System crash as dynamics of complex networks

Symbiotic bacterial communities and carbon metabolic profiles of Acropora coral with varying health status under thermal stress

Thermal-induced coral bleaching has received substantial research attention; however, the dynamics of symbiotic coral-associated bacterial communities are underexplored and the roles of coral with intermediate health status remain unclear. Using high-throughput sequencing and biochemical analyses, we found that the symbiotic zooxanthellae number gradually decreased with the increase of bleaching degree (non-bleached, semi-bleached, and fully-bleached) in the coral Acropora pruinosa. The semi-bleached host exhibited a relatively more complex microbial interaction network. For the carbon metabolic profiles, relatively higher carbon-fixing abilities observed in non-bleached coral symbiotic bacteria, followed by semi-bleached host, and lowest values appeared in fully-bleached coral. Partial least-squares pathway modeling revealed that bacterial community features and carbon metabolic function were directly related with health status, while temperature exerted a strong influence on the bleaching resilience. These findings can help us better understand the coral microecological feature and carbon metabolic potential under changing environment.

Bleached coral supports high diversity and heterogeneity of bacterial communities: Following the rule of the 'Anna Karenina principle'

Coral-associated bacteria are sensitive to the health status of coral and proven biomarker(s) of the coral bleaching. However, whether coral specificity or health status play a key role when coral-associated bacteria responding to coral bleaching is not known. Therefore, the bacterial communities of five species of healthy and bleached corals, Acropora millepora, Favites abdita, Galaxea fascicularis, Dipsastraea speciosa and Pocillopora damicornis, were collected along the coast of Sanya, South China Sea and targeted for associated bacterial studies. The relative abundance of the dominant class Gammaproteobacteria tended to be higher in healthy corals, while Alphaproteobacteria were more abundant in bleached corals. Dominant genus Achromobacter demonstrated higher relative abundance in healthy corals (0.675) than in bleached corals (0.151). Most of the bleached corals had high α diversity, β dispersion, heterogeneity and complexity of the co-occurrence network of bacterial communities, which support the 'Anna Karenina Principle (AKP)' of diverse in threatened objects and conserved in healthy ones. The bacterial communities in the bleached corals were mostly involved in the selection process, and communities in the healthy corals were involved in the undominated process, which is obtained based on the null model test of β nearest-taxon-index (βNTI) and Bray-Curtis-based Raup-Crick (RCBray). This evidence further confirmed the AKP and revealed that the bacterial communities in the bleached corals were driven by deterministic factors. These findings provide valuable insights into the connection between bacterial and coral status, and the application of the AKP in the changing patterns of bacterial communities during coral bleaching.

Impact of Nutrient Enrichment on Community Structure and Co-Occurrence Networks of Coral Symbiotic Microbiota in Duncanopsammia peltata: Zooxanthellae, Bacteria, and Archaea

Symbiotic microorganisms in reef-building corals, including algae, bacteria, archaea, fungi, and viruses, play critical roles in the adaptation of coral hosts to adverse environmental conditions. However, their adaptation and functional relationships in nutrient-rich environments have yet to be fully explored. This study investigated Duncanopsammia peltata and the surrounding seawater and sediments from protected and non-protected areas in the summer and winter in Dongshan Bay. High-throughput sequencing was used to characterize community changes, co-occurrence patterns, and factors influencing symbiotic coral microorganisms (zooxanthellae, bacteria, and archaea) in different environments. The results showed that nutrient enrichment in the protected and non-protected areas was the greatest in December, followed by the non-protected area in August. In contrast, the August protected area had the lowest nutrient enrichment. Significant differences were found in the composition of the bacterial and archaeal communities in seawater and sediments from different regions. Among the coral symbiotic microorganisms, the main dominant species of zooxanthellae is the C1 subspecies (42.22-56.35%). The dominant phyla of bacteria were Proteobacteria, Cyanobacteria, Firmicutes, and Bacteroidota. Only in the August protected area did a large number (41.98%) of SAR324_cladeMarine_group_B exist. The August protected and non-protected areas and December protected and non-protected areas contained beneficial bacteria as biomarkers. They were Nisaea, Spiroplasma, Endozoicomonas, and Bacillus. No pathogenic bacteria appeared in the protected area in August. The dominant phylum in Archaea was Crenarchaeota. These symbiotic coral microorganisms' relative abundances and compositions vary with environmental changes. The enrichment of dissolved inorganic nitrogen in environmental media is a key factor affecting the composition of coral microbial communities. Co-occurrence analysis showed that nutrient enrichment under anthropogenic disturbances enhanced the interactions between coral symbiotic microorganisms. These findings improve our understanding of the adaptations of coral holobionts to various nutritional environments.

Long-term effects on liver metabolism induced by ceftriaxone sodium pretreatment

Ceftriaxone is an emerging contaminant due to its potential harm, while its effects on liver are still need to be clarified. In this study, we first pretreated the 8-week-old C57BL/6J mice with high dose ceftriaxone sodium (Cef, 400 mg/mL, 0.2 mL per dose) for 8 days to prepare a gut dysbiosis model, then treated with normal feed for a two-month recovery period, and applied non-targeted metabolomics (including lipidomics) to investigate the variations of fecal and liver metabolome, and coupled with targeted determination of fecal short-chain fatty acids (SCFAs) and bile acids (BAs). Lastly, the correlations and mediation analysis between the liver metabolism and gut metabolism/microbes were carried, and the potential mechanisms of the mal-effects on gut-liver axis induced by Cef pretreatment were accordingly discussed. Compared to the control group, Cef pretreatment reduced the rate of weight gain and hepatosomatic index, induced bile duct epithelial cells proliferated around the central vein and appearance of binucleated hepatocytes, decreased the ratio of total branching chains amino acids (BCAAs) to total aromatic amino acids (AAAs) in liver metabolome. In fecal metabolome, the total fecal SCFAs and BAs did not change significantly while butyric acid decreased and the primary BAs increased after Cef pretreatment. Correlation and mediation analysis revealed one potential mechanism that Cef may first change the intestinal microbiota (such as destroying its normal structure, reducing its abundance and the stability of the microbial network or certain microbe abundance like Alistipes), and then change the intestinal metabolism (such as acetate, caproate, propionate), leading to liver metabolic disorder (such as spermidine, inosine, cinnamaldehyde). This study proved the possibility of Cef-induced liver damage, displayed the overall metabolic profile of the liver following Cef pretreatment and provided a theoretical framework for further research into the mechanism of Cef-induced liver damage.

Bacterial Communities Vary from Different Scleractinian Coral Species and between Bleached and Non-Bleached Corals

Bleaching is one of the most relevant factors implicated in the integrity of coral reef ecosystems, with the increasing frequency and intensity of damaging events representing a serious threat to reef biodiversity. Here, we analyzed changes in coral-associated bacteria from three types of non-bleached and bleached scleractinian corals (Acropora digitifera, Galaxea fascicularis, and Porites pukoensis) in Hainan Luhuitou peninsula coastal areas. The community structure of symbiotic bacteria differed significantly among the three apparently healthy corals. The bleached corals had higher bacterial alpha diversity and some specific bacteria genera, including Ruegeria, Methyloceanibacter, Filomicrobium, Halioglobus, Rubripirellula, Rhodopirellula, Silicimonas, Blastopirellula, Sva0996 marine group, Woeseia, and unclassified_c_Gammaproteobacteria, were consistently increased in bleached groups. Network analysis revealed significantly different degrees of modularity between bleached and non-bleached groups at the bacterial genus level, and a higher proportion of links was dominated by positive co-occurrences. Functional prediction analysis illustrated that coral-associated bacteria remained relatively consistent in the bleached and non-bleached groups. Structure equation modeling revealed that the bacterial community diversity and function were directly influenced by host and environment factors. These findings suggested that coral-associated bacterial responses to bleaching occur in a host-dependent manner, informing novel strategies for restoring coral and aiding adaption to bleaching stress. IMPORTANCE Accumulating evidence indicates that coral-associated bacteria play an important role in the health of holobionts. However, the variability of the symbiotic bacterial community structure among coral species with different coral health statuses remains largely unknown. Here, we investigated three apparent non-bleached (healthy) and bleached coral species (sampled in situ), involving related symbiotic bacterial profiles, including composition, alpha diversity, network relationship, and potential function. Structural equation modeling analysis was used to analyze the relationship between coral status and abiotic and biotic factors. The bacterial community structure of different groups was shown to exhibit host-specific traits. Both host and environmental impacts had primary effects on coral-associated microbial communities. Future studies are needed to identify the mechanisms that mediate divergent microbial consortia.

Prokaryotic and eukaryotic microbial communities associated with coral species have high host specificity in the South China Sea

Reef-building corals are well known for their obligate association with Symbiodiniaceae, and an array of other microbes, including bacteria, fungi, and symbiotic algae (i.e., total microbiome), which together form the coral holobiont. The total microbiome plays an intricate part in maintaining the homeostasis of the coral holobiont and is closely associated with host health. However, the composition of the coral associated microbiome and interaction between its different members remains elusive because few analyses have bridged taxonomically disparate groups. This research gaps have prevented a holistic understanding of the total microbiome. Thus, to simultaneously characterize the bacterial, fungal and symbiotic algal communities associated with different coral species, and explore the relationship between these symbionts and coral health, healthy and bleached tissues from four coral species, Acropora muricata, Galaxea fascicularis, Platygyra daedalea, and Pavona explanulata, were collected from the Xisha Islands of the South China Sea. Using high throughput sequencing, a high degree of host-specificity was observed among bacterial, fungal, and algal groups across coral species. There were no obvious changes in the microbial community structure of apparently healthy and bleached corals, but host bleaching allowed colonization of the holobionts by diverse opportunistic microbes, resulting in a significant elevation in the α-diversity of microbial communities. In addition, co-occurrence analysis of the coral microbiota also identified more complex microbial interactions in bleached corals than in healthy ones. In summary, this study characterized the structure of coral-associated microbiomes across four coral species, and systematically studied microbiome differences between healthy and bleached corals. The findings improve our understanding of the heterogeneity of symbiotic microorganisms and the impact of coral's physiological status on its associated microbial communities composition.

Opinion dynamics in financial markets via random networks

We investigate financial market dynamics by introducing a heterogeneous agent-based opinion formation model. In this work, we organize individuals in a financial market according to their trading strategy, namely, whether they are noise traders or fundamentalists. The opinion of a local majority compels the market exchanging behavior of noise traders, whereas the global behavior of the market influences the decisions of fundamentalist agents. We introduce a noise parameter, q, to represent the level of anxiety and perceived uncertainty regarding market behavior, enabling the possibility of adrift financial action. We place individuals as nodes in an Erdös-Rényi random graph, where the links represent their social interactions. At any given time, individuals assume one of two possible opinion states ±1 regarding buying or selling an asset. The model exhibits fundamental qualitative and quantitative real-world market features such as the distribution of logarithmic returns with fat tails, clustered volatility, and the long-term correlation of returns. We use Student's t distributions to fit the histograms of logarithmic returns, showing a gradual shift from a leptokurtic to a mesokurtic regime depending on the fraction of fundamentalist agents. Furthermore, we compare our results with those concerning the distribution of the logarithmic returns of several real-world financial indices.

Fragmentation of outage clusters during the recovery of power distribution grids

The understanding of recovery processes in power distribution grids is limited by the lack of realistic outage data, especially large-scale blackout datasets. By analyzing data from three electrical companies across the United States, we find that the recovery duration of an outage is connected with the downtime of its nearby outages and blackout intensity (defined as the peak number of outages during a blackout), but is independent of the number of customers affected. We present a cluster-based recovery framework to analytically characterize the dependence between outages, and interpret the dominant role blackout intensity plays in recovery. The recovery of blackouts is not random and has a universal pattern that is independent of the disruption cause, the post-disaster network structure, and the detailed repair strategy. Our study reveals that suppressing blackout intensity is a promising way to speed up restoration.

From the origin of life to pandemics: emergent phenomena in complex systems

When a large number of similar entities interact among each other and with their environment at a low scale, unexpected outcomes at higher spatio-temporal scales might spontaneously arise. This non-trivial phenomenon, known as emergence, characterizes a broad range of distinct complex systems-from physical to biological and social-and is often related to collective behaviour. It is ubiquitous, from non-living entities such as oscillators that under specific conditions synchronize, to living ones, such as birds flocking or fish schooling. Despite the ample phenomenological evidence of the existence of systems' emergent properties, central theoretical questions to the study of emergence remain unanswered, such as the lack of a widely accepted, rigorous definition of the phenomenon or the identification of the essential physical conditions that favour emergence. We offer here a general overview of the phenomenon of emergence and sketch current and future challenges on the topic. Our short review also serves as an introduction to the theme issue Emergent phenomena in complex physical and socio-technical systems: from cells to societies, where we provide a synthesis of the contents tackled in the issue and outline how they relate to these challenges, spanning from current advances in our understanding on the origin of life to the large-scale propagation of infectious diseases. This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.

Non-Markovian random walks characterize network robustness to nonlocal cascades

Localized perturbations in a real-world network have the potential to trigger cascade failures at the whole system level, hindering its operations and functions. Standard approaches analytically tackling this problem are mostly based either on static descriptions, such as percolation, or on models where the failure evolves through first-neighbor connections, crucially failing to capture the nonlocal behavior typical of real cascades. We introduce a dynamical model that maps the failure propagation across the network to a self-avoiding random walk that, at each step, has a probability to perform nonlocal jumps toward operational systems' units. Despite the inherent non-Markovian nature of the process, we are able to characterize the critical behavior of the system out of equilibrium, as well as the stopping time distribution of the cascades. Our numerical experiments on synthetic and empirical biological and transportation networks are in excellent agreement with theoretical expectation, demonstrating the ability of our framework to quantify the vulnerability to nonlocal cascade failures of complex systems with interconnected structure.

Lanza V, Rodríguez-Beltrán J, Galán JC, San Millán A, Cantón R, Coque TM. Evolutionary Pathways and Trajectories in Antibiotic Resistance

Evolution is the hallmark of life. Descriptions of the evolution of microorganisms have provided a wealth of information, but knowledge regarding "what happened" has precluded a deeper understanding of "how" evolution has proceeded, as in the case of antimicrobial resistance. The difficulty in answering the "how" question lies in the multihierarchical dimensions of evolutionary processes, nested in complex networks, encompassing all units of selection, from genes to communities and ecosystems. At the simplest ontological level (as resistance genes), evolution proceeds by random (mutation and drift) and directional (natural selection) processes; however, sequential pathways of adaptive variation can occasionally be observed, and under fixed circumstances (particular fitness landscapes), evolution is predictable. At the highest level (such as that of plasmids, clones, species, microbiotas), the systems' degrees of freedom increase dramatically, related to the variable dispersal, fragmentation, relatedness, or coalescence of bacterial populations, depending on heterogeneous and changing niches and selective gradients in complex environments. Evolutionary trajectories of antibiotic resistance find their way in these changing landscapes subjected to random variations, becoming highly entropic and therefore unpredictable. However, experimental, phylogenetic, and ecogenetic analyses reveal preferential frequented paths (highways) where antibiotic resistance flows and propagates, allowing some understanding of evolutionary dynamics, modeling and designing interventions. Studies on antibiotic resistance have an applied aspect in improving individual health, One Health, and Global Health, as well as an academic value for understanding evolution. Most importantly, they have a heuristic significance as a model to reduce the negative influence of anthropogenic effects on the environment.

Compositional homogeneity in the pathobiome of a new, slow-spreading coral disease

BACKGROUND

Coral reefs face unprecedented declines in diversity and cover, a development largely attributed to climate change-induced bleaching and subsequent disease outbreaks. Coral-associated microbiomes may strongly influence the fitness of their hosts and alter heat tolerance and disease susceptibility of coral colonies. Here, we describe a new coral disease found in Micronesia and present a detailed assessment of infection-driven changes in the coral microbiome.

RESULTS

Combining field monitoring and histological, microscopic and next-generation barcoding assessments, we demonstrate that the outbreak of the disease, named 'grey-patch disease', is associated with the establishment of cyanobacterial biofilm overgrowing coral tissue. The disease is characterised by slow progression rates, with coral tissue sometimes growing back over the GPD biofilm. Network analysis of the corals' microbiome highlighted the clustering of specific microbes which appeared to benefit from the onset of disease, resulting in the formation of 'infection clusters' in the microbiomes of apparently healthy corals.

CONCLUSIONS

Our results appear to be in contrast to the recently proposed Anna-Karenina principle, which states that disturbances (such as disease) trigger chaotic dynamics in microbial communities and increase β-diversity. Here, we show significantly higher community similarity (compositional homogeneity) in the pathobiome of diseased corals, compared to the microbiome associated with apparently healthy tissue. A possible explanation for this pattern is strong competition between the pathogenic community and those associated with the 'healthy' coral holobiont, homogenising the composition of the pathobiome. Further, one of our key findings is that multiple agents appear to be involved in degrading the corals' defences causing the onset of this disease. This supports recent findings indicating a need for a shift from the one-pathogen-one-disease paradigm to exploring the importance of multiple pathogenic players in any given disease.

Universal behavior of cascading failures in interdependent networks

Catastrophic and major disasters in real-world systems, such as blackouts in power grids or global failures in critical infrastructures, are often triggered by minor events which originate a cascading failure in interdependent graphs. We present here a self-consistent theory enabling the systematic analysis of cascading failures in such networks and encompassing a broad range of dynamical systems, from epidemic spreading, to birth-death processes, to biochemical and regulatory dynamics. We offer testable predictions on breakdown scenarios, and, in particular, we unveil the conditions under which the percolation transition is of the first-order or the second-order type, as well as prove that accounting for dynamics in the nodes always accelerates the cascading process. Besides applying directly to relevant real-world situations, our results give practical hints on how to engineer more robust networked systems.

Crash dynamics of interdependent networks

The emergence and evolution of real-world systems have been extensively studied in the last few years. However, equally important phenomena are related to the dynamics of systems' collapse, which has been less explored, especially when they can be cast into interdependent systems. In this paper, we develop a dynamical model that allows scrutinizing the collapse of systems composed of two interdependent networks. Specifically, we explore the dynamics of the system's collapse under two scenarios: in the first one, the condition for failure should be satisfied for the focal node as well as for its corresponding node in the other network; while in the second one, it is enough that failure of one of the nodes occurs in either of the two networks. We report extensive numerical simulations of the dynamics performed in different setups of interdependent networks, and analyze how the system behavior depends on the previous scenarios as well as on the topology of the interdependent system. Our results can provide valuable insights into the crashing dynamics and evolutionary properties of interdependent complex systems.

A Survey on Power System Blackout and Cascading Events: Research Motivations and Challenges

Power systems are the most complex systems and have great importance in modern life. They have direct impacts on the modernization, economic, political and social aspects. To operate such systems in a stable mode, several control and protection techniques are required. However, modern systems are equipped with several protection schemes with the aim of avoiding the unpredicted events and power outages, power systems are still encountering emergency and mal-operation situations. The most severe emergencies put the whole or at least a part of the system in danger. If the emergency is not well managed, the power system is likely to have cascading failures that might lead to a blackout. Due to the consequences, many countries around the world have research and expert teams who work to avoid blackouts on their systems. In this paper, a comprehensive review on the major blackouts and cascading events that have occurred in the last decade are introduced. A particular focus is given on the US power system outages and their causes since it is one of the leading power producers in the world and it is also due to the ready availability of data for the past events. The paper also highlights the root causes of different blackouts around the globe. Furthermore, blackout and cascading analysis methods and the consequences of blackouts are surveyed. Moreover, the challenges in the existing protective schemes and research gaps in the topic of power system blackout and cascading events are marked out. Research directions and issues to be considered in future power system blackout studies are also proposed.

Environment-based preference selection promotes cooperation in spatial prisoner's dilemma game

The impact of environment on individuals is particularly critical. In evolutionary games, adopting the strategy of the neighbor who performs better is nontrivial for the survival and maintenance of cooperation, in that such an action may help the agents to obtain higher benefit and more obvious evolutionary advantages. Inspired by this idea, we investigate the effect of the environment-based preference selection on the evolution of cooperation in spatial prisoner’s dilemma. A simple rule, incorporating individual preference selection via an adjustable parameter α to explore how the selection of the potential strategy sources influences individual behavior traits, is considered. Because social interaction may not be the only way of generating payoffs, we assume that the individual’s income is also affected by the environment. Besides, taking into account individual differences, we introduce the heterogeneity of the environment. Through numerous computing simulations, we find that environment-based preference selection, which accelerates the microscopic organization of cooperator clusters to resist the aggression of defectors, can truly promote cooperation within a large range of parameters. Our study indicates that the combination of heterogeneity and preference selection may be key for the sustainability of cooperation in structured populations.

Network recovery based on system crash early warning in a cascading failure model

This paper investigates the possibility of saving a network that is predicted to have a cascading failure that will eventually lead to a total collapse. We model cascading failures using the recently proposed KQ model. Then predict an impending total collapse by monitoring critical slowing down indicators and subsequently attempt to prevent the total collapse of the network by adding new nodes. To this end, we systematically evaluate five node addition rules, the effect of intervention delay and network degree heterogeneity. Surprisingly, unlike for random homogeneous networks, we find that a delayed intervention is preferred for saving scale free networks. We also find that for homogeneous networks, the best strategy is to wire newly added nodes to existing nodes in a uniformly random manner. For heterogeneous networks, however, a random selection of nodes based on their degree mostly outperforms a uniform random selection. These results provide new insights into restoring networks by adding nodes after observing early warnings of an impending complete breakdown.

Sensing Attribute Weights: A Novel Basic Belief Assignment Method

Dempster-Shafer evidence theory is widely used in many soft sensors data fusion systems on account of its good performance for handling the uncertainty information of soft sensors. However, how to determine basic belief assignment (BBA) is still an open issue. The existing methods to determine BBA do not consider the reliability of each attribute; at the same time, they cannot effectively determine BBA in the open world. In this paper, based on attribute weights, a novel method to determine BBA is proposed not only in the closed world, but also in the open world. The Gaussian model of each attribute is built using the training samples firstly. Second, the similarity between the test sample and the attribute model is measured based on the Gaussian membership functions. Then, the attribute weights are generated using the overlap degree among the classes. Finally, BBA is determined according to the sensed attribute weights. Several examples with small datasets show the validity of the proposed method.

Ordered visibility graph average aggregation operator: An application in produced water management

Complex networks are widely used in modeling complex system. How to aggregate data in complex systems is still an open issue. In this paper, an ordered visibility graph average aggregation operator is proposed which is inspired by the complex network theory and Newton's law of universal gravitation. First of all, the argument values are ordered in descending order. Then a new support function is proposed to measure the relationship among values in a visibility graph. After that, a weighted network is constructed to determine the weight of each value. Compared with the other operators, the new operator fully takes into account not only the information of orders but also the correlation degree between the values. Finally, an application of produced water management is illustrated to show the efficiency of the proposed method. The new method provides a universal way to aggregate data in complex systems.