arXiv subjects

Enrico Ser-Giacomi

Publications and source records attributed to Enrico Ser-Giacomi.

17 recordsLinked to original sources

arXiv2026

Three-dimensional Lagrangian ecosystems: carbon dynamics and potential for artificial fertilization

Transient supplies of nutrients to the surface ocean, both natural and artificial, stimulate blooms of phytoplankton and the formation of organic matter, driving air-sea gradients and uptake of CO$_2$. However, quantifying the associated carbon budget remains challenging, as it requires tracking the coupled biophysical evolution of water masses while they are transported, stretched and diluted. Here, we present an idealized three-dimensional model that describes biomass production and carbon dynamics within a Lagrangian patch in the ocean. The framework reproduces observed biogeochemical patterns from an artificial fertilization experiment and provides integrated metrics for the local carbon budget. Utilizing large ensembles of simulations, we examine the sensitivity of patch-scale primary production and carbon uptake to biochemical and physical factors. Our results show that patch dilution can enhance the ecosystem response, and how carbon uptake is sensitive to initial injected area, horizontal divergence and vertical diffusivity. In the context of renewed interest in ocean fertilization strategies for climate mitigation, our approach can thus provide quantitative tools to assess their efficacy and potential.

physics.ao-ph↗

arXiv2026

A Comparative Analysis of Clustering Algorithms for Characterizing Surface Ocean Variability in the Western Mediterranean

Understanding regional dynamical structures in the sea is fundamental to characterize energy transfer and transport properties, with implications in physical and biogeochemical modeling and characterization. In this work, we study the potential of clustering techniques to identify regional patterns, persistent or recurrent configurations, out of daily snapshots of sea surface temperature and kinetic energy in a region of the western Mediterranean Sea. From the methodological perspective, we use different clustering techniques: K-means, Self-Organizing Maps and InfoMap to verify if the patterns found are coherent across methods. Our results show that K-means and Self-Organizing Maps consistently delineate four distinct clusters of sea surface temperature configurations, aligned with the seasons even after removing the annual cycle, which indicates the persistence of seasonal structures beyond a mean effect in the temperature field. The study of surface kinetic energy, characterized by higher spatial and temporal variability, reveals more complex circulation regimes. While K-means and Self-Organizing Maps provide a robust and convergent classification of the dominant large-scale energy patterns, InfoMap uncovers finer-scale features such as localized jets and eddies. InfoMap, in particular, provides a complementary perspective to the partition-based methods, validating subtle yet significant hydrodynamic structures and acting as an anomaly detector for extreme events.

physics.ao-ph↗

arXiv2025

Comparing temporal and aggregated network descriptions of fluid transport in the Mediterranean Sea

Ocean currents exhibit strong time dependence at all scales that influences physical and biochemical dynamics. Network approaches to fluid transport permit to address explicitly how connectivity across the seascape is affected by the spatiotemporal variability of currents. However, such temporal aspect is mostly neglected, relying on a static representation of the flow. We here investigate the role of current variability on networks describing physical transport across the Mediterranean basin. We first focus on degree distributions and community structure comparing ensembles of temporal networks that explicitly resolve time dependence and their aggregated, i.e. time-averaged, counterparts. Furthermore, we explore the implications of the two approaches in a simple reaction dispersal model for a generic tracer. Our analysis evidences that aggregation induces structural network changes that cannot be easily avoided, not even introducing a pruning of the aggregated adjacency matrix. We also highlight that, depending on the time scales considered, the importance of the temporal features of the networks can vary significantly. Finally, we find that the tracer evolution obtained from a temporal dispersal kernel cannot be always approximated by aggregated adjacency matrices, in particular during transients of the dynamics.

physics.soc-ph↗

arXiv2023

A Lagrangian model for drifting ecosystems reveals heterogeneity-driven enhancement of marine plankton blooms

Marine plankton play a crucial role in carbon storage, oxygen production, global climate, and ecosystem function. Planktonic ecosystems are embedded in a Lagrangian patches of water that are continuously moving, stretching, and diluting. These processes drive inhomegeneities on a range of scales, with implications for the integrated ecosystem properties, but are hard to characterize. We present a theoretical framework which accounts for all these aspects; tracking the water patch hosting a drifting ecosystem along with its physical, environmental, and biochemical features. The model resolves patch dilution and internal physical mixing as a function of oceanic strain and diffusion. Ecological dynamics are parameterized by an idealized nutrient and phytoplankton population and we specifically capture the propagation of the biochemical spatial variances to represent within-patch heterogeneity. We find that, depending only on the physical processes to which the water patch is subjected, the plankton biomass response to a resource perturbation can vary several fold. This work indicates that we must account for these processes when interpreting and modelling marine ecosystems and provides a framework with which to do so.

q-bio.PE↗

arXiv2022

Local impacts on road networks and access to critical locations during extreme floods

Floods affected more than 2 billion people worldwide from 1998 to 2017 and their occurrence is expected to increase due to climate warming, population growth and rapid urbanization. Recent approaches for understanding the resilience of transportation networks when facing floods mostly use the framework of percolation but we show here on a realistic high-resolution flood simulation that it is inadequate. Indeed, the giant connected component is not relevant and instead, we propose to partition the road network in terms of accessibility of local towns and define new measures that characterize the impact of the flooding event. Our analysis allows to identify cities that will be pivotal during the flooding by providing to a large number of individuals critical services such as hospitalization services, food supply, etc. This approach is particularly relevant for practical risk management and will help decision makers for allocating resources in space and time.

physics.soc-ph↗

arXiv2021

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

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.

physics.ao-ph↗

arXiv2021

Explicit and implicit network connectivity: Analytical formulation and application to transport processes

Connectivity is a fundamental structural feature of a network that determines the outcome of any dynamics that happens on top of it. However, an analytical approach to obtain connection probabilities between nodes associated to paths of different lengths is still missing. Here, we derive exact expressions for random-walk connectivity probabilities across any range of numbers of steps in a generic temporal, directed and weighted network. This allows characterizing explicit connectivity realized by causal paths as well as implicit connectivity related to motifs of three nodes and two links called here pitchforks. We directly link such probabilities to the processes of tagging and sampling any quantity exchanged across the network, hence providing a natural framework to assess transport dynamics. Finally, we apply our theoretical framework to study ocean transport features in the Mediterranean Sea. We find that relevant transport structures, such as fluid barriers and corridors, can generate contrasting and counter-intuitive connectivity patterns bringing novel insights into how ocean currents drive seascape connectivity.

physics.ao-ph↗

arXiv2020

Impact of climate change on surface stirring and transport in the Mediterranean Sea

Understanding how climate change will affect oceanic fluid transport is crucial for environmental applications and human activities. However, a synoptic characterization of the influence of climate change on mesoscale stirring and transport in the surface ocean is missing. To bridge this gap, we exploit a high-resolution, fully-coupled climate model of the Mediterranean basin using a Network Theory approach. We project significant increases of horizontal stirring and kinetic energies in the next century, likely due to increments of available potential energy. The future evolution of basin-scale transport patterns hint at a rearrangement of the main hydrodynamic provinces, defined as regions of the surface ocean that are well-mixed internally but with minimal cross-flow across their boundaries. This results in increased heterogeneity of province sizes and stronger mixing in their interiors. Our approach can be readily applied to other oceanic regions, providing information for the present and future marine spatial planning.

physics.ao-ph↗

arXiv2018

Crossroads of the mesoscale circulation

Quantifying the mechanisms of tracer dispersion in the ocean remains a central question in oceanography, for problems ranging from nutrient delivery to phytoplankton, to the early detection of contaminants. Most analyses have been based on Lagrangian concepts of transport, focusing on the identification of features minimizing fluid exchange among regions, or more recently on network tools which focus on connectivity and transport pathways. Neither of these approaches allows ranking the geographical sites of major water passage and selecting them so that they monitor waters coming from separate parts of the ocean. These are instead key criteria when deploying an observing network. Here we address this issue by estimating at any point the extent of the ocean surface which transits through it in a given time window. With such information we are able to rank the sites with major fluxes that intercept waters originating from different regions. We show that this allows us to optimize an observing network, where a set of sampling sites can be chosen for monitoring the largest flux of water dispersing out of a given region. When the analysis is performed backward in time, this method allows us to identify the major sources which feed a target region. The method is first applied to a minimalistic model of a mesoscale eddy field, and then to realistic satellite-derived ocean currents in the Kerguelen area. In this region we identify the optimal location of fixed stations capable of intercepting the trajectories of 43 surface drifters, along with statistics on the temporal persistence of the stations determined in this way. We then identify possible hotspots of micro-nutrient enrichment for the recurrent spring phytoplanktonic bloom occuring here. Promising applications to other fields, such as larval connectivity, marine spatial planning or contaminant detection, are then discussed.

physics.ao-ph↗

arXiv2017

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.

physics.flu-dyn↗

arXiv2016

Clustering coefficient and periodic orbits in flow networks

We show that the clustering coefficient, a standard measure in network theory, when applied to flow networks, i.e. graph representations of fluid flows in which links between nodes represent fluid transport between spatial regions, identifies approximate locations of periodic trajectories in the flow system. This is true for steady flows and for periodic ones in which the time interval $τ$ used to construct the network is the period of the flow or a multiple of it. In other situations the clustering coefficient still identifies cyclic motion between regions of the fluid. Besides the fluid context, these ideas apply equally well to general dynamical systems. By varying the value of $τ$ used to construct the network, a kind of spectroscopy can be performed so that the observation of high values of mean clustering at a value of $τ$ reveals the presence of periodic orbits of period $3τ$ which impact phase space significantly. These results are illustrated with examples of increasing complexity, namely a steady and a periodically perturbed model two-dimensional fluid flow, the three-dimensional Lorenz system, and the turbulent surface flow obtained from a numerical model of circulation in the Mediterranean sea.

nlin.CD↗

arXiv2015

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.

physics.ao-ph↗

arXiv2015

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.

physics.soc-ph↗

arXiv2015

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.

physics.soc-ph↗

arXiv2015

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.

physics.ao-ph↗

arXiv2014

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.

physics.ao-ph↗

arXiv2012

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 $λ' =λ/J^2$. We conjecture that the equivalence extends to all orders in $λ$ and to higher orders in 1/J.

hep-th↗