Analyzing bacterial networks and interactions in skin and gills of Sparus aurata with microalgae-based additive feeding.

The inclusion of microalgae in functional fish diets has a notable impact on the welfare, metabolism and physiology of the organism. The microbial communities associated with the fish are directly influenced by the host's diet, and further understanding the impact on mucosal microbiota is needed. This study aimed to analyze the microbiota associated with the skin and gills of Sparus aurata fed a diet containing 10% microalgae.

Key epidemiological indicators and spatial autocorrelation patterns across five waves of COVID-19 in Catalonia.

This research studies the evolution of COVID-19 crude incident rates, effective reproduction number R(t) and their relationship with incidence spatial autocorrelation patterns in the 19 months following the disease outbreak in Catalonia (Spain). A cross-sectional ecological panel design based on n = 371 health-care geographical units is used. Five general outbreaks are described, systematically preceded by generalized values of R(t) > 1 in the two previous weeks.

The study of aggression and affiliation motifs in bottlenose dolphins' social networks.

Networks in biology have provided a powerful tool to describe and study very complex biological processes and systems such as animal societies. Social network analysis allows us to assess different processes occurring in animal groups. In the current study, we use this approach to investigate how conflict dynamics and post-conflict interactions shape the social networks of groups of captive bottlenose dolphins.

Inequalities in COVID-19 inequalities research: Who had the capacity to respond?

The COVID-19 pandemic has been testing countries' capacities and scientific preparedness to actively respond and collaborate on a common global threat. It has also heightened awareness of the urgent need to empirically describe and analyze health inequalities to be able to act effectively. In turn, this raises several important questions that need answering: What is known about the rapidly emerging COVID-19 inequalities research field? Which countries and world regions have been able to rapidly produce research on this topic? What research patterns and trends have emerged, and how to these compared to the (pre-COVID-19) global health inequalities research field? Which countries have been scientifically collaborating on this important topic? Where are the scientific knowledge gaps, and indirectly where might research capacities need to be strengthened? In order to answer these queries, we analyzed the global scientific production (2020-2021) on COVID-19 associated inequalities by conducting bibliometric and network analyses using the Scopus database.

Rapid evolution of SARS-CoV-2 challenges human defenses.

The race between pathogens and their hosts is a major evolutionary driver, where both reshuffle their genomes to overcome and reorganize the defenses for infection, respectively. Evolutionary theory helps formulate predictions on the future evolutionary dynamics of SARS-CoV-2, which can be monitored through unprecedented real-time tracking of SARS-CoV-2 population genomics at the global scale. Here we quantify the accelerating evolution of SARS-CoV-2 by tracking the SARS-CoV-2 mutation globally, with a focus on the Receptor Binding Domain (RBD) of the spike protein determining infection success.

Global COVID-19 lockdown highlights humans as both threats and custodians of the environment.

The global lockdown to mitigate COVID-19 pandemic health risks has altered human interactions with nature. Here, we report immediate impacts of changes in human activities on wildlife and environmental threats during the early lockdown months of 2020, based on 877 qualitative reports and 332 quantitative assessments from 89 different studies. Hundreds of reports of unusual species observations from around the world suggest that animals quickly responded to the reductions in human presence.

The global network of ports supporting high seas fishing.

Fisheries in waters beyond national jurisdiction ("high seas") are difficult to monitor and manage. Their regulation for sustainability requires critical information on how fishing effort is distributed across fishing and landing areas, including possible border effects at the exclusive economic zone (EEZ) limits. We infer the global network linking harbors supporting fishing vessels to fishing areas in high seas from automatic identification system tracking data in 2014, observing a modular structure, with vessels departing from a given harbor fishing mostly in a single province.

Depressed β-adrenergic inotropic responsiveness and intracellular calcium handling abnormalities in Duchenne Muscular Dystrophy patients' induced pluripotent stem cell-derived cardiomyocytes.

Duchenne muscular dystrophy (DMD), caused by mutations in the dystrophin gene, is an X-linked disease affecting male and rarely adult heterozygous females, resulting in death by the late 20s to early 30s. Previous studies reported depressed left ventricular function in DMD patients which may result from deranged intracellular Ca -handling. To decipher the mechanism(s) underlying the depressed LV function, we tested the hypothesis that iPSC-CMs generated from DMD patients feature blunted positive inotropic response to β-adrenergic stimulation.

Risk of Secondary Infection Waves of COVID-19 in an Insular Region: The Case of the Balearic Islands, Spain.

The Spanish government declared the lockdown on March 14th, 2020 to tackle the fast-spreading of COVID-19. As a consequence, the Balearic Islands remained almost fully isolated due to the closing of airports and ports, these isolation measures and the home-based confinement have led to a low prevalence of COVID-19 in this region. We propose a compartmental model for the spread of COVID-19 including five compartments (Susceptible, Exposed, Presymptomatic Infective, Diseased, and Recovered), and the mobility between municipalities.

Author Correction: Robustness to extinction and plasticity derived from mutualistic bipartite ecological networks.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Robustness to extinction and plasticity derived from mutualistic bipartite ecological networks.

Understanding the response of ecological networks to perturbations and disruptive events is needed to anticipate the biodiversity loss and extinction cascades. Here, we study how network plasticity reshapes the topology of mutualistic networks in response to species loss. We analyze more than one hundred empirical mutualistic networks and considered random and targeted removal as mechanisms of species extinction.

Incubation periods impact the spatial predictability of cholera and Ebola outbreaks in Sierra Leone.

Forecasting the spatiotemporal spread of infectious diseases during an outbreak is an important component of epidemic response. However, it remains challenging both methodologically and with respect to data requirements, as disease spread is influenced by numerous factors, including the pathogen's underlying transmission parameters and epidemiological dynamics, social networks and population connectivity, and environmental conditions. Here, using data from Sierra Leone, we analyze the spatiotemporal dynamics of recent cholera and Ebola outbreaks and compare and contrast the spread of these two pathogens in the same population.

Scaling of species distribution explains the vast potential marine prokaryote diversity.

Global ocean expeditions have provided minimum estimates of ocean's prokaryote diversity, supported by apparent asymptotes in the number of prokaryotes with sampling effort, of about 40,000 species, representing <1% of the species cataloged in the Earth Microbiome Project, despite being the largest habitat in the biosphere. Here we demonstrate that the abundance of prokaryote OTUs follows a scaling that can be represented by a power-law distribution, and as a consequence, we demonstrate, mathematically and through simulations, that the asymptote of rarefaction curves is an apparent one, which is only reached with sample sizes approaching the entire ecosystem. We experimentally confirm these findings using exhaustive repeated sampling of a prokaryote community in the Red Sea and the exploration of global assessments of prokaryote diversity in the ocean.

Flexible model of network embedding.

There has lately been increased interest in describing complex systems not merely as single networks but rather as collections of networks that are coupled to one another. We introduce an analytically tractable model that enables one to connect two layers in a multilayer network by controlling the locality of coupling. In particular we introduce a tractable model for embedding one network (A) into another (B), focusing on the case where network A has many more nodes than network B.

The importance of sample size in marine megafauna tagging studies.

Telemetry is a key, widely used tool to understand marine megafauna distribution, habitat use, behavior, and physiology; however, a critical question remains: "How many animals should be tracked to acquire meaningful data sets?" This question has wide-ranging implications including considerations of statistical power, animal ethics, logistics, and cost. While power analyses can inform sample sizes needed for statistical significance, they require some initial data inputs that are often unavailable. To inform the planning of telemetry and biologging studies of marine megafauna where few or no data are available or where resources are limited, we reviewed the types of information that have been obtained in previously published studies using different sample sizes.

Election Forensics: Quantitative methods for electoral fraud detection.

The last decade has witnessed an explosion on the computational power and a parallel increase of the access to large sets of data - the so called Big Data paradigm - which is enabling to develop brand new quantitative strategies underpinning description, understanding and control of complex scenarios. One interesting area of application concerns fraud detection from online data, and more particularly extracting meaningful information from massive digital fingerprints of electoral activity to detect, a posteriori, evidence of fraudulent behavior. In this short article we discuss a few quantitative methodologies that have emerged in recent years on this respect, which altogether form the nascent interdisciplinary field of election forensics.

Convergence of marine megafauna movement patterns in coastal and open oceans.

The extent of increasing anthropogenic impacts on large marine vertebrates partly depends on the animals' movement patterns. Effective conservation requires identification of the key drivers of movement including intrinsic properties and extrinsic constraints associated with the dynamic nature of the environments the animals inhabit. However, the relative importance of intrinsic versus extrinsic factors remains elusive.

Joint effect of ageing and multilayer structure prevents ordering in the voter model.

The voter model rules are simple, with agents copying the state of a random neighbor, but they lead to non-trivial dynamics. Besides opinion processes, the model has also applications for catalysis and species competition. Inspired by the temporal inhomogeneities found in human interactions, one can introduce ageing in the agents: the probability to update their state decreases with the time elapsed since the last change.

Influence of a patient transfer network of US inpatient facilities on the incidence of nosocomial infections.

Antibiotic-resistant bacterial infections are a substantial source of morbidity and mortality and have a common reservoir in inpatient settings. Transferring patients between facilities could be a mechanism for the spread of these infections. We wanted to assess whether a network of hospitals, linked by inpatient transfers, contributes to the spread of nosocomial infections and investigate how network structure may be leveraged to design efficient surveillance systems.

Big data analyses reveal patterns and drivers of the movements of southern elephant seals.

The growing number of large databases of animal tracking provides an opportunity for analyses of movement patterns at the scales of populations and even species. We used analytical approaches, developed to cope with "big data", that require no 'a priori' assumptions about the behaviour of the target agents, to analyse a pooled tracking dataset of 272 elephant seals (Mirounga leonina) in the Southern Ocean, that was comprised of >500,000 location estimates collected over more than a decade. Our analyses showed that the displacements of these seals were described by a truncated power law distribution across several spatial and temporal scales, with a clear signature of directed movement.

The Ecology of Human Mobility.

Mobile phones and other geolocated devices have produced unprecedented volumes of data on human movement. Analysis of pooled individual human trajectories using big data approaches has revealed a wealth of emergent features that have ecological parallels in animals across a diverse array of phenomena including commuting, epidemics, the spread of innovations and culture, and collective behaviour. Movement ecology, which explores how animals cope with and optimize variability in resources, has the potential to provide a theoretical framework to aid an understanding of human mobility and its impacts on ecosystems.

A quantitative assessment of Arctic shipping in 2010-2014.

Rapid loss of sea ice is opening up the Arctic Ocean to shipping, a practice that is forecasted to increase rapidly by 2050 when many models predict that the Arctic Ocean will largely be free of ice toward the end of summer. These forecasts carry considerable uncertainty because Arctic shipping was previously considered too sparse to allow for adequate validation. Here, we provide quantitative evidence that the extent of Arctic shipping in the period 2011-2014 is already significant and that it is concentrated (i) in the Norwegian and Barents Seas, and (ii) predominantly accessed via the Northeast and Northwest Passages.

Bayesian decision making in human collectives with binary choices.

Here we focus on the description of the mechanisms behind the process of information aggregation and decision making, a basic step to understand emergent phenomena in society, such as trends, information spreading or the wisdom of crowds. In many situations, agents choose between discrete options. We analyze experimental data on binary opinion choices in humans.

Is the voter model a model for voters?

The voter model has been studied extensively as a paradigmatic opinion dynamics model. However, its ability to model real opinion dynamics has not been addressed. We introduce a noisy voter model (accounting for social influence) with recurrent mobility of agents (as a proxy for social context), where the spatial and population diversity are taken as inputs to the model.

Dynamics of link states in complex networks: the case of a majority rule.

Motivated by the idea that some characteristics are specific to the relations between individuals and not to the individuals themselves, we study a prototype model for the dynamics of the states of the links in a fixed network of interacting units. Each link in the network can be in one of two equivalent states. A majority link-dynamics rule is implemented, so that in each dynamical step the state of a randomly chosen link is updated to the state of the majority of neighboring links.