Link Density Research Articles

Self-organized efficient transmission in dynamic networks

Effective protocols are needed to ensure successful transmission of signals, messages, or parcels through a network of intermediaries. Existing studies often overlook real-world constraints such as limited resources. We investigate the design of efficient and robust transmission strategies in dynamic networks subject to dissipation and resource limited node activity, as in wireless sensor networks. We find that dissipation and randomness can enhance transmission efficiency and network resilience. For a broad family of protocols, a self-organized dynamics assures global connectivity, even in the limit of low density of links, where random networks fail.

Exploring changes in epibenthic food web structure after implementation of a water-sediment regulation scheme

The water-sediment regulation scheme (WSRS) in the Yellow River is a large-scale initiative to artificially regulate the flow of sediment to the sea, thereby increasing the flood-carrying capacity of the riverbed and reservoirs. Currently, systematic studies on ecological impacts of WSRS at ecosystem-level are still insufficient. This limitation hampers the pursuit of a ‘green’, healthy, ecosystem and sustainable fisheries. This study constructed the topological structure of food webs in the Yellow River Estuary (YRE) before, during, and after implementation of the WSRS, analyzing changes in food web complexity and key species based on fishery independent data collected in June, July, and August 2023. The results showed decreases from 59 to 52 in the number of trophic species, and from 539 to 395 in the number of feeding relationships after WSRS implementation. Increased node density, decreased link density, and decreased structural complexity index also indicated a simplification of the YRE food web structure after WSRS implementation. The relatively low value of the characteristic path length indicated that the YRE food web has high connectivity with short path lengths of trophic interaction. Based on the ranking of various topological indices, Japanese seabass (Lateolabrax japonicas) and mantis shrimp (Oratosquilla oratoria) persisted as the key species. Our research revealed limited potential ecological effects that WSRS may have on the YRE food web over a short period. The effects did not persist, and omnivorous key species were identified as being critical in contributing to overall system resilience. These omnivores with high complexity, connectivity and low path lengths allowed the food web to quickly dissipate the exogenous disruption from the WSRS. This provides a theoretical basis for assessing the future ecological health and scientific management of YRE fisheries and similar large estuaries for which sediment transport mitigation is under consideration.

The disruption index is biased by citation inflation

Abstract A recent analysis of scientific publication and patent citation networks by Park et al. (Nature, 2023) suggests that publications and patents are becoming less disruptive over time. Here we show that the reported decrease in disruptiveness is an artifact of systematic shifts in the structure of citation networks unrelated to innovation system capacity. Instead, the decline is attributable to ‘citation inflation’, an unavoidable characteristic of real citation networks that manifests as a systematic time-dependent bias and renders cross-temporal analysis challenging. One driver of citation inflation is the ever-increasing lengths of reference lists over time, which in turn increases the density of links in citation networks, and causes the disruption index to converge to 0. The impact of this systematic bias further stymies efforts to correlate disruption to other measures that are also time-dependent, such as team size and citation counts. In order to demonstrate this fundamental measurement problem, we present three complementary lines of critique (deductive, empirical and computational modeling), and also make available an ensemble of synthetic citation networks that can be used to test alternative citation-based indices for systematic bias. Peer Review https://www.webofscience.com/api/gateway/wos/peer-review/10.1162/qss_a_00333

Australia's recently established predators restore complexity to food webs simplified by extinction.

Since prehistory, humans have altered the composition of ecosystems by causing extinctions and introducing species. However, our understanding of how waves of species extinctions and introductions influence the structure and function of ecological networks through time remains piecemeal. Here, focusing on Australia, which has experienced many extinctions and introductions since the Late Pleistocene, we compared the functional trait composition of Late Pleistocene (130,00-115,000 years before present [ybp]), Holocene (11,700-3,000 ybp), and current Australian mammalian predator assemblages (≥70% vertebrate meat consumption; ≥1kg adult body mass). We then constructed food webs for each period based on estimated prey body mass preferences. We found that introduced predators are functionally distinct from extinct Australian predators, but they rewire food webs toward a state that closely resembles the Late Pleistocene, prior to the megafauna extinctions. Both Late Pleistocene and current-day food webs consist of an apex predator and three smaller predators. This leads to food web networks with a similar total number of links, link densities, and compartmentalizations. However, this similarity depends on the presence of dingoes: in their absence, food webs become simplified and reminiscent of those following the Late Pleistocene extinctions. Our results suggest that recently established predators, even those implicated in species extinctions and declines, can restore complexity to food webs simplified by extinction.

CONFORMATIONAL STRUCTURE OF POLYAMPHOLYTES AND POLYELECTROLYTES ON THE SURFACE OF A LONGITUDINALLY POLARIZED GOLD SPHEROCYLINDER

Conformational changes in generally neutral polyampholytic, as well as uniformly charged macrochains, polypeptides adsorbed on the surface of a longitudinally polarized gold spherocylinder—a cylindrical nanorod with spherical ends—were studied. An analytical model of the equilibrium structure of adsorbed macrochains on the surface of a polarized spherocylinder is presented, highlighting the entropy and field factors of the radial-angular distribution of link density. In the course of molecular dynamics simulation, the radial distributions of the density of polypeptide atoms in the central cylindrical part of the nanorod, as well as on its terminal hemispheres, were calculated. In addition, the distributions of the linear density of polypeptide atoms along the axis of the nanorod were calculated. A dumbbell-shaped polyampholyte edge was formed on the surface of the polarized nanorod, dense in the extended central cylindrical part and loose at the ends of the nanorod. There was also a shift of the macromolecular edge from the units of a uniformly charged polypeptide to the oppositely charged end of the nanorod, onwhich this polyelectrolyte edge swelled.

Characterizing acoustic dimensions of health-related urban greenspace

The association of urban greenspace and human health and well-being is widely recognised, but the underlying mechanisms are incompletely understood. The acoustic environment (AE) is frequently proposed as a mediator between greenspace and human health. While it is commonly viewed as a negative health factor (e.g. noise pollution), there is growing evidence that it also has positive effects on human health. However, a general problem is the lack of information on the AE for greenspaces in high spatial resolution. To provide evidence-based support for research on this issue, we identify and assess acoustic properties of health-related urban greenspace by estimating the association between urban green area and selected acoustic indices.The analysis is based on 5-minute audio recordings collected systematically from 730 locations, four times a year (n = 2,746) in Bochum, Germany. To quantify the acoustic properties, we use an indicator-set of 30 sound pressure levels, 11 eco-, 78 psychoacoustic indices and 3 complex network measures. Greenspace is defined, in alignment with various health studies, as the percentage of green area within three buffer sizes (50, 100, 300 m) around each recording location.Through cluster analysis, we identify eleven acoustic dimensions in our indicator-set, for which representative indices are derived using principal component analysis. Descriptive statistics and multi-level regression models are used to analyse the associations between representative indices and greenspace. We find the highest effect sizes for Link Density (representing “acoustic dominance”), Acoustic Richness (representing “persistent sound volume”) and the Articulation Index (representing “sound volume”). Thus, in addition to “sound volume”, the AE of urban greenspace is characterised to a similar extent by at least two additional acoustic dimensions. If properties of the AE act as mediators between urban greenspace and human health, these three acoustic dimensions hold the potential to reflect them. Studies on pathways between greenspace and human health could incorporate measures of these dimensions to extend the understanding of the AE’s relevance for Public Health.

Thermomechanical properties of multifunctional polymer hybrid nanocomposites based on carbon nanotubes and nanosilica

AbstractNanocomposites containing low wt% of oxidized multi‐walled carbon nanotubes (MWCNT‐OXI), nanosilica (NS), and its hybrid (MWCNT‐OXI/NS) in epoxy resin were produced and evaluated. The used nanoparticles were studied by scanning electron microscopy (SEM), thermogravimetric analysis (TGA), and Raman spectroscopy while the nanocomposites were investigated in relation to its morphology, thermal, and mechanical properties. The results demonstrated significant improvements in the storage modulus (E′), glass transition temperature (Tg), and cross link density (CD), for the produced nanocomposites. Increases in thermal conductivity (TC) of up to 85% at 90°C were observed for the nanocomposites containing 1.0 wt% of the hybrid MWCNT‐OXI + NS nanofiller, when compared with neat polymer. It was also verified increases in the resistance to plastic deformation for the nanocomposites, maintained the polymer thermal stability with the addition of these nanoparticles. Finally, the use of MWCNT‐OXI and NS, combined or not, significantly improved the thermal and mechanical properties of polymer, showing multifunctional characteristics for the produced nanocomposites.

Sensor placement considering the observability of traffic dynamics: On the algebraic and graphical perspectives

In this paper, we present a new sensor location model that aims to maximize observability of link densities in a dynamic traffic network described using a piecewise linear system of ordinary differential equations. We develop an algebraic approach based on the eigenstructure to determine the sensor location for achieving full observability with a minimal number of sensors. Additionally, a graphical approach based on the concept of structural observability is developed. By exploiting the special property of flow conservation in traffic networks, we derive a simple analytical result that can be used to identify observable components in a partially observable system, which is the main contribution of this paper. The graphical and algebraic properties of observability are then integrated into a sensor location optimization model considering a wide range of traffic conditions. Through numerical experiments, we demonstrate the good performance of our sensor deployment strategies in terms of the average observability and estimation errors.

Criminal organizations exhibit hysteresis, resilience, and robustness by balancing security and efficiency

The interplay between (criminal) organizations and (law enforcement) disruption strategies is critical in criminology and social network analysis. Like legitimate businesses, criminal enterprises thrive by fulfilling specific demands and navigating their unique challenges, including balancing operational visibility and security. This study aims at comprehending criminal networks’ internal dynamics, resilience to law enforcement interventions, and robustness to changes in external conditions. Using a model based on evolutionary game theory, we analyze these networks as collaborative assemblies of roles, considering expected costs, potential benefits, and the certainty of expected outcomes. Here, we show that criminal organizations exhibit strong hysteresis effects, with increased resilience and robustness once established, challenging the effectiveness of traditional law enforcement strategies focused on deterrence through increased punishment. The hysteresis effect defines optimal thresholds for the formation or dissolution of criminal organisation. Our findings indicate that interventions of similar magnitude can lead to vastly different outcomes depending on the existing state of criminality. This result suggests that the relationship between stricter punishment and its deterrent effect on organized crime is complex and sometimes non-linear. Furthermore, we demonstrate that network structure, specifically interconnectedness (link density) and assortativity of specialized skills, significantly influences the formation and stability of criminal organizations, underscoring the importance of considering social connections and the accessibility of roles in combating organized crime. These insights contribute to a deeper understanding of the systemic nature of criminal behavior from an evolutionary perspective and highlight the need for adaptive, strategic approaches in policy-making and law enforcement to disrupt criminal networks effectively.

Water‐controlled ecosystems as complex networks: Evaluation of network‐based approaches to quantify patterns of connectivity

AbstractThis study provides a new perspective on understanding the intricacies of water‐mediated connectivity in ecosystems, bridging landscape ecology and geomorphology through network science. We highlight dryland and river‐floodplain ecosystems as distinct examples of contrasting water‐controlled systems. We (1) discuss central considerations in developing structural connectivity and functional connectivity networks of water‐mediated connectivity; (2) quantify the emergent patterns in these networks; and (3) evaluate the capacity of network science tools for investigating connectivity characteristics. With a focus on strength (weights) and direction, connectivity is quantified using seven parameters at both network and node levels. We find that link density, betweenness centrality and page rank centrality are highly sensitive to directionality; global efficiency and degree centrality are particularly sensitive to weights; and relative node efficiency remains unaffected by weights and directions. Our study underscores how network science approaches can transform how we quantify and understand water‐mediated connectivity, especially in consideration of the role(s) of weights and directionality. This interdisciplinary perspective, linking ecology, hydrology and geomorphology, has implications for both theoretical insights and practical applications in environmental management and conservation efforts.

Ecosystem engineers shape ecological network structure and stability: A framework and literature review

Abstract Ecosystem engineering is a ubiquitous process where species influence the physical environment and thereby structure ecological communities. However, there has been little effort to synthesize or predict how ecosystem engineering may impact the structure and stability of interaction networks. To assess current scientific understanding of ecosystem engineering impacts via habitat forming, habitat modification and bioturbation on interaction networks/food webs, we reviewed the literature covering marine, freshwater and terrestrial food webs, plant‐pollinator networks and theory. We provide a conceptual framework and identify three major pathways of engineering impact on networks through changes in resource availability and energy flow, habitat heterogeneity and environmental filtering. These three processes often work in concert and most studies report that engineering increases species richness. This is particularly marked for engineers that increase habitat heterogeneity and thereby the number of available niches. The response of network structure to ecosystem engineering varies, however some patterns emerge from this review. Engineered habitat heterogeneity leads to a higher number of links between species in the networks and increases link density. Connectance can be negatively or positively affected by ecosystem engineer impact, depending on the engineering pathway and the engineer impact of species richness. We discuss how ecosystem engineers can stabilize or destabilize communities through the changes in niche space, diversity, network structure and the dependency on the engineering impact. Theory and empirical evidence need to inform each other to better integrate ecosystem engineering and ecological networks. A mechanistic understanding how ecosystem engineering traits shape interactions networks and their stability will be important to predict species extinctions and can provide crucial information for conservation and ecosystem restoration. Read the free Plain Language Summary for this article on the Journal blog.

Coprime networks of the composite numbers: Pseudo-randomness and synchronizability

In this paper, we propose a network whose nodes are labeled by the composite numbers and two nodes are connected by an undirected link if they are relatively prime to each other. As the size of the network increases, the network will be connected whenever the largest possible node index n≥49. To investigate how the nodes are connected, we analytically describe that the link density saturates to 6/π2, whereas the average degree increases linearly with slope 6/π2 with the size of the network. To investigate how the neighbors of the nodes are connected to each other, we find the shortest path length will be at most 3 for 49≤n≤288 and it is at most 2 for n≥289. We also derive an analytic expression for the local clustering coefficients of the nodes, which quantifies how close the neighbors of a node to form a triangle. We also provide an expression for the number of r-length labeled cycles, which indicates the existence of a cycle of length at most O(logn). Finally, we show that this graph sequence is actually a sequence of weakly pseudo-random graphs. We numerically verify our observed analytical results. As a possible application, we have observed less synchronizability (the ratio of the largest and smallest positive eigenvalue of the Laplacian matrix is high) as compared to Erdős–Rényi random network and Barabási–Albert network. This unusual observation is consistent with the prolonged transient behaviors of ecological and predator–prey networks which can easily avoid the global synchronization.

Quorum sensing bacteria improve microbial networks stability and complexity in wastewater treatment plants

Quorum-sensing bacteria (QSB) are crucial factors for microbial communication, yet their ecological role in wastewater treatment plants (WWTPs) remains unclear. Here, we developed a method to identify QSB by comparing 16S rRNA gene sequences. QSB in 388 activated sludge samples collected from 130 WWTPs across China primarily were identified as rare taxa and conditionally rare taxa. A co-occurrence network shared by all sludge communities revealed that QSB exhibited higher average clustering coefficient (0.46) than non-QSB (0.15). Individual sludge networks demonstrated that quorum sensing microbiomes were positively correlated with network robustness and network complexity, including average clustering coefficient and link density. We confirmed that QSB keystones and QSB nodes have a positive impact on network complexity by influencing network modularity through a structural equation model. Meanwhile, QSB communities directly contributed to maintaining network robustness (r = 0.29, P < 0.05). Hence, QSB play an important role in promoting network complexity and stability. Furthermore, QSB communities were positively associated with the functional composition of activated sludge communities (r = 0.33, P < 0.01), especially the denitrification capacity (r = 0.45, P < 0.001). Overall, we elucidated the ecological significance of QSB and provided support for QS-based regulation of activated sludge microbial communities.

Interconnection between density-regulation and stability in competitive ecological network

In natural ecosystems, species can be characterized by the nonlinear density-dependent self-regulation of their growth profile. Species of many taxa show a substantial density-dependent reduction for low population size. Nevertheless, many show the opposite trend; density regulation is minimal for small populations and increases significantly when the population size is near the carrying capacity. The theta-logistic growth equation can portray the intraspecific density regulation in the growth profile, theta being the density regulation parameter. In this study, we examine the role of these different growth profiles on the stability of a competitive ecological community with the help of a mathematical model of competitive species interactions. This manuscript deals with the random matrix theory to understand the stability of the classical theta-logistic models of competitive interactions. Our results suggest that having more species with strong density dependence, which self-regulate at low densities, leads to more stable communities. With this, stability also depends on the complexity of the ecological network. Species network connectance (link density) shows a consistent trend of increasing stability, whereas community size (species richness) shows a context-dependent effect. We also interpret our results from the aspect of two different life history strategies: r and K-selection. Our results show that the stability of a competitive network increases with the fraction of r-selected species in the community. Our result is robust, irrespective of different network architectures.

Enhancing ecological complexity in soft‐bottom coastal ecosystems: the impact of introducing hard substrates

Coastal ecosystems globally face pressures, with natural coastal habitats being replaced by engineered structures. While hard structures for navigation‐purposes and coastal defense can negatively impact native communities, they can also be applied in ecological restoration as artificial reefs. This way substrates may facilitate establishment of biogenic (shellfish) reefs and provide habitat heterogeneity in soft‐sediment ecosystems. In a 1.5‐year experiment, we introduced six different types of natural or biodegradable hard substrates in a subtidal soft‐sediment system. We compared the substrates with surrounding soft sediment and evaluated differences among substrate types using biodiversity indices, community composition analyses, and food web indicators. This offers a comprehensive understanding of how the introduced hard substrates affect ecosystem complexity. Overall ecological complexity indicators were higher in the second year of the experiment. We found a significant increase in species richness, community composition, and link density (number of feeding interactions per species) on hard substrates compared to the surrounding sediment. However, Shannon diversity index and food web connectance (measure of food web saturation) did not differ between substrates and the surrounding sediment. Although differences among types of hard substrates were small, certain species were uniquely associated with specific substrates with wood and granite performing best. While there was no establishment of epibenthic shellfish reefs within 1.5 years, we conclude that introducing hard substrates effectively enhances ecological complexity in soft‐bottom coastal ecosystems within that timeframe. We recommend the use of substrates with a historical ecological relevance in the system for scaling up introduction of substrates for ecological restoration.

Detecting periodic time scales of changes in temporal networks

Abstract Temporal networks are commonly used to represent dynamical complex systems like social networks, simultaneous firing of neurons, human mobility or public transportation. Their dynamics may evolve on multiple time scales characterizing for instance periodic activity patterns or structural changes. The detection of these time scales can be challenging from the direct observation of simple dynamical network properties like the activity of nodes or the density of links. Here, we propose two new methods, which rely on already established static representations of temporal networks, namely supra-adjacency and temporal event graphs. We define dissimilarity metrics extracted from these representations and compute their power spectra from their Fourier transforms to effectively identify dominant periodic time scales characterizing the changes of the temporal network. We demonstrate our methods using synthetic and real-world data sets describing various kinds of temporal networks. We find that while in all cases the two methods outperform the reference measures, the supra-adjacency-based method identifies more easily periodic changes in network density, while the temporal event graph-based method is better suited to detect periodic changes in the group structure of the network. Our methodology may provide insights into different phenomena occurring at multiple time scales in systems represented by temporal networks.

Network structure shapes the impact of diversity in collective learning

It is widely believed that diversity arising from different skills enhances the performance of teams, and in particular, their ability to learn and innovate. However, diversity has also been associated with negative effects on the communication and coordination within collectives. Yet, despite the importance of diversity as a concept, we still lack a mechanistic understanding of how its impact is shaped by the underlying social network. To fill this gap, we model skill diversity within a simple model of collective learning and show that its effect on collective performance differs depending on the complexity of the task and the network density. In particular, we find that diversity consistently impairs performance in simple tasks. In contrast, in complex tasks, link density modifies the effect of diversity: while homogeneous populations outperform diverse ones in sparse networks, the opposite is true in dense networks, where diversity boosts collective performance. Our findings also provide insight on how to forge teams in an increasingly interconnected world: the more we are connected, the more we can benefit from diversity to solve complex problems.

A Dynamic Network Model of Societal Complexity and Resilience Inspired by Tainter's Theory of Collapse.

In recent years, several global events have severely disrupted economies and social structures, undermining confidence in the resilience of modern societies. Examples include the COVID-19 pandemic, which brought unprecedented health challenges and economic disruptions, and the emergence of geopolitical tensions and conflicts that have further strained international relations and economic stability. While empirical evidence on the dynamics and drivers of past societal collapse is mounting, a process-based understanding of these dynamics is still in its infancy. Here, we aim to identify and illustrate the underlying drivers of such societal instability or even collapse. The inspiration for this work is Joseph Tainter's theory of the "collapse of complex societies", which postulates that the complexity of societies increases as they solve problems, leading to diminishing returns on complexity investments and ultimately to collapse. In this work, we abstract this theory into a low-dimensional and stylized model of two classes of networked agents, hereafter referred to as "laborers" and "administrators". We numerically model the dynamics of societal complexity, measured as the fraction of "administrators", which was assumed to affect the productivity of connected energy-producing "laborers". We show that collapse becomes increasingly likely as the complexity of the model society continuously increases in response to external stresses that emulate Tainter's abstract notion of problems that societies must solve. We also provide an analytical approximation of the system's dominant dynamics, which matches well with the numerical experiments, and use it to study the influence on network link density, social mobility and productivity. Our work advances the understanding of social-ecological collapse and illustrates its potentially direct link to an ever-increasing societal complexity in response to external shocks or stresses via a self-reinforcing feedback.

SPATIAL PARTITION FOR HETEROGENEOUS CITY NETWORKS COMPOSED OF FACTORS THAT INFLUENCE THE DISTRIBUTION OF THE MACROSCOPIC FUNDAMENTAL DIAGRAM

Using a Macroscopic Fundamental Diagram (MFD) to implement partition control is effective in improving mobility in heterogeneous city networks. As one of the most complex issues in partition control, accurate sub-region partition is critical for control effectiveness. Current partition methods focus on the link density and precondition of existing MFD and disregard the factors that influence MFD distribution. To overcome this drawback, this study uses the characteristic value of the link and the intersection connected to the link as the analysis object and proposes an MFD sub-region partitioning method for large-scale networks. Firstly, the influences of road state parameters on MFD distribution are classified into traffic flow parameters, network physical properties, network operation mechanisms and emergencies. Simulation experiments are conducted to determine the degree to which these classifications affect MFD distribution. Secondly, a partition method combined with the link density and influence parameters of MFD is developed. The method is used for a preliminarily division of a road network through Minimum Spanning Tree (MST) and depth partition by the Normalised Cut (Ncut) algorithm. Finally, a case study is conducted in an actual city centre network, and results show that the developed method is superior to the single method based simply on link density.

Impacts of the accumulated extinction of endangered species on stream food webs

The world is facing a serious biodiversity-loss crisis and stream ecosystems are among the most vulnerable. Human-induced disturbances are accelerating the loss of stream biodiversity; however, their ecological impacts are poorly understood. Here, we comprehensively investigated the impact of biodiversity loss on stream food webs using massive food web data (> 1 300 webs). We analyzed the structural changes of food webs upon accumulation of biodiversity loss and specifically compared the severity of losses between fish or benthic macroinvertebrates. In particular, we focused on currently threatened and near-threatened species, to reflect realistic extinction. We simulated their sequential and accumulative extinctions and analyzed the changes in food web structural indices using a linear mixed effect model. Stream food webs tended to be robust against the loss of threatened species; however, the accumulated extinction, including both threatened and near-threatened species, caused substantial changes in food web structures. Notably, significant decreases in the number of links, link density, and generality were observed, indicating the vulnerability of the system. The loss of fish caused larger changes in the food web structure compared to that of benthic macroinvertebrates, indicating the relative importance of fish species in sustaining food web structures. Food web alteration may lead to substantial changes in ecosystem functioning. Our study suggests preemptive action to protect near-threatened species as well as threatened ones for conserving stream ecosystems and their services. Furthermore, we suggest that the food web framework is useful for diagnosing ecosystem-level impacts of species loss in biodiversity conservation.