Dataset available at http://hdl.handle.net/10261/151808, We study the problem of sinking particles in a realistic oceanic flow, with major energetic structures in the mesoscale, focussing in the range of particle sizes and densities appropriate for marine biogenic particles. Our aim is to unify the theoretical investigations with its applications in the oceanographic context and considering a mesoscale simulation of the oceanic velocity field. By using the equation of motion of small particles in a fluid flow, we assess the influence of physical processes such as the Coriolis force and the inertia of the particles, and we conclude that they represent negligible corrections to the most important terms, which are passive motion with the velocity of the flow, and a constant added vertical velocity due to gravity. Even if within this approximation three-dimensional clustering of particles can not occur, two-dimensional cuts or projections of the evolving three-dimensional density can display inhomogeneities similar to the ones observed in sinking ocean particles., We acknowledge support from Ministerio de Economía y Competitividad and Fondo Europeo de Desarrollo Regional through the LAOP project (CTM2015-66407-P, MINECO/FEDER), from the Office of Naval Research Grant No. N00014-16-1-2492, and through a Juan de la Cierva Incorporación fellowship (IJCI-2014-22343) granted to V.R., Peer reviewed

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., LAOP, CTM2015-66407-P (AEI/FEDER,EU), ESOTECOS FIS2015-63628-C2-1-R (AEI/FEDER, EU), “Investissements d’Avenir” implemented by ANR
(ANR-10-LABX-54 MEMOLIFE and ANR-11-IDEX-0001-02 PSL Research University), Peer reviewed

Brownian particles interacting via repulsive soft-core potentials can spontaneously aggregate, despite repelling each other, and form periodic crystals of particle clusters. We study this phenomenon in low-dimensional situations (one and two dimensions) at two levels of description: by performing numerical simulations of the discrete particle dynamics and by linear and nonlinear analysis of the corresponding Dean-Kawasaki equation for the macroscopic particle density. Restricting to low dimensions and neglecting fluctuation effects, we gain analytical insight into the mechanisms of the instability leading to clustering which turn out to be the interplay among diffusion, the intracluster forces, and the forces between neighboring clusters. We show that the deterministic part of the Dean-Kawasaki equation provides a good description of the particle dynamics, including width and shape of the clusters and over a wide range of parameters, and analyze with weakly nonlinear techniques the nature of the pattern-forming bifurcation in one and two dimensions. Finally, we briefly discuss the case of attractive forces., We acknowledge financial support from Ministerio de Economía y Competitividad and Fondo Europeo de Desarrollo Regional under Projects No. FIS2015-63628-C2-1-R (MINECO/FEDER), No. FIS2015-63628-C2-2-R (MINECO/FEDER), and No. CTM2015-66407-P (MINECO/FEDER). C.L. acknowledges the COST Action No. MP1305, supported by COST (European Cooperation in Science and Technology)., Peer reviewed

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.
The Lagrangian description of fluid dynamics, which focuses on the motion of the fluid particles as they are advected by the flow, provides a useful bridge between the theory of dynamical systems and the analysis of fluid transport and mixing, so that techniques and results can be transferred from one field to the other. Modern network theory has also been brought into contact with fluid dynamics and dynamical systems through the concept of flow networks, in which the motion of fluid particles between different regions is represented by links in a graph. In this paper, we use the flow network framework to show that the clustering coefficient, a standard measure in network theory, identifies periodic orbits, fundamental objects in the theory of dynamical systems, and is also of importance in the context of fluid motion., We acknowledge the financial support from Spanish Ministerio de Economía y Competitividad and Fondo Europeo de Desarrollo Regional under grants LAOP, CTM2015-66407-P (MINECO/FEDER) and ESOTECOS projects FIS2015-63628-C2-1-R (MINECO/FEDER), FIS2015-63628-C2-2-R (MINECO/FEDER), and from the program “Investissements d'Avenir” launched by the French Government and implemented by ANR under grants ANR-10-LABX-54 MEMOLIFE and ANR-11-IDEX-0001-02 PSL* Research University., No

Lagrangian Flow Network (LFN) is a modelling framework in which ocean sub-areas are represented as nodes in a network interconnected by links representing transport of propagules (eggs and larvae) by currents. We asses the sensitivity and robustness of four LFN-derived connectivity metrics measuring retention and exchange. The most relevant parameters are tested over large ranges and a wide region with contrasting hydrodynamics: density of released particles, node size (spatial scale of discretization), Pelagic Larval Duration (PLD) and spawning modality. We find a minimum density of released particles that guarantees reliable values for most of the metrics examined. We also find that node size has a nontrivial influence on them. Connectivity estimates for long PLDs are more robust against biological uncertainties (PLD and spawning date) than for short PLDs. For mass-spawners releasing propagules over short periods (≈ 2-10 days), daily release must be simulated to properly consider connectivity fluctuations due to variable currents. In contrast, average connectivity estimates for species that spawn repeatedly over longer durations (few weeks to few months) remain robust even using longer periodicity (5-10 days). Our results have implications to design connectivity experiments with particle-tracking models and to evaluate the reliability of their results., The authors acknowledge supports from Ministerio de Economia y Competitividad and Fondo Europeo de Desarrollo Regional through the LAOP project (CTM2015-66407-P, MINECO/FEDER) and through a Juan de la Cierva—Incorporación fellowship (IJCI-2014-22343) granted to VR, from ECs Marie-Curie ITN program (FP7-PEOPLE-2011-ITN) through the LINC project (289447) and from MISTRALS ENVI-Med through the HYDROGENCONNECT project. ES-G received partial support under the French program “Investissements d’Avenir” implemented by ANR (ANR-10-LABX-54 MEMOLIFE and ANR-11-IDEX-0001-02 PSL Research University)., Peer reviewed

Many natural processes rely on optimizing the success ratio of a search process. We use an experimental setup consisting of a simple online game in which players have to find a target hidden on a board, to investigate how the rounds are influenced by the detection of cues. We focus on the search duration and the statistics of the trajectories traced on the board. The experimental data are explained by a family of random-walk-based models and probabilistic analytical approximations. If no initial information is given to the players, the search is optimized for cues that cover an intermediate spatial scale. In addition, initial information about the extension of the cues results, in general, in faster searches. Finally, strategies used by informed players turn into non-stationary processes in which the length of e ach displacement evolves to show a well-defined characteristic scale that is not found in non-informed searches., This work is funded by the Gordon and Betty Moore Foundation through Grant GBMF2550.06 to RMG, Universitat de les Illes Balears through a 2015 Young Visiting Scholar grant to RMG, the US National Science Foundation through grant ABI 1458748 to JMC and Ministerio de Economía y Competitividad and Fondo Europeo de Desarrollo Regional through project CTM2015-66407-P (MINECO/FEDER) to CL., Peer reviewed

We study the appearance and properties of cluster crystals (solids in which the unit cell is occupied by a cluster of particles) in a two-dimensional system of self-propelled active Brownian particles with repulsive interactions. Self-propulsion deforms the clusters by depleting particle density inside, and for large speeds it melts the crystal. Continuous field descriptions at several levels of approximation allow us to identify the relevant physical mechanisms., We acknowledge financial support from grants LAOP, CTM2015-66407-P (AEI/FEDER, EU) and ESOTECOS, FIS2015-63628-C2-1-R (AEI/FEDER, EU)., Peer reviewed

A stochastic birth-death competition model for particles with excluded volume is proposed. The particles move, reproduce, and die on a regular lattice. While the death rate is constant, the birth rate is spatially nonlocal and implements inter-particle competition by a dependence on the number of particles within a finite distance. The finite volume of particles is accounted for by fixing an upper value to the number of particles that can occupy a lattice node, compromising births and movements. We derive closed macroscopic equations for the density of particles and spatial correlation at two adjacent sites. Under different conditions, the description is further reduced to a single equation for the particle density that contains three terms: diffusion, a linear death, and a highly nonlinear and nonlocal birth term. Steady-state homogeneous solutions, their stability which reveals spatial pattern formation, and the dynamics of time-dependent homogeneous solutions are discussed and compared, in the one-dimensional case, with numerical simulations of the particle system., We acknowledge financial support from grants LAOP, CTM2015-66407-P (AEI/FEDER, EU) and ESOTECOS, FIS2015-63628-C2-1-R and FIS2015-63628-C2-2-R (AEI/FEDER,
EU)., No

Particle systems interacting with a soft repulsion, at thermal equilibrium and under some circumstances, are known to form cluster crystals, i.e., periodic arrangements of particle aggregates. We study here how these states are modified by the presence of an additional hard-core repulsion, accounting for particle size. To this end we consider a two-dimensional system of Brownian particles interacting through a potential which includes hard-core and soft-core (of the GEM-α type) repulsive terms. The system shows different phases, and we focus in the regime where cluster crystals form. We consider two situations: the low-temperature one in which particles inside the clusters also show an ordered structure (crystal cluster-crystal phase), and the one occurring at higher temperature in which particles within the clusters are spatially disordered (fluid cluster crystal). An explicit expression for the energy in terms of the typical distance between clusters and the typical distance of the particles within the clusters is obtained for vanishing temperature, from which mean mean inter- and intracluster distances are obtained. Finite-temperature corrections are also discussed, considering explicitly the role of entropy., We acknowledge financial support from the Spanish Grants LAOP CTM2015-66407-P (AEI/FEDER, EU) and ESOTECOS FIS2015-63628-C2-1-R (AEI/FEDER, EU)., Peer reviewed

The skill of current predictions of the warm phase of the El Niño Southern Oscillation (ENSO) reduces significantly beyond a lag time of 6 months. In this paper, we aim to increase this prediction skill at lag times of up to 1 year. The new method combines a classical autoregressive integrated moving average technique with a modern machine learning approach (through an artificial neural network). The attributes in such a neural network are derived from knowledge of physical processes and topological properties of climate networks, and they are tested using a Zebiak–Cane-type model and observations. For predictions up to 6 months ahead, the results of the hybrid model give a slightly better skill than the CFSv2 ensemble prediction by the National Centers for Environmental Prediction (NCEP). Interestingly, results for a 12-month lead time prediction have a similar skill as the shorter lead time predictions., Cristóbal López and Emilio Hernández-García acknowledge support from Ministerio de Economia y Competitividad and Fondo Europeo de Desarrollo Regional through the LAOP project (CTM2015-66407-P, MINECO/FEDER)., Peer reviewed

Data generated in this study are available from the URL https://doi.org/10.20350/digitalCSIC/8630, Sedimentation of particles in the ocean leads to inhomogeneous horizontal distributions at depth, even if the release process is homogeneous. We study this phenomenon considering a horizontal sheet of sinking particles immersed in an oceanic flow and determine how the particles are distributed when they sediment on the seabed (or are collected at a given depth). The study is performed from a Lagrangian viewpoint attending to the properties of the oceanic flow and the physical characteristics (size and density) of typical biogenic sinking particles. Two main processes determine the distribution, the stretching of the sheet caused by the flow, and its projection on the surface where particles accumulate. These mechanisms are checked, besides an analysis of their relative importance to produce inhomogeneities, with numerical experiments in the Benguela region. Faster (heavier or larger) sinking particles distribute more homogeneously than slower ones., We acknowledge financial support from the Spanish Grants LAOP CTM2015-66407-P (AEI/FEDER, EU)
and ESOTECOS FIS2015-63628-C2-1-R (AEI/FEDER, EU). G. D. acknowledges support from the
Hungarian Grant NKFI-124256 (NKFIH).We acknowledge support from the Spanish Research Agency,
through Grant MDM-2017-0711 from the Maria de Maeztu Program for Units of Excellence in R&D., Peer reviewed

Marine 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., M. Hidalgo acknowledges support of two contracts funded by the Spanish national program “Ramon y Cajal” (RYC‐2015‐18646) and by the regional government of the Balearic Islands, the later co‐funded by the European Social Fund 2014‐2020. V. Rossi acknowledges support of a post‐doctoral ‘Juan de la Cierva Incorporacion’ fellowship (IJCI‐2014‐22343) provided by the Spanish MICINN and a networking grant through the HYDROGENCONNECT project funded by the French program MISTRALS ENVI‐Med. E. Ser‐Giacomi thanks French program “Investissements d'Avenir” (ANR‐10‐LABX‐54 MEMOLIFE and ANR‐11‐IDEX‐0001‐02 PSL Research University). This work was also supported by the Spanish National projects LAOP (CTM2015‐66407‐P) P. Monroy and E. Hernandez‐Garcia and CLIFISH (CTM2015‐66400‐C3‐1‐R) and to M. Hidalgo, B. Guijarro, and E. Massuti (AEI/FEDER, EU). P. Reglero and M. Hidalgo acknowledge funding of the H2020 PANDORA project (Nr. 773713)., Peer reviewed

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. Until now, most of the analysis has been based on Lagrangian concepts of transport, often focusing on the identification of features that minimize fluid exchange among regions, or more recently, on network tools which focus instead on connectivity and transport pathways. Neither of these approaches, however, allows us to rank the geographical sites of major water passage, and at the same time, to select 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 occurring here. Promising applications to other fields, such as larval connectivity, marine spatial planning or contaminant detection, are then discussed., This work is a contribution to the CNES/TOSCA projects LAECOS and BIOSWOT, and it was partly funded by the Copernicus Marine Environment Monitoring Service (CMEMS) Sea Level Thematic Assembly Centre (SL-TAC). C.L and E. H-G. acknowledge support from Ministerio de Economía y Competitividad and Fondo Europeo de Desarrollo Regional through the LAOP project (CTM2015-66407-P, MINECO/FEDER)., No

We study the teleconnection between El Niño–Southern Oscillation (ENSO) and the Indian summer monsoon (IM) in large ensemble simulations, the Max Planck Institute Earth System Model (MPI-ESM), and the Community Earth System Model (CESM1). We characterize ENSO by the June–August Niño-3 box-average SST and the IM by the June–September average precipitation over India, and define their teleconnection in a changing climate as an ensemble-wise correlation. To test robustness, we also consider somewhat different variables that can characterize ENSO and the IM. We utilize ensembles converged to the system’s snapshot attractor for analyzing possible changes in the teleconnection. Our main finding is that the teleconnection strength is typically increasing on the long term in view of appropriately revised ensemble-wise indices. Indices involving a more western part of the Pacific reveal, furthermore, a short-term but rather strong increase in strength followed by some decrease at the turn of the century. Using the station-based Southern Oscillation index (SOI) as opposed to area-based indices leads to the identification of somewhat more erratic trends, but the turn-of-the-century “bump” is well detectable with it. All this is in contrast, if not in contradiction, to the discussion in the literature of a weakening teleconnection in the late twentieth century. We show here that this discrepancy can be due to any of three reasons: 1) ensemble-wise and temporal correlation coefficients used in the literature are different quantities; 2) the temporal moving correlation has a high statistical variability but possibly also persistence; or 3) MPI-ESM does not represent the Earth system faithfully., The simulations for the MPI-RCP8.5E were supported by the H2020 grant for the CRESCENDO project (Grant 641816). MH is thankful for the great support of the DFG Cluster of Excellence CliSAP. This research was supported by the National Research, Development and Innovation Office, NKFIH, under Grants PD124272, K125171, and FK124256. GD was supported by the Ministerio de Economía, Industria y Competitividad of the Spanish Government under Grant LAOP CTM2015-66407-P (AEI/FEDER, EU), and by the European Social Fund under CAIB grant PD/020/2018 “Margalida Comas”. TB, VL, and FL were supported by the H2020 grants for the CRESCENDO (Grant 641816) and Blue-Action (Grant 727852) projects. VL has been supported by the DFG Sfb/Transregio TRR181 project. TB was also supported by the Institute for Basic Science (IBS), under IBS-R028-D1., Peer reviewed

Vegetation patterns are abundant in arid and semiarid ecosystems, but how they form remains unclear. One of the most extended theories lies in the existence of scale-dependent feedbacks (SDF) in plant-to-plant and plant-water interactions. Short distances are dominated by facilitative interactions, whereas competitive interactions dominate at larger scales. These feedbacks shape spatially inhomogeneous distributions of water that ultimately drive the emergence of patterns of vegetation. Even though the presence of facilitative and competitive interactions is clear, they are often hard to disentangle in the field, and therefore their relevance in vegetation pattern formation is still disputable. Here, we review the biological processes that have been proposed to explain pattern formation in arid ecosystems and how they have been implemented in mathematical models. We conclude by discussing the existence of similar structures in different biological and physical systems., This work is funded by the Gordon & Betty Moore Foundation through grant GBMF2550.06 to RMG and Ministerio de Economía y Competitividad and Fondo Europeo de Desarrollo Regional through project CTM2015-66407-P (MINECO/FEDER) to CL., No