scholarly journals What drives the assembly of plant-associated protist microbiomes?

2020 ◽  
Author(s):  
Kenneth Dumack ◽  
Kai Feng ◽  
Sebastian Flues ◽  
Melanie Sapp ◽  
Susanne Schreiter ◽  
...  
Keyword(s):  
Plant Species ◽  
Beta Diversity ◽  
Small World ◽  
Strong Impact ◽  
Dominant Group ◽  
Environmental Filters ◽  
Species Identity ◽  
Scale Free ◽  
Network Analyses ◽  
Species Specific

AbstractIn a field experiment we investigated the influence of the environmental filters soil type and plant species identity on rhizosphere community assembly of Cercozoa, a dominant group of (mostly bacterivorous) soil protists. The experiment was set up with two plant species, lettuce and potato, grown in an experimental plot system with three contrasting soils. Plant species (14%) and rhizosphere origin (vs. bulk soil) with 13%, together explained four times more variation in cercozoan beta diversity than the three soil types (7% explained variation in beta diversity). Our results clearly confirm the existence of plant species-specific protist communities. Network analyses of bacteria-Cercozoa rhizosphere communities identified scale-free small world topologies, indicating mechanisms of self-organization. While the assembly of rhizosphere bacterial communities is bottom-up controlled through the resource supply from root (secondary) metabolites, our results support the hypothesis that the net effect may depend on the strength of top-down control by protist grazers. Since grazing of protists has a strong impact on the composition and functioning of bacteria communities, protists expand the repertoire of plant genes by functional traits, and should be considered as ‘protist microbiomes’ in analogy to ‘bacterial microbiomes’.HighlightMicrobiomes of rhizosphere protists are plant species-specific and tightly co-evolving with their bacterial prey, thereby extending and modifying the functional repertoire of the bacterial-plant symbiosis.

scholarly journals Statistical Analysis to Bitcoin Transactions Network

2020 ◽  
Vol 9 (5) ◽  
pp. 85
Author(s):  
Argyrios Kalampakas ◽  
Georgios C. Makris
Keyword(s):  
Economic Activity ◽  
Scientific Evidence ◽  
Small World ◽  
Holistic Approach ◽  
Research Community ◽  
Statistical Analyses ◽  
Random Networks ◽  
Scale Free ◽  
Network Analyses ◽  
Financial Transactions

There is abundantly documented scientific evidence that the financial transactions that have grown rapidly recently, in conjuction with the interest of the public, were due to the sharp rise in the price of Bitcoin in December 2017. As a consequence, a freshly emerging dataset in the research community has emerged. Therefore, the aim of the present investigation was to examine the analyses of data in this newly emerging dataset in the research community. In order to achieve the extraction of data, their conversion to network and finally their fragmentation, the studied variables were analyzed by using two parts of analysis, namely, statistical network analyses and economic activity analyses. Network statistical analyses was employed aiming to analyze, in a holistic approach, the complex systems of modern times which are represented as networks, as it is impossible to analyze them partially, in order to avoid incorrect conclusions. Additionally, the analyses of economic activity, which is related to indicators from the stock market and the economics of science, was used, after it had been transferred and matched with the economic model represented by Bitcoin. The results distinguished the extent of the data generated by the statistical analyses of the networks and the analyses of economic activity. With respect to data presented, we established that the daily transaction networks were scale free networks which were not evolving like ER random networks and they were not defined as the small world. Also, it was demonstrated that daily transaction networks cannot be reproduced in a random way like ER random networks. Furthermore, the opportunities and problems encountered in conducting the present research were briefly presented.

scholarly journals Species-specific, age-varying plant traits affect herbivore growth and survival

2020 ◽  
Author(s):  
Louie H. Yang ◽  
Meredith L. Cenzer ◽  
Laura J. Morgan ◽  
Griffin W. Hall
Keyword(s):  
Host Plant ◽  
Plant Species ◽  
Plant Traits ◽  
Abiotic Factors ◽  
Danaus Plexippus ◽  
Plant Age ◽  
Species Identity ◽  
Growth And Survival ◽  
Windows Of Opportunity ◽  
Species Specific

AbstractSeasonal windows of opportunity represent intervals of time within a year during which organisms have improved prospects of achieving life history aims such as growth or reproduction, and may be commonly structured by temporal variation in abiotic factors, bottom-up factors, and top-down factors. Although seasonal windows of opportunity are likely to be common, few studies have examined the factors that structure seasonal windows of opportunity in time. Here, we experimentally manipulated host plant age in two milkweed species (Asclepias fascicularis and Asclepias speciosa) in order to investigate the role of plant species-specific and plant age-varying traits on the survival and growth of monarch caterpillars (Danaus plexippus). We show that the two plant species showed diverging trajectories of defense traits with increasing age. These species-specific and age-varying host plant traits significantly affected the growth and survival of monarch caterpillars through both resource quality- and resource quantity-based constraints. The effects of plant age on monarch developmental success were comparable to and sometimes larger than those of plant species identity. We conclude that species-specific and age-varying plant traits are likely to be important factors with the potential to structure seasonal windows of opportunity for monarch development, and examine the implications of these findings for both broader patterns in the ontogeny of plant defense traits and the specific ecology of milkweed-monarch interactions in a changing world.

scholarly journals Evolution of Conformity Dynamics in Complex Social Networks

Symmetry ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 299 ◽  
Author(s):  
Yuhui Gong ◽  
Qian Yu
Keyword(s):  
Social Networks ◽  
Random Network ◽  
Small World ◽  
Network Size ◽  
Small World Network ◽  
Scale Free Network ◽  
Small World Networks ◽  
Dominant Group ◽  
Scale Free ◽  
Free Network

Conformity is a common phenomenon among people in social networks. In this paper, we focus on customers’ conformity behaviors in a symmetry market where customers are located in a social network. We establish a conformity model and analyze it in ring network, random network, small-world network, and scale-free network. Our simulations shown that topology structure, network size, and initial market share have significant effects on the evolution of customers’ conformity behaviors. The market will likely converge to a monopoly state in small-world networks but will form a duopoly market in scale networks. As the size of the network increases, there is a greater possibility of forming a dominant group of preferences in small-world network, and the market will converge to the monopoly of the product which has the initial selector in the market. Also, network density will become gradually significant in small-world networks.

Species identity matters: Functional responses to warming in congeneric turfs differ from those of a canopy algae but are species-specific

2021 ◽  
pp. 107396
Author(s):  
Isabella Provera ◽  
Cristina Piñeiro-Corbeira ◽  
Rodolfo Barreiro ◽  
Laura Díaz-Acosta ◽  
Pilar Díaz-Tapia
Keyword(s):  
Functional Responses ◽  
Species Identity ◽  
Species Specific ◽  
Canopy Algae

Alkaline soil pH affects bulk soil, rhizosphere and root endosphere microbiomes of plants growing in a Sandhills ecosystem

2021 ◽  
Vol 97 (4) ◽  
Author(s):  
Lucas Dantas Lopes ◽  
Jingjie Hao ◽  
Daniel P Schachtman
Keyword(s):  
Microbial Communities ◽  
Plant Species ◽  
Soil Ph ◽  
Soil Microbial Communities ◽  
Bulk Soil ◽  
Strong Impact ◽  
Alkaline Soil ◽  
Alkaline Soils ◽  
Soil Microbial ◽  
Soil Rhizosphere

ABSTRACT Soil pH is a major factor shaping bulk soil microbial communities. However, it is unclear whether the belowground microbial habitats shaped by plants (e.g. rhizosphere and root endosphere) are also affected by soil pH. We investigated this question by comparing the microbial communities associated with plants growing in neutral and strongly alkaline soils in the Sandhills, which is the largest sand dune complex in the northern hemisphere. Bulk soil, rhizosphere and root endosphere DNA were extracted from multiple plant species and analyzed using 16S rRNA amplicon sequencing. Results showed that rhizosphere, root endosphere and bulk soil microbiomes were different in the contrasting soil pH ranges. The strongest impact of plant species on the belowground microbiomes was in alkaline soils, suggesting a greater selective effect under alkali stress. Evaluation of soil chemical components showed that in addition to soil pH, cation exchange capacity also had a strong impact on shaping bulk soil microbial communities. This study extends our knowledge regarding the importance of pH to microbial ecology showing that root endosphere and rhizosphere microbial communities were also influenced by this soil component, and highlights the important role that plants play particularly in shaping the belowground microbiomes in alkaline soils.

Top Museums on Instagram

2019 ◽  
Vol 3 (2) ◽  
pp. 18-42 ◽  
Author(s):  
Vasiliki G. Vrana ◽  
Dimitrios A. Kydros ◽  
Evangelos C. Kehris ◽  
Anastasios-Ioannis T. Theocharidis ◽  
George I. Kavavasilis
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Small World ◽  
Marketing Strategies ◽  
The Other ◽  
Small World Network ◽  
Scale Free ◽  
Centrality Metrics ◽  
Photo Sharing ◽  
Visualization Algorithms

Pictures speak louder than words. In this fast-moving world where people hardly have time to read anything, photo-sharing sites become more and more popular. Instagram is being used by millions of people and has created a “sharing ecosystem” that also encourages curation, expression, and produces feedback. Museums are moving quickly to integrate Instagram into their marketing strategies, provide information, engage with audience and connect to other museums Instagram accounts. Taking into consideration that people may not see museum accounts in the same way that the other museum accounts do, the article first describes accounts' performance of the top, most visited museums worldwide and next investigates their interconnection. The analysis uses techniques from social network analysis, including visualization algorithms and calculations of well-established metrics. The research reveals the most important modes of the network by calculating the appropriate centrality metrics and shows that the network formed by the museum Instagram accounts is a scale–free small world network.

STABILITY OF TWO TYPICAL COMPLEX DYNAMICAL NETWORKS

2008 ◽  
Vol 22 (05) ◽  
pp. 553-560 ◽  
Author(s):  
WU-JIE YUAN ◽  
XIAO-SHU LUO ◽  
PIN-QUN JIANG ◽  
BING-HONG WANG ◽  
JIN-QING FANG
Keyword(s):  
Numerical Simulation ◽  
Dissipative System ◽  
Small World ◽  
Complex Dynamical Networks ◽  
Dynamical Networks ◽  
Scale Free ◽  
Scale Free Networks ◽  
General Complex ◽  
The Stability ◽  
Theoretical Results

When being constructed, complex dynamical networks can lose stability in the sense of Lyapunov (i. s. L.) due to positive feedback. Thus, there is much important worthiness in the theory and applications of complex dynamical networks to study the stability. In this paper, according to dissipative system criteria, we give the stability condition in general complex dynamical networks, especially, in NW small-world and BA scale-free networks. The results of theoretical analysis and numerical simulation show that the stability i. s. L. depends on the maximal connectivity of the network. Finally, we show a numerical example to verify our theoretical results.

Words, constructions and corpora: Network representations of constructional semantics for Mandarin space particles

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Alvin Cheng-Hsien Chen
Keyword(s):  
Clustering Coefficient ◽  
Linguistic Knowledge ◽  
Scale Free ◽  
Network Analyses ◽  
Semantic Fields ◽  
Text Corpora ◽  
Quantitative Properties ◽  
Local Clustering Coefficient ◽  
Linguistic Units

AbstractIn this study, we aim to demonstrate the effectiveness of network science in exploring the emergence of constructional semantics from the connectedness and relationships between linguistic units. With Mandarin locative constructions (MLCs) as a case study, we extracted constructional tokens from a representative corpus, including their respective space particles (SPs) and the head nouns of the landmarks (LMs), which constitute the nodes of the network. We computed edges based on the lexical similarities of word embeddings learned from large text corpora and the SP-LM contingency from collostructional analysis. We address three issues: (1) For each LM, how prototypical is it of the meaning of the SP? (2) For each SP, how semantically cohesive are its LM exemplars? (3) What are the emerging semantic fields from the constructional network of MLCs? We address these questions by examining the quantitative properties of the network at three levels: microscopic (i.e., node centrality and local clustering coefficient), mesoscopic (i.e., community) and macroscopic properties (i.e., small-worldness and scale-free). Our network analyses bring to the foreground the importance of repeated language experiences in the shaping and entrenchment of linguistic knowledge.

Independence polynomial and matching polynomial of the Koch network

2015 ◽  
Vol 29 (32) ◽  
pp. 1550234
Author(s):  
Yunhua Liao ◽  
Xiaoliang Xie
Keyword(s):  
Lattice Gas ◽  
Small World ◽  
Partition Functions ◽  
Complete Class ◽  
Dimer Model ◽  
Scale Free ◽  
Matching Polynomial ◽  
Independence Polynomial ◽  
Classical Models ◽  
Explicit Formulae

The lattice gas model and the monomer-dimer model are two classical models in statistical mechanics. It is well known that the partition functions of these two models are associated with the independence polynomial and the matching polynomial in graph theory, respectively. Both polynomials have been shown to belong to the “[Formula: see text]-complete” class, which indicate the problems are computationally “intractable”. We consider these two polynomials of the Koch networks which are scale-free with small-world effects. Explicit recurrences are derived, and explicit formulae are presented for the number of independent sets of a certain type.

scholarly journals Analysis on Invulnerability of Wireless Sensor Network towards Cascading Failures Based on Coupled Map Lattice

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Xiuwen Fu ◽  
Yongsheng Yang ◽  
Haiqing Yao
Keyword(s):  
Random Network ◽  
Small World ◽  
Coupled Map Lattice ◽  
Wireless Sensor ◽  
Cascading Failures ◽  
Scale Free Network ◽  
Scale Free ◽  
Network Topologies ◽  
Free Network ◽  
Entire Network

Previous research of wireless sensor networks (WSNs) invulnerability mainly focuses on the static topology, while ignoring the cascading process of the network caused by the dynamic changes of load. Therefore, given the realistic features of WSNs, in this paper we research the invulnerability of WSNs with respect to cascading failures based on the coupled map lattice (CML). The invulnerability and the cascading process of four types of network topologies (i.e., random network, small-world network, homogenous scale-free network, and heterogeneous scale-free network) under various attack schemes (i.e., random attack, max-degree attack, and max-status attack) are investigated, respectively. The simulation results demonstrate that the rise of interference R and coupling coefficient ε will increase the risks of cascading failures. Cascading threshold values Rc and εc exist, where cascading failures will spread to the entire network when R>Rc or ε>εc. When facing a random attack or max-status attack, the network with higher heterogeneity tends to have a stronger invulnerability towards cascading failures. Conversely, when facing a max-degree attack, the network with higher uniformity tends to have a better performance. Besides that, we have also proved that the spreading speed of cascading failures is inversely proportional to the average path length of the network and the increase of average degree k can improve the network invulnerability.

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