ about a plane-wave limit. The resulting spectrum is shown to match precisely, both in magnitude and degeneration that of the corresponding solutions of the all-loop Gromov--Vieira Bethe Ansatz. The one-loop dispersion relation correction is calculated for all the single oscillator states of the theory, with the level matching condition lifted. It is shown to have all logarithmic divergences cancelled and to leave only a finite exponentially suppressed contribution, as shown earlier for light bosons. We argue that there is no ambiguity in the choice of the regularization for the self-energy sum, since the regularization applied is the only one preserving unitarity. Interaction matrices in the full degenerate two-oscillator sector are calculated and the spectrum of all two light magnon oscillators is completely determined. The same finite-size corrections, at the order 1/J, where $J$ is the length of the chain, in the two-magnon sector are calculated from the all loop Bethe Ansatz. The corrections obtained by the two completely different methods coincide up to the fourth order in $\lambda' =\lambda/J^2$. We conjecture that the equivalence extends to all orders in $\lambda$ and to higher orders in 1/J.Comment: 32 pages. Published version; journal reference adde