Search results for "Community structure"

showing 10 items of 163 documents

Effect of multiple agricultural stressors on freshwater ecosystems: The role of community structure, trophic status, and biodiversity-functioning rel…

2022

Abstract The toxicity and widespread use of agricultural pesticides threaten freshwater biodiversity, but their long-term effects under different nutrient concentrations are poorly understood. We evaluated the single or combined effects of two pesticides (chlorpyrifos and diuron) under different nutrient regimes (mesotrophic and eutrophic) on community structure and ecosystem functions in replicated pond mesocosms. The individual application of nutrients and pesticides affected community composition and species richness. Ecosystem functioning was generally less sensitive to chemical stress than community structure, while eutrophication fostered the dominance of species that are more resilie…

Environmental EngineeringEcologyCommunity structureBiodiversityFresh WaterQ Science (General)BiodiversityBiologyPollutionFreshwater ecosystemEnvironmental ChemistryEcosystemSpecies richnessEcosystem respirationEutrophicationWaste Management and DisposalEcosystemTrophic level
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Soil biogeochemistry and microbial community dynamics in Pinus pinaster Ait. forests subjected to increased fire frequency.

2022

Fire frequency might increase in many fire-dominated ecosystems of the world due to the combined effects of global warming, land-use change and increased human pressures. Understanding how changes in fire frequency can affect the main soil biogeochemical dynamics, as well as the microbial community, in the long term is utmost important. Here we determined the effect of changes in fire frequency and other fire history characteristics on soil C and N dynamics and the main microbial groups (using soil fatty acid profiles), in Pinus pinaster forests from central Spain. Stands were chosen to differ in the number of fires (1 to 3) occurred between 1976 and 2018, in the time elapsed since the last…

Environmental EngineeringMicrobiotaSettore AGR/13 - Chimica AgrariaMicrobial community structureTime since the last fireMediterraneanForestsSoil CPinusPollutionWildfiresSoil NSoilEnvironmental ChemistryHumansFire return intervalBurnsWaste Management and DisposalEcosystemThe Science of the total environment
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Changes in predator community structure shifts the efficacy of two warning signals in Arctiid moths

2013

Summary 1. Polymorphism in warning coloration is puzzling because positive frequency-dependent selection by predators is expected to promote monomorphic warning signals in defended prey. 2. We studied predation on the warning-coloured wood tiger moth (Parasemia plantaginis )b y using artificial prey resembling white and yellow male colour morphs in five separate populations with different naturally occurring morph frequencies. 3. We tested whether predation favours one of the colour morphs over the other and whether that is influenced either by local, natural colour morph frequencies or predator community composition. 4. We found that yellow specimens were attacked less than white ones rega…

EstoniaMaleFood ChainPolymorphism GeneticbiologyPigmentationTigerEcologyFrequency-dependent selectionCommunity structureAposematismMothsbiology.organism_classificationBiotaPredationSpatial heterogeneitySongbirdsScotlandParasemia plantaginisPredatory BehaviorAnimalsAnimal Science and ZoologyPredatorFinlandEcology Evolution Behavior and SystematicsJournal of Animal Ecology
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Multi-scale analysis of the European airspace using network community detection

2014

We show that the European airspace can be represented as a multi-scale traffic network whose nodes are airports, sectors, or navigation points and links are defined and weighted according to the traffic of flights between the nodes. By using a unique database of the air traffic in the European airspace, we investigate the architecture of these networks with a special emphasis on their community structure. We propose that unsupervised network community detection algorithms can be used to monitor the current use of the airspaces and improve it by guiding the design of new ones. Specifically, we compare the performance of three community detection algorithms, also by using a null model which t…

FOS: Computer and information sciencesDatabases FactualDistributed computingSocial SciencesPoison controllcsh:MedicineSociologycommunity detectionData Mininglcsh:SciencePhysicsMultidisciplinaryMathematical modelApplied MathematicsPhysicsCommunity structureComputer Science - Social and Information NetworksAir traffic controlAir TravelSocial NetworksPhysical SciencesInterdisciplinary PhysicsSocial SystemsEngineering and TechnologyFree flightInformation TechnologyNetwork AnalysisAlgorithmsResearch ArticlePhysics - Physics and SocietyComputer and Information SciencesControl (management)FOS: Physical sciencesComputerApplications_COMPUTERSINOTHERSYSTEMSPhysics and Society (physics.soc-ph)Statistical MechanicsDatabasescomplex networkHumansArchitectureNetworks network communities socio-technical system complex systems Air Traffic ManagementSocial and Information Networks (cs.SI)Null modellcsh:RModels TheoreticalSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Computational SociologySignal ProcessingAir trafficlcsh:QMathematics
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An Empirical Study of the Relation Between Community Structure and Transitivity

2012

One of the most prominent properties in real-world networks is the presence of a community structure, i.e. dense and loosely interconnected groups of nodes called communities. In an attempt to better understand this concept, we study the relationship between the strength of the community structure and the network transitivity (or clustering coefficient). Although intuitively appealing, this analysis was not performed before. We adopt an approach based on random models to empirically study how one property varies depending on the other. It turns out the transitivity increases with the community structure strength, and is also affected by the distribution of the community sizes. Furthermore, …

FOS: Computer and information sciencesPhysics - Physics and SocietyProperty (philosophy)FOS: Physical sciencesPhysics and Society (physics.soc-ph)[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]01 natural sciencesComplex NetworksClustering010305 fluids & plasmasEmpirical research0103 physical sciences010306 general physicstransitivityCommunity StructureClustering coefficientMathematicsSocial and Information Networks (cs.SI)Transitive relationCommunity structure[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Computer Science - Social and Information NetworksComplex networkDegree distributionZero (linguistics)Mathematical economics
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Extracting Backbones in Weighted Modular Complex Networks

2020

AbstractNetwork science provides effective tools to model and analyze complex systems. However, the increasing size of real-world networks becomes a major hurdle in order to understand their structure and topological features. Therefore, mapping the original network into a smaller one while preserving its information is an important issue. Extracting the so-called backbone of a network is a very challenging problem that is generally handled either by coarse-graining or filter-based methods. Coarse-graining methods reduce the network size by grouping similar nodes, while filter-based methods prune the network by discarding nodes or edges based on a statistical property. In this paper, we pro…

FOS: Computer and information sciencesPhysics - Physics and SocietyTheoretical computer scienceComputer scienceMathematics and computingComplex systemComplex networkslcsh:MedicineFOS: Physical sciencesNetwork science02 engineering and technologyPhysics and Society (physics.soc-ph)[INFO] Computer Science [cs]01 natural sciencesArticle010305 fluids & plasmasSet (abstract data type)020204 information systems0103 physical sciences0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]lcsh:ScienceAuthor CorrectionComputingMilieux_MISCELLANEOUSConnected componentSocial and Information Networks (cs.SI)Multidisciplinarybusiness.industryPhysicslcsh:RCommunity structureComputer Science - Social and Information NetworksComplex networkModular designlcsh:Qbusiness
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Towards realistic artificial benchmark for community detection algorithms evaluation

2013

Many algorithms have been proposed for revealing the community structure in complex networks. Tests under a wide range of realistic conditions must be performed in order to select the most appropriate for a particular application. Artificially generated networks are often used for this purpose. The most realistic generative method to date has been proposed by Lancichinetti, Fortunato and Radicchi (LFR). However, it does not produce networks with some typical features of real-world networks. To overcome this drawback, we investigate two alternative modifications of this algorithm. Experimental results show that in both cases, centralisation and degree correlation values of generated networks…

FOS: Computer and information sciencesPhysics - Physics and Societypreferential attachmentComputer Networks and CommunicationsComputer science[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]FOS: Physical sciencesvirtual communitiesPhysics and Society (physics.soc-ph)01 natural sciences010305 fluids & plasmasEducation0103 physical sciencescommunity detectionbenchmarking010306 general physicsSocial and Information Networks (cs.SI)CommunicationComputer Science - Social and Information Networkscomplex networksweb based communitiesonline communitiesconfiguration modellingIdentification (information)LFR benchmarkBenchmark (computing)[ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH]community structureAlgorithmtopological propertiesSoftware
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Centrality measures for networks with community structure

2016

Understanding the network structure, and finding out the influential nodes is a challenging issue in the large networks. Identifying the most influential nodes in the network can be useful in many applications like immunization of nodes in case of epidemic spreading, during intentional attacks on complex networks. A lot of research is done to devise centrality measures which could efficiently identify the most influential nodes in the network. There are two major approaches to the problem: On one hand, deterministic strategies that exploit knowledge about the overall network topology in order to find the influential nodes, while on the other end, random strategies are completely agnostic ab…

FOS: Computer and information sciencesStatistics and ProbabilityPhysics - Physics and SocietyExploitComplex networksFOS: Physical sciencesNetwork sciencePhysics and Society (physics.soc-ph)Network theoryMachine learningcomputer.software_genreNetwork topologyImmunization strategies01 natural sciences010305 fluids & plasmas0103 physical sciences010306 general physicsMathematicsSocial and Information Networks (cs.SI)Structure (mathematical logic)[PHYS.PHYS]Physics [physics]/Physics [physics]business.industryCommunity structureComputer Science - Social and Information NetworksComplex networkEpidemic dynamicsCondensed Matter Physics[ PHYS.PHYS ] Physics [physics]/Physics [physics]Community structureArtificial intelligenceData miningbusinessCentralitycomputer
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Immunization Strategies Based on the Overlapping Nodes in Networks with Community Structure

2016

International audience; Understanding how the network topology affects the spread of an epidemic is a main concern in order to develop efficient immunization strategies. While there is a great deal of work dealing with the macroscopic topological properties of the networks, few studies have been devoted to the influence of the community structure. Furthermore, while in many real-world networks communities may overlap, in these studies non-overlapping community structures are considered. In order to gain insight about the influence of the overlapping nodes in the epidemic process we conduct an empirical evaluation of basic deterministic immunization strategies based on the overlapping nodes.…

FOS: Computer and information sciencesTheoretical computer science[ INFO ] Computer Science [cs]Computer scienceProcess (engineering)Epidemic02 engineering and technologyNetwork topology01 natural sciencesComplex NetworksDiffusion020204 information systems0103 physical sciencesNode (computer science)[INFO.INFO-SY]Computer Science [cs]/Systems and Control [cs.SY]0202 electrical engineering electronic engineering information engineeringOverlapping community[INFO]Computer Science [cs]010306 general physicsSocial and Information Networks (cs.SI)Connected componentWelfare economicsCommunity structureComputer Science - Social and Information NetworksAttackImmunization (finance)Complex networkDynamicsMembership number[ INFO.INFO-SY ] Computer Science [cs]/Systems and Control [cs.SY]ImmunizationEpidemic model
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Can lake restoration by fish removal improve the status of profundal macroinvertebrate assemblages?

2013

Summary Removal of fish to restore lake pelagic food webs and water quality has been shown to increase the abundance of benthic invertebrates in shallow areas due to decreased predation pressure, while responses of profundal macroinvertebrate assemblages are less well documented. We used multivariate analyses and a Before-After-Control-Impact design to assess the impacts of fish removal (in total 101 000 kg of percid and cyprinid fish) on profundal macroinvertebrate species composition and abundance and ecological status in two basins of a eutrophic boreal lake. In the deeper main basin, macroinvertebrate community composition and classification of ecological status were not affected by fis…

FisheryBiomanipulationEcologyBenthic zoneAbundance (ecology)Community structureEnvironmental sciencePelagic zoneProfundal zoneAquatic ScienceEutrophicationTrophic levelFreshwater Biology
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