Diversity and Phylogenetic Structure of Two Complex Marine Microbial Communities
2004-09-01
Science 190 and Engineering DOCTORAL DISSERTATION Diversity and Phylogenetic Structure of Two Complex Marine Microbial Communities by Vanja Klepac-Ceraj...Two Complex Marine Microbial Communities by Vanja Klepac-Ceraj Massachusetts Institute of Technology Cambridge, Massachusetts 02139 and Woods Hole...Phylogenetic Structure of Two Complex Marine Microbial Communities. Ph.D. Thesis. MIT/WHOI, 2004-11. Approved for publication; distribution unlimited
Detecting community structure via the maximal sub-graphs and belonging degrees in complex networks
NASA Astrophysics Data System (ADS)
Cui, Yaozu; Wang, Xingyuan; Eustace, Justine
2014-12-01
Community structure is a common phenomenon in complex networks, and it has been shown that some communities in complex networks often overlap each other. So in this paper we propose a new algorithm to detect overlapping community structure in complex networks. To identify the overlapping community structure, our algorithm firstly extracts fully connected sub-graphs which are maximal sub-graphs from original networks. Then two maximal sub-graphs having the key pair-vertices can be merged into a new larger sub-graph using some belonging degree functions. Furthermore we extend the modularity function to evaluate the proposed algorithm. In addition, overlapping nodes between communities are founded successfully. Finally we report the comparison between the modularity and the computational complexity of the proposed algorithm with some other existing algorithms. The experimental results show that the proposed algorithm gives satisfactory results.
Paxton, Avery B; Pickering, Emily A; Adler, Alyssa M; Taylor, J Christopher; Peterson, Charles H
2017-01-01
Structural complexity, a form of habitat heterogeneity, influences the structure and function of ecological communities, generally supporting increased species density, richness, and diversity. Recent research, however, suggests the most complex habitats may not harbor the highest density of individuals and number of species, especially in areas with elevated human influence. Understanding nuances in relationships between habitat heterogeneity and ecological communities is warranted to guide habitat-focused conservation and management efforts. We conducted fish and structural habitat surveys of thirty warm-temperate reefs on the southeastern US continental shelf to quantify how structural complexity influences fish communities. We found that intermediate complexity maximizes fish abundance on natural and artificial reefs, as well as species richness on natural reefs, challenging the current paradigm that abundance and other fish community metrics increase with increasing complexity. Naturally occurring rocky reefs of flat and complex morphologies supported equivalent abundance, biomass, species richness, and community composition of fishes. For flat and complex morphologies of rocky reefs to receive equal consideration as essential fish habitat (EFH), special attention should be given to detecting pavement type rocky reefs because their ephemeral nature makes them difficult to detect with typical seafloor mapping methods. Artificial reefs of intermediate complexity also maximized fish abundance, but human-made structures composed of low-lying concrete and metal ships differed in community types, with less complex, concrete structures supporting lower numbers of fishes classified largely as demersal species and metal ships protruding into the water column harboring higher numbers of fishes, including more pelagic species. Results of this study are essential to the process of evaluating habitat function provided by different types and shapes of reefs on the seafloor so that all EFH across a wide range of habitat complexity may be accurately identified and properly managed.
Multi-frequency complex network from time series for uncovering oil-water flow structure.
Gao, Zhong-Ke; Yang, Yu-Xuan; Fang, Peng-Cheng; Jin, Ning-De; Xia, Cheng-Yi; Hu, Li-Dan
2015-02-04
Uncovering complex oil-water flow structure represents a challenge in diverse scientific disciplines. This challenge stimulates us to develop a new distributed conductance sensor for measuring local flow signals at different positions and then propose a novel approach based on multi-frequency complex network to uncover the flow structures from experimental multivariate measurements. In particular, based on the Fast Fourier transform, we demonstrate how to derive multi-frequency complex network from multivariate time series. We construct complex networks at different frequencies and then detect community structures. Our results indicate that the community structures faithfully represent the structural features of oil-water flow patterns. Furthermore, we investigate the network statistic at different frequencies for each derived network and find that the frequency clustering coefficient enables to uncover the evolution of flow patterns and yield deep insights into the formation of flow structures. Current results present a first step towards a network visualization of complex flow patterns from a community structure perspective.
The way to uncover community structure with core and diversity
NASA Astrophysics Data System (ADS)
Chang, Y. F.; Han, S. K.; Wang, X. D.
2018-07-01
Communities are ubiquitous in nature and society. Individuals that share common properties often self-organize to form communities. Avoiding the shortages of computation complexity, pre-given information and unstable results in different run, in this paper, we propose a simple and efficient method to deepen our understanding of the emergence and diversity of communities in complex systems. By introducing the rational random selection, our method reveals the hidden deterministic and normal diverse community states of community structure. To demonstrate this method, we test it with real-world systems. The results show that our method could not only detect community structure with high sensitivity and reliability, but also provide instructional information about the hidden deterministic community world and the real normal diverse community world by giving out the core-community, the real-community, the tide and the diversity. Thizs is of paramount importance in understanding, predicting, and controlling a variety of collective behaviors in complex systems.
Identification of hybrid node and link communities in complex networks
He, Dongxiao; Jin, Di; Chen, Zheng; Zhang, Weixiong
2015-01-01
Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organizational structures in real networks. We introduce a new scheme and an effective approach for identifying complex mixture structures of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large network of semantically associated words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately. PMID:25728010
Identification of hybrid node and link communities in complex networks.
He, Dongxiao; Jin, Di; Chen, Zheng; Zhang, Weixiong
2015-03-02
Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organizational structures in real networks. We introduce a new scheme and an effective approach for identifying complex mixture structures of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large network of semantically associated words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately.
Identification of hybrid node and link communities in complex networks
NASA Astrophysics Data System (ADS)
He, Dongxiao; Jin, Di; Chen, Zheng; Zhang, Weixiong
2015-03-01
Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organizational structures in real networks. We introduce a new scheme and an effective approach for identifying complex mixture structures of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large network of semantically associated words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately.
Pickering, Emily A.; Adler, Alyssa M.; Taylor, J. Christopher; Peterson, Charles H.
2017-01-01
Structural complexity, a form of habitat heterogeneity, influences the structure and function of ecological communities, generally supporting increased species density, richness, and diversity. Recent research, however, suggests the most complex habitats may not harbor the highest density of individuals and number of species, especially in areas with elevated human influence. Understanding nuances in relationships between habitat heterogeneity and ecological communities is warranted to guide habitat-focused conservation and management efforts. We conducted fish and structural habitat surveys of thirty warm-temperate reefs on the southeastern US continental shelf to quantify how structural complexity influences fish communities. We found that intermediate complexity maximizes fish abundance on natural and artificial reefs, as well as species richness on natural reefs, challenging the current paradigm that abundance and other fish community metrics increase with increasing complexity. Naturally occurring rocky reefs of flat and complex morphologies supported equivalent abundance, biomass, species richness, and community composition of fishes. For flat and complex morphologies of rocky reefs to receive equal consideration as essential fish habitat (EFH), special attention should be given to detecting pavement type rocky reefs because their ephemeral nature makes them difficult to detect with typical seafloor mapping methods. Artificial reefs of intermediate complexity also maximized fish abundance, but human-made structures composed of low-lying concrete and metal ships differed in community types, with less complex, concrete structures supporting lower numbers of fishes classified largely as demersal species and metal ships protruding into the water column harboring higher numbers of fishes, including more pelagic species. Results of this study are essential to the process of evaluating habitat function provided by different types and shapes of reefs on the seafloor so that all EFH across a wide range of habitat complexity may be accurately identified and properly managed. PMID:28873447
Community Detection in Complex Networks via Clique Conductance.
Lu, Zhenqi; Wahlström, Johan; Nehorai, Arye
2018-04-13
Network science plays a central role in understanding and modeling complex systems in many areas including physics, sociology, biology, computer science, economics, politics, and neuroscience. One of the most important features of networks is community structure, i.e., clustering of nodes that are locally densely interconnected. Communities reveal the hierarchical organization of nodes, and detecting communities is of great importance in the study of complex systems. Most existing community-detection methods consider low-order connection patterns at the level of individual links. But high-order connection patterns, at the level of small subnetworks, are generally not considered. In this paper, we develop a novel community-detection method based on cliques, i.e., local complete subnetworks. The proposed method overcomes the deficiencies of previous similar community-detection methods by considering the mathematical properties of cliques. We apply the proposed method to computer-generated graphs and real-world network datasets. When applied to networks with known community structure, the proposed method detects the structure with high fidelity and sensitivity. When applied to networks with no a priori information regarding community structure, the proposed method yields insightful results revealing the organization of these complex networks. We also show that the proposed method is guaranteed to detect near-optimal clusters in the bipartition case.
Energy Spectral Behaviors of Communication Networks of Open-Source Communities
Yang, Jianmei; Yang, Huijie; Liao, Hao; Wang, Jiangtao; Zeng, Jinqun
2015-01-01
Large-scale online collaborative production activities in open-source communities must be accompanied by large-scale communication activities. Nowadays, the production activities of open-source communities, especially their communication activities, have been more and more concerned. Take CodePlex C # community for example, this paper constructs the complex network models of 12 periods of communication structures of the community based on real data; then discusses the basic concepts of quantum mapping of complex networks, and points out that the purpose of the mapping is to study the structures of complex networks according to the idea of quantum mechanism in studying the structures of large molecules; finally, according to this idea, analyzes and compares the fractal features of the spectra in different quantum mappings of the networks, and concludes that there are multiple self-similarity and criticality in the communication structures of the community. In addition, this paper discusses the insights and application conditions of different quantum mappings in revealing the characteristics of the structures. The proposed quantum mapping method can also be applied to the structural studies of other large-scale organizations. PMID:26047331
Virality Prediction and Community Structure in Social Networks
NASA Astrophysics Data System (ADS)
Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol
2013-08-01
How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications.
Virality Prediction and Community Structure in Social Networks
Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol
2013-01-01
How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications. PMID:23982106
Virality prediction and community structure in social networks.
Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol
2013-01-01
How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications.
NASA Astrophysics Data System (ADS)
Ji, Junzhong; Song, Xiangjing; Liu, Chunnian; Zhang, Xiuzhen
2013-08-01
Community structure detection in complex networks has been intensively investigated in recent years. In this paper, we propose an adaptive approach based on ant colony clustering to discover communities in a complex network. The focus of the method is the clustering process of an ant colony in a virtual grid, where each ant represents a node in the complex network. During the ant colony search, the method uses a new fitness function to percept local environment and employs a pheromone diffusion model as a global information feedback mechanism to realize information exchange among ants. A significant advantage of our method is that the locations in the grid environment and the connections of the complex network structure are simultaneously taken into account in ants moving. Experimental results on computer-generated and real-world networks show the capability of our method to successfully detect community structures.
Revealing the Complexity of Community-Campus Interactions
ERIC Educational Resources Information Center
Nichols, Naomi Elizabeth; Phipps, David; Gaetz, Stephen; Fisher, Alison L.; Tanguay, Nancy
2014-01-01
In this paper, four qualitative case studies capture the complex interplay between the social and structural relations that shape community - academic partnerships. Collaborations begin as relationships among people. They are sustained by institutional structures that recognize and support these relationships. Productive collaborations centralize…
Typology of State-Level Community College Governance Structures
ERIC Educational Resources Information Center
Fletcher, Jeffrey A.; Friedel, Janice Nahra
2017-01-01
Despite having a well-documented history about community colleges across the United States, relatively few discussions have covered state-level governance structures. To understand the typology of state community college governance structures, it must first be recognized that community college governance is characterized as a complex web of…
Complexity and dynamics of topological and community structure in complex networks
NASA Astrophysics Data System (ADS)
Berec, Vesna
2017-07-01
Complexity is highly susceptible to variations in the network dynamics, reflected on its underlying architecture where topological organization of cohesive subsets into clusters, system's modular structure and resulting hierarchical patterns, are cross-linked with functional dynamics of the system. Here we study connection between hierarchical topological scales of the simplicial complexes and the organization of functional clusters - communities in complex networks. The analysis reveals the full dynamics of different combinatorial structures of q-th-dimensional simplicial complexes and their Laplacian spectra, presenting spectral properties of resulting symmetric and positive semidefinite matrices. The emergence of system's collective behavior from inhomogeneous statistical distribution is induced by hierarchically ordered topological structure, which is mapped to simplicial complex where local interactions between the nodes clustered into subcomplexes generate flow of information that characterizes complexity and dynamics of the full system.
Community structural characteristics and the adoption of fluoridation.
Smith, R A
1981-01-01
A study of community structural characteristics associated with fluoridation outcomes was conducted in 47 communities. A three-part outcome distinction was utilized: communities never having publicly considered the fluoridation issue, those rejecting it, and those accepting it. The independent variables reflect the complexity of the community social and economic structure, social integration, and the centralization of authority. Results of mean comparisons show statistically significant differences between the three outcome types on the independent variables. A series of discriminant analyses provides furtheor evidence of how the independent variables are associated with each outcome type. Non-considering communities are shown to be low in complexity, and high in social integration and the centralization of governmental authority. Rejecters are shown to be high in complexity, but low in social integration and centralized authority. Adopters are relatively high on all three sets of variables. Theretical reasoning is provided to support the hypothesis and why these results are expected. The utility of these results and structural explanations in general are discussed, especially for public/environmental health planning and political activities. PMID:7258427
Game theory and extremal optimization for community detection in complex dynamic networks.
Lung, Rodica Ioana; Chira, Camelia; Andreica, Anca
2014-01-01
The detection of evolving communities in dynamic complex networks is a challenging problem that recently received attention from the research community. Dynamics clearly add another complexity dimension to the difficult task of community detection. Methods should be able to detect changes in the network structure and produce a set of community structures corresponding to different timestamps and reflecting the evolution in time of network data. We propose a novel approach based on game theory elements and extremal optimization to address dynamic communities detection. Thus, the problem is formulated as a mathematical game in which nodes take the role of players that seek to choose a community that maximizes their profit viewed as a fitness function. Numerical results obtained for both synthetic and real-world networks illustrate the competitive performance of this game theoretical approach.
Identifying and characterizing key nodes among communities based on electrical-circuit networks.
Zhu, Fenghui; Wang, Wenxu; Di, Zengru; Fan, Ying
2014-01-01
Complex networks with community structures are ubiquitous in the real world. Despite many approaches developed for detecting communities, we continue to lack tools for identifying overlapping and bridging nodes that play crucial roles in the interactions and communications among communities in complex networks. Here we develop an algorithm based on the local flow conservation to effectively and efficiently identify and distinguish the two types of nodes. Our method is applicable in both undirected and directed networks without a priori knowledge of the community structure. Our method bypasses the extremely challenging problem of partitioning communities in the presence of overlapping nodes that may belong to multiple communities. Due to the fact that overlapping and bridging nodes are of paramount importance in maintaining the function of many social and biological networks, our tools open new avenues towards understanding and controlling real complex networks with communities accompanied with the key nodes.
Community structure from spectral properties in complex networks
NASA Astrophysics Data System (ADS)
Servedio, V. D. P.; Colaiori, F.; Capocci, A.; Caldarelli, G.
2005-06-01
We analyze the spectral properties of complex networks focusing on their relation to the community structure, and develop an algorithm based on correlations among components of different eigenvectors. The algorithm applies to general weighted networks, and, in a suitably modified version, to the case of directed networks. Our method allows to correctly detect communities in sharply partitioned graphs, however it is useful to the analysis of more complex networks, without a well defined cluster structure, as social and information networks. As an example, we test the algorithm on a large scale data-set from a psychological experiment of free word association, where it proves to be successful both in clustering words, and in uncovering mental association patterns.
Followers are not enough: a multifaceted approach to community detection in online social networks.
Darmon, David; Omodei, Elisa; Garland, Joshua
2015-01-01
In online social media networks, individuals often have hundreds or even thousands of connections, which link these users not only to friends, associates, and colleagues, but also to news outlets, celebrities, and organizations. In these complex social networks, a 'community' as studied in the social network literature, can have very different meaning depending on the property of the network under study. Taking into account the multifaceted nature of these networks, we claim that community detection in online social networks should also be multifaceted in order to capture all of the different and valuable viewpoints of 'community.' In this paper we focus on three types of communities beyond follower-based structural communities: activity-based, topic-based, and interaction-based. We analyze a Twitter dataset using three different weightings of the structural network meant to highlight these three community types, and then infer the communities associated with these weightings. We show that interesting insights can be obtained about the complex community structure present in social networks by studying when and how these four community types give rise to similar as well as completely distinct community structure.
Interactive effects of temperature and habitat complexity on freshwater communities.
Scrine, Jennifer; Jochum, Malte; Ólafsson, Jón S; O'Gorman, Eoin J
2017-11-01
Warming can lead to increased growth of plants or algae at the base of the food web, which may increase the overall complexity of habitat available for other organisms. Temperature and habitat complexity have both been shown to alter the structure and functioning of communities, but they may also have interactive effects, for example, if the shade provided by additional habitat negates the positive effect of temperature on understory plant or algal growth. This study explored the interactive effects of these two major environmental factors in a manipulative field experiment, by assessing changes in ecosystem functioning (primary production and decomposition) and community structure in the presence and absence of artificial plants along a natural stream temperature gradient of 5-18°C. There was no effect of temperature or habitat complexity on benthic primary production, but epiphytic production increased with temperature in the more complex habitat. Cellulose decomposition rate increased with temperature, but was unaffected by habitat complexity. Macroinvertebrate communities were less similar to each other as temperature increased, while habitat complexity only altered community composition in the coldest streams. There was also an overall increase in macroinvertebrate abundance, body mass, and biomass in the warmest streams, driven by increasing dominance of snails and blackfly larvae. Presence of habitat complexity, however, dampened the strength of this temperature effect on the abundance of macroinvertebrates in the benthos. The interactive effects that were observed suggest that habitat complexity can modify the effects of temperature on important ecosystem functions and community structure, which may alter energy flow through the food web. Given that warming is likely to increase habitat complexity, particularly at higher latitudes, more studies should investigate these two major environmental factors in combination to improve our ability to predict the impacts of future global change.
Natural shorelines promote the stability of fish communities in an urbanized coastal system.
Scyphers, Steven B; Gouhier, Tarik C; Grabowski, Jonathan H; Beck, Michael W; Mareska, John; Powers, Sean P
2015-01-01
Habitat loss and fragmentation are leading causes of species extinctions in terrestrial, aquatic and marine systems. Along coastlines, natural habitats support high biodiversity and valuable ecosystem services but are often replaced with engineered structures for coastal protection or erosion control. We coupled high-resolution shoreline condition data with an eleven-year time series of fish community structure to examine how coastal protection structures impact community stability. Our analyses revealed that the most stable fish communities were nearest natural shorelines. Structurally complex engineered shorelines appeared to promote greater stability than simpler alternatives as communities nearest vertical walls, which are among the most prevalent structures, were most dissimilar from natural shorelines and had the lowest stability. We conclude that conserving and restoring natural habitats is essential for promoting ecological stability. However, in scenarios when natural habitats are not viable, engineered landscapes designed to mimic the complexity of natural habitats may provide similar ecological functions.
Natural Shorelines Promote the Stability of Fish Communities in an Urbanized Coastal System
Scyphers, Steven B.; Gouhier, Tarik C.; Grabowski, Jonathan H.; Beck, Michael W.; Mareska, John; Powers, Sean P.
2015-01-01
Habitat loss and fragmentation are leading causes of species extinctions in terrestrial, aquatic and marine systems. Along coastlines, natural habitats support high biodiversity and valuable ecosystem services but are often replaced with engineered structures for coastal protection or erosion control. We coupled high-resolution shoreline condition data with an eleven-year time series of fish community structure to examine how coastal protection structures impact community stability. Our analyses revealed that the most stable fish communities were nearest natural shorelines. Structurally complex engineered shorelines appeared to promote greater stability than simpler alternatives as communities nearest vertical walls, which are among the most prevalent structures, were most dissimilar from natural shorelines and had the lowest stability. We conclude that conserving and restoring natural habitats is essential for promoting ecological stability. However, in scenarios when natural habitats are not viable, engineered landscapes designed to mimic the complexity of natural habitats may provide similar ecological functions. PMID:26039407
Relationships between structural complexity, coral traits, and reef fish assemblages
NASA Astrophysics Data System (ADS)
Darling, Emily S.; Graham, Nicholas A. J.; Januchowski-Hartley, Fraser A.; Nash, Kirsty L.; Pratchett, Morgan S.; Wilson, Shaun K.
2017-06-01
With the ongoing loss of coral cover and the associated flattening of reef architecture, understanding the links between coral habitat and reef fishes is of critical importance. Here, we investigate whether considering coral traits and functional diversity provides new insights into the relationship between structural complexity and reef fish communities, and whether coral traits and community composition can predict structural complexity. Across 157 sites in Seychelles, Maldives, the Chagos Archipelago, and Australia's Great Barrier Reef, we find that structural complexity and reef zone are the strongest and most consistent predictors of reef fish abundance, biomass, species richness, and trophic structure. However, coral traits, diversity, and life histories provided additional predictive power for models of reef fish assemblages, and were key drivers of structural complexity. Our findings highlight that reef complexity relies on living corals—with different traits and life histories—continuing to build carbonate skeletons, and that these nuanced relationships between coral assemblages and habitat complexity can affect the structure of reef fish assemblages. Seascape-level estimates of structural complexity are rapid and cost effective with important implications for the structure and function of fish assemblages, and should be incorporated into monitoring programs.
Community structure in traffic zones based on travel demand
NASA Astrophysics Data System (ADS)
Sun, Li; Ling, Ximan; He, Kun; Tan, Qian
2016-09-01
Large structure in complex networks can be studied by dividing it into communities or modules. Urban traffic system is one of the most critical infrastructures. It can be abstracted into a complex network composed of tightly connected groups. Here, we analyze community structure in urban traffic zones based on the community detection method in network science. Spectral algorithm using the eigenvectors of matrices is employed. Our empirical results indicate that the traffic communities are variant with the travel demand distribution, since in the morning the majority of the passengers are traveling from home to work and in the evening they are traveling a contrary direction. Meanwhile, the origin-destination pairs with large number of trips play a significant role in urban traffic network's community division. The layout of traffic community in a city also depends on the residents' trajectories.
Li, Zhenping; Zhang, Xiang-Sun; Wang, Rui-Sheng; Liu, Hongwei; Zhang, Shihua
2013-01-01
Identification of communities in complex networks is an important topic and issue in many fields such as sociology, biology, and computer science. Communities are often defined as groups of related nodes or links that correspond to functional subunits in the corresponding complex systems. While most conventional approaches have focused on discovering communities of nodes, some recent studies start partitioning links to find overlapping communities straightforwardly. In this paper, we propose a new quantity function for link community identification in complex networks. Based on this quantity function we formulate the link community partition problem into an integer programming model which allows us to partition a complex network into overlapping communities. We further propose a genetic algorithm for link community detection which can partition a network into overlapping communities without knowing the number of communities. We test our model and algorithm on both artificial networks and real-world networks. The results demonstrate that the model and algorithm are efficient in detecting overlapping community structure in complex networks. PMID:24386268
Online Community Detection for Large Complex Networks
Pan, Gang; Zhang, Wangsheng; Wu, Zhaohui; Li, Shijian
2014-01-01
Complex networks describe a wide range of systems in nature and society. To understand complex networks, it is crucial to investigate their community structure. In this paper, we develop an online community detection algorithm with linear time complexity for large complex networks. Our algorithm processes a network edge by edge in the order that the network is fed to the algorithm. If a new edge is added, it just updates the existing community structure in constant time, and does not need to re-compute the whole network. Therefore, it can efficiently process large networks in real time. Our algorithm optimizes expected modularity instead of modularity at each step to avoid poor performance. The experiments are carried out using 11 public data sets, and are measured by two criteria, modularity and NMI (Normalized Mutual Information). The results show that our algorithm's running time is less than the commonly used Louvain algorithm while it gives competitive performance. PMID:25061683
Epidemic spreading on complex networks with community structures
Stegehuis, Clara; van der Hofstad, Remco; van Leeuwaarden, Johan S. H.
2016-01-01
Many real-world networks display a community structure. We study two random graph models that create a network with similar community structure as a given network. One model preserves the exact community structure of the original network, while the other model only preserves the set of communities and the vertex degrees. These models show that community structure is an important determinant of the behavior of percolation processes on networks, such as information diffusion or virus spreading: the community structure can both enforce as well as inhibit diffusion processes. Our models further show that it is the mesoscopic set of communities that matters. The exact internal structures of communities barely influence the behavior of percolation processes across networks. This insensitivity is likely due to the relative denseness of the communities. PMID:27440176
A density-based clustering model for community detection in complex networks
NASA Astrophysics Data System (ADS)
Zhao, Xiang; Li, Yantao; Qu, Zehui
2018-04-01
Network clustering (or graph partitioning) is an important technique for uncovering the underlying community structures in complex networks, which has been widely applied in various fields including astronomy, bioinformatics, sociology, and bibliometric. In this paper, we propose a density-based clustering model for community detection in complex networks (DCCN). The key idea is to find group centers with a higher density than their neighbors and a relatively large integrated-distance from nodes with higher density. The experimental results indicate that our approach is efficient and effective for community detection of complex networks.
Distributed learning automata-based algorithm for community detection in complex networks
NASA Astrophysics Data System (ADS)
Khomami, Mohammad Mehdi Daliri; Rezvanian, Alireza; Meybodi, Mohammad Reza
2016-03-01
Community structure is an important and universal topological property of many complex networks such as social and information networks. The detection of communities of a network is a significant technique for understanding the structure and function of networks. In this paper, we propose an algorithm based on distributed learning automata for community detection (DLACD) in complex networks. In the proposed algorithm, each vertex of network is equipped with a learning automation. According to the cooperation among network of learning automata and updating action probabilities of each automaton, the algorithm interactively tries to identify high-density local communities. The performance of the proposed algorithm is investigated through a number of simulations on popular synthetic and real networks. Experimental results in comparison with popular community detection algorithms such as walk trap, Danon greedy optimization, Fuzzy community detection, Multi-resolution community detection and label propagation demonstrated the superiority of DLACD in terms of modularity, NMI, performance, min-max-cut and coverage.
NASA Astrophysics Data System (ADS)
Muscoloni, Alessandro; Vittorio Cannistraci, Carlo
2018-05-01
The investigation of the hidden metric space behind complex network topologies is a fervid topic in current network science and the hyperbolic space is one of the most studied, because it seems associated to the structural organization of many real complex systems. The popularity-similarity-optimization (PSO) model simulates how random geometric graphs grow in the hyperbolic space, generating realistic networks with clustering, small-worldness, scale-freeness and rich-clubness. However, it misses to reproduce an important feature of real complex networks, which is the community organization. The geometrical-preferential-attachment (GPA) model was recently developed in order to confer to the PSO also a soft community structure, which is obtained by forcing different angular regions of the hyperbolic disk to have a variable level of attractiveness. However, the number and size of the communities cannot be explicitly controlled in the GPA, which is a clear limitation for real applications. Here, we introduce the nonuniform PSO (nPSO) model. Differently from GPA, the nPSO generates synthetic networks in the hyperbolic space where heterogeneous angular node attractiveness is forced by sampling the angular coordinates from a tailored nonuniform probability distribution (for instance a mixture of Gaussians). The nPSO differs from GPA in other three aspects: it allows one to explicitly fix the number and size of communities; it allows one to tune their mixing property by means of the network temperature; it is efficient to generate networks with high clustering. Several tests on the detectability of the community structure in nPSO synthetic networks and wide investigations on their structural properties confirm that the nPSO is a valid and efficient model to generate realistic complex networks with communities.
Followers Are Not Enough: A Multifaceted Approach to Community Detection in Online Social Networks
2015-01-01
In online social media networks, individuals often have hundreds or even thousands of connections, which link these users not only to friends, associates, and colleagues, but also to news outlets, celebrities, and organizations. In these complex social networks, a ‘community’ as studied in the social network literature, can have very different meaning depending on the property of the network under study. Taking into account the multifaceted nature of these networks, we claim that community detection in online social networks should also be multifaceted in order to capture all of the different and valuable viewpoints of ‘community.’ In this paper we focus on three types of communities beyond follower-based structural communities: activity-based, topic-based, and interaction-based. We analyze a Twitter dataset using three different weightings of the structural network meant to highlight these three community types, and then infer the communities associated with these weightings. We show that interesting insights can be obtained about the complex community structure present in social networks by studying when and how these four community types give rise to similar as well as completely distinct community structure. PMID:26267868
Sensitivity of system stability to model structure
Hosack, G.R.; Li, H.W.; Rossignol, P.A.
2009-01-01
A community is stable, and resilient, if the levels of all community variables can return to the original steady state following a perturbation. The stability properties of a community depend on its structure, which is the network of direct effects (interactions) among the variables within the community. These direct effects form feedback cycles (loops) that determine community stability. Although feedback cycles have an intuitive interpretation, identifying how they form the feedback properties of a particular community can be intractable. Furthermore, determining the role that any specific direct effect plays in the stability of a system is even more daunting. Such information, however, would identify important direct effects for targeted experimental and management manipulation even in complex communities for which quantitative information is lacking. We therefore provide a method that determines the sensitivity of community stability to model structure, and identifies the relative role of particular direct effects, indirect effects, and feedback cycles in determining stability. Structural sensitivities summarize the degree to which each direct effect contributes to stabilizing feedback or destabilizing feedback or both. Structural sensitivities prove useful in identifying ecologically important feedback cycles within the community structure and for detecting direct effects that have strong, or weak, influences on community stability. The approach may guide the development of management intervention and research design. We demonstrate its value with two theoretical models and two empirical examples of different levels of complexity. ?? 2009 Elsevier B.V. All rights reserved.
Integrating succession and community assembly perspectives
Chang, Cynthia; HilleRisLambers, Janneke
2016-01-01
Succession and community assembly research overlap in many respects, such as through their focus on how ecological processes like dispersal, environmental filters, and biotic interactions influence community structure. Indeed, many recent advances have been made by successional studies that draw on modern analytical techniques introduced by contemporary community assembly studies. However, community assembly studies generally lack a temporal perspective, both on how the forces structuring communities might change over time and on how historical contingency (e.g. priority effects and legacy effects) and complex transitions (e.g. threshold effects) might alter community trajectories. We believe a full understanding of the complex interacting processes that shape community dynamics across large temporal scales can best be achieved by combining concepts, tools, and study systems into an integrated conceptual framework that draws upon both succession and community assembly theory. PMID:27785355
A spectral method to detect community structure based on distance modularity matrix
NASA Astrophysics Data System (ADS)
Yang, Jin-Xuan; Zhang, Xiao-Dong
2017-08-01
There are many community organizations in social and biological networks. How to identify these community structure in complex networks has become a hot issue. In this paper, an algorithm to detect community structure of networks is proposed by using spectra of distance modularity matrix. The proposed algorithm focuses on the distance of vertices within communities, rather than the most weakly connected vertex pairs or number of edges between communities. The experimental results show that our method achieves better effectiveness to identify community structure for a variety of real-world networks and computer generated networks with a little more time-consumption.
Correlations between Community Structure and Link Formation in Complex Networks
Liu, Zhen; He, Jia-Lin; Kapoor, Komal; Srivastava, Jaideep
2013-01-01
Background Links in complex networks commonly represent specific ties between pairs of nodes, such as protein-protein interactions in biological networks or friendships in social networks. However, understanding the mechanism of link formation in complex networks is a long standing challenge for network analysis and data mining. Methodology/Principal Findings Links in complex networks have a tendency to cluster locally and form so-called communities. This widely existed phenomenon reflects some underlying mechanism of link formation. To study the correlations between community structure and link formation, we present a general computational framework including a theory for network partitioning and link probability estimation. Our approach enables us to accurately identify missing links in partially observed networks in an efficient way. The links having high connection likelihoods in the communities reveal that links are formed preferentially to create cliques and accordingly promote the clustering level of the communities. The experimental results verify that such a mechanism can be well captured by our approach. Conclusions/Significance Our findings provide a new insight into understanding how links are created in the communities. The computational framework opens a wide range of possibilities to develop new approaches and applications, such as community detection and missing link prediction. PMID:24039818
NASA Astrophysics Data System (ADS)
Perotti, Juan Ignacio; Tessone, Claudio Juan; Caldarelli, Guido
2015-12-01
The quest for a quantitative characterization of community and modular structure of complex networks produced a variety of methods and algorithms to classify different networks. However, it is not clear if such methods provide consistent, robust, and meaningful results when considering hierarchies as a whole. Part of the problem is the lack of a similarity measure for the comparison of hierarchical community structures. In this work we give a contribution by introducing the hierarchical mutual information, which is a generalization of the traditional mutual information and makes it possible to compare hierarchical partitions and hierarchical community structures. The normalized version of the hierarchical mutual information should behave analogously to the traditional normalized mutual information. Here the correct behavior of the hierarchical mutual information is corroborated on an extensive battery of numerical experiments. The experiments are performed on artificial hierarchies and on the hierarchical community structure of artificial and empirical networks. Furthermore, the experiments illustrate some of the practical applications of the hierarchical mutual information, namely the comparison of different community detection methods and the study of the consistency, robustness, and temporal evolution of the hierarchical modular structure of networks.
Fragmentation alters stream fish community structure in dendritic ecological networks.
Perkin, Joshuah S; Gido, Keith B
2012-12-01
Effects of fragmentation on the ecology of organisms occupying dendritic ecological networks (DENs) have recently been described through both conceptual and mathematical models, but few hypotheses have been tested in complex, real-world ecosystems. Stream fishes provide a model system for assessing effects of fragmentation on the structure of communities occurring within DENs, including how fragmentation alters metacommunity dynamics and biodiversity. A recently developed habitat-availability measure, the "dendritic connectivity index" (DCI), allows for assigning quantitative measures of connectivity in DENs regardless of network extent or complexity, and might be used to predict fish community response to fragmentation. We characterized stream fish community structure in 12 DENs in the Great Plains, USA, during periods of dynamic (summer) and muted (fall) discharge regimes to test the DCI as a predictive model of fish community response to fragmentation imposed by road crossings. Results indicated that fish communities in stream segments isolated by road crossings had reduced species richness (alpha diversity) relative to communities that maintained connectivity with the surrounding DEN during summer and fall. Furthermore, isolated communities had greater dissimilarity (beta diversity) to downstream sites notisolated by road crossings during summer and fall. Finally, dissimilarity among communities within DENs decreased as a function of increased habitat connectivity (measured using the DCI) for summer and fall, suggesting that communities within highly connected DENs tend to be more homogeneous. Our results indicate that the DCI is sensitive to community effects of fragmentation in riverscapes and might be used by managers to predict ecological responses to changes in habitat connectivity. Moreover, our findings illustrate that relating structural connectivity of riverscapes to functional connectivity among communities might aid in maintaining metacommunity dynamics and biodiversity in complex dendritic ecosystems.
Structural Preferential Attachment: Network Organization beyond the Link
NASA Astrophysics Data System (ADS)
Hébert-Dufresne, Laurent; Allard, Antoine; Marceau, Vincent; Noël, Pierre-André; Dubé, Louis J.
2011-10-01
We introduce a mechanism which models the emergence of the universal properties of complex networks, such as scale independence, modularity and self-similarity, and unifies them under a scale-free organization beyond the link. This brings a new perspective on network organization where communities, instead of links, are the fundamental building blocks of complex systems. We show how our simple model can reproduce social and information networks by predicting their community structure and more importantly, how their nodes or communities are interconnected, often in a self-similar manner.
Extracting Communities from Complex Networks by the k-Dense Method
NASA Astrophysics Data System (ADS)
Saito, Kazumi; Yamada, Takeshi; Kazama, Kazuhiro
To understand the structural and functional properties of large-scale complex networks, it is crucial to efficiently extract a set of cohesive subnetworks as communities. There have been proposed several such community extraction methods in the literature, including the classical k-core decomposition method and, more recently, the k-clique based community extraction method. The k-core method, although computationally efficient, is often not powerful enough for uncovering a detailed community structure and it produces only coarse-grained and loosely connected communities. The k-clique method, on the other hand, can extract fine-grained and tightly connected communities but requires a substantial amount of computational load for large-scale complex networks. In this paper, we present a new notion of a subnetwork called k-dense, and propose an efficient algorithm for extracting k-dense communities. We applied our method to the three different types of networks assembled from real data, namely, from blog trackbacks, word associations and Wikipedia references, and demonstrated that the k-dense method could extract communities almost as efficiently as the k-core method, while the qualities of the extracted communities are comparable to those obtained by the k-clique method.
NASA Astrophysics Data System (ADS)
Shepard, R.
2008-12-01
Microbial communities are architects of incredibly complex and diverse morphological structures. Each morphology is a snapshot that reflects the complex interactions within the microbial community and between the community and its environment. Characterizing morphology as an emergent property of microbial communities is thus relevant to understanding the evolution of multicellularity and complexity in developmental systems, to the identification of biosignatures, and to furthering our understanding of modern and ancient microbial ecology. Recently discovered cyanobacterial mats in Pavilion Lake, British Columbia construct unusual complex architecture on the scale of decimeters that incorporates significant void space. Fundamental mesoscale morphological elements include terraces, arches, bridges, depressions, domes, and pillars. The mats themselves also exhibit several microscale morphologies, with reticulate structures being the dominant example. The reticulate structures exhibit a diverse spectrum of morphologies with endmembers characterized by either angular or curvilinear ridges. In laboratory studies, aggregation into reticulate structures occurs as a result of the random gliding and colliding among motile cyanobacterial filaments. Likewise, when Pavilion reticulate mats were sampled and brought to the surface, cyanobacteria invariably migrated out of the mat onto surrounding surfaces. Filaments were observed to move rapidly in clumps, preferentially following paths of previous filaments. The migrating filaments organized into new angular and ropey reticulate biofilms within hours of sampling, demonstrating that cell motility is responsible for the reticulate patterns. Because the morphogenesis of reticulate structures can be linked to motility behaviors of filamentous cyanobacteria, the Willow Point mats provide a unique natural laboratory in which to elucidate the connections between a specific microbial behavior and the construction of complex microbial community morphology. To this end, we identified and characterized fundamental building blocks of the mesoscale morphologies, including bridges, anchors, and curved edges. These morphological building blocks were compared with the suite of motility behaviors and patterns observed in reticulate morphogenesis. Results of this comparison suggest that cyanobacterial motility plays a significant and often dominant role in the morphogenesis of the entire suite of morphologies observed in the microbial mats of Pavilion Lake.
Komyakova, Valeriya; Munday, Philip L.; Jones, Geoffrey P.
2013-01-01
The structure of coral reef habitat has a pronounced influence on the diversity, composition and abundance of reef-associated fishes. However, the particular features of the habitat that are most critical are not always known. Coral habitats can vary in many characteristics, notably live coral cover, topographic complexity and coral diversity, but the relative effects of these habitat characteristics are often not distinguished. Here, we investigate the strength of the relationships between these habitat features and local fish diversity, abundance and community structure in the lagoon of Lizard Island, Great Barrier Reef. In a spatial comparison using sixty-six 2m2 quadrats, fish species richness, total abundance and community structure were examined in relation to a wide range of habitat variables, including topographic complexity, habitat diversity, coral diversity, coral species richness, hard coral cover, branching coral cover and the cover of corymbose corals. Fish species richness and total abundance were strongly associated with coral species richness and cover, but only weakly associated with topographic complexity. Regression tree analysis showed that coral species richness accounted for most of the variation in fish species richness (63.6%), while hard coral cover explained more variation in total fish abundance (17.4%), than any other variable. In contrast, topographic complexity accounted for little spatial variation in reef fish assemblages. In degrading coral reef environments, the potential effects of loss of coral cover and topographic complexity are often emphasized, but these findings suggest that reduced coral biodiversity may ultimately have an equal, or greater, impact on reef-associated fish communities. PMID:24349455
Komyakova, Valeriya; Munday, Philip L; Jones, Geoffrey P
2013-01-01
The structure of coral reef habitat has a pronounced influence on the diversity, composition and abundance of reef-associated fishes. However, the particular features of the habitat that are most critical are not always known. Coral habitats can vary in many characteristics, notably live coral cover, topographic complexity and coral diversity, but the relative effects of these habitat characteristics are often not distinguished. Here, we investigate the strength of the relationships between these habitat features and local fish diversity, abundance and community structure in the lagoon of Lizard Island, Great Barrier Reef. In a spatial comparison using sixty-six 2m(2) quadrats, fish species richness, total abundance and community structure were examined in relation to a wide range of habitat variables, including topographic complexity, habitat diversity, coral diversity, coral species richness, hard coral cover, branching coral cover and the cover of corymbose corals. Fish species richness and total abundance were strongly associated with coral species richness and cover, but only weakly associated with topographic complexity. Regression tree analysis showed that coral species richness accounted for most of the variation in fish species richness (63.6%), while hard coral cover explained more variation in total fish abundance (17.4%), than any other variable. In contrast, topographic complexity accounted for little spatial variation in reef fish assemblages. In degrading coral reef environments, the potential effects of loss of coral cover and topographic complexity are often emphasized, but these findings suggest that reduced coral biodiversity may ultimately have an equal, or greater, impact on reef-associated fish communities.
Research on energy stock market associated network structure based on financial indicators
NASA Astrophysics Data System (ADS)
Xi, Xian; An, Haizhong
2018-01-01
A financial market is a complex system consisting of many interacting units. In general, due to the various types of information exchange within the industry, there is a relationship between the stocks that can reveal their clear structural characteristics. Complex network methods are powerful tools for studying the internal structure and function of the stock market, which allows us to better understand the stock market. Applying complex network methodology, a stock associated network model based on financial indicators is created. Accordingly, we set threshold value and use modularity to detect the community network, and we analyze the network structure and community cluster characteristics of different threshold situations. The study finds that the threshold value of 0.7 is the abrupt change point of the network. At the same time, as the threshold value increases, the independence of the community strengthens. This study provides a method of researching stock market based on the financial indicators, exploring the structural similarity of financial indicators of stocks. Also, it provides guidance for investment and corporate financial management.
A bacterial pioneer produces cellulase complexes that persist through community succession
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kolinko, Sebastian; Wu, Yu-Wei; Tachea, Firehiwot
Cultivation of microbial consortia provides low-complexity communities that can serve as tractable models to understand community dynamics. Time-resolved metagenomics demonstrated that an aerobic cellulolytic consortium cultivated from compost exhibited community dynamics consistent with the definition of an endogenous heterotrophic succession. The genome of the proposed pioneer population, 'Candidatus Reconcilibacillus cellulovorans', possessed a gene cluster containing multidomain glycoside hydrolases (GHs). Purification of the soluble cellulase activity from a 300litre cultivation of this consortium revealed that ~70% of the activity arose from the 'Ca. Reconcilibacillus cellulovorans' multidomain GHs assembled into cellulase complexes through glycosylation. These remarkably stable complexes have supramolecular structures formore » enzymatic cellulose hydrolysis that are distinct from cellulosomes. The persistence of these complexes during cultivation indicates that they may be active through multiple cultivations of this consortium and act as public goods that sustain the community. Thus, the provision of extracellular GHs as public goods may influence microbial community dynamics in native biomass-deconstructing communities relevant to agriculture, human health and biotechnology.« less
A bacterial pioneer produces cellulase complexes that persist through community succession
Kolinko, Sebastian; Wu, Yu-Wei; Tachea, Firehiwot; ...
2017-11-06
Cultivation of microbial consortia provides low-complexity communities that can serve as tractable models to understand community dynamics. Time-resolved metagenomics demonstrated that an aerobic cellulolytic consortium cultivated from compost exhibited community dynamics consistent with the definition of an endogenous heterotrophic succession. The genome of the proposed pioneer population, 'Candidatus Reconcilibacillus cellulovorans', possessed a gene cluster containing multidomain glycoside hydrolases (GHs). Purification of the soluble cellulase activity from a 300litre cultivation of this consortium revealed that ~70% of the activity arose from the 'Ca. Reconcilibacillus cellulovorans' multidomain GHs assembled into cellulase complexes through glycosylation. These remarkably stable complexes have supramolecular structures formore » enzymatic cellulose hydrolysis that are distinct from cellulosomes. The persistence of these complexes during cultivation indicates that they may be active through multiple cultivations of this consortium and act as public goods that sustain the community. Thus, the provision of extracellular GHs as public goods may influence microbial community dynamics in native biomass-deconstructing communities relevant to agriculture, human health and biotechnology.« less
A bacterial pioneer produces cellulase complexes that persist through community succession.
Kolinko, Sebastian; Wu, Yu-Wei; Tachea, Firehiwot; Denzel, Evelyn; Hiras, Jennifer; Gabriel, Raphael; Bäcker, Nora; Chan, Leanne Jade G; Eichorst, Stephanie A; Frey, Dario; Chen, Qiushi; Azadi, Parastoo; Adams, Paul D; Pray, Todd R; Tanjore, Deepti; Petzold, Christopher J; Gladden, John M; Simmons, Blake A; Singer, Steven W
2018-01-01
Cultivation of microbial consortia provides low-complexity communities that can serve as tractable models to understand community dynamics. Time-resolved metagenomics demonstrated that an aerobic cellulolytic consortium cultivated from compost exhibited community dynamics consistent with the definition of an endogenous heterotrophic succession. The genome of the proposed pioneer population, 'Candidatus Reconcilibacillus cellulovorans', possessed a gene cluster containing multidomain glycoside hydrolases (GHs). Purification of the soluble cellulase activity from a 300litre cultivation of this consortium revealed that ~70% of the activity arose from the 'Ca. Reconcilibacillus cellulovorans' multidomain GHs assembled into cellulase complexes through glycosylation. These remarkably stable complexes have supramolecular structures for enzymatic cellulose hydrolysis that are distinct from cellulosomes. The persistence of these complexes during cultivation indicates that they may be active through multiple cultivations of this consortium and act as public goods that sustain the community. The provision of extracellular GHs as public goods may influence microbial community dynamics in native biomass-deconstructing communities relevant to agriculture, human health and biotechnology.
Epidemic spreading on complex networks with overlapping and non-overlapping community structure
NASA Astrophysics Data System (ADS)
Shang, Jiaxing; Liu, Lianchen; Li, Xin; Xie, Feng; Wu, Cheng
2015-02-01
Many real-world networks exhibit community structure where vertices belong to one or more communities. Recent studies show that community structure plays an import role in epidemic spreading. In this paper, we investigate how the extent of overlap among communities affects epidemics. In order to experiment on the characteristic of overlapping communities, we propose a rewiring algorithm that can change the community structure from overlapping to non-overlapping while maintaining the degree distribution of the network. We simulate the Susceptible-Infected-Susceptible (SIS) epidemic process on synthetic scale-free networks and real-world networks by applying our rewiring algorithm. Experiments show that epidemics spread faster on networks with higher level of overlapping communities. Furthermore, overlapping communities' effect interacts with the average degree's effect. Our work further illustrates the important role of overlapping communities in the process of epidemic spreading.
Purahong, Witoon; Schloter, Michael; Pecyna, Marek J; Kapturska, Danuta; Däumlich, Veronika; Mital, Sanchit; Buscot, François; Hofrichter, Martin; Gutknecht, Jessica L M; Krüger, Dirk
2014-11-12
The widespread paradigm in ecology that community structure determines function has recently been challenged by the high complexity of microbial communities. Here, we investigate the patterns of and connections between microbial community structure and microbially-mediated ecological function across different forest management practices and temporal changes in leaf litter across beech forest ecosystems in Central Europe. Our results clearly indicate distinct pattern of microbial community structure in response to forest management and time. However, those patterns were not reflected when potential enzymatic activities of microbes were measured. We postulate that in our forest ecosystems, a disconnect between microbial community structure and function may be present due to differences between the drivers of microbial growth and those of microbial function.
Terrestrial origin of bacterial communities in complex boreal freshwater networks.
Ruiz-González, Clara; Niño-García, Juan Pablo; Del Giorgio, Paul A
2015-08-25
Bacteria inhabiting boreal freshwaters are part of metacommunities where local assemblages are often linked by the flow of water in the landscape, yet the resulting spatial structure and the boundaries of the network metacommunity have never been explored. Here, we reconstruct the spatial structure of the bacterial metacommunity in a complex boreal aquatic network by determining the taxonomic composition of bacterial communities along the entire terrestrial/aquatic continuum, including soil and soilwaters, headwater streams, large rivers and lakes. We show that the network metacommunity has a directional spatial structure driven by a common terrestrial origin of aquatic communities, which are numerically dominated by taxa recruited from soils. Local community assembly is driven by variations along the hydrological continuum in the balance between mass effects and species sorting of terrestrial taxa, and seems further influenced by priority effects related to the spatial sequence of entry of soil bacteria into the network. © 2015 John Wiley & Sons Ltd/CNRS.
Community detection in complex networks using proximate support vector clustering
NASA Astrophysics Data System (ADS)
Wang, Feifan; Zhang, Baihai; Chai, Senchun; Xia, Yuanqing
2018-03-01
Community structure, one of the most attention attracting properties in complex networks, has been a cornerstone in advances of various scientific branches. A number of tools have been involved in recent studies concentrating on the community detection algorithms. In this paper, we propose a support vector clustering method based on a proximity graph, owing to which the introduced algorithm surpasses the traditional support vector approach both in accuracy and complexity. Results of extensive experiments undertaken on computer generated networks and real world data sets illustrate competent performances in comparison with the other counterparts.
Coral identity underpins architectural complexity on Caribbean reefs.
Alvarez-Filip, Lorenzo; Dulvy, Nicholas K; Côte, Isabelle M; Watkinson, Andrew R; Gill, Jennifer A
2011-09-01
The architectural complexity of ecosystems can greatly influence their capacity to support biodiversity and deliver ecosystem services. Understanding the components underlying this complexity can aid the development of effective strategies for ecosystem conservation. Caribbean coral reefs support and protect millions of livelihoods, but recent anthropogenic change is shifting communities toward reefs dominated by stress-resistant coral species, which are often less architecturally complex. With the regionwide decline in reef fish abundance, it is becoming increasingly important to understand changes in coral reef community structure and function. We quantify the influence of coral composition, diversity, and morpho-functional traits on the architectural complexity of reefs across 91 sites at Cozumel, Mexico. Although reef architectural complexity increases with coral cover and species richness, it is highest on sites that are low in taxonomic evenness and dominated by morpho-functionally important, reef-building coral genera, particularly Montastraea. Sites with similar coral community composition also tend to occur on reefs with very similar architectural complexity, suggesting that reef structure tends to be determined by the same key species across sites. Our findings provide support for prioritizing and protecting particular reef types, especially those dominated by key reef-building corals, in order to enhance reef complexity.
Linking Knowledge and Action: PRI's Community Consultant.
ERIC Educational Resources Information Center
Spencer, Gregory P.
Within the Partnership for Rural Improvement (PRI), community consultants operate within three complex sets of relationships: client groups, the organizational structure of PRI, and the local operational base. Community consultants are responsible for developing and facilitating rural development and for providing assistance in community and…
Rudolf, Volker H W; Rasmussen, Nick L
2013-05-01
A central challenge in community ecology is to understand the connection between biodiversity and the functioning of ecosystems. While traditional approaches have largely focused on species-level diversity, increasing evidence indicates that there exists substantial ecological diversity among individuals within species. By far, the largest source of this intraspecific diversity stems from variation among individuals in ontogenetic stage and size. Although such ontogenetic shifts are ubiquitous in natural communities, whether and how they scale up to influence the structure and functioning of complex ecosystems is largely unknown. Here we take an experimental approach to examine the consequences of ontogenetic niche shifts for the structure of communities and ecosystem processes. In particular we experimentally manipulated the stage structure in a keystone predator, larvae of the dragonfly Anax junius, in complex experimental pond communities to test whether changes in the population stage or size structure of a keystone species scale up to alter community structure and ecosystem processes, and how functional differences scale with relative differences in size among stages. We found that the functional role of A. junius was stage-specific. Altering what stages were present in a pond led to concurrent changes in community structure, primary producer biomass (periphyton and phytoplankton), and ultimately altered ecosystem processes (respiration and net primary productivity), indicating a strong, but stage-specific, trophic cascade. Interestingly, the stage-specific effects did not simply scale with size or biomass of the predator, but instead indicated clear ontogenetic niche shifts in ecological interactions. Thus, functional differences among stages within a keystone species scaled up to alter the functioning of entire ecosystems. Therefore, our results indicate that the classical approach of assuming an average functional role of a species can be misleading because functional roles are dynamic and will change with shifts in the stage structure of the species. In general this emphasizes the importance of accounting for functional diversity below the species level to predict how natural and anthropogenic changes alter the functioning of natural ecosystems.
Bryson, Mitch; Ferrari, Renata; Figueira, Will; Pizarro, Oscar; Madin, Josh; Williams, Stefan; Byrne, Maria
2017-08-01
Habitat structural complexity is one of the most important factors in determining the makeup of biological communities. Recent advances in structure-from-motion and photogrammetry have resulted in a proliferation of 3D digital representations of habitats from which structural complexity can be measured. Little attention has been paid to quantifying the measurement errors associated with these techniques, including the variability of results under different surveying and environmental conditions. Such errors have the potential to confound studies that compare habitat complexity over space and time. This study evaluated the accuracy, precision, and bias in measurements of marine habitat structural complexity derived from structure-from-motion and photogrammetric measurements using repeated surveys of artificial reefs (with known structure) as well as natural coral reefs. We quantified measurement errors as a function of survey image coverage, actual surface rugosity, and the morphological community composition of the habitat-forming organisms (reef corals). Our results indicated that measurements could be biased by up to 7.5% of the total observed ranges of structural complexity based on the environmental conditions present during any particular survey. Positive relationships were found between measurement errors and actual complexity, and the strength of these relationships was increased when coral morphology and abundance were also used as predictors. The numerous advantages of structure-from-motion and photogrammetry techniques for quantifying and investigating marine habitats will mean that they are likely to replace traditional measurement techniques (e.g., chain-and-tape). To this end, our results have important implications for data collection and the interpretation of measurements when examining changes in habitat complexity using structure-from-motion and photogrammetry.
Wilson, Shaun K; Babcock, Russ C; Fisher, Rebecca; Holmes, Thomas H; Moore, James A Y; Thomson, Damian P
2012-10-01
Habitat degradation and fishing are major drivers of temporal and spatial changes in fish communities. The independent effects of these drivers are well documented, but the relative importance and interaction between fishing and habitat shifts is poorly understood, particularly in complex systems such as coral reefs. To assess the combined and relative effects of fishing and habitat we examined the composition of fish communities on patch reefs across a gradient of high to low structural complexity in fished and unfished areas of the Ningaloo Marine Park, Western Australia. Biomass and species richness of fish were positively correlated with structural complexity of reefs and negatively related to macroalgal cover. Total abundance of fish was also positively related to structural complexity, however this relationship was stronger on fished reefs than those where fishing is prohibited. The interaction between habitat condition and fishing pressure is primarily due to the high abundance of small bodied planktivorous fish on fished reefs. However, the influence of management zones on the abundance and biomass of predators and target species is small, implying spatial differences in fishing pressure are low and unlikely to be driving this interaction. Our results emphasise the importance of habitat in structuring reef fish communities on coral reefs especially when gradients in fishing pressure are low. The influence of fishing effort on this relationship may however become more important as fishing pressure increases. Copyright © 2012 Elsevier Ltd. All rights reserved.
Incorporating profile information in community detection for online social networks
NASA Astrophysics Data System (ADS)
Fan, W.; Yeung, K. H.
2014-07-01
Community structure is an important feature in the study of complex networks. It is because nodes of the same community may have similar properties. In this paper we extend two popular community detection methods to partition online social networks. In our extended methods, the profile information of users is used for partitioning. We apply the extended methods in several sample networks of Facebook. Compared with the original methods, the community structures we obtain have higher modularity. Our results indicate that users' profile information is consistent with the community structure of their friendship network to some extent. To the best of our knowledge, this paper is the first to discuss how profile information can be used to improve community detection in online social networks.
Rogers, Alice; Blanchard, Julia L; Newman, Steven P; Dryden, Charlie S; Mumby, Peter J
2018-02-01
Refuge availability and fishing alter predator-prey interactions on coral reefs, but our understanding of how they interact to drive food web dynamics, community structure and vulnerability of different trophic groups is unclear. Here, we apply a size-based ecosystem model of coral reefs, parameterized with empirical measures of structural complexity, to predict fish biomass, productivity and community structure in reef ecosystems under a broad range of refuge availability and fishing regimes. In unfished ecosystems, the expected positive correlation between reef structural complexity and biomass emerges, but a non-linear effect of predation refuges is observed for the productivity of predatory fish. Reefs with intermediate complexity have the highest predator productivity, but when refuge availability is high and prey are less available, predator growth rates decrease, with significant implications for fisheries. Specifically, as fishing intensity increases, predators in habitats with high refuge availability exhibit vulnerability to over-exploitation, resulting in communities dominated by herbivores. Our study reveals mechanisms for threshold dynamics in predators living in complex habitats and elucidates how predators can be food-limited when most of their prey are able to hide. We also highlight the importance of nutrient recycling via the detrital pathway, to support high predator biomasses on coral reefs. © 2018 by the Ecological Society of America.
Modeling microbial community structure and functional diversity across time and space.
Larsen, Peter E; Gibbons, Sean M; Gilbert, Jack A
2012-07-01
Microbial communities exhibit exquisitely complex structure. Many aspects of this complexity, from the number of species to the total number of interactions, are currently very difficult to examine directly. However, extraordinary efforts are being made to make these systems accessible to scientific investigation. While recent advances in high-throughput sequencing technologies have improved accessibility to the taxonomic and functional diversity of complex communities, monitoring the dynamics of these systems over time and space - using appropriate experimental design - is still expensive. Fortunately, modeling can be used as a lens to focus low-resolution observations of community dynamics to enable mathematical abstractions of functional and taxonomic dynamics across space and time. Here, we review the approaches for modeling bacterial diversity at both the very large and the very small scales at which microbial systems interact with their environments. We show that modeling can help to connect biogeochemical processes to specific microbial metabolic pathways. © 2012 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.
Es'kov, A K
2013-01-01
Species composition of epiphytic communities within different formations of Phú Quôc Island (Southern Vietnam) is studied. The dependence of species composition and structural complexity of epiphytic communities on formation quality is demonstrated. Representatives of different families differ notably in their sensitivity to disturbances. Most vulnerable are Orchidaceae which represent the dominant group in epiphytic community of rain forest and which drop out almost completely under anthropogenic impacts. In less disturbed forests, epiphyte species diversity increases mainly at the expense of "lower" synusias and directly depends on the formation layering. Diminishing of layering numbers leads to dropping out of species belonging to "lower" synusias. Among epiphytes, the indicators of disturbed communities can be detected, namely species of ruderal strategy (explerents). In primal rain forest, they are absent or barely noticeable. An index is proposed for estimation of epiphytic communitiy complexity.
Vulnerability of coral reef fisheries to a loss of structural complexity.
Rogers, Alice; Blanchard, Julia L; Mumby, Peter J
2014-05-05
Coral reefs face a diverse array of threats, from eutrophication and overfishing to climate change. As live corals are lost and their skeletons eroded, the structural complexity of reefs declines. This may have important consequences for the survival and growth of reef fish because complex habitats mediate predator-prey interactions [1, 2] and influence competition [3-5] through the provision of prey refugia. A positive correlation exists between structural complexity and reef fish abundance and diversity in both temperate and tropical ecosystems [6-10]. However, it is not clear how the diversity of available refugia interacts with individual predator-prey relationships to explain emergent properties at the community scale. Furthermore, we do not yet have the ability to predict how habitat loss might affect the productivity of whole reef communities and the fisheries they support. Using data from an unfished reserve in The Bahamas, we find that structural complexity is associated not only with increased fish biomass and abundance, but also with nonlinearities in the size spectra of fish, implying disproportionately high abundances of certain size classes. By developing a size spectrum food web model that links the vulnerability of prey to predation with the structural complexity of a reef, we show that these nonlinearities can be explained by size-structured prey refugia that reduce mortality rates and alter growth rates in different parts of the size spectrum. Fitting the model with data from a structurally complex habitat, we predict that a loss of complexity could cause more than a 3-fold reduction in fishery productivity. Copyright © 2014 Elsevier Ltd. All rights reserved.
Manucharova, N A; Trosheva, E V; Kol'tsova, E M; Demkina, E V; Karaevskaya, E V; Rivkina, E M; Mardanov, A V; El'-Registan, G I
2016-01-01
A prokaryotic mesophilic organotrophic community responsible for 10% of the total microbial number determined by epifluorescence microscopy was reactivated in the samples ofAntarctic permafrost retrieved from the environment favoring long-term preservation of microbial communities (7500 years). No culturable forms were obtained without resuscitation procedures (CFU = 0). Proteobacteria, Actinobacteria, and Firmicutes were the dominant microbial groups in the complex. Initiation of the reactivated microbial complex by addition of chitin (0.1% wt/vol) resulted in an increased share of metabolically active biomass (up to 50%) due to the functional domination of chitinolytics caused by the target resource. Thus, sequential application of resuscitation procedures and initiation of a specific physiological group (in this case, chitinolytics) to a permafrost-preserved microbial community made it possible to reveal a prokaryotic complex capable of reversion of metabolic activity (FISH data), to determine its phylogenetic structure by metagenomic anal-ysis, and to isolate a pure culture of the dominant microorganism with high chitinolytic activity.
A complex speciation–richness relationship in a simple neutral model
Desjardins-Proulx, Philippe; Gravel, Dominique
2012-01-01
Speciation is the “elephant in the room” of community ecology. As the ultimate source of biodiversity, its integration in ecology's theoretical corpus is necessary to understand community assembly. Yet, speciation is often completely ignored or stripped of its spatial dimension. Recent approaches based on network theory have allowed ecologists to effectively model complex landscapes. In this study, we use this framework to model allopatric and parapatric speciation in networks of communities. We focus on the relationship between speciation, richness, and the spatial structure of communities. We find a strong opposition between speciation and local richness, with speciation being more common in isolated communities and local richness being higher in more connected communities. Unlike previous models, we also find a transition to a positive relationship between speciation and local richness when dispersal is low and the number of communities is small. We use several measures of centrality to characterize the effect of network structure on diversity. The degree, the simplest measure of centrality, is the best predictor of local richness and speciation, although it loses some of its predictive power as connectivity grows. Our framework shows how a simple neutral model can be combined with network theory to reveal complex relationships between speciation, richness, and the spatial organization of populations. PMID:22957181
Hager, Kevin W.; Fullerton, Heather; Butterfield, David A.; Moyer, Craig L.
2017-01-01
The Mariana region exhibits a rich array of hydrothermal venting conditions in a complex geological setting, which provides a natural laboratory to study the influence of local environmental conditions on microbial community structure as well as large-scale patterns in microbial biogeography. We used high-throughput amplicon sequencing of the bacterial small subunit (SSU) rRNA gene from 22 microbial mats collected from four hydrothermally active locations along the Mariana Arc and back-arc to explore the structure of lithotrophically-based microbial mat communities. The vent effluent was classified as iron- or sulfur-rich corresponding with two distinct community types, dominated by either Zetaproteobacteria or Epsilonproteobacteria, respectively. The Zetaproteobacterial-based communities had the highest richness and diversity, which supports the hypothesis that Zetaproteobacteria function as ecosystem engineers creating a physical habitat within a chemical environment promoting enhanced microbial diversity. Gammaproteobacteria were also high in abundance within the iron-dominated mats and some likely contribute to primary production. In addition, we also compare sampling scale, showing that bulk sampling of microbial mats yields higher diversity than micro-scale sampling. We present a comprehensive analysis and offer new insights into the community structure and diversity of lithotrophically-driven microbial mats from a hydrothermal region associated with high microbial biodiversity. Our study indicates an important functional role of for the Zetaproteobacteria altering the mat habitat and enhancing community interactions and complexity. PMID:28970817
Effects of Actinomycete Secondary Metabolites on Sediment Microbial Communities.
Patin, Nastassia V; Schorn, Michelle; Aguinaldo, Kristen; Lincecum, Tommie; Moore, Bradley S; Jensen, Paul R
2017-02-15
Marine sediments harbor complex microbial communities that remain poorly studied relative to other biomes such as seawater. Moreover, bacteria in these communities produce antibiotics and other bioactive secondary metabolites, yet little is known about how these compounds affect microbial community structure. In this study, we used next-generation amplicon sequencing to assess native microbial community composition in shallow tropical marine sediments. The results revealed complex communities comprised of largely uncultured taxa, with considerable spatial heterogeneity and known antibiotic producers comprising only a small fraction of the total diversity. Organic extracts from cultured strains of the sediment-dwelling actinomycete genus Salinispora were then used in mesocosm studies to address how secondary metabolites shape sediment community composition. We identified predatory bacteria and other taxa that were consistently reduced in the extract-treated mesocosms, suggesting that they may be the targets of allelopathic interactions. We tested related taxa for extract sensitivity and found general agreement with the culture-independent results. Conversely, several taxa were enriched in the extract-treated mesocosms, suggesting that some bacteria benefited from the interactions. The results provide evidence that bacterial secondary metabolites can have complex and significant effects on sediment microbial communities. Ocean sediments represent one of Earth's largest and most poorly studied biomes. These habitats are characterized by complex microbial communities where competition for space and nutrients can be intense. This study addressed the hypothesis that secondary metabolites produced by the sediment-inhabiting actinomycete Salinispora arenicola affect community composition and thus mediate interactions among competing microbes. Next-generation amplicon sequencing of mesocosm experiments revealed complex communities that shifted following exposure to S. arenicola extracts. The results reveal that certain predatory bacteria were consistently less abundant following exposure to extracts, suggesting that microbial metabolites mediate competitive interactions. Other taxa increased in relative abundance, suggesting a benefit from the extracts themselves or the resulting changes in the community. This study takes a first step toward assessing the impacts of bacterial metabolites on sediment microbial communities. The results provide insight into how low-abundance organisms may help structure microbial communities in ocean sediments. Copyright © 2017 American Society for Microbiology.
NASA Astrophysics Data System (ADS)
Schuler, Caleb G.; Havig, Jeff R.; Hamilton, Trinity L.
2017-11-01
Microbial communities in hydrothermal systems exist in a range of macroscopic morphologies including stromatolites, mats, and filaments. The architects of these structures are typically autotrophic, serving as primary producers. Structures attributed to microbial life have been documented in the rock record dating back to the Archean including recent reports of microbially-related structures in terrestrial hot springs that date back as far as 3.5 Ga. Microbial structures exhibit a range of complexity from filaments to more complex mats and stromatolites and the complexity impacts preservation potential. As a result, interpretation of these structures in the rock record relies on isotopic signatures in combination with overall morphology and paleoenvironmental setting. However, the relationships between morphology, microbial community composition, and primary productivity remain poorly constrained. To begin to address this gap, we examined community composition and carbon fixation in filaments, mats, and stromatolites from the Greater Obsidian Pool Area (GOPA) of the Mud Volcano Area, Yellowstone National Park, WY. We targeted morphologies dominated by bacterial phototrophs located in close proximity within the same pool which are exposed to similar geochemistry as well as bacterial mat, algal filament and chemotrophic filaments from nearby springs. Our results indicate i) natural abundance δ13C values of biomass from these features (-11.0 to -24.3 ‰) are similar to those found in the rock record; ii) carbon uptake rates of photoautotrophic communities is greater than chemoautotrophic; iii) oxygenic photosynthesis, anoxygenic photosynthesis, and chemoautotrophy often contribute to carbon fixation within the same morphology; and iv) increasing phototrophic biofilm complexity corresponds to a significant decrease in rates of carbon fixation—filaments had the highest uptake rates whereas carbon fixation by stromatolites was significantly lower. Our data highlight important differences in primary productivity between structures despite indistinguishable δ13C values of the biomass. Furthermore, low primary productivity by stromatolites compared to other structures underscores the need to consider a larger role for microbial mats and filaments in carbon fixation and O2 generation during the Archean and Proterozoic.
Ortega Cisneros, Kelly; Smit, Albertus J.; Laudien, Jürgen; Schoeman, David S.
2011-01-01
Sandy beach ecological theory states that physical features of the beach control macrobenthic community structure on all but the most dissipative beaches. However, few studies have simultaneously evaluated the relative importance of physical, chemical and biological factors as potential explanatory variables for meso-scale spatio-temporal patterns of intertidal community structure in these systems. Here, we investigate macroinfaunal community structure of a micro-tidal sandy beach that is located on an oligotrophic subtropical coast and is influenced by seasonal estuarine input. We repeatedly sampled biological and environmental variables at a series of beach transects arranged at increasing distances from the estuary mouth. Sampling took place over a period of five months, corresponding with the transition between the dry and wet season. This allowed assessment of biological-physical relationships across chemical and nutritional gradients associated with a range of estuarine inputs. Physical, chemical, and biological response variables, as well as measures of community structure, showed significant spatio-temporal patterns. In general, bivariate relationships between biological and environmental variables were rare and weak. However, multivariate correlation approaches identified a variety of environmental variables (i.e., sampling session, the C∶N ratio of particulate organic matter, dissolved inorganic nutrient concentrations, various size fractions of photopigment concentrations, salinity and, to a lesser extent, beach width and sediment kurtosis) that either alone or combined provided significant explanatory power for spatio-temporal patterns of macroinfaunal community structure. Overall, these results showed that the macrobenthic community on Mtunzini Beach was not structured primarily by physical factors, but instead by a complex and dynamic blend of nutritional, chemical and physical drivers. This emphasises the need to recognise ocean-exposed sandy beaches as functional ecosystems in their own right. PMID:21858213
Ortega Cisneros, Kelly; Smit, Albertus J; Laudien, Jürgen; Schoeman, David S
2011-01-01
Sandy beach ecological theory states that physical features of the beach control macrobenthic community structure on all but the most dissipative beaches. However, few studies have simultaneously evaluated the relative importance of physical, chemical and biological factors as potential explanatory variables for meso-scale spatio-temporal patterns of intertidal community structure in these systems. Here, we investigate macroinfaunal community structure of a micro-tidal sandy beach that is located on an oligotrophic subtropical coast and is influenced by seasonal estuarine input. We repeatedly sampled biological and environmental variables at a series of beach transects arranged at increasing distances from the estuary mouth. Sampling took place over a period of five months, corresponding with the transition between the dry and wet season. This allowed assessment of biological-physical relationships across chemical and nutritional gradients associated with a range of estuarine inputs. Physical, chemical, and biological response variables, as well as measures of community structure, showed significant spatio-temporal patterns. In general, bivariate relationships between biological and environmental variables were rare and weak. However, multivariate correlation approaches identified a variety of environmental variables (i.e., sampling session, the C∶N ratio of particulate organic matter, dissolved inorganic nutrient concentrations, various size fractions of photopigment concentrations, salinity and, to a lesser extent, beach width and sediment kurtosis) that either alone or combined provided significant explanatory power for spatio-temporal patterns of macroinfaunal community structure. Overall, these results showed that the macrobenthic community on Mtunzini Beach was not structured primarily by physical factors, but instead by a complex and dynamic blend of nutritional, chemical and physical drivers. This emphasises the need to recognise ocean-exposed sandy beaches as functional ecosystems in their own right.
Detecting and evaluating communities in complex human and biological networks
NASA Astrophysics Data System (ADS)
Morrison, Greg; Mahadevan, L.
2012-02-01
We develop a simple method for detecting the community structure in a network can by utilizing a measure of closeness between nodes. This approach readily leads to a method of coarse graining the network, which allows the detection of the natural hierarchy (or hierarchies) of community structure without appealing to an unknown resolution parameter. The closeness measure can also be used to evaluate the robustness of an individual node's assignment to its community (rather than evaluating only the quality of the global structure). Each of these methods in community detection and evaluation are illustrated using a variety of real world networks of either biological or sociological importance and illustrate the power and flexibility of the approach.
A clustering algorithm for determining community structure in complex networks
NASA Astrophysics Data System (ADS)
Jin, Hong; Yu, Wei; Li, ShiJun
2018-02-01
Clustering algorithms are attractive for the task of community detection in complex networks. DENCLUE is a representative density based clustering algorithm which has a firm mathematical basis and good clustering properties allowing for arbitrarily shaped clusters in high dimensional datasets. However, this method cannot be directly applied to community discovering due to its inability to deal with network data. Moreover, it requires a careful selection of the density parameter and the noise threshold. To solve these issues, a new community detection method is proposed in this paper. First, we use a spectral analysis technique to map the network data into a low dimensional Euclidean Space which can preserve node structural characteristics. Then, DENCLUE is applied to detect the communities in the network. A mathematical method named Sheather-Jones plug-in is chosen to select the density parameter which can describe the intrinsic clustering structure accurately. Moreover, every node on the network is meaningful so there were no noise nodes as a result the noise threshold can be ignored. We test our algorithm on both benchmark and real-life networks, and the results demonstrate the effectiveness of our algorithm over other popularity density based clustering algorithms adopted to community detection.
NASA Astrophysics Data System (ADS)
Fu, Yu-Hsiang; Huang, Chung-Yuan; Sun, Chuen-Tsai
2016-11-01
Using network community structures to identify multiple influential spreaders is an appropriate method for analyzing the dissemination of information, ideas and infectious diseases. For example, data on spreaders selected from groups of customers who make similar purchases may be used to advertise products and to optimize limited resource allocation. Other examples include community detection approaches aimed at identifying structures and groups in social or complex networks. However, determining the number of communities in a network remains a challenge. In this paper we describe our proposal for a two-phase evolutionary framework (TPEF) for determining community numbers and maximizing community modularity. Lancichinetti-Fortunato-Radicchi benchmark networks were used to test our proposed method and to analyze execution time, community structure quality, convergence, and the network spreading effect. Results indicate that our proposed TPEF generates satisfactory levels of community quality and convergence. They also suggest a need for an index, mechanism or sampling technique to determine whether a community detection approach should be used for selecting multiple network spreaders.
Opinion diversity and community formation in adaptive networks
NASA Astrophysics Data System (ADS)
Yu, Y.; Xiao, G.; Li, G.; Tay, W. P.; Teoh, H. F.
2017-10-01
It is interesting and of significant importance to investigate how network structures co-evolve with opinions. In this article, we show that, a simple model integrating consensus formation, link rewiring, and opinion change allows complex system dynamics to emerge, driving the system into a dynamic equilibrium with the co-existence of diversified opinions. Specifically, similar opinion holders may form into communities yet with no strict community consensus; and rather than being separated into disconnected communities, different communities are connected by a non-trivial proportion of inter-community links. More importantly, we show that the complex dynamics may lead to different numbers of communities at the steady state with a given tolerance between different opinion holders. We construct a framework for theoretically analyzing the co-evolution process. Theoretical analysis and extensive simulation results reveal some useful insights into the complex co-evolution process, including the formation of dynamic equilibrium, the transition between different steady states with different numbers of communities, and the dynamics between opinion distribution and network modularity.
Reverter, Miriam; Cutmore, Scott C; Bray, Rodney; Cribb, Thomas H; Sasal, Pierre
2016-10-01
We studied the monogenean communities of 34 species of butterflyfish from the tropical Indo-West Pacific, identifying 13 dactylogyrid species (including two species that are presently undescribed). Monogenean assemblages differed significantly between host species in terms of taxonomic structure, intensity and prevalence. Parasite richness ranged from 0 (Chaetodon lunulatus) to 11 (C. auriga, C. citrinellus and C. lunula). Host specificity varied between the dactylogyrids species, being found on 2-29 of the 34 chaetodontid species examined. Sympatric butterflyfish species were typically parasitized by different combinations of dactylogyrid species, suggesting the existence of complex host-parasite interactions. We identified six clusters of butterflyfish species based on the similarities of their dactylogyrid communities. Dactylogyrid richness and diversity were not related to host size, diet specialization, depth range or phylogeny of butterflyfish species. However, there was a weak positive correlation between monogenean richness and diversity and host geographical range. Most communities of dactylogyrids were dominated by Haliotrema aurigae and H. angelopterum, indicating the importance of the genus Haliotrema in shaping monogenean communities of butterflyfishes. This study casts light on the structure of the monogenean communities of butterflyfishes, suggesting that the diversity and complexity of community structures arises from a combination of host species-specific parameters.
Erika s. Svendsen; Lindsay K. Campbell
2008-01-01
Urban environmental stewardship activities are on the rise in cities throughout the Northeast. Groups participating in stewardship activities range in age, size, and geography and represent an increasingly complex and dynamic arrangement of civil society, government and business sectors. To better understand the structure, function and network of these community-based...
Interactive effects of live coral and structural complexity on the recruitment of reef fishes
NASA Astrophysics Data System (ADS)
Coker, D. J.; Graham, N. A. J.; Pratchett, M. S.
2012-12-01
Corals reefs are subjected to multiple disturbances that modify levels of coral cover and structural complexity of the reef matrix, and in turn influence the structure of associated fish communities. With disturbances predicted to increase, insight into how changes in substrate condition will influence the recruitment of many fishes is essential for understanding the recovery of reef fish populations following biological and physical disturbances. While studies have revealed that both live coral cover and structural complexity are important for many fishes, there is a lack of understanding regarding how a combination of these changes will impact the recruitment of fishes. This study used experimentally constructed patch reefs consisting of six different habitat treatments; three levels of live coral cover (high, medium, low) crossed with two levels of structural complexity (high, low), to test the independent and combined effects of live coral cover and structural complexity on the recruitment and recovery of fish communities. The abundance and species diversity of fishes varied significantly among the six habitat treatments, but differences were not clearly associated with either coral cover or structural complexity and varied through time. More striking, however, was a significant difference in the composition of fish assemblages among treatments, due mostly to disproportionate abundance of coral-dwelling fishes on high coral cover, high complexity reefs. Overall, it appears that coral cover had a more important influence than structural complexity, at least for the contrasting levels of structural complexity achieved on experimental patch reefs. Furthermore, we found that live coral cover is important for the recruitment of some non-coral-dependent fishes. This study confirms that live coral cover is critical for the maintenance of high biodiversity on tropical coral reefs, and that sustained and ongoing declines in coral cover will adversely affect recruitment for many different species of reef fishes.
Network Community Detection based on the Physarum-inspired Computational Framework.
Gao, Chao; Liang, Mingxin; Li, Xianghua; Zhang, Zili; Wang, Zhen; Zhou, Zhili
2016-12-13
Community detection is a crucial and essential problem in the structure analytics of complex networks, which can help us understand and predict the characteristics and functions of complex networks. Many methods, ranging from the optimization-based algorithms to the heuristic-based algorithms, have been proposed for solving such a problem. Due to the inherent complexity of identifying network structure, how to design an effective algorithm with a higher accuracy and a lower computational cost still remains an open problem. Inspired by the computational capability and positive feedback mechanism in the wake of foraging process of Physarum, which is a large amoeba-like cell consisting of a dendritic network of tube-like pseudopodia, a general Physarum-based computational framework for community detection is proposed in this paper. Based on the proposed framework, the inter-community edges can be identified from the intra-community edges in a network and the positive feedback of solving process in an algorithm can be further enhanced, which are used to improve the efficiency of original optimization-based and heuristic-based community detection algorithms, respectively. Some typical algorithms (e.g., genetic algorithm, ant colony optimization algorithm, and Markov clustering algorithm) and real-world datasets have been used to estimate the efficiency of our proposed computational framework. Experiments show that the algorithms optimized by Physarum-inspired computational framework perform better than the original ones, in terms of accuracy and computational cost. Moreover, a computational complexity analysis verifies the scalability of our framework.
NASA Astrophysics Data System (ADS)
Duris, J. W.; Rossbach, S.; Atekwana, E. A.; Werkema, D., Jr.
2003-04-01
Little is known about the complex interactions between microbial communities and electrical properties in contaminated aquifers. In order to investigate possible connections between these parameters a study was undertaken to investigate the hypothesis that the degradation of hydrocarbons by resident microbial communities causes a local increase in organic acid concentrations, which in turn cause an increase in native mineral weathering and a concurrent increase in the bulk electrical conductivity of soil. Microbial community structure was analyzed using a 96-well most probable number (MPN) method and rDNA intergenic spacer region analysis (RISA). Microbial community structure was found to change in the presence of hydrocarbon contaminants and these changes were consistently observed in regions of high electrical conductivity. We infer from this relationship that geophysical methods for monitoring the subsurface are a promising new technology for monitoring changes in microbial community structure and simultaneous changes in geochemistry that are associated with hydrocarbon degradation.
NASA Astrophysics Data System (ADS)
Ruitton, S.; Francour, P.; Boudouresque, C. F.
2000-02-01
In situ surveys were used to examine the contribution of benthic herbivorous invertebrates and fishes to the organization of Mediterranean rocky sublittoral communities. Shallow (1-3 m) and deep (6-8 m) sampling sites, in natural areas and on man-made structures, were characterized by a structural complexity index (cavity index and mean size of cavity aperture), algal cover (encrusting, turfy, shrubby and arborescent algae) and the density of benthic herbivorous invertebrates and fish. A relationship between structural complexity and biota was only evident for some fish species ( Diplodus spp. and Sarpa salpa) at deep sites, where they not only feed but also shelter. Three benthic herbivorous invertebrates, the sea urchins Paracentrotus lividus and Arbacia lixula, and the limpet Patella caerulea , are associated with communities dominated by encrusting algae. Variations in their abundance and role in structuring algal communities follow a depth gradient: P. caerulea and A. lixula are mainly present at shallow sites and P. lividus at deep sites. These benthic herbivorous invertebrates may account for the structure of shallow algal communities. In contrast, at deep sites, fishes (the omnivorous Diplodus spp. and the herbivorous S. salpa) have a potential importance in controlling sublittoral algae, in addition to invertebrates. It is suggested that the ecological impact of herbivorous and omnivorous fishes in temperate seas could be greater than is generally thought. Experiments should be designed to validate this postulate.
Locating Structural Centers: A Density-Based Clustering Method for Community Detection
Liu, Gongshen; Li, Jianhua; Nees, Jan P.
2017-01-01
Uncovering underlying community structures in complex networks has received considerable attention because of its importance in understanding structural attributes and group characteristics of networks. The algorithmic identification of such structures is a significant challenge. Local expanding methods have proven to be efficient and effective in community detection, but most methods are sensitive to initial seeds and built-in parameters. In this paper, we present a local expansion method by density-based clustering, which aims to uncover the intrinsic network communities by locating the structural centers of communities based on a proposed structural centrality. The structural centrality takes into account local density of nodes and relative distance between nodes. The proposed algorithm expands a community from the structural center to the border with a single local search procedure. The local expanding procedure follows a heuristic strategy as allowing it to find complete community structures. Moreover, it can identify different node roles (cores and outliers) in communities by defining a border region. The experiments involve both on real-world and artificial networks, and give a comparison view to evaluate the proposed method. The result of these experiments shows that the proposed method performs more efficiently with a comparative clustering performance than current state of the art methods. PMID:28046030
Ubiquitousness of link-density and link-pattern communities in real-world networks
NASA Astrophysics Data System (ADS)
Šubelj, L.; Bajec, M.
2012-01-01
Community structure appears to be an intrinsic property of many complex real-world networks. However, recent work shows that real-world networks reveal even more sophisticated modules than classical cohesive (link-density) communities. In particular, networks can also be naturally partitioned according to similar patterns of connectedness among the nodes, revealing link-pattern communities. We here propose a propagation based algorithm that can extract both link-density and link-pattern communities, without any prior knowledge of the true structure. The algorithm was first validated on different classes of synthetic benchmark networks with community structure, and also on random networks. We have further applied the algorithm to different social, information, technological and biological networks, where it indeed reveals meaningful (composites of) link-density and link-pattern communities. The results thus seem to imply that, similarly as link-density counterparts, link-pattern communities appear ubiquitous in nature and design.
COMMUNITY LEVEL ANALYSIS OF VECTOR-BORNE DISEASE
Ecological community structure is particularly important in vector-borne zoonotic diseases with complex life cycles. Single population models, such as the so-called Ross-Macdonald model (Baily, 1982), have been important in developing and characterizing our current understanding...
Diversity, structure and convergent evolution of the global sponge microbiome
Thomas, Torsten; Moitinho-Silva, Lucas; Lurgi, Miguel; Björk, Johannes R.; Easson, Cole; Astudillo-García, Carmen; Olson, Julie B.; Erwin, Patrick M.; López-Legentil, Susanna; Luter, Heidi; Chaves-Fonnegra, Andia; Costa, Rodrigo; Schupp, Peter J.; Steindler, Laura; Erpenbeck, Dirk; Gilbert, Jack; Knight, Rob; Ackermann, Gail; Victor Lopez, Jose; Taylor, Michael W.; Thacker, Robert W.; Montoya, Jose M.; Hentschel, Ute; Webster, Nicole S.
2016-01-01
Sponges (phylum Porifera) are early-diverging metazoa renowned for establishing complex microbial symbioses. Here we present a global Porifera microbiome survey, set out to establish the ecological and evolutionary drivers of these host–microbe interactions. We show that sponges are a reservoir of exceptional microbial diversity and major contributors to the total microbial diversity of the world's oceans. Little commonality in species composition or structure is evident across the phylum, although symbiont communities are characterized by specialists and generalists rather than opportunists. Core sponge microbiomes are stable and characterized by generalist symbionts exhibiting amensal and/or commensal interactions. Symbionts that are phylogenetically unique to sponges do not disproportionally contribute to the core microbiome, and host phylogeny impacts complexity rather than composition of the symbiont community. Our findings support a model of independent assembly and evolution in symbiont communities across the entire host phylum, with convergent forces resulting in analogous community organization and interactions. PMID:27306690
M. Case; C.B. Halpern; S.A. Levin
2013-01-01
Pocket gophers (Geomyidae) are major agents of disturbance in North American grasslands. Gopher mounds bury existing plants and influence community structure through various mechanisms. However, in mountain meadows that experience winter snowpack, gophers also create winter castings, smaller tube-shaped deposits, previously ignored in studies of plantâgopher...
A variable circular-plot method for estimating bird numbers
R. T. Reynolds; J. M. Scott; R. A. Nussbaum
1980-01-01
A bird census method is presented that is designed for tall, structurally complex vegetation types, and rugged terrain. With this method the observer counts all birds seen or heard around a station, and estimates the horizontal distance from the station to each bird. Count periods at stations vary according to the avian community and structural complexity of the...
Discrete particle swarm optimization for identifying community structures in signed social networks.
Cai, Qing; Gong, Maoguo; Shen, Bo; Ma, Lijia; Jiao, Licheng
2014-10-01
Modern science of networks has facilitated us with enormous convenience to the understanding of complex systems. Community structure is believed to be one of the notable features of complex networks representing real complicated systems. Very often, uncovering community structures in networks can be regarded as an optimization problem, thus, many evolutionary algorithms based approaches have been put forward. Particle swarm optimization (PSO) is an artificial intelligent algorithm originated from social behavior such as birds flocking and fish schooling. PSO has been proved to be an effective optimization technique. However, PSO was originally designed for continuous optimization which confounds its applications to discrete contexts. In this paper, a novel discrete PSO algorithm is suggested for identifying community structures in signed networks. In the suggested method, particles' status has been redesigned in discrete form so as to make PSO proper for discrete scenarios, and particles' updating rules have been reformulated by making use of the topology of the signed network. Extensive experiments compared with three state-of-the-art approaches on both synthetic and real-world signed networks demonstrate that the proposed method is effective and promising. Copyright © 2014 Elsevier Ltd. All rights reserved.
Effect of copper sulphate treatment on natural phytoplanktonic communities.
Le Jeune, Anne-Hélène; Charpin, Marie; Deluchat, Véronique; Briand, Jean-François; Lenain, Jean-François; Baudu, Michel; Amblard, Christian
2006-12-01
Copper sulphate treatment is widely used as a global and empirical method to remove or control phytoplankton blooms without precise description of the impact on phytoplanktonic populations. The effects of two copper sulphate treatments on natural phytoplanktonic communities sampled in the spring and summer seasons, were assessed by indoor mesocosm experiments. The initial copper-complexing capacity of each water sample was evaluated before each treatment. The copper concentrations applied were 80 microg l(-1) and 160 microg l(-1) of copper, below and above the water complexation capacity, respectively. The phytoplanktonic biomass recovered within a few days after treatment. The highest copper concentration, which generated a highly toxic environment, caused a global decrease in phytoplankton diversity, and led to the development and dominance of nanophytoplanktonic Chlorophyceae. In mesocosms treated with 80 microg l(-1) of copper, the effect on phytoplanktonic community size-class structure and composition was dependent on seasonal variation. This could be related to differences in community composition, and thus to species sensitivity to copper and to differences in copper bioavailability between spring and summer. Both treatments significantly affected cyanobacterial biomass and caused changes in the size-class structure and composition of phytoplanktonic communities which may imply modifications of the ecosystem structure and function.
Mesoscopic Community Structure of Financial Markets Revealed by Price and Sign Fluctuations.
Almog, Assaf; Besamusca, Ferry; MacMahon, Mel; Garlaschelli, Diego
2015-01-01
The mesoscopic organization of complex systems, from financial markets to the brain, is an intermediate between the microscopic dynamics of individual units (stocks or neurons, in the mentioned cases), and the macroscopic dynamics of the system as a whole. The organization is determined by "communities" of units whose dynamics, represented by time series of activity, is more strongly correlated internally than with the rest of the system. Recent studies have shown that the binary projections of various financial and neural time series exhibit nontrivial dynamical features that resemble those of the original data. This implies that a significant piece of information is encoded into the binary projection (i.e. the sign) of such increments. Here, we explore whether the binary signatures of multiple time series can replicate the same complex community organization of the financial market, as the original weighted time series. We adopt a method that has been specifically designed to detect communities from cross-correlation matrices of time series data. Our analysis shows that the simpler binary representation leads to a community structure that is almost identical with that obtained using the full weighted representation. These results confirm that binary projections of financial time series contain significant structural information.
O'Sullivan, Tracey L; Kuziemsky, Craig E; Toal-Sullivan, Darene; Corneil, Wayne
2013-09-01
Complexity is a useful frame of reference for disaster management and understanding population health. An important means to unraveling the complexities of disaster management is to recognize the interdependencies between health care and broader social systems and how they intersect to promote health and resilience before, during and after a crisis. While recent literature has expanded our understanding of the complexity of disasters at the macro level, few studies have examined empirically how dynamic elements of critical social infrastructure at the micro level influence community capacity. The purpose of this study was to explore empirically the complexity of disasters, to determine levers for action where interventions can be used to facilitate collaborative action and promote health among high risk populations. A second purpose was to build a framework for critical social infrastructure and develop a model to identify potential points of intervention to promote population health and resilience. A community-based participatory research design was used in nine focus group consultations (n = 143) held in five communities in Canada, between October 2010 and March 2011, using the Structured Interview Matrix facilitation technique. The findings underscore the importance of interconnectedness of hard and soft systems at the micro level, with culture providing the backdrop for the social fabric of each community. Open coding drawing upon the tenets of complexity theory was used to develop four core themes that provide structure for the framework that evolved; they relate to dynamic context, situational awareness and connectedness, flexible planning, and collaboration, which are needed to foster adaptive responses to disasters. Seven action recommendations are presented, to promote community resilience and population health. Copyright © 2012 Elsevier Ltd. All rights reserved.
Schools and Neighborhood-Based Collaboration: Structural Resistances and Realities.
ERIC Educational Resources Information Center
Smithmier, Angela
Community-based interagency collaboration among schools and other public service agencies is one reform idea for addressing the complex conditions of children with a high level of needs. This paper presents findings of a study that explored the workings of one community-based collaboration, referred to as the Community-Based Collaboration for…
NASA Astrophysics Data System (ADS)
Oliveira, Micael
The CECAM Electronic Structure Library (ESL) is a community-driven effort to segregate shared pieces of software as libraries that could be contributed and used by the community. Besides allowing to share the burden of developing and maintaining complex pieces of software, these can also become a target for re-coding by software engineers as hardware evolves, ensuring that electronic structure codes remain at the forefront of HPC trends. In a series of workshops hosted at the CECAM HQ in Lausanne, the tools and infrastructure for the project were prepared, and the first contributions were included and made available online (http://esl.cecam.org). In this talk I will present the different aspects and aims of the ESL and how these can be useful for the electronic structure community.
NASA Astrophysics Data System (ADS)
Zhuo, Zhao; Cai, Shi-Min; Tang, Ming; Lai, Ying-Cheng
2018-04-01
One of the most challenging problems in network science is to accurately detect communities at distinct hierarchical scales. Most existing methods are based on structural analysis and manipulation, which are NP-hard. We articulate an alternative, dynamical evolution-based approach to the problem. The basic principle is to computationally implement a nonlinear dynamical process on all nodes in the network with a general coupling scheme, creating a networked dynamical system. Under a proper system setting and with an adjustable control parameter, the community structure of the network would "come out" or emerge naturally from the dynamical evolution of the system. As the control parameter is systematically varied, the community hierarchies at different scales can be revealed. As a concrete example of this general principle, we exploit clustered synchronization as a dynamical mechanism through which the hierarchical community structure can be uncovered. In particular, for quite arbitrary choices of the nonlinear nodal dynamics and coupling scheme, decreasing the coupling parameter from the global synchronization regime, in which the dynamical states of all nodes are perfectly synchronized, can lead to a weaker type of synchronization organized as clusters. We demonstrate the existence of optimal choices of the coupling parameter for which the synchronization clusters encode accurate information about the hierarchical community structure of the network. We test and validate our method using a standard class of benchmark modular networks with two distinct hierarchies of communities and a number of empirical networks arising from the real world. Our method is computationally extremely efficient, eliminating completely the NP-hard difficulty associated with previous methods. The basic principle of exploiting dynamical evolution to uncover hidden community organizations at different scales represents a "game-change" type of approach to addressing the problem of community detection in complex networks.
Binzer, Amrei; Guill, Christian; Rall, Björn C; Brose, Ulrich
2016-01-01
Warming and eutrophication are two of the most important global change stressors for natural ecosystems, but their interaction is poorly understood. We used a dynamic model of complex, size-structured food webs to assess interactive effects on diversity and network structure. We found antagonistic impacts: Warming increases diversity in eutrophic systems and decreases it in oligotrophic systems. These effects interact with the community size structure: Communities of similarly sized species such as parasitoid-host systems are stabilized by warming and destabilized by eutrophication, whereas the diversity of size-structured predator-prey networks decreases strongly with warming, but decreases only weakly with eutrophication. Nonrandom extinction risks for generalists and specialists lead to higher connectance in networks without size structure and lower connectance in size-structured communities. Overall, our results unravel interactive impacts of warming and eutrophication and suggest that size structure may serve as an important proxy for predicting the community sensitivity to these global change stressors. © 2015 John Wiley & Sons Ltd.
Network community structure and loop coefficient method
NASA Astrophysics Data System (ADS)
Vragović, I.; Louis, E.
2006-07-01
A modular structure, in which groups of tightly connected nodes could be resolved as separate entities, is a property that can be found in many complex networks. In this paper, we propose a algorithm for identifying communities in networks. It is based on a local measure, so-called loop coefficient that is a generalization of the clustering coefficient. Nodes with a large loop coefficient tend to be core inner community nodes, while other vertices are usually peripheral sites at the borders of communities. Our method gives satisfactory results for both artificial and real-world graphs, if they have a relatively pronounced modular structure. This type of algorithm could open a way of interpreting the role of nodes in communities in terms of the local loop coefficient, and could be used as a complement to other methods.
Hierarchical sequencing of online social graphs
NASA Astrophysics Data System (ADS)
Andjelković, Miroslav; Tadić, Bosiljka; Maletić, Slobodan; Rajković, Milan
2015-10-01
In online communications, patterns of conduct of individual actors and use of emotions in the process can lead to a complex social graph exhibiting multilayered structure and mesoscopic communities. Using simplicial complexes representation of graphs, we investigate in-depth topology of the online social network constructed from MySpace dialogs which exhibits original community structure. A simulation of emotion spreading in this network leads to the identification of two emotion-propagating layers. Three topological measures are introduced, referred to as the structure vectors, which quantify graph's architecture at different dimension levels. Notably, structures emerging through shared links, triangles and tetrahedral faces, frequently occur and range from tree-like to maximal 5-cliques and their respective complexes. On the other hand, the structures which spread only negative or only positive emotion messages appear to have much simpler topology consisting of links and triangles. The node's structure vector represents the number of simplices at each topology level in which the node resides and the total number of such simplices determines what we define as the node's topological dimension. The presented results suggest that the node's topological dimension provides a suitable measure of the social capital which measures the actor's ability to act as a broker in compact communities, the so called Simmelian brokerage. We also generalize the results to a wider class of computer-generated networks. Investigating components of the node's vector over network layers reveals that same nodes develop different socio-emotional relations and that the influential nodes build social capital by combining their connections in different layers.
BridgeRank: A novel fast centrality measure based on local structure of the network
NASA Astrophysics Data System (ADS)
Salavati, Chiman; Abdollahpouri, Alireza; Manbari, Zhaleh
2018-04-01
Ranking nodes in complex networks have become an important task in many application domains. In a complex network, influential nodes are those that have the most spreading ability. Thus, identifying influential nodes based on their spreading ability is a fundamental task in different applications such as viral marketing. One of the most important centrality measures to ranking nodes is closeness centrality which is efficient but suffers from high computational complexity O(n3) . This paper tries to improve closeness centrality by utilizing the local structure of nodes and presents a new ranking algorithm, called BridgeRank centrality. The proposed method computes local centrality value for each node. For this purpose, at first, communities are detected and the relationship between communities is completely ignored. Then, by applying a centrality in each community, only one best critical node from each community is extracted. Finally, the nodes are ranked based on computing the sum of the shortest path length of nodes to obtained critical nodes. We have also modified the proposed method by weighting the original BridgeRank and selecting several nodes from each community based on the density of that community. Our method can find the best nodes with high spread ability and low time complexity, which make it applicable to large-scale networks. To evaluate the performance of the proposed method, we use the SIR diffusion model. Finally, experiments on real and artificial networks show that our method is able to identify influential nodes so efficiently, and achieves better performance compared to other recent methods.
Warming alters community size structure and ecosystem functioning
Dossena, Matteo; Yvon-Durocher, Gabriel; Grey, Jonathan; Montoya, José M.; Perkins, Daniel M.; Trimmer, Mark; Woodward, Guy
2012-01-01
Global warming can affect all levels of biological complexity, though we currently understand least about its potential impact on communities and ecosystems. At the ecosystem level, warming has the capacity to alter the structure of communities and the rates of key ecosystem processes they mediate. Here we assessed the effects of a 4°C rise in temperature on the size structure and taxonomic composition of benthic communities in aquatic mesocosms, and the rates of detrital decomposition they mediated. Warming had no effect on biodiversity, but altered community size structure in two ways. In spring, warmer systems exhibited steeper size spectra driven by declines in total community biomass and the proportion of large organisms. By contrast, in autumn, warmer systems had shallower size spectra driven by elevated total community biomass and a greater proportion of large organisms. Community-level shifts were mirrored by changes in decomposition rates. Temperature-corrected microbial and macrofaunal decomposition rates reflected the shifts in community structure and were strongly correlated with biomass across mesocosms. Our study demonstrates that the 4°C rise in temperature expected by the end of the century has the potential to alter the structure and functioning of aquatic ecosystems profoundly, as well as the intimate linkages between these levels of ecological organization. PMID:22496185
Eddie L. Shea; Lisa A. Schulte; Brian J. Palik
2017-01-01
Structural complexity is widely recognized as an inherent characteristic of unmanaged forests critical to their function and resilience, but often reduced in their managed counterparts. Variable retention harvesting (VRH) has been proposed as a way to restore or enhance structural complexity in managed forests, and thereby sustain attendant biodiversity and ecosystem...
Adaptive multi-resolution Modularity for detecting communities in networks
NASA Astrophysics Data System (ADS)
Chen, Shi; Wang, Zhi-Zhong; Bao, Mei-Hua; Tang, Liang; Zhou, Ji; Xiang, Ju; Li, Jian-Ming; Yi, Chen-He
2018-02-01
Community structure is a common topological property of complex networks, which attracted much attention from various fields. Optimizing quality functions for community structures is a kind of popular strategy for community detection, such as Modularity optimization. Here, we introduce a general definition of Modularity, by which several classical (multi-resolution) Modularity can be derived, and then propose a kind of adaptive (multi-resolution) Modularity that can combine the advantages of different Modularity. By applying the Modularity to various synthetic and real-world networks, we study the behaviors of the methods, showing the validity and advantages of the multi-resolution Modularity in community detection. The adaptive Modularity, as a kind of multi-resolution method, can naturally solve the first-type limit of Modularity and detect communities at different scales; it can quicken the disconnecting of communities and delay the breakup of communities in heterogeneous networks; and thus it is expected to generate the stable community structures in networks more effectively and have stronger tolerance against the second-type limit of Modularity.
How Community Has Shaped the Protein Data Bank
Berman, Helen M.; Kleywegt, Gerard J.; Nakamura, Haruki; Markley, John L.
2015-01-01
Following several years of community discussion, the Protein Data Bank (PDB) was established in 1971 as a public repository for the coordinates of three-dimensional models of biological macromolecules. Since then, the number, size, and complexity of structural models have continued to grow, reflecting the productivity of structural biology. Managed by the Worldwide PDB organization, the PDB has been able to meet increasing demands for the quantity of structural information and of quality. In addition to providing unrestricted access to structural information, the PDB also works to promote data standards and to raise the profile of structural biology with broader audiences. In this perspective, we describe the history of PDB and the many ways in which the community continues to shape the archive. PMID:24010707
Yamamoto, Shuji; Suzuki, Kei; Araki, Yoko; Mochihara, Hiroki; Hosokawa, Tetsuya; Kubota, Hiroko; Chiba, Yusuke; Rubaba, Owen; Tashiro, Yosuke; Futamata, Hiroyuki
2014-01-01
The relationship between the bacterial communities in anolyte and anode biofilms and the electrochemical properties of microbial fuel cells (MFCs) was investigated when a complex organic waste-decomposing solution was continuously supplied to MFCs as an electron donor. The current density increased gradually and was maintained at approximately 100 to 150 mA m−2. Polarization curve analyses revealed that the maximum power density was 7.4 W m−3 with an internal resistance of 110 Ω. Bacterial community structures in the organic waste-decomposing solution and MFCs differed from each other. Clonal analyses targeting 16S rRNA genes indicated that bacterial communities in the biofilms on MFCs developed to specific communities dominated by novel Geobacter. Multidimensional scaling analyses based on DGGE profiles revealed that bacterial communities in the organic waste-decomposing solution fluctuated and had no dynamic equilibrium. Bacterial communities on the anolyte in MFCs had a dynamic equilibrium with fluctuations, while those of the biofilm converged to the Geobacter-dominated structure. These bacterial community dynamics of MFCs differed from those of control-MFCs under open circuit conditions. These results suggested that bacterial communities in the anolyte and biofilm have a gentle symbiotic system through electron flow, which resulted in the advance of current density from complex organic waste. PMID:24789988
Yamamoto, Shuji; Suzuki, Kei; Araki, Yoko; Mochihara, Hiroki; Hosokawa, Tetsuya; Kubota, Hiroko; Chiba, Yusuke; Rubaba, Owen; Tashiro, Yosuke; Futamata, Hiroyuki
2014-01-01
The relationship between the bacterial communities in anolyte and anode biofilms and the electrochemical properties of microbial fuel cells (MFCs) was investigated when a complex organic waste-decomposing solution was continuously supplied to MFCs as an electron donor. The current density increased gradually and was maintained at approximately 100 to 150 mA m(-2). Polarization curve analyses revealed that the maximum power density was 7.4 W m(-3) with an internal resistance of 110 Ω. Bacterial community structures in the organic waste-decomposing solution and MFCs differed from each other. Clonal analyses targeting 16S rRNA genes indicated that bacterial communities in the biofilms on MFCs developed to specific communities dominated by novel Geobacter. Multidimensional scaling analyses based on DGGE profiles revealed that bacterial communities in the organic waste-decomposing solution fluctuated and had no dynamic equilibrium. Bacterial communities on the anolyte in MFCs had a dynamic equilibrium with fluctuations, while those of the biofilm converged to the Geobacter-dominated structure. These bacterial community dynamics of MFCs differed from those of control-MFCs under open circuit conditions. These results suggested that bacterial communities in the anolyte and biofilm have a gentle symbiotic system through electron flow, which resulted in the advance of current density from complex organic waste.
Rusch, Adrien; Birkhofer, Klaus; Bommarco, Riccardo; Smith, Henrik G; Ekbom, Barbara
2014-07-01
Agricultural intensification is recognised as a major driver of biodiversity loss in human-modified landscapes. Several agro-environmental measures at different spatial scales have been suggested to mitigate the negative impact of intensification on biodiversity and ecosystem services. The effect of these measures on the functional structure of service-providing communities remains, however, largely unexplored. Using two distinct landscape designs, we examined how the management options of organic farming at the field scale and crop diversification at the landscape level affect the taxonomic and functional structure of generalist predator communities and how these effects vary along a landscape complexity gradient. Organic farming as well as landscapes with longer and more diversified crop rotations enhanced the activity-density of spiders and rove beetles, but not the species richness or evenness. Our results indicate that the two management options affected the functional composition of communities, as they primarily enhanced the activity-density of functionally similar species. The two management options increased the functional similarity between spider species in regards to hunting mode and habitat preference. Organic farming enhanced the functional similarity of rove beetles. Management options at field and landscape levels were generally more important predictors of community structure when compared to landscape complexity. Our study highlights the importance of considering the functional composition of generalist predators in order to understand how agro-environmental measures at various scales shape community assemblages and ecosystem functioning in agricultural landscapes.
Emergence of a learning community: a transforming experience at the boundaries
NASA Astrophysics Data System (ADS)
Raia, Federica
2013-03-01
I narrate a process of transformation, a professional and personal journey framed by an experience that captured my attention shaping my interpretation and reflections. From a critical complexity framework I discuss the emergence of a learning community from the cooperation among individuals of diverse social and cultural worlds sharing the need to change a traditional professional development program structure and develop a new science education Masters Degree/Certification program. I zoom into the continual redefinition of the community, its evolution and complex interrelations among its participants and the emergence of a learning community as a boundary space having an emancipatory role and allowing growth and learning. I analyze the dialectical relationship between agents' behavior either impeding growth or having an emancipatory function of a mindful RelationalAct in a complex adaptive system framework.
NASA Astrophysics Data System (ADS)
Jiang, Shengqin; Lu, Xiaobo; Cai, Guoliang; Cai, Shuiming
2017-12-01
This paper focuses on the cluster synchronisation problem of coupled complex networks with uncertain disturbances under an adaptive fixed-time control strategy. To begin with, complex dynamical networks with community structure which are subject to uncertain disturbances are taken into account. Then, a novel adaptive control strategy combined with fixed-time techniques is proposed to guarantee the nodes in the communities to desired states in a settling time. In addition, the stability of complex error systems is theoretically proved based on Lyapunov stability theorem. At last, two examples are presented to verify the effectiveness of the proposed adaptive fixed-time control.
USDA-ARS?s Scientific Manuscript database
Dynamics of seasonal microbial community compositions in algae cultivation ponds are complex. There is very limited knowledge on community compositions that may play significant roles in the bioconversion of manure nu¬trients to animal feed. Algae production is an alternative where land area for pro...
Organizing for Change: A Case Study of Grassroots Leadership at a Kentucky Community College
ERIC Educational Resources Information Center
Borregard, Andrea Rae
2016-01-01
Community colleges constitute a special type of higher education organization: their complex mission, dynamics, personnel structures, and values require a distinct set of understandings and skills to lead and manage them well. Most of the research on leadership in community colleges focuses on leaders in positions of power (presidents, provosts,…
Emergence of structured communities through evolutionary dynamics.
Shtilerman, Elad; Kessler, David A; Shnerb, Nadav M
2015-10-21
Species-rich communities, in which many competing species coexist in a single trophic level, are quite frequent in nature, but pose a formidable theoretical challenge. In particular, it is known that complex competitive systems become unstable and unfeasible when the number of species is large. Recently, many studies have attributed the stability of natural communities to the structure of the interspecific interaction network, yet the nature of such structures and the underlying mechanisms responsible for them remain open questions. Here we introduce an evolutionary model, based on the generic Lotka-Volterra competitive framework, from which a stable, structured, diverse community emerges spontaneously. The modular structure of the competition matrix reflects the phylogeny of the community, in agreement with the hierarchial taxonomic classification. Closely related species tend to have stronger niche overlap and weaker fitness differences, as opposed to pairs of species from different modules. The competitive-relatedness hypothesis and the idea of emergent neutrality are discussed in the context of this evolutionary model. Copyright © 2015 Elsevier Ltd. All rights reserved.
Vendian cyanobacterial communities as a preservation factor of fossil eucaryotic algal remains
NASA Astrophysics Data System (ADS)
Leonov, M. V.
2003-01-01
A new fossil complex of organic micro-organisms from Upper Vendian deposits of Mezen syneclise is described. This complex consists of cyanobacterial mat fragments represented by taxa Leiotrichoides tipicus Hermannn, 1974 and Palaeolyngbya aff. catenata Hermann, 1974. On the surface of this communities were found remains of cord-like thalli Eoholynia mosquensis Gnilovskaya, 1975. They may be referred to the eucaryotic algae with parenchimatous type of tallus structure. The phytoleims of megascopic probably eucaryotic algae were also found jointly with organic biofilms. Their type of preservation was determinated by this burial with the organic biofilms produced by cyanobacterial communities.
Little is known about the complex interactions between microbial communities and electrical properties in contaminated aquifers. In order to investigate possible connections between these parameters a study was undertaken to investigate the hypothesis that the degradation of hydr...
Enhanced biodiversity beyond marine reserve boundaries: the cup spillith over.
Russ, Garry R; Alcala, Angel C
2011-01-01
Overfishing can have detrimental effects on marine biodiversity and the structure of marine ecosystems. No-take marine reserves (NTMRs) are much advocated as a means of protecting biodiversity and ecosystem structure from overharvest. In contrast to terrestrial protected areas, NTMRs are not only expected to conserve or recover biodiversity and ecosystems within their boundaries, but also to enhance biodiversity beyond their boundaries by exporting species richness and more complex biological communities. Here we show that species richness of large predatory reef fish increased fourfold and 11-fold inside two Philippine no-take marine reserves over 14 and 25 years, respectively. Outside one reserve (Apo) the species richness also increased. This increase beyond the Apo reserve boundary was 78% higher closer to the boundary (200-250 m) than farther from it (250-500 m). The increase in richness beyond the boundary could not be explained by improvements over time in habitat or prey availability. Furthermore, community composition of predatory fish outside but close to (200-250 m) the Apo reserve became very similar to that inside the reserve over time, almost converging with it in multivariate space after 26 years of reserve protection. This is consistent with the suggestion that, as community composition inside Apo reserve increased in complexity, this complexity spilled over the boundary into nearby fished areas. Clearly, the spillover of species richness and community complexity is a direct consequence of the spillover of abundance of multiple species. However, this spillover of species richness and community complexity demonstrates an important benefit of biodiversity and ecosystem export from reserves, and it provides hope that reserves can help to reverse the decline of marine ecosystems and biodiversity.
The BioPlex Network: A Systematic Exploration of the Human Interactome.
Huttlin, Edward L; Ting, Lily; Bruckner, Raphael J; Gebreab, Fana; Gygi, Melanie P; Szpyt, John; Tam, Stanley; Zarraga, Gabriela; Colby, Greg; Baltier, Kurt; Dong, Rui; Guarani, Virginia; Vaites, Laura Pontano; Ordureau, Alban; Rad, Ramin; Erickson, Brian K; Wühr, Martin; Chick, Joel; Zhai, Bo; Kolippakkam, Deepak; Mintseris, Julian; Obar, Robert A; Harris, Tim; Artavanis-Tsakonas, Spyros; Sowa, Mathew E; De Camilli, Pietro; Paulo, Joao A; Harper, J Wade; Gygi, Steven P
2015-07-16
Protein interactions form a network whose structure drives cellular function and whose organization informs biological inquiry. Using high-throughput affinity-purification mass spectrometry, we identify interacting partners for 2,594 human proteins in HEK293T cells. The resulting network (BioPlex) contains 23,744 interactions among 7,668 proteins with 86% previously undocumented. BioPlex accurately depicts known complexes, attaining 80%-100% coverage for most CORUM complexes. The network readily subdivides into communities that correspond to complexes or clusters of functionally related proteins. More generally, network architecture reflects cellular localization, biological process, and molecular function, enabling functional characterization of thousands of proteins. Network structure also reveals associations among thousands of protein domains, suggesting a basis for examining structurally related proteins. Finally, BioPlex, in combination with other approaches, can be used to reveal interactions of biological or clinical significance. For example, mutations in the membrane protein VAPB implicated in familial amyotrophic lateral sclerosis perturb a defined community of interactors. Copyright © 2015 Elsevier Inc. All rights reserved.
The BioPlex Network: A Systematic Exploration of the Human Interactome
Huttlin, Edward L.; Ting, Lily; Bruckner, Raphael J.; Gebreab, Fana; Gygi, Melanie P.; Szpyt, John; Tam, Stanley; Zarraga, Gabriela; Colby, Greg; Baltier, Kurt; Dong, Rui; Guarani, Virginia; Vaites, Laura Pontano; Ordureau, Alban; Rad, Ramin; Erickson, Brian K.; Wühr, Martin; Chick, Joel; Zhai, Bo; Kolippakkam, Deepak; Mintseris, Julian; Obar, Robert A.; Harris, Tim; Artavanis-Tsakonas, Spyros; Sowa, Mathew E.; DeCamilli, Pietro; Paulo, Joao A.; Harper, J. Wade; Gygi, Steven P.
2015-01-01
SUMMARY Protein interactions form a network whose structure drives cellular function and whose organization informs biological inquiry. Using high-throughput affinity-purification mass spectrometry, we identify interacting partners for 2,594 human proteins in HEK293T cells. The resulting network (BioPlex) contains 23,744 interactions among 7,668 proteins with 86% previously undocumented. BioPlex accurately depicts known complexes, attaining 80-100% coverage for most CORUM complexes. The network readily subdivides into communities that correspond to complexes or clusters of functionally related proteins. More generally, network architecture reflects cellular localization, biological process, and molecular function, enabling functional characterization of thousands of proteins. Network structure also reveals associations among thousands of protein domains, suggesting a basis for examining structurally-related proteins. Finally, BioPlex, in combination with other approaches can be used to reveal interactions of biological or clinical significance. For example, mutations in the membrane protein VAPB implicated in familial Amyotrophic Lateral Sclerosis perturb a defined community of interactors. PMID:26186194
Bacterial community changes in an industrial algae production system.
Fulbright, Scott P; Robbins-Pianka, Adam; Berg-Lyons, Donna; Knight, Rob; Reardon, Kenneth F; Chisholm, Stephen T
2018-04-01
While microalgae are a promising feedstock for production of fuels and other chemicals, a challenge for the algal bioproducts industry is obtaining consistent, robust algae growth. Algal cultures include complex bacterial communities and can be difficult to manage because specific bacteria can promote or reduce algae growth. To overcome bacterial contamination, algae growers may use closed photobioreactors designed to reduce the number of contaminant organisms. Even with closed systems, bacteria are known to enter and cohabitate, but little is known about these communities. Therefore, the richness, structure, and composition of bacterial communities were characterized in closed photobioreactor cultivations of Nannochloropsis salina in F/2 medium at different scales, across nine months spanning late summer-early spring, and during a sequence of serially inoculated cultivations. Using 16S rRNA sequence data from 275 samples, bacterial communities in small, medium, and large cultures were shown to be significantly different. Larger systems contained richer bacterial communities compared to smaller systems. Relationships between bacterial communities and algae growth were complex. On one hand, blooms of a specific bacterial type were observed in three abnormal, poorly performing replicate cultivations, while on the other, notable changes in the bacterial community structures were observed in a series of serial large-scale batch cultivations that had similar growth rates. Bacteria common to the majority of samples were identified, including a single OTU within the class Saprospirae that was found in all samples. This study contributes important information for crop protection in algae systems, and demonstrates the complex ecosystems that need to be understood for consistent, successful industrial algae cultivation. This is the first study to profile bacterial communities during the scale-up process of industrial algae systems.
How community has shaped the Protein Data Bank.
Berman, Helen M; Kleywegt, Gerard J; Nakamura, Haruki; Markley, John L
2013-09-03
Following several years of community discussion, the Protein Data Bank (PDB) was established in 1971 as a public repository for the coordinates of three-dimensional models of biological macromolecules. Since then, the number, size, and complexity of structural models have continued to grow, reflecting the productivity of structural biology. Managed by the Worldwide PDB organization, the PDB has been able to meet increasing demands for the quantity of structural information and of quality. In addition to providing unrestricted access to structural information, the PDB also works to promote data standards and to raise the profile of structural biology with broader audiences. In this perspective, we describe the history of PDB and the many ways in which the community continues to shape the archive. Copyright © 2013 Elsevier Ltd. All rights reserved.
Stochastic blockmodeling of the modules and core of the Caenorhabditis elegans connectome.
Pavlovic, Dragana M; Vértes, Petra E; Bullmore, Edward T; Schafer, William R; Nichols, Thomas E
2014-01-01
Recently, there has been much interest in the community structure or mesoscale organization of complex networks. This structure is characterised either as a set of sparsely inter-connected modules or as a highly connected core with a sparsely connected periphery. However, it is often difficult to disambiguate these two types of mesoscale structure or, indeed, to summarise the full network in terms of the relationships between its mesoscale constituents. Here, we estimate a community structure with a stochastic blockmodel approach, the Erdős-Rényi Mixture Model, and compare it to the much more widely used deterministic methods, such as the Louvain and Spectral algorithms. We used the Caenorhabditis elegans (C. elegans) nervous system (connectome) as a model system in which biological knowledge about each node or neuron can be used to validate the functional relevance of the communities obtained. The deterministic algorithms derived communities with 4-5 modules, defined by sparse inter-connectivity between all modules. In contrast, the stochastic Erdős-Rényi Mixture Model estimated a community with 9 blocks or groups which comprised a similar set of modules but also included a clearly defined core, made of 2 small groups. We show that the "core-in-modules" decomposition of the worm brain network, estimated by the Erdős-Rényi Mixture Model, is more compatible with prior biological knowledge about the C. elegans nervous system than the purely modular decomposition defined deterministically. We also show that the blockmodel can be used both to generate stochastic realisations (simulations) of the biological connectome, and to compress network into a small number of super-nodes and their connectivity. We expect that the Erdős-Rényi Mixture Model may be useful for investigating the complex community structures in other (nervous) systems.
Agudo-Adriani, Esteban A; Cappelletto, Jose; Cavada-Blanco, Francoise; Croquer, Aldo
2016-01-01
In the past decade, significant efforts have been made to describe fish-habitat associations. However, most studies have oversimplified actual connections between fish assemblages and their habitats by using univariate correlations. The purpose of this study was to identify the features of habitat forming corals that facilitate and influences assemblages of associated species such as fishes. For this we developed three-dimensional models of colonies of Acropora cervicornis to estimate geometry (length and height), structural complexity (i.e., volume, density of branches, etc.) and biological features of the colonies (i.e., live coral tissue, algae). We then correlated these colony characteristics with the associated fish assemblage using multivariate analyses. We found that geometry and complexity were better predictors of the structure of fish community, compared to other variables such as percentage of live coral tissue or algae. Combined, the geometry of each colony explained 40% of the variability of the fish assemblage structure associated with this coral species; 61% of the abundance and 69% of fish richness, respectively. Our study shows that three-dimensional reconstructions of discrete colonies of Acropora cervicornis provides a useful description of the colonial structural complexity and may explain a great deal of the variance in the structure of the associated coral reef fish community. This demonstration of the strongly trait-dependent ecosystem role of this threatened species has important implications for restoration and conservation efforts.
Cappelletto, Jose; Cavada-Blanco, Francoise; Croquer, Aldo
2016-01-01
In the past decade, significant efforts have been made to describe fish-habitat associations. However, most studies have oversimplified actual connections between fish assemblages and their habitats by using univariate correlations. The purpose of this study was to identify the features of habitat forming corals that facilitate and influences assemblages of associated species such as fishes. For this we developed three-dimensional models of colonies of Acropora cervicornis to estimate geometry (length and height), structural complexity (i.e., volume, density of branches, etc.) and biological features of the colonies (i.e., live coral tissue, algae). We then correlated these colony characteristics with the associated fish assemblage using multivariate analyses. We found that geometry and complexity were better predictors of the structure of fish community, compared to other variables such as percentage of live coral tissue or algae. Combined, the geometry of each colony explained 40% of the variability of the fish assemblage structure associated with this coral species; 61% of the abundance and 69% of fish richness, respectively. Our study shows that three-dimensional reconstructions of discrete colonies of Acropora cervicornis provides a useful description of the colonial structural complexity and may explain a great deal of the variance in the structure of the associated coral reef fish community. This demonstration of the strongly trait-dependent ecosystem role of this threatened species has important implications for restoration and conservation efforts. PMID:27069801
First steps of ecological restoration in Mediterranean lagoons: Shifts in phytoplankton communities
NASA Astrophysics Data System (ADS)
Leruste, A.; Malet, N.; Munaron, D.; Derolez, V.; Hatey, E.; Collos, Y.; De Wit, R.; Bec, B.
2016-10-01
Along the French Mediterranean coast, a complex of eight lagoons underwent intensive eutrophication over four decades, mainly related to nutrient over-enrichment from continuous sewage discharges. The lagoon complex displayed a wide trophic gradient from mesotrophy to hypertrophy and primary production was dominated by phytoplankton communities. In 2005, the implementation of an 11 km offshore outfall system diverted the treated sewage effluents leading to a drastic reduction of anthropogenic inputs of nitrogen and phosphorus into the lagoons. Time series data have been examined from 2000 to 2013 for physical, chemical and biological (phytoplankton) variables of the water column during the summer period. Since 2006, total nitrogen and phosphorus concentrations as well as chlorophyll biomass strongly decreased revealing an improvement in lagoon water quality. In summertime, the decline in phytoplankton biomass was accompanied by shifts in community structure and composition that could be explained by adopting a functional approach by considering the common functional traits of the main algal groups. These phytoplankton communities were dominated by functional groups of small-sized and fast-growing algae (diatoms, cryptophytes and green algae). The trajectories of summer phytoplankton communities displayed a complex response to changing nutrient loads over time. While diatoms were the major group in 2006 in all the lagoons, the summer phytoplankton composition in hypertrophic lagoons has shifted towards green algae, which are particularly well adapted to summertime conditions. All lagoons showed increasing proportion and occurrence of peridinin-rich dinophytes over time, probably related to their capacity for mixotrophy. The diversity patterns were marked by a strong variability in eutrophic and hypertrophic lagoons whereas phytoplankton community structure reached the highest diversity and stability in mesotrophic lagoons. We observe that during the re-oligotrophication process in coastal lagoons, phytoplankton shows complex trajectories with similarities with those observed in freshwater lake systems.
Issues in Benchmarking and Assessing Institutional Engagement
ERIC Educational Resources Information Center
Furco, Andrew; Miller, William
2009-01-01
The process of assessing and benchmarking community engagement can take many forms. To date, more than two dozen assessment tools for measuring community engagement institutionalization have been published. These tools vary substantially in purpose, level of complexity, scope, process, structure, and focus. While some instruments are designed to…
Peinetti, H.R.; Baker, B.W.; Coughenour, M.B.
2009-01-01
Beaver-willow (Castor-Salix) communities are a unique and vital component of healthy wetlands throughout the Holarctic region. Beaver selectively forage willow to provide fresh food, stored winter food, and construction material. The effects of this complex foraging behavior on the structure and function of willow communities is poorly understood. Simulation modeling may help ecologists understand these complex interactions. In this study, a modified version of the SAVANNA ecosystem model was developed to better understand how beaver foraging affects the structure and function of a willow community in a simulated riparian ecosystem in Rocky Mountain National Park, Colorado (RMNP). The model represents willow in terms of plant and stem dynamics and beaver foraging in terms of the quantity and quality of stems cut to meet the energetic and life history requirements of beaver. Given a site where all stems were equally available, the model suggested a simulated beaver family of 2 adults, 2 yearlings, and 2 kits required a minimum of 4 ha of willow (containing about10 stems m-2) to persist in a steady-state condition. Beaver created a willow community where the annual net primary productivity (ANPP) was 2 times higher and plant architecture was more diverse than the willow community without beaver. Beaver foraging created a plant architecture dominated by medium size willow plants, which likely explains how beaver can increase ANPP. Long-term simulations suggested that woody biomass stabilized at similar values even though availability differed greatly at initial condition. Simulations also suggested that willow ANPP increased across a range of beaver densities until beaver became food limited. Thus, selective foraging by beaver increased productivity, decreased biomass, and increased structural heterogeneity in a simulated willow community.
Spurgeon, David J; Keith, Aidan M; Schmidt, Olaf; Lammertsma, Dennis R; Faber, Jack H
2013-12-01
Change in land use and management can impact massively on soil ecosystems. Ecosystem engineers and other functional biodiversity in soils can be influenced directly by such change and this in turn can affect key soil functions. Here, we employ meta-analysis to provide a quantitative assessment of the effects of changes in land use and land management across a range of successional/extensification transitions (conventional arable → no or reduced tillage → grassland → wooded land) on community metrics for two functionally important soil taxa, earthworms and fungi. An analysis of the relationships between community change and soil structural properties was also included. Meta-analysis highlighted a consistent trend of increased earthworm and fungal community abundances and complexity following transitions to lower intensity and later successional land uses. The greatest changes were seen for early stage transitions, such as introduction of reduced tillage regimes and conversion to grassland from arable land. Not all changes, however, result in positive effects on the assessed community metrics. For example, whether woodland conversion positively or negatively affects community size and complexity depends on woodland type and, potentially, the changes in soil properties, such as pH, that may occur during conversion. Alterations in soil communities tended to facilitate subsequent changes in soil structure and hydrology. For example, increasing earthworm abundances and functional group composition were shown to be positively correlated with water infiltration rate (dependent on tillage regime and habitat characteristics); while positive changes in fungal biomass measures were positively associated with soil microaggregate stability. These findings raise the potential to manage landscapes to increase ecosystem service provision from soil biota in relation to regulation of soil structure and water flow.
Ofaim, Shany; Ofek-Lalzar, Maya; Sela, Noa; Jinag, Jiandong; Kashi, Yechezkel; Minz, Dror; Freilich, Shiri
2017-01-01
Advances in metagenomics enable high resolution description of complex bacterial communities in their natural environments. Consequently, conceptual approaches for community level functional analysis are in high need. Here, we introduce a framework for a metagenomics-based analysis of community functions. Environment-specific gene catalogs, derived from metagenomes, are processed into metabolic-network representation. By applying established ecological conventions, network-edges (metabolic functions) are assigned with taxonomic annotations according to the dominance level of specific groups. Once a function-taxonomy link is established, prediction of the impact of dominant taxa on the overall community performances is assessed by simulating removal or addition of edges (taxa associated functions). This approach is demonstrated on metagenomic data describing the microbial communities from the root environment of two crop plants – wheat and cucumber. Predictions for environment-dependent effects revealed differences between treatments (root vs. soil), corresponding to documented observations. Metabolism of specific plant exudates (e.g., organic acids, flavonoids) was linked with distinct taxonomic groups in simulated root, but not soil, environments. These dependencies point to the impact of these metabolite families as determinants of community structure. Simulations of the activity of pairwise combinations of taxonomic groups (order level) predicted the possible production of complementary metabolites. Complementation profiles allow formulating a possible metabolic role for observed co-occurrence patterns. For example, production of tryptophan-associated metabolites through complementary interactions is unique to the tryptophan-deficient cucumber root environment. Our approach enables formulation of testable predictions for species contribution to community activity and exploration of the functional outcome of structural shifts in complex bacterial communities. Understanding community-level metabolism is an essential step toward the manipulation and optimization of microbial function. Here, we introduce an analysis framework addressing three key challenges of such data: producing quantified links between taxonomy and function; contextualizing discrete functions into communal networks; and simulating environmental impact on community performances. New technologies will soon provide a high-coverage description of biotic and a-biotic aspects of complex microbial communities such as these found in gut and soil. This framework was designed to allow the integration of high-throughput metabolomic and metagenomic data toward tackling the intricate associations between community structure, community function, and metabolic inputs. PMID:28878756
Community detection in complex networks by using membrane algorithm
NASA Astrophysics Data System (ADS)
Liu, Chuang; Fan, Linan; Liu, Zhou; Dai, Xiang; Xu, Jiamei; Chang, Baoren
Community detection in complex networks is a key problem of network analysis. In this paper, a new membrane algorithm is proposed to solve the community detection in complex networks. The proposed algorithm is based on membrane systems, which consists of objects, reaction rules, and a membrane structure. Each object represents a candidate partition of a complex network, and the quality of objects is evaluated according to network modularity. The reaction rules include evolutionary rules and communication rules. Evolutionary rules are responsible for improving the quality of objects, which employ the differential evolutionary algorithm to evolve objects. Communication rules implement the information exchanged among membranes. Finally, the proposed algorithm is evaluated on synthetic, real-world networks with real partitions known and the large-scaled networks with real partitions unknown. The experimental results indicate the superior performance of the proposed algorithm in comparison with other experimental algorithms.
Tool for simplifying the complex interactions within resilient communities
NASA Astrophysics Data System (ADS)
Stwertka, C.; Albert, M. R.; White, K. D.
2016-12-01
In recent decades, scientists have observed and documented impacts from climate change that will impact multiple sectors, will be impacted by decisions from multiple sectors, and will change over time. This complex human-engineered system has a large number of moving, interacting parts, which are interdependent and evolve over time towards their purpose. Many of the existing resilience frameworks and vulnerability frameworks focus on interactions between the domains, but do not include the structure of the interactions. We present an engineering systems approach to investigate the structural elements that influence a community's ability to be resilient. In this presentation we will present and analyze four common methods for building community resilience, utilizing our common framework. For several existing case studies we examine the stress points in the system and identify the impacts on the outcomes from the case studies. In ongoing research we will apply our system tool to a new case in the field.
Community structure in networks
NASA Astrophysics Data System (ADS)
Newman, Mark
2004-03-01
Many networked systems, including physical, biological, social, and technological networks, appear to contain ``communities'' -- groups of nodes within which connections are dense, but between which they are sparser. The ability to find such communities in an automated fashion could be of considerable use. Communities in a web graph for instance might correspond to sets of web sites dealing with related topics, while communities in a biochemical network or an electronic circuit might correspond to functional units of some kind. We present a number of new methods for community discovery, including methods based on ``betweenness'' measures and methods based on modularity optimization. We also give examples of applications of these methods to both computer-generated and real-world network data, and show how our techniques can be used to shed light on the sometimes dauntingly complex structure of networked systems.
Flow-pattern identification and nonlinear dynamics of gas-liquid two-phase flow in complex networks.
Gao, Zhongke; Jin, Ningde
2009-06-01
The identification of flow pattern is a basic and important issue in multiphase systems. Because of the complexity of phase interaction in gas-liquid two-phase flow, it is difficult to discern its flow pattern objectively. In this paper, we make a systematic study on the vertical upward gas-liquid two-phase flow using complex network. Three unique network construction methods are proposed to build three types of networks, i.e., flow pattern complex network (FPCN), fluid dynamic complex network (FDCN), and fluid structure complex network (FSCN). Through detecting the community structure of FPCN by the community-detection algorithm based on K -mean clustering, useful and interesting results are found which can be used for identifying five vertical upward gas-liquid two-phase flow patterns. To investigate the dynamic characteristics of gas-liquid two-phase flow, we construct 50 FDCNs under different flow conditions, and find that the power-law exponent and the network information entropy, which are sensitive to the flow pattern transition, can both characterize the nonlinear dynamics of gas-liquid two-phase flow. Furthermore, we construct FSCN and demonstrate how network statistic can be used to reveal the fluid structure of gas-liquid two-phase flow. In this paper, from a different perspective, we not only introduce complex network theory to the study of gas-liquid two-phase flow but also indicate that complex network may be a powerful tool for exploring nonlinear time series in practice.
Surveying traffic congestion based on the concept of community structure of complex networks
NASA Astrophysics Data System (ADS)
Ma, Lili; Zhang, Zhanli; Li, Meng
2016-07-01
In this paper, taking the traffic of Beijing city as an instance, we study city traffic states, especially traffic congestion, based on the concept of network community structure. Concretely, using the floating car data (FCD) information of vehicles gained from the intelligent transport system (ITS) of the city, we construct a new traffic network model which is with floating cars as network nodes and time-varying. It shows that this traffic network has Gaussian degree distributions at different time points. Furthermore, compared with free traffic situations, our simulations show that the traffic network generally has more obvious community structures with larger values of network fitness for congested traffic situations, and through the GPSspg web page, we show that all of our results are consistent with the reality. Then, it indicates that network community structure should be an available way for investigating city traffic congestion problems.
An Adaptive Complex Network Model for Brain Functional Networks
Gomez Portillo, Ignacio J.; Gleiser, Pablo M.
2009-01-01
Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence) of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution. PMID:19738902
Cole, Jason C.
2017-01-01
Many ligand-discovery stories tell of the use of structures of protein–ligand complexes, but the contribution of structural chemistry is such a core part of finding and improving ligands that it is often overlooked. More than 800 000 crystal structures are available to the community through the Cambridge Structural Database (CSD). Individually, these structures can be of tremendous value and the collection of crystal structures is even more helpful. This article provides examples of how small-molecule crystal structures have been used to complement those of protein–ligand complexes to address challenges ranging from affinity, selectivity and bioavailability though to solubility. PMID:28291759
Discovering Network Structure Beyond Communities
NASA Astrophysics Data System (ADS)
Nishikawa, Takashi; Motter, Adilson E.
2011-11-01
To understand the formation, evolution, and function of complex systems, it is crucial to understand the internal organization of their interaction networks. Partly due to the impossibility of visualizing large complex networks, resolving network structure remains a challenging problem. Here we overcome this difficulty by combining the visual pattern recognition ability of humans with the high processing speed of computers to develop an exploratory method for discovering groups of nodes characterized by common network properties, including but not limited to communities of densely connected nodes. Without any prior information about the nature of the groups, the method simultaneously identifies the number of groups, the group assignment, and the properties that define these groups. The results of applying our method to real networks suggest the possibility that most group structures lurk undiscovered in the fast-growing inventory of social, biological, and technological networks of scientific interest.
Approximation of Nash equilibria and the network community structure detection problem
2017-01-01
Game theory based methods designed to solve the problem of community structure detection in complex networks have emerged in recent years as an alternative to classical and optimization based approaches. The Mixed Nash Extremal Optimization uses a generative relation for the characterization of Nash equilibria to identify the community structure of a network by converting the problem into a non-cooperative game. This paper proposes a method to enhance this algorithm by reducing the number of payoff function evaluations. Numerical experiments performed on synthetic and real-world networks show that this approach is efficient, with results better or just as good as other state-of-the-art methods. PMID:28467496
Chatellard, Lucile; Trably, Eric; Carrère, Hélène
2016-12-01
The impact on dark fermentation of seven carbohydrates as model substrates of lignocellulosic fractions (glucose, cellobiose, microcrystalline cellulose, arabinose, xylose, xylan and wheat straw) was investigated. Metabolic patterns and bacterial communities were characterized at the end of batch tests inoculated with manure digestate. It was found that hydrogen production was linked to the sugar type (pentose or hexose) and the degree of polymerisation. Hexoses produced less hydrogen, with a specific selection of lactate-producing bacterial community structures. Maximal hydrogen production was five times higher on pentose-based substrates, with specific bacterial community structures producing acetate and butyrate as main metabolites. Low hydrogen amounts accumulated from complex sugars (cellulose, xylan and wheat straw). A relatively high proportion of the reads was affiliated to Ruminococcaceae suggesting an efficient hydrolytic activity. Knowing that the bacterial community structure is very specific to a particular substrate offers new possibilities to design more efficient H 2 -producing biological systems. Copyright © 2016 Elsevier Ltd. All rights reserved.
Salem Community College's 1999-2002 Strategic Plan Authoring & Implementation Strategy.
ERIC Educational Resources Information Center
Salem Community Coll., Penns Grove, NJ.
This document outlines the Strategic Planning Initiative (SPI) for New Jersey's Salem Community College. This is the first plan the college has authored in seven years. The report provides a theoretical framework for heterarchical planning, which allows for complexity and interrelations of structural analysis, and lateral decision making. The…
Predicting effects of climate change on the composition and function of soil microbial communities
NASA Astrophysics Data System (ADS)
Dubinsky, E.; Brodie, E.; Myint, C.; Ackerly, D.; van Nostrand, J.; Bird, J.; Zhou, J.; Andersen, G.; Firestone, M.
2008-12-01
Complex soil microbial communities regulate critical ecosystem processes that will be altered by climate change. A critical step towards predicting the impacts of climate change on terrestrial ecosystems is to determine the primary controllers of soil microbial community composition and function, and subsequently evaluate climate change scenarios that alter these controllers. We surveyed complex soil bacterial and archaeal communities across a range of climatic and edaphic conditions to identify critical controllers of soil microbial community composition in the field and then tested the resulting predictions using a 2-year manipulation of precipitation and temperature using mesocosms of California annual grasslands. Community DNA extracted from field soils sampled from six different ecosystems was assayed for bacterial and archaeal communities using high-density phylogenetic microarrays as well as functional gene arrays. Correlations among the relative abundances of thousands of microbial taxa and edaphic factors such as soil moisture and nutrient content provided a basis for predicting community responses to changing soil conditions. Communities of soil bacteria and archaea were strongly structured by single environmental predictors, particularly variables related to soil water. Bacteria in the Actinomycetales and Bacilli consistently demonstrated a strong negative response to increasing soil moisture, while taxa in a greater variety of lineages responded positively to increasing soil moisture. In the climate change experiment, overall bacterial community structure was impacted significantly by total precipitation but not by plant species. Changes in soil moisture due to decreased rainfall resulted in significant and predictable alterations in community structure. Over 70% of the bacterial taxa in common with the cross-ecosystem study responded as predicted to altered precipitation, with the most conserved response from Actinobacteria. The functional consequences of these predictable changes in community composition were measured with functional arrays that detect genes involved in the metabolism of carbon, nitrogen and other elements. The response of soil microbial communities to altered precipitation can be predicted from the distribution of microbial taxa across moisture gradients.
Overlapping community detection based on link graph using distance dynamics
NASA Astrophysics Data System (ADS)
Chen, Lei; Zhang, Jing; Cai, Li-Jun
2018-01-01
The distance dynamics model was recently proposed to detect the disjoint community of a complex network. To identify the overlapping structure of a network using the distance dynamics model, an overlapping community detection algorithm, called L-Attractor, is proposed in this paper. The process of L-Attractor mainly consists of three phases. In the first phase, L-Attractor transforms the original graph to a link graph (a new edge graph) to assure that one node has multiple distances. In the second phase, using the improved distance dynamics model, a dynamic interaction process is introduced to simulate the distance dynamics (shrink or stretch). Through the dynamic interaction process, all distances converge, and the disjoint community structure of the link graph naturally manifests itself. In the third phase, a recovery method is designed to convert the disjoint community structure of the link graph to the overlapping community structure of the original graph. Extensive experiments are conducted on the LFR benchmark networks as well as real-world networks. Based on the results, our algorithm demonstrates higher accuracy and quality than other state-of-the-art algorithms.
Rapid evolution of hosts begets species diversity at the cost of intraspecific diversity.
Frickel, Jens; Theodosiou, Loukas; Becks, Lutz
2017-10-17
Ecosystems are complex food webs in which multiple species interact and ecological and evolutionary processes continuously shape populations and communities. Previous studies on eco-evolutionary dynamics have shown that the presence of intraspecific diversity affects community structure and function, and that eco-evolutionary feedback dynamics can be an important driver for its maintenance. Within communities, feedbacks are, however, often indirect, and they can feed back over many generations. Here, we studied eco-evolutionary feedbacks in evolving communities over many generations and compared two-species systems (virus-host and prey-predator) with a more complex three-species system (virus-host-predator). Both indirect density- and trait-mediated effects drove the dynamics in the complex system, where host-virus coevolution facilitated coexistence of predator and virus, and where coexistence, in return, lowered intraspecific diversity of the host population. Furthermore, ecological and evolutionary dynamics were significantly altered in the three-species system compared with the two-species systems. We found that the predator slowed host-virus coevolution in the complex system and that the virus' effect on the overall population dynamics was negligible when the three species coexisted. Overall, we show that a detailed understanding of the mechanism driving eco-evolutionary feedback dynamics is necessary for explaining trait and species diversity in communities, even in communities with only three species.
Comte, Jérôme; del Giorgio, Paul A.
2011-01-01
Bacterioplankton community metabolism is central to the functioning of aquatic ecosystems, and strongly reactive to changes in the environment, yet the processes underlying this response remain unclear. Here we explore the role that community composition plays in shaping the bacterial metabolic response to resource gradients that occur along aquatic ecotones in a complex watershed in Québec. Our results show that the response is mediated by complex shifts in community structure, and structural equation analysis confirmed two main pathways, one involving adjustments in the level of activity of existing phylotypes, and the other the replacement of the dominant phylotypes. These contrasting response pathways were not determined by the type or the intensity of the gradients involved, as we had hypothesized, but rather it would appear that some compositional configurations may be intrinsically more plastic than others. Our results suggest that community composition determines this overall level of community plasticity, but that composition itself may be driven by factors independent of the environmental gradients themselves, such that the response of bacterial communities to a given type of gradient may alternate between the adjustment and replacement pathways. We conclude that community composition influences the pathways of response in these bacterial communities, but not the metabolic outcome itself, which is driven by the environment, and which can be attained through multiple alternative configurations. PMID:21980410
Graptolite community responses to global climate change and the Late Ordovician mass extinction.
Sheets, H David; Mitchell, Charles E; Melchin, Michael J; Loxton, Jason; Štorch, Petr; Carlucci, Kristi L; Hawkins, Andrew D
2016-07-26
Mass extinctions disrupt ecological communities. Although climate changes produce stress in ecological communities, few paleobiological studies have systematically addressed the impact of global climate changes on the fine details of community structure with a view to understanding how changes in community structure presage, or even cause, biodiversity decline during mass extinctions. Based on a novel Bayesian approach to biotope assessment, we present a study of changes in species abundance distribution patterns of macroplanktonic graptolite faunas (∼447-444 Ma) leading into the Late Ordovician mass extinction. Communities at two contrasting sites exhibit significant decreases in complexity and evenness as a consequence of the preferential decline in abundance of dysaerobic zone specialist species. The observed changes in community complexity and evenness commenced well before the dramatic population depletions that mark the tipping point of the extinction event. Initially, community changes tracked changes in the oceanic water masses, but these relations broke down during the onset of mass extinction. Environmental isotope and biomarker data suggest that sea surface temperature and nutrient cycling in the paleotropical oceans changed sharply during the latest Katian time, with consequent changes in the extent of the oxygen minimum zone and phytoplankton community composition. Although many impacted species persisted in ephemeral populations, increased extinction risk selectively depleted the diversity of paleotropical graptolite species during the latest Katian and early Hirnantian. The effects of long-term climate change on habitats can thus degrade populations in ways that cascade through communities, with effects that culminate in mass extinction.
Graptolite community responses to global climate change and the Late Ordovician mass extinction
NASA Astrophysics Data System (ADS)
Sheets, H. David; Mitchell, Charles E.; Melchin, Michael J.; Loxton, Jason; Štorch, Petr; Carlucci, Kristi L.; Hawkins, Andrew D.
2016-07-01
Mass extinctions disrupt ecological communities. Although climate changes produce stress in ecological communities, few paleobiological studies have systematically addressed the impact of global climate changes on the fine details of community structure with a view to understanding how changes in community structure presage, or even cause, biodiversity decline during mass extinctions. Based on a novel Bayesian approach to biotope assessment, we present a study of changes in species abundance distribution patterns of macroplanktonic graptolite faunas (˜447-444 Ma) leading into the Late Ordovician mass extinction. Communities at two contrasting sites exhibit significant decreases in complexity and evenness as a consequence of the preferential decline in abundance of dysaerobic zone specialist species. The observed changes in community complexity and evenness commenced well before the dramatic population depletions that mark the tipping point of the extinction event. Initially, community changes tracked changes in the oceanic water masses, but these relations broke down during the onset of mass extinction. Environmental isotope and biomarker data suggest that sea surface temperature and nutrient cycling in the paleotropical oceans changed sharply during the latest Katian time, with consequent changes in the extent of the oxygen minimum zone and phytoplankton community composition. Although many impacted species persisted in ephemeral populations, increased extinction risk selectively depleted the diversity of paleotropical graptolite species during the latest Katian and early Hirnantian. The effects of long-term climate change on habitats can thus degrade populations in ways that cascade through communities, with effects that culminate in mass extinction.
Epidemic spreading in time-varying community networks.
Ren, Guangming; Wang, Xingyuan
2014-06-01
The spreading processes of many infectious diseases have comparable time scale as the network evolution. Here, we present a simple networks model with time-varying community structure, and investigate susceptible-infected-susceptible epidemic spreading processes in this model. By both theoretic analysis and numerical simulations, we show that the efficiency of epidemic spreading in this model depends intensively on the mobility rate q of the individuals among communities. We also find that there exists a mobility rate threshold qc. The epidemic will survive when q > qc and die when q < qc. These results can help understanding the impacts of human travel on the epidemic spreading in complex networks with community structure.
Argento, Elena; Reza-Paul, Sushena; Lorway, Robert; Jain, Jinendra; Bhagya, M; Fathima, Mary; Sreeram, S V; Hafeezur, Rahman Syed; O'Neil, John
2011-01-01
Evidence from community-led HIV prevention projects suggests that structural interventions may result in reduced rates of HIV and STIs. The complex relationship between empowerment and confronting stigma, discrimination and physical abuse necessitates further investigation into the impact that such interventions have on the personal risks for sex workers. This article aims to describe lived experiences of members from a sex worker's collective in Mysore, India and how they have confronted structural violence. The narratives highlight experiences of violence and the development and implementation of strategies that have altered the social, physical, and emotional environment for sex workers. Building an enabling environment was key to reducing personal risks inherent to sex work, emphasizing the importance of community-led structural interventions for sex workers in India.
Valm, Alex M; Mark Welch, Jessica L; Rieken, Christopher W; Hasegawa, Yuko; Sogin, Mitchell L; Oldenbourg, Rudolf; Dewhirst, Floyd E; Borisy, Gary G
2011-03-08
Microbes in nature frequently function as members of complex multitaxon communities, but the structural organization of these communities at the micrometer level is poorly understood because of limitations in labeling and imaging technology. We report here a combinatorial labeling strategy coupled with spectral image acquisition and analysis that greatly expands the number of fluorescent signatures distinguishable in a single image. As an imaging proof of principle, we first demonstrated visualization of Escherichia coli labeled by fluorescence in situ hybridization (FISH) with 28 different binary combinations of eight fluorophores. As a biological proof of principle, we then applied this Combinatorial Labeling and Spectral Imaging FISH (CLASI-FISH) strategy using genus- and family-specific probes to visualize simultaneously and differentiate 15 different phylotypes in an artificial mixture of laboratory-grown microbes. We then illustrated the utility of our method for the structural analysis of a natural microbial community, namely, human dental plaque, a microbial biofilm. We demonstrate that 15 taxa in the plaque community can be imaged simultaneously and analyzed and that this community was dominated by early colonizers, including species of Streptococcus, Prevotella, Actinomyces, and Veillonella. Proximity analysis was used to determine the frequency of inter- and intrataxon cell-to-cell associations which revealed statistically significant intertaxon pairings. Cells of the genera Prevotella and Actinomyces showed the most interspecies associations, suggesting a central role for these genera in establishing and maintaining biofilm complexity. The results provide an initial systems-level structural analysis of biofilm organization.
Cascading failures in complex networks with community structure
NASA Astrophysics Data System (ADS)
Lin, Guoqiang; di, Zengru; Fan, Ying
2014-12-01
Much empirical evidence shows that when attacked with cascading failures, scale-free or even random networks tend to collapse more extensively when the initially deleted node has higher betweenness. Meanwhile, in networks with strong community structure, high-betweenness nodes tend to be bridge nodes that link different communities, and the removal of such nodes will reduce only the connections among communities, leaving the networks fairly stable. Understanding what will affect cascading failures and how to protect or attack networks with strong community structure is therefore of interest. In this paper, we have constructed scale-free Community Networks (SFCN) and Random Community Networks (RCN). We applied these networks, along with the Lancichinett-Fortunato-Radicchi (LFR) benchmark, to the cascading-failure scenario to explore their vulnerability to attack and the relationship between cascading failures and the degree distribution and community structure of a network. The numerical results show that when the networks are of a power-law distribution, a stronger community structure will result in the failure of fewer nodes. In addition, the initial removal of the node with the highest betweenness will not lead to the worst cascading, i.e. the largest avalanche size. The Betweenness Overflow (BOF), an index that we developed, is an effective indicator of this tendency. The RCN, however, display a different result. In addition, the avalanche size of each node can be adopted as an index to evaluate the importance of the node.
Digital Reef Rugosity Estimates Coral Reef Habitat Complexity
Dustan, Phillip; Doherty, Orla; Pardede, Shinta
2013-01-01
Ecological habitats with greater structural complexity contain more species due to increased niche diversity. This is especially apparent on coral reefs where individual coral colonies aggregate to give a reef its morphology, species zonation, and three dimensionality. Structural complexity is classically measured with a reef rugosity index, which is the ratio of a straight line transect to the distance a flexible chain of equal length travels when draped over the reef substrate; yet, other techniques from visual categories to remote sensing have been used to characterize structural complexity at scales from microhabitats to reefscapes. Reef-scale methods either lack quantitative precision or are too time consuming to be routinely practical, while remotely sensed indices are mismatched to the finer scale morphology of coral colonies and reef habitats. In this communication a new digital technique, Digital Reef Rugosity (DRR) is described which utilizes a self-contained water level gauge enabling a diver to quickly and accurately characterize rugosity with non-invasive millimeter scale measurements of coral reef surface height at decimeter intervals along meter scale transects. The precise measurements require very little post-processing and are easily imported into a spreadsheet for statistical analyses and modeling. To assess its applicability we investigated the relationship between DRR and fish community structure at four coral reef sites on Menjangan Island off the northwest corner of Bali, Indonesia and one on mainland Bali to the west of Menjangan Island; our findings show a positive relationship between DRR and fish diversity. Since structural complexity drives key ecological processes on coral reefs, we consider that DRR may become a useful quantitative community-level descriptor to characterize reef complexity. PMID:23437380
Digital reef rugosity estimates coral reef habitat complexity.
Dustan, Phillip; Doherty, Orla; Pardede, Shinta
2013-01-01
Ecological habitats with greater structural complexity contain more species due to increased niche diversity. This is especially apparent on coral reefs where individual coral colonies aggregate to give a reef its morphology, species zonation, and three dimensionality. Structural complexity is classically measured with a reef rugosity index, which is the ratio of a straight line transect to the distance a flexible chain of equal length travels when draped over the reef substrate; yet, other techniques from visual categories to remote sensing have been used to characterize structural complexity at scales from microhabitats to reefscapes. Reef-scale methods either lack quantitative precision or are too time consuming to be routinely practical, while remotely sensed indices are mismatched to the finer scale morphology of coral colonies and reef habitats. In this communication a new digital technique, Digital Reef Rugosity (DRR) is described which utilizes a self-contained water level gauge enabling a diver to quickly and accurately characterize rugosity with non-invasive millimeter scale measurements of coral reef surface height at decimeter intervals along meter scale transects. The precise measurements require very little post-processing and are easily imported into a spreadsheet for statistical analyses and modeling. To assess its applicability we investigated the relationship between DRR and fish community structure at four coral reef sites on Menjangan Island off the northwest corner of Bali, Indonesia and one on mainland Bali to the west of Menjangan Island; our findings show a positive relationship between DRR and fish diversity. Since structural complexity drives key ecological processes on coral reefs, we consider that DRR may become a useful quantitative community-level descriptor to characterize reef complexity.
Hu, Ning; Li, Hui; Tang, Zheng; Li, Zhongfang; Tian, Jing; Lou, Yilai; Li, Jianwei; Li, Guichun; Hu, Xiaomin
2016-06-17
We examined community diversity, structure and carbon footprint of nematode food web along a chronosequence of T. Sinensis reforestation on degraded Karst. In general, after the reforestation: a serious of diversity parameters and community indices (Shannon-Weinier index (H'), structure index (SI), etc.) were elevated; biomass ratio of fungivores to bacterivores (FFC/BFC), and fungi to bacteria (F/B) were increased, and nematode channel ratio (NCR) were decreased; carbon footprints of all nematode trophic groups, and biomass of bacteria and fungi were increased. Our results indicate that the Karst aboveground vegetation restoration was accompanied with belowground nematode food web development: increasing community complexity, function and fungal dominance in decomposition pathway, and the driving forces included the bottom-up effect (resource control), connectedness of functional groups, as well as soil environments.
Hu, Ning; Li, Hui; Tang, Zheng; Li, Zhongfang; Tian, Jing; Lou, Yilai; Li, Jianwei; Li, Guichun; Hu, Xiaomin
2016-01-01
We examined community diversity, structure and carbon footprint of nematode food web along a chronosequence of T. Sinensis reforestation on degraded Karst. In general, after the reforestation: a serious of diversity parameters and community indices (Shannon-Weinier index (H′), structure index (SI), etc.) were elevated; biomass ratio of fungivores to bacterivores (FFC/BFC), and fungi to bacteria (F/B) were increased, and nematode channel ratio (NCR) were decreased; carbon footprints of all nematode trophic groups, and biomass of bacteria and fungi were increased. Our results indicate that the Karst aboveground vegetation restoration was accompanied with belowground nematode food web development: increasing community complexity, function and fungal dominance in decomposition pathway, and the driving forces included the bottom-up effect (resource control), connectedness of functional groups, as well as soil environments. PMID:27311984
Co-acclimation of bacterial communities under stresses of hydrocarbons with different structures
Wang, Hui; Wang, Bin; Dong, Wenwen; Hu, Xiaoke
2016-01-01
Crude oil is a complex mixture of hydrocarbons with different structures; its components vary in bioavailability and toxicity. It is important to understand how bacterial communities response to different hydrocarbons and their co-acclimation in the process of degradation. In this study, microcosms with the addition of structurally different hydrocarbons were setup to investigate the successions of bacterial communities and the interactions between different bacterial taxa. Hydrocarbons were effectively degraded in all microcosms after 40 days. High-throughput sequencing offered a great quantity of data for analyzing successions of bacterial communities. The results indicated that the bacterial communities responded dramatically different to various hydrocarbons. KEGG database and PICRUSt were applied to predict functions of individual bacterial taxa and networks were constructed to analyze co-acclimations between functional bacterial groups. Almost all functional genes catalyzing degradation of different hydrocarbons were predicted in bacterial communities. Most of bacterial taxa were believed to conduct biodegradation processes via interactions with each other. This study addressed a few investigated area of bacterial community responses to structurally different organic pollutants and their co-acclimation and interactions in the process of biodegradation. The study could provide useful information to guide the bioremediation of crude oil pollution. PMID:27698451
USDA-ARS?s Scientific Manuscript database
Soil microorganisms play essential roles in soil organic matter dynamics and nutrient cycling in agroecosystems and have been used as soil quality indicators. The response of soil microbial communities to land management is complex and the long-term impacts of cropping systems on soil microbes is l...
Emergent Complex Behavior in Social Networks: Examples from the Ktunaxa Speech Community
ERIC Educational Resources Information Center
Horsethief, Christopher
2012-01-01
Language serves as a primary tool for structuring identity and loss of language represents the loss of that identity. This study utilizes a social network analysis of Ktunaxa speech community activities for evidence of internally generated revitalization efforts. These behaviors include instances of self-organized emergence. Such emergent behavior…
Burke, M.K.; King, S.L.; Eisenbies, M.H.; Gartner, D.
2000-01-01
Intro paragraph: Characterization of bottomland hardwood vegetation in relatively undisturbed forests can provide critical information for developing effective wetland creation and restoration techniques and for assessing the impacts of management and development. Classification is a useful technique in characterizing vegetation because it summarizes complex data sets, assists in hypothesis generation about factors influencing community variation, and helps refine models of community structure. Hierarchical classification of communities is particularly useful for showing relationships among samples (Gauche 1982).
Bacterial communities in an ultrapure water containing storage tank of a power plant.
Bohus, Veronika; Kéki, Zsuzsa; Márialigeti, Károly; Baranyi, Krisztián; Patek, Gábor; Schunk, János; Tóth, Erika M
2011-12-01
Ultrapure waters (UPWs) containing low levels of organic and inorganic compounds provide extreme environment. On contrary to that microbes occur in such waters and form biofilms on surfaces, thus may induce corrosion processes in many industrial applications. In our study, refined saltless water (UPW) produced for the boiler of a Hungarian power plant was examined before and after storage (sampling the inlet [TKE] and outlet [TKU] waters of a storage tank) with cultivation and culture independent methods. Our results showed increased CFU and direct cell counts after the storage. Cultivation results showed the dominance of aerobic, chemoorganotrophic α-Proteobacteria in both samples. In case of TKU sample, a more complex bacterial community structure could be detected. The applied molecular method (T-RFLP) indicated the presence of a complex microbial community structure with changes in the taxon composition: while in the inlet water sample (TKE) α-Proteobacteria (Sphingomonas sp., Novosphingobium hassiacum) dominated, in the outlet water sample (TKU) the bacterial community shifted towards the dominance of α-Proteobacteria (Rhodoferax sp., Polynucleobacter sp., Sterolibacter sp.), CFB (Bacteroidetes, formerly Cytophaga-Flavobacterium-Bacteroides group) and Firmicutes. This shift to the direction of fermentative communities suggests that storage could help the development of communities with an increased tendency toward corrosion.
Community-based participatory research in complex settings: clean mind–dirty hands
Makhoul, Jihad; Nakkash, Rima; Harpham, Trudy; Qutteina, Yara
2014-01-01
Despite the abundance of the literature which discusses factors supporting or inhibiting effective participation of community members in community-based research, there is a paucity of publications analysing challenges to participation in complex settings. This manuscript describes an intervention built on researcher–community partnership amid complex social conditions which challenged participation of community members at different stages of the research process. The research took place in a Palestinian refugee camp in Beirut, Lebanon and 1 of 12 in Lebanon which suffer from deteriorating social, economic and physical conditions perpetuated by state-imposed restrictions. The research team developed a community coalition which was involved in all stages of planning, designing, implementation and dissemination. In all those stages the aim was to maintain rigorous research, to follow a ‘clean mind’ approach to research, but maintain principles of community participation which necessitate ‘a dirty hand’. Despite commitment to the principles of community-based participatory research, participation of community members (including youth, parents and teachers) was affected to a great extent by the social, physical and structural conditions of the community context. Characteristics of the context where research is conducted and how it affects community members should not be overlooked since multiple factors beyond the researchers' control could interfere with the rigour of scientific research. Researchers need to develop a plan for participation with the community from the beginning with an understanding of the community forces that affect meaningful participation and address possible deterrence. PMID:23872385
Food-web complexity across hydrothermal vents on the Azores triple junction
NASA Astrophysics Data System (ADS)
Portail, Marie; Brandily, Christophe; Cathalot, Cécile; Colaço, Ana; Gélinas, Yves; Husson, Bérengère; Sarradin, Pierre-Marie; Sarrazin, Jozée
2018-01-01
The assessment and comparison of food webs across various hydrothermal vent sites can enhance our understanding of ecological processes involved in the structure and function of biodiversity. The Menez Gwen, Lucky Strike and Rainbow vent fields are located on the Azores triple junction of the Mid-Atlantic Ridge. These fields have distinct depths (from 850 to 2320 m) and geological contexts (basaltic and ultramafic), but share similar faunal assemblages defined by the presence of foundation species that include Bathymodiolus azoricus, alvinocarid shrimp and gastropods. We compared the food webs of 13 faunal assemblages at these three sites using carbon and nitrogen stable isotope analyses (SIA). Results showed that photosynthesis-derived organic matter is a negligible basal source for vent food webs, at all depths. The contribution of methanotrophy versus autotrophy based on Calvin-Benson-Bassham (CBB) or reductive tricarboxylic acid (rTCA) cycles varied between and within vent fields according to the concentrations of reduced compounds (e.g. CH4, H2S). Species that were common to vent fields showed high trophic flexibility, suggesting weak trophic links to the metabolism of chemosynthetic primary producers. At the community level, a comparison of SIA-derived metrics between mussel assemblages from two vent fields (Menez Gwen & Lucky Strike) showed that the functional structure of food webs was highly similar in terms of basal niche diversification, functional specialization and redundancy. Coupling SIA to functional trait approaches included more variability within the analyses, but the functional structures were still highly comparable. These results suggest that despite variable environmental conditions (physico-chemical factors and basal sources) and faunal community structure, functional complexity remained relatively constant among mussel assemblages. This functional similarity may be favoured by the propensity of species to adapt to fluid variations and practise trophic flexibility. Furthermore, the different pools of species at vent fields may play similar functions in the community such as the change in composition does not affect the overall functional structure. Finally, the absence of a relationship between the functional structure and taxonomic diversity as well as the high overlap between species' isotopic niches within communities indicates that co-occuring species may have redundant functions. Therefore, the addition of species within in a functional group does not necessarily lead to more complexity. Overall, this study highlights the complexity of food webs within chemosynthetic communities and emphasizes the need to better characterize species' ecological niches and biotic interactions.
Mesoscopic Community Structure of Financial Markets Revealed by Price and Sign Fluctuations
Almog, Assaf; Besamusca, Ferry; MacMahon, Mel; Garlaschelli, Diego
2015-01-01
The mesoscopic organization of complex systems, from financial markets to the brain, is an intermediate between the microscopic dynamics of individual units (stocks or neurons, in the mentioned cases), and the macroscopic dynamics of the system as a whole. The organization is determined by “communities” of units whose dynamics, represented by time series of activity, is more strongly correlated internally than with the rest of the system. Recent studies have shown that the binary projections of various financial and neural time series exhibit nontrivial dynamical features that resemble those of the original data. This implies that a significant piece of information is encoded into the binary projection (i.e. the sign) of such increments. Here, we explore whether the binary signatures of multiple time series can replicate the same complex community organization of the financial market, as the original weighted time series. We adopt a method that has been specifically designed to detect communities from cross-correlation matrices of time series data. Our analysis shows that the simpler binary representation leads to a community structure that is almost identical with that obtained using the full weighted representation. These results confirm that binary projections of financial time series contain significant structural information. PMID:26226226
A Stochastic Model for Detecting Overlapping and Hierarchical Community Structure
Cao, Xiaochun; Wang, Xiao; Jin, Di; Guo, Xiaojie; Tang, Xianchao
2015-01-01
Community detection is a fundamental problem in the analysis of complex networks. Recently, many researchers have concentrated on the detection of overlapping communities, where a vertex may belong to more than one community. However, most current methods require the number (or the size) of the communities as a priori information, which is usually unavailable in real-world networks. Thus, a practical algorithm should not only find the overlapping community structure, but also automatically determine the number of communities. Furthermore, it is preferable if this method is able to reveal the hierarchical structure of networks as well. In this work, we firstly propose a generative model that employs a nonnegative matrix factorization (NMF) formulization with a l2,1 norm regularization term, balanced by a resolution parameter. The NMF has the nature that provides overlapping community structure by assigning soft membership variables to each vertex; the l2,1 regularization term is a technique of group sparsity which can automatically determine the number of communities by penalizing too many nonempty communities; and hence the resolution parameter enables us to explore the hierarchical structure of networks. Thereafter, we derive the multiplicative update rule to learn the model parameters, and offer the proof of its correctness. Finally, we test our approach on a variety of synthetic and real-world networks, and compare it with some state-of-the-art algorithms. The results validate the superior performance of our new method. PMID:25822148
A network function-based definition of communities in complex networks.
Chauhan, Sanjeev; Girvan, Michelle; Ott, Edward
2012-09-01
We consider an alternate definition of community structure that is functionally motivated. We define network community structure based on the function the network system is intended to perform. In particular, as a specific example of this approach, we consider communities whose function is enhanced by the ability to synchronize and/or by resilience to node failures. Previous work has shown that, in many cases, the largest eigenvalue of the network's adjacency matrix controls the onset of both synchronization and percolation processes. Thus, for networks whose functional performance is dependent on these processes, we propose a method that divides a given network into communities based on maximizing a function of the largest eigenvalues of the adjacency matrices of the resulting communities. We also explore the differences between the partitions obtained by our method and the modularity approach (which is based solely on consideration of network structure). We do this for several different classes of networks. We find that, in many cases, modularity-based partitions do almost as well as our function-based method in finding functional communities, even though modularity does not specifically incorporate consideration of function.
An Object-Oriented Approach to Writing Computational Electromagnetics Codes
NASA Technical Reports Server (NTRS)
Zimmerman, Martin; Mallasch, Paul G.
1996-01-01
Presently, most computer software development in the Computational Electromagnetics (CEM) community employs the structured programming paradigm, particularly using the Fortran language. Other segments of the software community began switching to an Object-Oriented Programming (OOP) paradigm in recent years to help ease design and development of highly complex codes. This paper examines design of a time-domain numerical analysis CEM code using the OOP paradigm, comparing OOP code and structured programming code in terms of software maintenance, portability, flexibility, and speed.
Emergence of a Communication System: International Sign
NASA Astrophysics Data System (ADS)
Rosenstock, Rachel
International Sign (henceforth IS) is a communication system that is used widely in the international Deaf Community. The present study is one of the first to research extensively the origin of both the IS lexicon and grammatical structures. Findings demonstrate that IS is both influenced by naturally evolved sign languages used in grown deaf communities (henceforth SLs) and relies heavily on iconic, universal structures. This paper shows that IS continues to develop from a simplistic iconic system into a conventionalized system with increasingly complex rules.
Development of Structural Geology and Tectonics Data System with Field and Lab Interface
NASA Astrophysics Data System (ADS)
Newman, J.; Tikoff, B.; Walker, J. D.; Good, J.; Michels, Z. D.; Ash, J.; Andrew, J.; Williams, R. T.; Richard, S. M.
2015-12-01
We have developed a prototype Data System for Structural Geology and Tectonics (SG&T). The goal of this effort is to enable recording and sharing data within the geoscience community, to encourage interdisciplinary research, and to facilitate the investigation of scientific questions that cannot currently be addressed. The development of the Data System emphasizes community input in order to build a system that encompasses the needs of researchers, in terms of data and usability. SG&T data is complex for a variety of reasons, including the wide range of temporal and spatial scales (many orders of magnitude each), the complex three-dimensional geometry of some geological structures, inherent spatial nature of the data, and the difficulty of making temporal inferences from spatial observations. To successful implement the step of developing a SG&T data system, we must simultaneously solve three problems: 1) How to digitize SG&T data; 2) How to design a software system that is applicable; and 3) How to construct a very flexible user interface. To address the first problem, we introduce the "Spot" concept, which allows tracking of hierarchical and spatial relations between structures at all scales, and will link map scale, mesoscale, and laboratory scale data. A Spot, in this sense, is analogous to the beam size of analytical equipment used for in situ analysis of rocks; it is the size over which a measurement or quantity is applicable. A Spot can be a single measurement, an aggregation of individual measurements, or even establish relationships between numerous other Spots. We address the second problem through the use of a Graph database to better preserve the myriad of potentially complex relationships. In order to construct a flexible user interface that follows a natural workflow, and that serves the needs of the community, we have begun the process of engaging the SG&T community in order to utilize the expertise of a large group of scientists to ensure the quality and usability of this data system. These activities have included Town Halls, subdiscipline-specific workshops to develop community standards, and pilot projects to test the data system in the field during the study of a variety of geologic structures.
Community detection in complex networks using deep auto-encoded extreme learning machine
NASA Astrophysics Data System (ADS)
Wang, Feifan; Zhang, Baihai; Chai, Senchun; Xia, Yuanqing
2018-06-01
Community detection has long been a fascinating topic in complex networks since the community structure usually unveils valuable information of interest. The prevalence and evolution of deep learning and neural networks have been pushing forward the advancement in various research fields and also provide us numerous useful and off the shelf techniques. In this paper, we put the cascaded stacked autoencoders and the unsupervised extreme learning machine (ELM) together in a two-level embedding process and propose a novel community detection algorithm. Extensive comparison experiments in circumstances of both synthetic and real-world networks manifest the advantages of the proposed algorithm. On one hand, it outperforms the k-means clustering in terms of the accuracy and stability thus benefiting from the determinate dimensions of the ELM block and the integration of sparsity restrictions. On the other hand, it endures smaller complexity than the spectral clustering method on account of the shrinkage in time spent on the eigenvalue decomposition procedure.
Segregation of the Anodic Microbial Communities in a Microbial Fuel Cell Cascade
Hodgson, Douglas M.; Smith, Ann; Dahale, Sonal; Stratford, James P.; Li, Jia V.; Grüning, André; Bushell, Michael E.; Marchesi, Julian R.; Avignone Rossa, C.
2016-01-01
Metabolic interactions within microbial communities are essential for the efficient degradation of complex organic compounds, and underpin natural phenomena driven by microorganisms, such as the recycling of carbon-, nitrogen-, and sulfur-containing molecules. These metabolic interactions ultimately determine the function, activity and stability of the community, and therefore their understanding would be essential to steer processes where microbial communities are involved. This is exploited in the design of microbial fuel cells (MFCs), bioelectrochemical devices that convert the chemical energy present in substrates into electrical energy through the metabolic activity of microorganisms, either single species or communities. In this work, we analyzed the evolution of the microbial community structure in a cascade of MFCs inoculated with an anaerobic microbial community and continuously fed with a complex medium. The analysis of the composition of the anodic communities revealed the establishment of different communities in the anodes of the hydraulically connected MFCs, with a decrease in the abundance of fermentative taxa and a concurrent increase in respiratory taxa along the cascade. The analysis of the metabolites in the anodic suspension showed a metabolic shift between the first and last MFC, confirming the segregation of the anodic communities. Those results suggest a metabolic interaction mechanism between the predominant fermentative bacteria at the first stages of the cascade and the anaerobic respiratory electrogenic population in the latter stages, which is reflected in the observed increase in power output. We show that our experimental system represents an ideal platform for optimization of processes where the degradation of complex substrates is involved, as well as a potential tool for the study of metabolic interactions in complex microbial communities. PMID:27242723
Social significance of community structure: Statistical view
NASA Astrophysics Data System (ADS)
Li, Hui-Jia; Daniels, Jasmine J.
2015-01-01
Community structure analysis is a powerful tool for social networks that can simplify their topological and functional analysis considerably. However, since community detection methods have random factors and real social networks obtained from complex systems always contain error edges, evaluating the significance of a partitioned community structure is an urgent and important question. In this paper, integrating the specific characteristics of real society, we present a framework to analyze the significance of a social community. The dynamics of social interactions are modeled by identifying social leaders and corresponding hierarchical structures. Instead of a direct comparison with the average outcome of a random model, we compute the similarity of a given node with the leader by the number of common neighbors. To determine the membership vector, an efficient community detection algorithm is proposed based on the position of the nodes and their corresponding leaders. Then, using a log-likelihood score, the tightness of the community can be derived. Based on the distribution of community tightness, we establish a connection between p -value theory and network analysis, and then we obtain a significance measure of statistical form . Finally, the framework is applied to both benchmark networks and real social networks. Experimental results show that our work can be used in many fields, such as determining the optimal number of communities, analyzing the social significance of a given community, comparing the performance among various algorithms, etc.
A multiomics approach to study the microbiome response to phytoplankton blooms.
Song, Liyan
2017-06-01
Phytoplankton blooms are predictable features of marine and freshwater habitats. Despite a good knowledge base of the environmental factors controlling blooms, complex interactions between the bacterial and archaeal communities and phytoplankton bloom taxa are only now emerging. Here, the current research on bacterial community's structural and functional response to phytoplankton blooms is reviewed and discussed and further research is proposed. More attention should be paid on structure and function of autotrophic bacteria and archaea during phytoplankton blooms. A multiomics integration approach is needed to investigate bacterial and archaeal communities' diversity, metabolic diversity, and biogeochemical functions of microbial interactions during phytoplankton blooms.
Latif, Asam; Waring, Justin; Watmough, Deborah; Barber, Nick; Chuter, Anthony; Davies, James; Salema, Nde-Eshimuni; Boyd, Matthew J; Elliott, Rachel A
Community pharmacies are increasingly commissioned to deliver new, complex health interventions in response to the growing demands on family doctors and secondary health care services. Little is known about how these complex interventions are being accommodated and translated into the community pharmacy setting and whether their aims and objectives are realized in practice. The New Medicine Service (NMS) is a complex medicine management intervention that aims to support patients' adherence to newly prescribed medicines for a long-term condition. This study explores the recent implementation of the NMS in community pharmacies across England. It also seeks to understand how the service is becoming manifest in practice and what lessons can be learned for future service implementation. Structured, organizational ethnographic observations and in situ workplace interviews with pharmacists and support staff were undertaken within 23 English community pharmacies. Additionally, one-to-one, semi-structured interviews were carried out with 47 community pharmacists and 11 general practitioners (GPs). Observational and interview data were transcribed and analyzed thematically and guided by Damschroder's consolidated framework for implementation research. The NMS workload had been implemented and absorbed into pharmacists' daily routines alongside existing responsibilities with no extra resources and little evidence of reduction in other responsibilities. Pharmacists were pragmatic, simplifying, and adapting the NMS to facilitate its delivery and using discretion to circumvent perceived non-essential paperwork. Pharmacist understanding of the NMS was found to impact on what they believed should be achieved from the service. Despite pharmacists holding positive views about the value of the NMS, not all were convinced of its perceived benefits and necessity, with reports that many consultations did not identify any problems with the patients' medicines. GPs were generally supportive of the initiative but were unaware of the service or potential benefits. Poorly developed existing pharmacist-GP relationships impeded implementation. This study identifies the multifaceted and complex processes involved in implementing a new community pharmacy service in England. Community pharmacy workflow, infrastructure, and public and professional relationships all affect NMS implementation. Greater prior engagement with the pharmacy workforce and GPs, robust piloting and a phased rollout together with ongoing support and updates, are potentials strategies to ensure future implementation of pharmacy services meet their intended aims in practice. Copyright © 2015 Elsevier Inc. All rights reserved.
Epidemic spreading in time-varying community networks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ren, Guangming, E-mail: wangxy@dlut.edu.cn, E-mail: ren-guang-ming@163.com; Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024; Wang, Xingyuan, E-mail: wangxy@dlut.edu.cn, E-mail: ren-guang-ming@163.com
2014-06-15
The spreading processes of many infectious diseases have comparable time scale as the network evolution. Here, we present a simple networks model with time-varying community structure, and investigate susceptible-infected-susceptible epidemic spreading processes in this model. By both theoretic analysis and numerical simulations, we show that the efficiency of epidemic spreading in this model depends intensively on the mobility rate q of the individuals among communities. We also find that there exists a mobility rate threshold q{sub c}. The epidemic will survive when q > q{sub c} and die when q < q{sub c}. These results can help understanding the impacts of human travel onmore » the epidemic spreading in complex networks with community structure.« less
Stochastic Blockmodeling of the Modules and Core of the Caenorhabditis elegans Connectome
Pavlovic, Dragana M.; Vértes, Petra E.; Bullmore, Edward T.; Schafer, William R.; Nichols, Thomas E.
2014-01-01
Recently, there has been much interest in the community structure or mesoscale organization of complex networks. This structure is characterised either as a set of sparsely inter-connected modules or as a highly connected core with a sparsely connected periphery. However, it is often difficult to disambiguate these two types of mesoscale structure or, indeed, to summarise the full network in terms of the relationships between its mesoscale constituents. Here, we estimate a community structure with a stochastic blockmodel approach, the Erdős-Rényi Mixture Model, and compare it to the much more widely used deterministic methods, such as the Louvain and Spectral algorithms. We used the Caenorhabditis elegans (C. elegans) nervous system (connectome) as a model system in which biological knowledge about each node or neuron can be used to validate the functional relevance of the communities obtained. The deterministic algorithms derived communities with 4–5 modules, defined by sparse inter-connectivity between all modules. In contrast, the stochastic Erdős-Rényi Mixture Model estimated a community with 9 blocks or groups which comprised a similar set of modules but also included a clearly defined core, made of 2 small groups. We show that the “core-in-modules” decomposition of the worm brain network, estimated by the Erdős-Rényi Mixture Model, is more compatible with prior biological knowledge about the C. elegans nervous system than the purely modular decomposition defined deterministically. We also show that the blockmodel can be used both to generate stochastic realisations (simulations) of the biological connectome, and to compress network into a small number of super-nodes and their connectivity. We expect that the Erdős-Rényi Mixture Model may be useful for investigating the complex community structures in other (nervous) systems. PMID:24988196
Rapid evolution of hosts begets species diversity at the cost of intraspecific diversity
Frickel, Jens; Theodosiou, Loukas
2017-01-01
Ecosystems are complex food webs in which multiple species interact and ecological and evolutionary processes continuously shape populations and communities. Previous studies on eco-evolutionary dynamics have shown that the presence of intraspecific diversity affects community structure and function, and that eco-evolutionary feedback dynamics can be an important driver for its maintenance. Within communities, feedbacks are, however, often indirect, and they can feed back over many generations. Here, we studied eco-evolutionary feedbacks in evolving communities over many generations and compared two-species systems (virus–host and prey–predator) with a more complex three-species system (virus–host–predator). Both indirect density- and trait-mediated effects drove the dynamics in the complex system, where host–virus coevolution facilitated coexistence of predator and virus, and where coexistence, in return, lowered intraspecific diversity of the host population. Furthermore, ecological and evolutionary dynamics were significantly altered in the three-species system compared with the two-species systems. We found that the predator slowed host–virus coevolution in the complex system and that the virus’ effect on the overall population dynamics was negligible when the three species coexisted. Overall, we show that a detailed understanding of the mechanism driving eco-evolutionary feedback dynamics is necessary for explaining trait and species diversity in communities, even in communities with only three species. PMID:28973943
Graham, Emily B.; Knelman, Joseph E.; Schindlbacher, Andreas; ...
2016-02-24
In this study, microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of processmore » rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Graham, Emily B.; Knelman, Joseph E.; Schindlbacher, Andreas
In this study, microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of processmore » rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.« less
Graham, Emily B.; Knelman, Joseph E.; Schindlbacher, Andreas; Siciliano, Steven; Breulmann, Marc; Yannarell, Anthony; Beman, J. M.; Abell, Guy; Philippot, Laurent; Prosser, James; Foulquier, Arnaud; Yuste, Jorge C.; Glanville, Helen C.; Jones, Davey L.; Angel, Roey; Salminen, Janne; Newton, Ryan J.; Bürgmann, Helmut; Ingram, Lachlan J.; Hamer, Ute; Siljanen, Henri M. P.; Peltoniemi, Krista; Potthast, Karin; Bañeras, Lluís; Hartmann, Martin; Banerjee, Samiran; Yu, Ri-Qing; Nogaro, Geraldine; Richter, Andreas; Koranda, Marianne; Castle, Sarah C.; Goberna, Marta; Song, Bongkeun; Chatterjee, Amitava; Nunes, Olga C.; Lopes, Ana R.; Cao, Yiping; Kaisermann, Aurore; Hallin, Sara; Strickland, Michael S.; Garcia-Pausas, Jordi; Barba, Josep; Kang, Hojeong; Isobe, Kazuo; Papaspyrou, Sokratis; Pastorelli, Roberta; Lagomarsino, Alessandra; Lindström, Eva S.; Basiliko, Nathan; Nemergut, Diana R.
2016-01-01
Microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology. PMID:26941732
Graham, Emily B; Knelman, Joseph E; Schindlbacher, Andreas; Siciliano, Steven; Breulmann, Marc; Yannarell, Anthony; Beman, J M; Abell, Guy; Philippot, Laurent; Prosser, James; Foulquier, Arnaud; Yuste, Jorge C; Glanville, Helen C; Jones, Davey L; Angel, Roey; Salminen, Janne; Newton, Ryan J; Bürgmann, Helmut; Ingram, Lachlan J; Hamer, Ute; Siljanen, Henri M P; Peltoniemi, Krista; Potthast, Karin; Bañeras, Lluís; Hartmann, Martin; Banerjee, Samiran; Yu, Ri-Qing; Nogaro, Geraldine; Richter, Andreas; Koranda, Marianne; Castle, Sarah C; Goberna, Marta; Song, Bongkeun; Chatterjee, Amitava; Nunes, Olga C; Lopes, Ana R; Cao, Yiping; Kaisermann, Aurore; Hallin, Sara; Strickland, Michael S; Garcia-Pausas, Jordi; Barba, Josep; Kang, Hojeong; Isobe, Kazuo; Papaspyrou, Sokratis; Pastorelli, Roberta; Lagomarsino, Alessandra; Lindström, Eva S; Basiliko, Nathan; Nemergut, Diana R
2016-01-01
Microorganisms are vital in mediating the earth's biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: 'When do we need to understand microbial community structure to accurately predict function?' We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.
ERIC Educational Resources Information Center
McCabe, Declan J.; Knight, Evelyn J.
2016-01-01
Since being introduced by Connor and Simberloff in response to Diamond's assembly rules, null model analysis has been a controversial tool in community ecology. Despite being commonly used in the primary literature, null model analysis has not featured prominently in general textbooks. Complexity of approaches along with difficulty in interpreting…
Fabricius, K E; De'ath, G; Noonan, S; Uthicke, S
2014-01-22
The ecological effects of ocean acidification (OA) from rising atmospheric carbon dioxide (CO2) on benthic marine communities are largely unknown. We investigated in situ the consequences of long-term exposure to high CO2 on coral-reef-associated macroinvertebrate communities around three shallow volcanic CO2 seeps in Papua New Guinea. The densities of many groups and the number of taxa (classes and phyla) of macroinvertebrates were significantly reduced at elevated CO2 (425-1100 µatm) compared with control sites. However, sensitivities of some groups, including decapod crustaceans, ascidians and several echinoderms, contrasted with predictions of their physiological CO2 tolerances derived from laboratory experiments. High CO2 reduced the availability of structurally complex corals that are essential refugia for many reef-associated macroinvertebrates. This loss of habitat complexity was also associated with losses in many macroinvertebrate groups, especially predation-prone mobile taxa, including crustaceans and crinoids. The transition from living to dead coral as substratum and habitat further altered macroinvertebrate communities, with far more taxa losing than gaining in numbers. Our study shows that indirect ecological effects of OA (reduced habitat complexity) will complement its direct physiological effects and together with the loss of coral cover through climate change will severely affect macroinvertebrate communities in coral reefs.
Fabricius, K. E.; De'ath, G.; Noonan, S.; Uthicke, S.
2014-01-01
The ecological effects of ocean acidification (OA) from rising atmospheric carbon dioxide (CO2) on benthic marine communities are largely unknown. We investigated in situ the consequences of long-term exposure to high CO2 on coral-reef-associated macroinvertebrate communities around three shallow volcanic CO2 seeps in Papua New Guinea. The densities of many groups and the number of taxa (classes and phyla) of macroinvertebrates were significantly reduced at elevated CO2 (425–1100 µatm) compared with control sites. However, sensitivities of some groups, including decapod crustaceans, ascidians and several echinoderms, contrasted with predictions of their physiological CO2 tolerances derived from laboratory experiments. High CO2 reduced the availability of structurally complex corals that are essential refugia for many reef-associated macroinvertebrates. This loss of habitat complexity was also associated with losses in many macroinvertebrate groups, especially predation-prone mobile taxa, including crustaceans and crinoids. The transition from living to dead coral as substratum and habitat further altered macroinvertebrate communities, with far more taxa losing than gaining in numbers. Our study shows that indirect ecological effects of OA (reduced habitat complexity) will complement its direct physiological effects and together with the loss of coral cover through climate change will severely affect macroinvertebrate communities in coral reefs. PMID:24307670
Use of the intestinal parasite community of Sigmodon hispidus as a biomonitor in terrestrial systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Faulkner, B.C.; Lochmiller, R.L.
1995-12-31
The goal of this study was to assess the potential usefulness of parasite communities of small mammals as an endpoint for community level risk assessment in terrestrial ecosystems. A total of 350 wild cotton rats (Sigmodon hispidus) were collected from a Superfund site in southwestern Oklahoma between fall 1993 and fall 1995. Three contaminated study sites, representing common petrochemical disposal methods and all containing complex mixtures of contaminants, including arsenic, lead, fluoride, phenols, and hydrocarbons, were monitored seasonally. Animals were collected and gastrointestinal contents were examined grossly and microscopically for helminths and coccidial parasites. All parasites were identified to speciesmore » and enumerated so that measurable alterations of the parasite community structure could be established. The authors also sampled possible intermediate host communities concurrently with Sigmodon collections. Structural characteristics of the parasite communities were compared between replicated toxic and reference study sites.« less
Ramirez, Kelly S; Knight, Christopher G; de Hollander, Mattias; Brearley, Francis Q; Constantinides, Bede; Cotton, Anne; Creer, Si; Crowther, Thomas W; Davison, John; Delgado-Baquerizo, Manuel; Dorrepaal, Ellen; Elliott, David R; Fox, Graeme; Griffiths, Robert I; Hale, Chris; Hartman, Kyle; Houlden, Ashley; Jones, David L; Krab, Eveline J; Maestre, Fernando T; McGuire, Krista L; Monteux, Sylvain; Orr, Caroline H; van der Putten, Wim H; Roberts, Ian S; Robinson, David A; Rocca, Jennifer D; Rowntree, Jennifer; Schlaeppi, Klaus; Shepherd, Matthew; Singh, Brajesh K; Straathof, Angela L; Bhatnagar, Jennifer M; Thion, Cécile; van der Heijden, Marcel G A; de Vries, Franciska T
2018-02-01
The emergence of high-throughput DNA sequencing methods provides unprecedented opportunities to further unravel bacterial biodiversity and its worldwide role from human health to ecosystem functioning. However, despite the abundance of sequencing studies, combining data from multiple individual studies to address macroecological questions of bacterial diversity remains methodically challenging and plagued with biases. Here, using a machine-learning approach that accounts for differences among studies and complex interactions among taxa, we merge 30 independent bacterial data sets comprising 1,998 soil samples from 21 countries. Whereas previous meta-analysis efforts have focused on bacterial diversity measures or abundances of major taxa, we show that disparate amplicon sequence data can be combined at the taxonomy-based level to assess bacterial community structure. We find that rarer taxa are more important for structuring soil communities than abundant taxa, and that these rarer taxa are better predictors of community structure than environmental factors, which are often confounded across studies. We conclude that combining data from independent studies can be used to explore bacterial community dynamics, identify potential 'indicator' taxa with an important role in structuring communities, and propose hypotheses on the factors that shape bacterial biogeography that have been overlooked in the past.
Acidobacteria appear to dominate the microbiome of two sympatric Caribbean Sponges and one Zoanthid.
O'Connor-Sánchez, Aileen; Rivera-Domínguez, Adán J; Santos-Briones, César de los; López-Aguiar, Lluvia K; Peña-Ramírez, Yuri J; Prieto-Davo, Alejandra
2014-12-10
Marine invertebrate-associated microbial communities are interesting examples of complex symbiotic systems and are a potential source of biotechnological products. In this work, pyrosequencing-based assessment from bacterial community structures of sediments, two sponges, and one zoanthid collected in the Mexican Caribbean was performed. The results suggest that the bacterial diversity at the species level is higher in the sediments than in the animal samples. Analysis of bacterial communities' structure showed that about two thirds of the bacterial diversity in all the samples belongs to the phyla Acidobacteria and Proteobacteria. The genus Acidobacterium appears to dominate the bacterial community in all the samples, reaching almost 80% in the sponge Hyrtios. Our evidence suggests that the sympatric location of these benthonic species may lead to common bacterial structure features among their bacterial communities. The results may serve as a first insight to formulate hypotheses that lead to more extensive studies of sessile marine organisms' microbiomes from the Mexican Caribbean.
Accelerating the Mining of Influential Nodes in Complex Networks through Community Detection
DOE Office of Scientific and Technical Information (OSTI.GOV)
Halappanavar, Mahantesh; Sathanur, Arun V.; Nandi, Apurba
Computing the set of influential nodes with a given size to ensure maximal spread of influence on a complex network is a challenging problem impacting multiple applications. A rigorous approach to influence maximization involves utilization of optimization routines that comes with a high computational cost. In this work, we propose to exploit the existence of communities in complex networks to accelerate the mining of influential seeds. We provide intuitive reasoning to explain why our approach should be able to provide speedups without significantly degrading the extent of the spread of influence when compared to the case of influence maximization withoutmore » using the community information. Additionally, we have parallelized the complete workflow by leveraging an existing parallel implementation of the Louvain community detection algorithm. We then conduct a series of experiments on a dataset with three representative graphs to first verify our implementation and then demonstrate the speedups. Our method achieves speedups ranging from 3x - 28x for graphs with small number of communities while nearly matching or even exceeding the activation performance on the entire graph. Complexity analysis reveals that dramatic speedups are possible for larger graphs that contain a correspondingly larger number of communities. In addition to the speedups obtained from the utilization of the community structure, scalability results show up to 6.3x speedup on 20 cores relative to the baseline run on 2 cores. Finally, current limitations of the approach are outlined along with the planned next steps.« less
Plant structure predicts leaf litter capture in the tropical montane bromeliad Tillandsia turneri.
Ospina-Bautista, F; Estévez Varón, J V
2016-05-03
Leaves intercepted by bromeliads become an important energy and matter resource for invertebrate communities, bacteria, fungi, and the plant itself. The relationship between bromeliad structure, defined as its size and complexity, and accumulated leaf litter was studied in 55 bromeliads of Tillandsia turneri through multiple regression and the Akaike information criterion. Leaf litter accumulation in bromeliads was best explained by size and complexity variables such as plant cover, sheath length, and leaf number. In conclusion, plant structure determines the amount of litter that enters bromeliads, and changes in its structure could affect important processes within ecosystem functioning or species richness.
Water regime history drives responses of soil Namib Desert microbial communities to wetting events
NASA Astrophysics Data System (ADS)
Frossard, Aline; Ramond, Jean-Baptiste; Seely, Mary; Cowan, Don A.
2015-07-01
Despite the dominance of microorganisms in arid soils, the structures and functional dynamics of microbial communities in hot deserts remain largely unresolved. The effects of wetting event frequency and intensity on Namib Desert microbial communities from two soils with different water-regime histories were tested over 36 days. A total of 168 soil microcosms received wetting events mimicking fog, light rain and heavy rainfall, with a parallel “dry condition” control. T-RFLP data showed that the different wetting events affected desert microbial community structures, but these effects were attenuated by the effects related to the long-term adaptation of both fungal and bacterial communities to soil origins (i.e. soil water regime histories). The intensity of the water pulses (i.e. the amount of water added) rather than the frequency of wetting events had greatest effect in shaping bacterial and fungal community structures. In contrast to microbial diversity, microbial activities (enzyme activities) showed very little response to the wetting events and were mainly driven by soil origin. This experiment clearly demonstrates the complexity of microbial community responses to wetting events in hyperarid hot desert soil ecosystems and underlines the dynamism of their indigenous microbial communities.
Water regime history drives responses of soil Namib Desert microbial communities to wetting events.
Frossard, Aline; Ramond, Jean-Baptiste; Seely, Mary; Cowan, Don A
2015-07-21
Despite the dominance of microorganisms in arid soils, the structures and functional dynamics of microbial communities in hot deserts remain largely unresolved. The effects of wetting event frequency and intensity on Namib Desert microbial communities from two soils with different water-regime histories were tested over 36 days. A total of 168 soil microcosms received wetting events mimicking fog, light rain and heavy rainfall, with a parallel "dry condition" control. T-RFLP data showed that the different wetting events affected desert microbial community structures, but these effects were attenuated by the effects related to the long-term adaptation of both fungal and bacterial communities to soil origins (i.e. soil water regime histories). The intensity of the water pulses (i.e. the amount of water added) rather than the frequency of wetting events had greatest effect in shaping bacterial and fungal community structures. In contrast to microbial diversity, microbial activities (enzyme activities) showed very little response to the wetting events and were mainly driven by soil origin. This experiment clearly demonstrates the complexity of microbial community responses to wetting events in hyperarid hot desert soil ecosystems and underlines the dynamism of their indigenous microbial communities.
Detection of communities with Naming Game-based methods
Ribeiro, Carlos Henrique Costa
2017-01-01
Complex networks are often organized in groups or communities of agents that share the same features and/or functions, and this structural organization is built naturally with the formation of the system. In social networks, we argue that the dynamic of linguistic interactions of agreement among people can be a crucial factor in generating this community structure, given that sharing opinions with another person bounds them together, and disagreeing constantly would probably weaken the relationship. We present here a computational model of opinion exchange that uncovers the community structure of a network. Our aim is not to present a new community detection method proper, but to show how a model of social communication dynamics can reveal the (simple and overlapping) community structure in an emergent way. Our model is based on a standard Naming Game, but takes into consideration three social features: trust, uncertainty and opinion preference, that are built over time as agents communicate among themselves. We show that the separate addition of each social feature in the Naming Game results in gradual improvements with respect to community detection. In addition, the resulting uncertainty and trust values classify nodes and edges according to role and position in the network. Also, our model has shown a degree of accuracy both for non-overlapping and overlapping communities that are comparable with most algorithms specifically designed for topological community detection. PMID:28797097
A Spatially Continuous Model of Carbohydrate Digestion and Transport Processes in the Colon
Moorthy, Arun S.; Brooks, Stephen P. J.; Kalmokoff, Martin; Eberl, Hermann J.
2015-01-01
A spatially continuous mathematical model of transport processes, anaerobic digestion and microbial complexity as would be expected in the human colon is presented. The model is a system of first-order partial differential equations with context determined number of dependent variables, and stiff, non-linear source terms. Numerical simulation of the model is used to elucidate information about the colon-microbiota complex. It is found that the composition of materials on outflow of the model does not well-describe the composition of material in other model locations, and inferences using outflow data varies according to model reactor representation. Additionally, increased microbial complexity allows the total microbial community to withstand major system perturbations in diet and community structure. However, distribution of strains and functional groups within the microbial community can be modified depending on perturbation length and microbial kinetic parameters. Preliminary model extensions and potential investigative opportunities using the computational model are discussed. PMID:26680208
Differences in Intertidal Microbial Assemblages on Urban Structures and Natural Rocky Reef
Tan, Elisa L.-Y.; Mayer-Pinto, Mariana; Johnston, Emma L.; Dafforn, Katherine A.
2015-01-01
Global seascapes are increasingly modified to support high levels of human activity in the coastal zone. Modifications include the addition of defense structures and boating infrastructure, such as seawalls and marinas that replace natural habitats. Artificial structures support different macrofaunal communities to those found on natural rocky shores; however, little is known about differences in microbial community structure or function in urban seascapes. Understanding how artificial constructions in marine environments influence microbial communities is important as these assemblages contribute to many basic ecological processes. In this study, the bacterial communities of intertidal biofilms were compared between artificial structures (seawalls) and natural habitats (rocky shores) within Sydney Harbour. Plots were cleared on each type of habitat at eight locations. After 3 weeks the newly formed biofilm was sampled and the 16S rRNA gene sequenced using the Illumina Miseq platform. To account for differences in orientation and substrate material between seawalls and rocky shores that might have influenced our survey, we also deployed recruitment blocks next to the habitats at all locations for 3 weeks and then sampled and sequenced their microbial communities. Intertidal bacterial community structure sampled from plots differed between seawalls and rocky shores, but when substrate material, age and orientation were kept constant (with recruitment blocks) then bacterial communities were similar in composition and structure among habitats. This suggests that changes in bacterial communities on seawalls are not related to environmental differences between locations, but may be related to other intrinsic factors that differ between the habitats such as orientation, complexity, or predation. This is one of the first comparisons of intertidal microbial communities on natural and artificial surfaces and illustrates substantial ecological differences with potential consequences for biofilm function and the recruitment of macrofauna. PMID:26635747
Kelaher, B P
2003-05-01
The physical structure of a habitat generally has a strong influence on the diversity and abundance of associated organisms. I investigated the role of coralline algal turf structure in determining spatial variation of gastropod assemblages at different tidal heights of a rocky shore near Sydney, Australia. The structural characteristics of algal turf tested were frond density (or structural complexity) and frond length (the vertical scale over which structural complexity was measured). This definition of structural complexity assumes that complexity of the habitat increases with increasing frond density. While frond length was unrelated to gastropod community structure, I found significant correlations between density of fronds and multivariate and univariate measures of gastropod assemblages, indicating the importance of structural complexity. In contrast to previous studies, here there were negative relationships between the density of fronds and the richness and abundance of gastropods. Artificial habitat mimics were used to manipulate the density of fronds to test the hypothesis that increasing algal structural complexity decreases the richness and abundance of gastropods. As predicted, there were significantly more species of gastropods in loosely packed than in tightly packed turf at both low- and mid-shore levels. Despite large differences between gastropod assemblages at different tidal heights, the direction and magnitude of these negative effects were similar at low- and mid-shore levels and, therefore, relatively independent of local environmental conditions. These novel results extend our previous understanding of the ecological effects of habitat structure because they demonstrate possible limitations of commonly used definitions of structural complexity, as well as distinct upper thresholds in the relationship between structural complexity and faunal species richness.
NASA Astrophysics Data System (ADS)
Maron, Pierre-Alain; Lejon, David P. H.; Carvalho, Esmeralda; Bizet, Karine; Lemanceau, Philippe; Ranjard, Lionel; Mougel, Christophe
The density, genetic structure and diversity of airborne bacterial communities were assessed in the outdoor atmosphere. Two air samples were collected on the same location (north of France) at two dates (March 2003 (sample1) and May 2003 (sample 2)). Molecular culture -independent methods were used to characterise airborne bacterial communities regardless of the cell culturability. The automated-ribosomal intergenic spacer analysis (A-RISA) was performed to characterise the community structure in each sample. For both sampling dates, complex A-RISA patterns were observed suggesting a highly diverse community structure, comparable to those found in soil, water or sediment environments. Furthermore, differences in the genetic structure of airborne bacterial communities were observed between samples 1 and 2 suggesting an important variability in time. A clone library of 16S rDNA directly amplified from air DNA of sample 1 was constructed and sequenced to analyse the community composition and diversity. The Proteobacteria group had the greatest representation (60%), with bacteria belonging to the different subdivisions α- (19%), β-(21%), γ-(12%) and δ-(8%). Firmicute and Actinobacteria were also well represented with 14% and 12%, respectively. Most of the identified bacteria are known to be commonly associated with soil or plant environments suggesting that the atmosphere is mainly colonised transiently by microorganisms from local sources, depending on air fluxes.
A novel community detection method in bipartite networks
NASA Astrophysics Data System (ADS)
Zhou, Cangqi; Feng, Liang; Zhao, Qianchuan
2018-02-01
Community structure is a common and important feature in many complex networks, including bipartite networks, which are used as a standard model for many empirical networks comprised of two types of nodes. In this paper, we propose a two-stage method for detecting community structure in bipartite networks. Firstly, we extend the widely-used Louvain algorithm to bipartite networks. The effectiveness and efficiency of the Louvain algorithm have been proved by many applications. However, there lacks a Louvain-like algorithm specially modified for bipartite networks. Based on bipartite modularity, a measure that extends unipartite modularity and that quantifies the strength of partitions in bipartite networks, we fill the gap by developing the Bi-Louvain algorithm that iteratively groups the nodes in each part by turns. This algorithm in bipartite networks often produces a balanced network structure with equal numbers of two types of nodes. Secondly, for the balanced network yielded by the first algorithm, we use an agglomerative clustering method to further cluster the network. We demonstrate that the calculation of the gain of modularity of each aggregation, and the operation of joining two communities can be compactly calculated by matrix operations for all pairs of communities simultaneously. At last, a complete hierarchical community structure is unfolded. We apply our method to two benchmark data sets and a large-scale data set from an e-commerce company, showing that it effectively identifies community structure in bipartite networks.
Clustering algorithm for determining community structure in large networks
NASA Astrophysics Data System (ADS)
Pujol, Josep M.; Béjar, Javier; Delgado, Jordi
2006-07-01
We propose an algorithm to find the community structure in complex networks based on the combination of spectral analysis and modularity optimization. The clustering produced by our algorithm is as accurate as the best algorithms on the literature of modularity optimization; however, the main asset of the algorithm is its efficiency. The best match for our algorithm is Newman’s fast algorithm, which is the reference algorithm for clustering in large networks due to its efficiency. When both algorithms are compared, our algorithm outperforms the fast algorithm both in efficiency and accuracy of the clustering, in terms of modularity. Thus, the results suggest that the proposed algorithm is a good choice to analyze the community structure of medium and large networks in the range of tens and hundreds of thousand vertices.
Deterministic Assembly of Complex Bacterial Communities in Guts of Germ-Free Cockroaches
Mikaelyan, Aram; Thompson, Claire L.; Hofer, Markus J.
2015-01-01
The gut microbiota of termites plays important roles in the symbiotic digestion of lignocellulose. However, the factors shaping the microbial community structure remain poorly understood. Because termites cannot be raised under axenic conditions, we established the closely related cockroach Shelfordella lateralis as a germ-free model to study microbial community assembly and host-microbe interactions. In this study, we determined the composition of the bacterial assemblages in cockroaches inoculated with the gut microbiota of termites and mice using pyrosequencing analysis of their 16S rRNA genes. Although the composition of the xenobiotic communities was influenced by the lineages present in the foreign inocula, their structure resembled that of conventional cockroaches. Bacterial taxa abundant in conventional cockroaches but rare in the foreign inocula, such as Dysgonomonas and Parabacteroides spp., were selectively enriched in the xenobiotic communities. Donor-specific taxa, such as endomicrobia or spirochete lineages restricted to the gut microbiota of termites, however, either were unable to colonize germ-free cockroaches or formed only small populations. The exposure of xenobiotic cockroaches to conventional adults restored their normal microbiota, which indicated that autochthonous lineages outcompete foreign ones. Our results provide experimental proof that the assembly of a complex gut microbiota in insects is deterministic. PMID:26655763
Baggio, Jacopo A; BurnSilver, Shauna B; Arenas, Alex; Magdanz, James S; Kofinas, Gary P; De Domenico, Manlio
2016-11-29
Network analysis provides a powerful tool to analyze complex influences of social and ecological structures on community and household dynamics. Most network studies of social-ecological systems use simple, undirected, unweighted networks. We analyze multiplex, directed, and weighted networks of subsistence food flows collected in three small indigenous communities in Arctic Alaska potentially facing substantial economic and ecological changes. Our analysis of plausible future scenarios suggests that changes to social relations and key households have greater effects on community robustness than changes to specific wild food resources.
Voting behavior, coalitions and government strength through a complex network analysis.
Dal Maso, Carlo; Pompa, Gabriele; Puliga, Michelangelo; Riotta, Gianni; Chessa, Alessandro
2014-01-01
We analyze the network of relations between parliament members according to their voting behavior. In particular, we examine the emergent community structure with respect to political coalitions and government alliances. We rely on tools developed in the Complex Network literature to explore the core of these communities and use their topological features to develop new metrics for party polarization, internal coalition cohesiveness and government strength. As a case study, we focus on the Chamber of Deputies of the Italian Parliament, for which we are able to characterize the heterogeneity of the ruling coalition as well as parties specific contributions to the stability of the government over time. We find sharp contrast in the political debate which surprisingly does not imply a relevant structure based on established parties. We take a closer look to changes in the community structure after parties split up and their effect on the position of single deputies within communities. Finally, we introduce a way to track the stability of the government coalition over time that is able to discern the contribution of each member along with the impact of its possible defection. While our case study relies on the Italian parliament, whose relevance has come into the international spotlight in the present economic downturn, the methods developed here are entirely general and can therefore be applied to a multitude of other scenarios.
Combined node and link partitions method for finding overlapping communities in complex networks
Jin, Di; Gabrys, Bogdan; Dang, Jianwu
2015-01-01
Community detection in complex networks is a fundamental data analysis task in various domains, and how to effectively find overlapping communities in real applications is still a challenge. In this work, we propose a new unified model and method for finding the best overlapping communities on the basis of the associated node and link partitions derived from the same framework. Specifically, we first describe a unified model that accommodates node and link communities (partitions) together, and then present a nonnegative matrix factorization method to learn the parameters of the model. Thereafter, we infer the overlapping communities based on the derived node and link communities, i.e., determine each overlapped community between the corresponding node and link community with a greedy optimization of a local community function conductance. Finally, we introduce a model selection method based on consensus clustering to determine the number of communities. We have evaluated our method on both synthetic and real-world networks with ground-truths, and compared it with seven state-of-the-art methods. The experimental results demonstrate the superior performance of our method over the competing ones in detecting overlapping communities for all analysed data sets. Improved performance is particularly pronounced in cases of more complicated networked community structures. PMID:25715829
Hui Zhu; Deli Wang; Qinfeng Guo; Jun Liu; Ling Wang
2015-01-01
The structure and dynamics of insect community in grasslands can be influenced by grazing management via altered characteristics of plant community. However, attempts to better understand the complex relationships among plants, insects, and large herbivores is still hampered largely by the interactive effects of plants, insects, and large grazers on each other. In this...
NASA Astrophysics Data System (ADS)
Brad, Traian; Chiriac, Cecilia; Szekeres, Edina; Coman, Cristian; Rudi, Knut; Sandor, Mignon
2017-04-01
Twenty microcosm enclosures containing two types of soil (i.e. a rich Chernozemic and a poorer soil) were fertilized with mineral (NPK-complex) and organic (Gülle, manure and a green fertilizer) materials and placed under dry and wet water regimes. After 10, 20 and 30 days of the experiment, soil samples were analyzed for the structure and composition of microbial communities using next generation sequencing techniques (Illumina) and statistical analysis. The differences between bacteria communities in different soil types, and in different fertilization and hydric treatments were analyzed using quantitative phylogenetic distances and the ANOSIM test. The two types of soil especially selected for the structure of microbial communities, while moisture and the type of fertilizer appeared to have a smaller influence on microbial diversity in microcosms. The alpha-diversity indices (species richness, evenness and phylogenetic diversity) had higher values for the poorer soil compared to the rich Chernozemic soil. For both soil types, the highest bacteria diversity values were obtained after fertilization with manure. The microbial communities in the analyzed soils were complex and dominated by sequences belonging to Actinobacteria, Proteobacteria, Acidobacteria and Firmicutes.
The social structure of microbial community involved in colonization resistance.
He, Xuesong; McLean, Jeffrey S; Guo, Lihong; Lux, Renate; Shi, Wenyuan
2014-03-01
It is well established that host-associated microbial communities can interfere with the colonization and establishment of microbes of foreign origins, a phenomenon often referred to as bacterial interference or colonization resistance. However, due to the complexity of the indigenous microbiota, it has been extremely difficult to elucidate the community colonization resistance mechanisms and identify the bacterial species involved. In a recent study, we have established an in vitro mice oral microbial community (O-mix) and demonstrated its colonization resistance against an Escherichia coli strain of mice gut origin. In this study, we further analyzed the community structure of the O-mix by using a dilution/regrowth approach and identified the bacterial species involved in colonization resistance against E. coli. Our results revealed that, within the O-mix there were three different types of bacterial species forming unique social structure. They act as 'Sensor', 'Mediator' and 'Killer', respectively, and have coordinated roles in initiating the antagonistic action and preventing the integration of E. coli. The functional role of each identified bacterial species was further confirmed by E. coli-specific responsiveness of the synthetic communities composed of different combination of the identified players. The study reveals for the first time the sophisticated structural and functional organization of a colonization resistance pathway within a microbial community. Furthermore, our results emphasize the importance of 'Facilitation' or positive interactions in the development of community-level functions, such as colonization resistance.
Traveling salesman problems with PageRank Distance on complex networks reveal community structure
NASA Astrophysics Data System (ADS)
Jiang, Zhongzhou; Liu, Jing; Wang, Shuai
2016-12-01
In this paper, we propose a new algorithm for community detection problems (CDPs) based on traveling salesman problems (TSPs), labeled as TSP-CDA. Since TSPs need to find a tour with minimum cost, cities close to each other are usually clustered in the tour. This inspired us to model CDPs as TSPs by taking each vertex as a city. Then, in the final tour, the vertices in the same community tend to cluster together, and the community structure can be obtained by cutting the tour into a couple of paths. There are two challenges. The first is to define a suitable distance between each pair of vertices which can reflect the probability that they belong to the same community. The second is to design a suitable strategy to cut the final tour into paths which can form communities. In TSP-CDA, we deal with these two challenges by defining a PageRank Distance and an automatic threshold-based cutting strategy. The PageRank Distance is designed with the intrinsic properties of CDPs in mind, and can be calculated efficiently. In the experiments, benchmark networks with 1000-10,000 nodes and varying structures are used to test the performance of TSP-CDA. A comparison is also made between TSP-CDA and two well-established community detection algorithms. The results show that TSP-CDA can find accurate community structure efficiently and outperforms the two existing algorithms.
Störmer, Rebecca; Wichels, Antje; Gerdts, Gunnar
2013-12-15
The dumping of dredged sediments represents a major stressor for coastal ecosystems. The impact on the ecosystem function is determined by its complexity not easy to assess. In the present study, we evaluated the potential of bacterial community analyses to act as ecological indicators in environmental monitoring programmes. We investigated the functional structure of bacterial communities, applying functional gene arrays (GeoChip4.2). The relationship between functional genes and environmental factors was analysed using distance-based multivariate multiple regression. Apparently, both the function and structure of the bacterial communities are impacted by dumping activities. The bacterial community at the dumping centre displayed a significant reduction of its entire functional diversity compared with that found at a reference site. DDX compounds separated bacterial communities of the dumping site from those of un-impacted sites. Thus, bacterial community analyses show great potential as ecological indicators in environmental monitoring. Copyright © 2013 Elsevier Ltd. All rights reserved.
Mohanty, Anee; Wu, Yichao; Cao, Bin
2014-10-01
In natural and engineered environments, microorganisms often exist as complex communities, which are key to the health of ecosystems and the success of bioprocesses in various engineering applications. With the rapid development of nanotechnology in recent years, engineered nanomaterials (ENMs) have been considered one type of emerging contaminants that pose great potential risks to the proper function of microbial communities in natural and engineered ecosystems. The impacts of ENMs on microorganisms have attracted increasing research attentions; however, most studies focused on the antimicrobial activities of ENMs at single cell and population level. Elucidating the influence of ENMs on microbial communities represents a critical step toward a comprehensive understanding of the ecotoxicity of ENMs. In this mini-review, we summarize and discuss recent research work on the impacts of ENMs on microbial communities in natural and engineered ecosystems, with an emphasis on their influences on the community structure and function. We also highlight several important research topics which may be of great interest to the research community.
NASA Astrophysics Data System (ADS)
Berahmand, Kamal; Bouyer, Asgarali
2018-03-01
Community detection is an essential approach for analyzing the structural and functional properties of complex networks. Although many community detection algorithms have been recently presented, most of them are weak and limited in different ways. Label Propagation Algorithm (LPA) is a well-known and efficient community detection technique which is characterized by the merits of nearly-linear running time and easy implementation. However, LPA has some significant problems such as instability, randomness, and monster community detection. In this paper, an algorithm, namely node’s label influence policy for label propagation algorithm (LP-LPA) was proposed for detecting efficient community structures. LP-LPA measures link strength value for edges and nodes’ label influence value for nodes in a new label propagation strategy with preference on link strength and for initial nodes selection, avoid of random behavior in tiebreak states, and efficient updating order and rule update. These procedures can sort out the randomness issue in an original LPA and stabilize the discovered communities in all runs of the same network. Experiments on synthetic networks and a wide range of real-world social networks indicated that the proposed method achieves significant accuracy and high stability. Indeed, it can obviously solve monster community problem with regard to detecting communities in networks.
Minor, M A; Ermilov, S G; Philippov, D A; Prokin, A A
2016-11-01
We investigated communities of oribatid mites in five peat bogs in the north-west of the East European plain. We aimed to determine the extent to which geographic factors (latitude, separation distance), local environment (Sphagnum moss species, ground water level, biogeochemistry) and local habitat complexity (diversity of vascular plants and bryophytes in the surrounding plant community) influence diversity and community composition of Oribatida. There was a significant north-to-south increase in Oribatida abundance. In the variance partitioning, spatial factors explained 33.1 % of variability in abundance across samples; none of the environmental factors were significant. Across all bogs, Oribatida species richness and community composition were similar in Sphagnum rubellum and Sphagnum magellanicum, but significantly different and less diverse in Sphagnum cuspidatum. Sphagnum microhabitat explained 52.2 % of variability in Oribatida species richness, whereas spatial variables explained only 8.7 %. There was no distance decay in community similarity between bogs with increased geographical distance. The environmental variables explained 34.9 % of the variance in community structure, with vascular plants diversity, bryophytes diversity, and ground water level all contributing significantly; spatial variables explained 15.1 % of the total variance. Overall, only 50 % of the Oribatida community variance was explained by the spatial structure and environmental variables. We discuss relative importance of spatial and local environmental factors, and make general inferences about the formation of fauna in Sphagnum bogs.
STRUCTURAL INEQUALITY AND SOCIAL SUPPORT FOR WOMEN PRISONERS RELEASED TO RURAL COMMUNITIES
Nicdao, Ethel G.; Trott, Elise M.; Kellett, Nicole C.
2016-01-01
Incarceration and community reentry for rural women reflect gendered processes. We draw upon in-depth semi-structured interviews and focus groups to examine the return of women prisoners to underserved rural communities, while attending to the perspectives of their closest social supporters. Our findings underscore the complexity of the reentry process for rural women and its particular impact on their families. We challenge dominant discourses of personal responsibility that detract from the structura violence and injustice shaping reentry experiences for women and their social supporters. We also consider the policy implications of discharge and reentry planning for rural women and their families, as well as strategies to reduce recidivism. PMID:27274615
Information transfer in community structured multiplex networks
NASA Astrophysics Data System (ADS)
Solé Ribalta, Albert; Granell, Clara; Gómez, Sergio; Arenas, Alex
2015-08-01
The study of complex networks that account for different types of interactions has become a subject of interest in the last few years, specially because its representational power in the description of users interactions in diverse online social platforms (Facebook, Twitter, Instagram, etc.). The mathematical description of these interacting networks has been coined under the name of multilayer networks, where each layer accounts for a type of interaction. It has been shown that diffusive processes on top of these networks present a phenomenology that cannot be explained by the naive superposition of single layer diffusive phenomena but require the whole structure of interconnected layers. Nevertheless, the description of diffusive phenomena on multilayer networks has obviated the fact that social networks have strong mesoscopic structure represented by different communities of individuals driven by common interests, or any other social aspect. In this work, we study the transfer of information in multilayer networks with community structure. The final goal is to understand and quantify, if the existence of well-defined community structure at the level of individual layers, together with the multilayer structure of the whole network, enhances or deteriorates the diffusion of packets of information.
Goetz, Katja; Kleine-Budde, Katja; Bramesfeld, Anke; Stegbauer, Constance
2018-03-01
Working requirements of community mental healthcare professionals in integrated care are complex. There is a lack of research concerning the relation of job satisfaction, working atmosphere and individual characteristics. For the current study, a survey evaluating job satisfaction and working atmosphere of mental healthcare professionals in integrated care was performed. About 321 community mental healthcare professionals were included in the survey; the response rate was 59.5%. The professional background of community mental healthcare professionals included nursing, social work and psychology. Community mental healthcare professionals reported the highest satisfaction with colleagues and the lowest satisfaction with income. Moreover, it could be shown that more responsibility, more recognition and more variety in job tasks lead to an increase of overall job satisfaction. Healthcare for mentally ill patients in the community setting is complex and requires well-structured care with appropriate responsibilities within the team. A co-operative relationship among colleagues as well as clearly defined responsibilities seem to be the key for the job satisfaction of community mental healthcare professionals in integrated care. © 2017 John Wiley & Sons Ltd.
Dynamic structure of stock communities: a comparative study between stock returns and turnover rates
NASA Astrophysics Data System (ADS)
Su, Li-Ling; Jiang, Xiong-Fei; Li, Sai-Ping; Zhong, Li-Xin; Ren, Fei
2017-07-01
The detection of community structure in stock market is of theoretical and practical significance for the study of financial dynamics and portfolio risk estimation. We here study the community structures in Chinese stock markets from the aspects of both price returns and turnover rates, by using a combination of the PMFG and infomap methods based on a distance matrix. An empirical study using the overall data set shows that for both returns and turnover rates the largest communities are composed of specific industrial or conceptional sectors and the correlation inside a sector is generally larger than the correlation between different sectors. However, the community structure for turnover rates is more complex than that for returns, which indicates that the interactions between stocks revealed by turnover rates may contain more information. This conclusion is further confirmed by the analysis of the changes in the dynamics of community structures over five sub-periods. Sectors like banks, real estate, health care and New Shanghai take turns to comprise a few of the largest communities in different sub-periods, and more interestingly several specific sectors appear in the communities with different rank orders for returns and turnover rates even in the same sub-period. To better understand their differences, a comparison between the evolution of the returns and turnover rates of the stocks from these sectors is conducted. We find that stock prices only had large changes around important events while turnover rates surged after each of these events relevant to specific sectors, which shows strong evidence that the turnover rates are more susceptible to exogenous shocks than returns and its measurement for community detection may contain more useful information about market structure.
Schaub, Michael T.; Delvenne, Jean-Charles; Yaliraki, Sophia N.; Barahona, Mauricio
2012-01-01
In recent years, there has been a surge of interest in community detection algorithms for complex networks. A variety of computational heuristics, some with a long history, have been proposed for the identification of communities or, alternatively, of good graph partitions. In most cases, the algorithms maximize a particular objective function, thereby finding the ‘right’ split into communities. Although a thorough comparison of algorithms is still lacking, there has been an effort to design benchmarks, i.e., random graph models with known community structure against which algorithms can be evaluated. However, popular community detection methods and benchmarks normally assume an implicit notion of community based on clique-like subgraphs, a form of community structure that is not always characteristic of real networks. Specifically, networks that emerge from geometric constraints can have natural non clique-like substructures with large effective diameters, which can be interpreted as long-range communities. In this work, we show that long-range communities escape detection by popular methods, which are blinded by a restricted ‘field-of-view’ limit, an intrinsic upper scale on the communities they can detect. The field-of-view limit means that long-range communities tend to be overpartitioned. We show how by adopting a dynamical perspective towards community detection [1], [2], in which the evolution of a Markov process on the graph is used as a zooming lens over the structure of the network at all scales, one can detect both clique- or non clique-like communities without imposing an upper scale to the detection. Consequently, the performance of algorithms on inherently low-diameter, clique-like benchmarks may not always be indicative of equally good results in real networks with local, sparser connectivity. We illustrate our ideas with constructive examples and through the analysis of real-world networks from imaging, protein structures and the power grid, where a multiscale structure of non clique-like communities is revealed. PMID:22384178
Unraveling the Complexity of Wildland Urban Interface Fires.
Mahmoud, Hussam; Chulahwat, Akshat
2018-06-18
Recent wildland urban interface fires have demonstrated the unrelenting destructive nature of these events and have called for an urgent need to address the problem. The Wildfire paradox reinforces the ideology that forest fires are inevitable and are actually beneficial; therefore focus should to be shifted towards minimizing potential losses to communities. This requires the development of vulnerability-based frameworks that can be used to provide holistic understanding of risk. In this study, we devise a probabilistic approach for quantifying community vulnerability to wildfires by applying concepts of graph theory. A directed graph for community in question is developed to model wildfire inside a community by incorporating different fire propagation modes. The model accounts for relevant community-specific characteristics including wind conditions, community layout, individual structural features, and the surrounding wildland vegetation. We calibrate the framework to study the infamous 1991 Oakland fire in an attempt to unravel the complexity of community fires. We use traditional centrality measures to identify critical behavior patterns and to evaluate the effect of fire mitigation strategies. Unlike current practice, the results are shown to be community-specific with substantial dependency of risk on meteorological conditions, environmental factors, and community characteristics and layout.
Environmental Regulation of Microbial Community Structure
NASA Technical Reports Server (NTRS)
Bebout, Leslie; DesMarais, D.; Heyenga, G.; Nelson, F.; DeVincenzi, D. (Technical Monitor)
2002-01-01
Most naturally occurring microbes live in complex microbial communities consisting of thousands of phylotypes of microorganisms living in close proximity. Each of these draws nutrients from the environment and releases metabolic waste products, which may in turn serve as substrates for other microbial groups. Gross environmental changes, such as irradiance level, hydrodynamic flow regime, temperature or water chemistry can directly affect the productivity of some community members, which in turn will affect other dependent microbial populations and rate processes. As a first step towards the development of "standard" natural communities of microorganisms for a variety of potential NASA applications, we are measuring biogeochemical cycling in artificially structured communities of microorganisms, created using natural microbial mat communities as inoculum. The responses of these artificially assembled communities of microorganisms to controlled shifts in ecosystem incubation conditions is being determined. This research requires close linking of environmental monitoring, with community composition in a closed and controlled incubation setting. We are developing new incubation chamber designs to allow for this integrated approach to examine the interplay between environmental conditions, microbial community composition and biogeochemical processes.
Implementing Problem Based Learning through Engineers without Borders Student Projects
ERIC Educational Resources Information Center
Wittig, Ann
2013-01-01
Engineers Without Borders USA (EWB) is a nonprofit organization that partners student chapters with communities in fundamental need of potable water, clean air, sanitation, irrigation, energy, basic structures for schools and clinics, roads and bridges, etc. While EWB projects may vary in complexity, they are all realistic, ill-structured and…
Predicting the consequences of species loss using size-structured biodiversity approaches.
Brose, Ulrich; Blanchard, Julia L; Eklöf, Anna; Galiana, Nuria; Hartvig, Martin; R Hirt, Myriam; Kalinkat, Gregor; Nordström, Marie C; O'Gorman, Eoin J; Rall, Björn C; Schneider, Florian D; Thébault, Elisa; Jacob, Ute
2017-05-01
Understanding the consequences of species loss in complex ecological communities is one of the great challenges in current biodiversity research. For a long time, this topic has been addressed by traditional biodiversity experiments. Most of these approaches treat species as trait-free, taxonomic units characterizing communities only by species number without accounting for species traits. However, extinctions do not occur at random as there is a clear correlation between extinction risk and species traits. In this review, we assume that large species will be most threatened by extinction and use novel allometric and size-spectrum concepts that include body mass as a primary species trait at the levels of populations and individuals, respectively, to re-assess three classic debates on the relationships between biodiversity and (i) food-web structural complexity, (ii) community dynamic stability, and (iii) ecosystem functioning. Contrasting current expectations, size-structured approaches suggest that the loss of large species, that typically exploit most resource species, may lead to future food webs that are less interwoven and more structured by chains of interactions and compartments. The disruption of natural body-mass distributions maintaining food-web stability may trigger avalanches of secondary extinctions and strong trophic cascades with expected knock-on effects on the functionality of the ecosystems. Therefore, we argue that it is crucial to take into account body size as a species trait when analysing the consequences of biodiversity loss for natural ecosystems. Applying size-structured approaches provides an integrative ecological concept that enables a better understanding of each species' unique role across communities and the causes and consequences of biodiversity loss. © 2016 Cambridge Philosophical Society.
The structural role of weak and strong links in a financial market network
NASA Astrophysics Data System (ADS)
Garas, A.; Argyrakis, P.; Havlin, S.
2008-05-01
We investigate the properties of correlation based networks originating from economic complex systems, such as the network of stocks traded at the New York Stock Exchange (NYSE). The weaker links (low correlation) of the system are found to contribute to the overall connectivity of the network significantly more than the strong links (high correlation). We find that nodes connected through strong links form well defined communities. These communities are clustered together in more complex ways compared to the widely used classification according to the economic activity. We find that some companies, such as General Electric (GE), Coca Cola (KO), and others, can be involved in different communities. The communities are found to be quite stable over time. Similar results were obtained by investigating markets completely different in size and properties, such as the Athens Stock Exchange (ASE). The present method may be also useful for other networks generated through correlations.
Complex food webs prevent competitive exclusion among producer species.
Brose, Ulrich
2008-11-07
Herbivorous top-down forces and bottom-up competition for nutrients determine the coexistence and relative biomass patterns of producer species. Combining models of predator-prey and producer-nutrient interactions with a structural model of complex food webs, I investigated these two aspects in a dynamic food-web model. While competitive exclusion leads to persistence of only one producer species in 99.7% of the simulated simple producer communities without consumers, embedding the same producer communities in complex food webs generally yields producer coexistence. In simple producer communities, the producers with the most efficient nutrient-intake rates increase in biomass until they competitively exclude inferior producers. In food webs, herbivory predominantly reduces the biomass density of those producers that dominated in producer communities, which yields a more even biomass distribution. In contrast to prior analyses of simple modules, this facilitation of producer coexistence by herbivory does not require a trade-off between the nutrient-intake efficiency and the resistance to herbivory. The local network structure of food webs (top-down effects of the number of herbivores and the herbivores' maximum consumption rates) and the nutrient supply (bottom-up effect) interactively determine the relative biomass densities of the producer species. A strong negative feedback loop emerges in food webs: factors that increase producer biomasses also increase herbivory, which reduces producer biomasses. This negative feedback loop regulates the coexistence and biomass patterns of the producers by balancing biomass increases of producers and biomass fluxes to herbivores, which prevents competitive exclusion.
Data System for Structural Geology and Tectonics
NASA Astrophysics Data System (ADS)
Newman, Julie; Walker, J. Douglas; Tikoff, Basil; Good, Jessica; Michels, Zachary; Ash, Jason; Andrew, Joseph; Williams, Randolph
2016-04-01
We are prototyping a Data System for Structural Geology and Tectonics (SG&T) data that is platform independent (from mobile device to desktop) to enable collection and sharing of data from field to laboratory settings. The goals of this effort, funded by US National Science Foundation, are to enable recording and sharing data within the geoscience community, to encourage interdisciplinary research, and to facilitate the investigation of scientific questions that cannot currently be addressed. The development of the Data System emphasizes community input in order to build a system that encompasses the needs of researchers, in terms of data and usability. SG&T data is complex for a variety of reasons, including the wide range of temporal and spatial scales (many orders of magnitude each), the complex three-dimensional geometry of some geological structures, inherent spatial nature of the data, and the difficulty of making temporal inferences from spatial observations. To successfully implement the development of a SG&T data system, we must simultaneously solve three problems: 1) How to digitize SG&T data; 2) How to design a software system that is applicable; and 3) How to construct a very flexible user interface. To address the first problem, we introduce the "Spot" concept, which allows tracking of hierarchical and spatial relations between structures at all scales, and will link map scale, mesoscale, and laboratory scale data. A Spot is an observation or relationship with an area of significance. A Spot can be a single measurement, an aggregate of individual measurements, or even relationships between numerous other Spots. We address the second problem of software design through the use of a graph database to better preserve the myriad of potentially complex relationships. In order to construct a flexible user interface that follows a natural workflow and that serves the needs of the community, we are engaging the SG&T community in order to utilize the expertise of a large group of scientists to ensure the quality and usability of this data system. These activities have included Town Halls at GSA and AGU, subdiscipline-specific workshops to develop community standards, and pilot projects to test the data system in the field during the study of a variety of geologic structures.
The ground truth about metadata and community detection in networks.
Peel, Leto; Larremore, Daniel B; Clauset, Aaron
2017-05-01
Across many scientific domains, there is a common need to automatically extract a simplified view or coarse-graining of how a complex system's components interact. This general task is called community detection in networks and is analogous to searching for clusters in independent vector data. It is common to evaluate the performance of community detection algorithms by their ability to find so-called ground truth communities. This works well in synthetic networks with planted communities because these networks' links are formed explicitly based on those known communities. However, there are no planted communities in real-world networks. Instead, it is standard practice to treat some observed discrete-valued node attributes, or metadata, as ground truth. We show that metadata are not the same as ground truth and that treating them as such induces severe theoretical and practical problems. We prove that no algorithm can uniquely solve community detection, and we prove a general No Free Lunch theorem for community detection, which implies that there can be no algorithm that is optimal for all possible community detection tasks. However, community detection remains a powerful tool and node metadata still have value, so a careful exploration of their relationship with network structure can yield insights of genuine worth. We illustrate this point by introducing two statistical techniques that can quantify the relationship between metadata and community structure for a broad class of models. We demonstrate these techniques using both synthetic and real-world networks, and for multiple types of metadata and community structures.
Zhang, Husen; Chen, Xi; Braithwaite, Daniel; He, Zhen
2014-01-01
Understanding the microbial community structure and genetic potential of anode biofilms is key to improve extracellular electron transfers in microbial fuel cells. We investigated effect of substrate and temporal dynamics of anodic biofilm communities using phylogenetic and metagenomic approaches in parallel with electrochemical characterizations. The startup non-steady state anodic bacterial structures were compared for a simple substrate, acetate, and for a complex substrate, landfill leachate, using a single-chamber air-cathode microbial fuel cell. Principal coordinate analysis showed that distinct community structures were formed with each substrate type. The bacterial diversity measured as Shannon index decreased with time in acetate cycles, and was restored with the introduction of leachate. The change of diversity was accompanied by an opposite trend in the relative abundance of Geobacter-affiliated phylotypes, which were acclimated to over 40% of total Bacteria at the end of acetate-fed conditions then declined in the leachate cycles. The transition from acetate to leachate caused a decrease in output power density from 243±13 mW/m2 to 140±11 mW/m2, accompanied by a decrease in Coulombic electron recovery from 18±3% to 9±3%. The leachate cycles selected protein-degrading phylotypes within phylum Synergistetes. Metagenomic shotgun sequencing showed that leachate-fed communities had higher cell motility genes including bacterial chemotaxis and flagellar assembly, and increased gene abundance related to metal resistance, antibiotic resistance, and quorum sensing. These differentially represented genes suggested an altered anodic biofilm community in response to additional substrates and stress from the complex landfill leachate. PMID:25202990
Zhang, Husen; Chen, Xi; Braithwaite, Daniel; He, Zhen
2014-01-01
Understanding the microbial community structure and genetic potential of anode biofilms is key to improve extracellular electron transfers in microbial fuel cells. We investigated effect of substrate and temporal dynamics of anodic biofilm communities using phylogenetic and metagenomic approaches in parallel with electrochemical characterizations. The startup non-steady state anodic bacterial structures were compared for a simple substrate, acetate, and for a complex substrate, landfill leachate, using a single-chamber air-cathode microbial fuel cell. Principal coordinate analysis showed that distinct community structures were formed with each substrate type. The bacterial diversity measured as Shannon index decreased with time in acetate cycles, and was restored with the introduction of leachate. The change of diversity was accompanied by an opposite trend in the relative abundance of Geobacter-affiliated phylotypes, which were acclimated to over 40% of total Bacteria at the end of acetate-fed conditions then declined in the leachate cycles. The transition from acetate to leachate caused a decrease in output power density from 243±13 mW/m2 to 140±11 mW/m2, accompanied by a decrease in Coulombic electron recovery from 18±3% to 9±3%. The leachate cycles selected protein-degrading phylotypes within phylum Synergistetes. Metagenomic shotgun sequencing showed that leachate-fed communities had higher cell motility genes including bacterial chemotaxis and flagellar assembly, and increased gene abundance related to metal resistance, antibiotic resistance, and quorum sensing. These differentially represented genes suggested an altered anodic biofilm community in response to additional substrates and stress from the complex landfill leachate.
SCOUT: simultaneous time segmentation and community detection in dynamic networks
Hulovatyy, Yuriy; Milenković, Tijana
2016-01-01
Many evolving complex real-world systems can be modeled via dynamic networks. An important problem in dynamic network research is community detection, which finds groups of topologically related nodes. Typically, this problem is approached by assuming either that each time point has a distinct community organization or that all time points share a single community organization. The reality likely lies between these two extremes. To find the compromise, we consider community detection in the context of the problem of segment detection, which identifies contiguous time periods with consistent network structure. Consequently, we formulate a combined problem of segment community detection (SCD), which simultaneously partitions the network into contiguous time segments with consistent community organization and finds this community organization for each segment. To solve SCD, we introduce SCOUT, an optimization framework that explicitly considers both segmentation quality and partition quality. SCOUT addresses limitations of existing methods that can be adapted to solve SCD, which consider only one of segmentation quality or partition quality. In a thorough evaluation, SCOUT outperforms the existing methods in terms of both accuracy and computational complexity. We apply SCOUT to biological network data to study human aging. PMID:27881879
Freund, Anat; Band-Winterstein, Tova
2017-07-01
Community is a complex issue, especially in two particular populations overlap: Haredi society, which embraces cultural codes common to closed communities, and the mental health population characterized by its own unique needs. The present study explores the encounter experience of social workers with the cultural perceptions of mental health clients in the Haredi community in light of Community Cultural Psychiatry. A qualitative-phenomenological approach was adopted. In-depth semi-structured interviews were conducted with 27 social workers, mental health professionals, who are in contact with ultra-Orthodox Jewish clients. Three major themes emerged from the data analysis: (1) Exclusion vs. grace and compassion. (2) Mental health: A professional or cultural arena? (3) Mental health help-seeking changing processes. This study shows that the attitude in the Haredi community toward mental health therapy undergoes a process of change. It is important to strengthen this process, together with preserving existing community informal structures of help.
Wang, Xiaohui; Xia, Yu; Wen, Xianghua; Yang, Yunfeng; Zhou, Jizhong
2014-01-01
Biological WWTPs must be functionally stable to continuously and steadily remove contaminants which rely upon the activity of complex microbial communities. However, knowledge is still lacking in regard to microbial community functional structures and their linkages to environmental variables. To investigate microbial community functional structures of activated sludge in wastewater treatment plants (WWTPs) and to understand the effects of environmental factors on their structure. 12 activated sludge samples were collected from four WWTPs in Beijing. A comprehensive functional gene array named GeoChip 4.2 was used to determine the microbial functional genes involved in a variety of biogeochemical processes such as carbon, nitrogen, phosphorous and sulfur cycles, metal resistance, antibiotic resistance and organic contaminant degradation. High similarities of the microbial community functional structures were found among activated sludge samples from the four WWTPs, as shown by both diversity indices and the overlapped genes. For individual gene category, such as egl, amyA, lip, nirS, nirK, nosZ, ureC, ppx, ppk, aprA, dsrA, sox and benAB, there were a number of microorganisms shared by all 12 samples. Canonical correspondence analysis (CCA) showed that the microbial functional patterns were highly correlated with water temperature, dissolved oxygen (DO), ammonia concentrations and loading rate of chemical oxygen demand (COD). Based on the variance partitioning analyses (VPA), a total of 53% of microbial community variation from GeoChip data can be explained by wastewater characteristics (25%) and operational parameters (23%), respectively. This study provided an overall picture of microbial community functional structures of activated sludge in WWTPs and discerned the linkages between microbial communities and environmental variables in WWTPs.
Netgram: Visualizing Communities in Evolving Networks
Mall, Raghvendra; Langone, Rocco; Suykens, Johan A. K.
2015-01-01
Real-world complex networks are dynamic in nature and change over time. The change is usually observed in the interactions within the network over time. Complex networks exhibit community like structures. A key feature of the dynamics of complex networks is the evolution of communities over time. Several methods have been proposed to detect and track the evolution of these groups over time. However, there is no generic tool which visualizes all the aspects of group evolution in dynamic networks including birth, death, splitting, merging, expansion, shrinkage and continuation of groups. In this paper, we propose Netgram: a tool for visualizing evolution of communities in time-evolving graphs. Netgram maintains evolution of communities over 2 consecutive time-stamps in tables which are used to create a query database using the sql outer-join operation. It uses a line-based visualization technique which adheres to certain design principles and aesthetic guidelines. Netgram uses a greedy solution to order the initial community information provided by the evolutionary clustering technique such that we have fewer line cross-overs in the visualization. This makes it easier to track the progress of individual communities in time evolving graphs. Netgram is a generic toolkit which can be used with any evolutionary community detection algorithm as illustrated in our experiments. We use Netgram for visualization of topic evolution in the NIPS conference over a period of 11 years and observe the emergence and merging of several disciplines in the field of information processing systems. PMID:26356538
Luiz, Amom Mendes; Sawaya, Ricardo J.
2018-01-01
Ecological communities are complex entities that can be maintained and structured by niche-based processes such as environmental conditions, and spatial processes such as dispersal. Thus, diversity patterns may be shaped simultaneously at different spatial scales by very distinct processes. Herein we assess whether and how functional, taxonomic, and phylogenetic beta diversities of frog tadpoles are explained by environmental and/or spatial predictors. We implemented a distance–based redundancy analysis to explore variation in components of beta diversity explained by pure environmental and pure spatial predictors, as well as their interactions, at both fine and broad spatial scales. Our results indicated important but complex roles of spatial and environmental predictors in structuring phylogenetic, taxonomic and functional beta diversities. The pure fine-scales spatial fraction was more important in structuring all beta diversity components, especially to functional and taxonomical spatial turnover. Environmental variables such as canopy cover and vegetation structure were important predictors of all components, but especially to functional and taxonomic beta diversity. We emphasize that distinct factors related to environment and space are affecting distinct components of beta diversity in different ways. Although weaker, phylogenetic beta diversity, which is structured more on biogeographical scales, and thus can be represented by spatially structured processes, was more related to broad spatial processes than other components. However, selected fine-scale spatial predictors denoted negative autocorrelation, which may be revealing the existence of differences in unmeasured habitat variables among samples. Although overall important, local environmental-based processes explained better functional and taxonomic beta diversity, as these diversity components carry an important ecological value. We highlight the importance of assessing different components of diversity patterns at different scales by spatially explicit models in order to improve our understanding of community structure and help to unravel the complex nature of biodiversity. PMID:29672575
Beyond vertical integration--Community based medical education.
Kennedy, Emma Margaret
2006-11-01
The term 'vertical integration' is used broadly in medical education, sometimes when discussing community based medical education (CBME). This article examines the relevance of the term 'vertical integration' and provides an alternative perspective on the complexities of facilitating the CBME process. The principles of learner centredness, patient centredness and flexibility are fundamental to learning in the diverse contexts of 'community'. Vertical integration as a structural concept is helpful for academic organisations but has less application to education in the community setting; a different approach illuminates the strengths and challenges of CBME that need consideration by these organisations.
Community structure of zooplankton in the main entrance of Bahía Magdalena, México during 1996.
Gómez-Gutiérrez, J; Palomares-García, R; Hernández-Trujillo, S; Carballido-Carranza, A
2001-06-01
The zooplankton community structure, including copepods, euphausiids, chaetognaths, and decapod larvae, was monitored during six circadian cycles using Bongo net (500 microns mesh net) samples from Bahía Magdalena, on the southwest coast of Baja California, México. Samples were obtained during three oceanographic surveys (March, July, and December 1996) to describe the changes in the zooplankton community structure throughout the main mouth of Bahía Magdalena. The zooplankton community structure showed strong changes with a close relation to environmental conditions. During March, a well-mixed water column with low temperature and salinity indicated an influence of the California Current water and local upwelling processes. During July, temperature increased and a wide salinity range was recorded. The stratification of the water column was intense during summer, enhancing the thermocline. The highest temperatures and salinity were recorded in December, related to the presence of the Costa Rica Coastal Current (CRCC). The thermocline deepened as water temperature increased. A typical temperate community structure with low specific richness dominated by Calanus pacificus, Nyctiphanes simplex, and Acartia clausi and high zooplankton biomass (average 9.3 and 5.5 ml 1000 m-3 respectively) during March and July shifted to a more complex tropical community structure with a low zooplankton biomass in December (average 0.37 ml 1000 m-3). The mouth of Bahía Magdalena has a vigorous exchange of water caused by tidal currents. The zooplankton community structure was not significantly different between the central part of Bahía Magdalena and the continental shelf outside the bay for all months. The results suggest a more dynamic inside-outside interaction of zooplankton assemblages than first thought.
Community Detection in Signed Networks: the Role of Negative ties in Different Scales
Esmailian, Pouya; Jalili, Mahdi
2015-01-01
Extracting community structure of complex network systems has many applications from engineering to biology and social sciences. There exist many algorithms to discover community structure of networks. However, it has been significantly under-explored for networks with positive and negative links as compared to unsigned ones. Trying to fill this gap, we measured the quality of partitions by introducing a Map Equation for signed networks. It is based on the assumption that negative relations weaken positive flow from a node towards a community, and thus, external (internal) negative ties increase the probability of staying inside (escaping from) a community. We further extended the Constant Potts Model, providing a map spectrum for signed networks. Accordingly, a partition is selected through balancing between abridgment and expatiation of a signed network. Most importantly, multi-scale spectrum of signed networks revealed how informative are negative ties in different scales, and quantified the topological placement of negative ties between dense positive ones. Moreover, an inconsistency was found in the signed Modularity: as the number of negative ties increases, the density of positive ties is neglected more. These results shed lights on the community structure of signed networks. PMID:26395815
LaPara, Timothy M; Klatt, Christian G; Chen, Ruoyu
2006-02-10
Membrane-coupled bioreactors (MBRs) offer substantial benefits compared to conventional reactor designs for biological wastewater treatment. MBR treatment efficiency, however, has not been optimized because the effects of the MBR on process microbiology are poorly understood. In this study, the structure and function of the microbial communities growing in MBRs fed simple synthetic wastewater were investigated. In four starch-fed MBRs, the bacterial community substantially increased its alpha-glucosidase affinity (>1000-fold), while the leucine aminopeptidase and heptanoate esterase affinities increased slightly (<40-fold) or remained relatively constant. Concomitant to these physiological adaptations, shifts in the bacterial community structure in two of the starch-fed MBRs were detected by PCR-DGGE. Four of the bacterial populations detected by PCR-DGGE were isolated and exhibited specific growth rates in batch culture ranging from 0.009 to 0.22 h(-1). Our results suggest that bacterial communities growing under increasingly stringent nutrient limitation adapt their enzyme activities primarily for the nutrients provided, but that there is also a more subtle response not linked to the substrates included in the feed medium. Our research also demonstrates that MBRs can support relatively complex bacterial communities even on simple feed media.
Emergence of communities and diversity in social networks
Han, Xiao; Cao, Shinan; Shen, Zhesi; Zhang, Boyu; Wang, Wen-Xu; Cressman, Ross
2017-01-01
Communities are common in complex networks and play a significant role in the functioning of social, biological, economic, and technological systems. Despite widespread interest in detecting community structures in complex networks and exploring the effect of communities on collective dynamics, a deep understanding of the emergence and prevalence of communities in social networks is still lacking. Addressing this fundamental problem is of paramount importance in understanding, predicting, and controlling a variety of collective behaviors in society. An elusive question is how communities with common internal properties arise in social networks with great individual diversity. Here, we answer this question using the ultimatum game, which has been a paradigm for characterizing altruism and fairness. We experimentally show that stable local communities with different internal agreements emerge spontaneously and induce social diversity into networks, which is in sharp contrast to populations with random interactions. Diverse communities and social norms come from the interaction between responders with inherent heterogeneous demands and rational proposers via local connections, where the former eventually become the community leaders. This result indicates that networks are significant in the emergence and stabilization of communities and social diversity. Our experimental results also provide valuable information about strategies for developing network models and theories of evolutionary games and social dynamics. PMID:28235785
Emergence of communities and diversity in social networks.
Han, Xiao; Cao, Shinan; Shen, Zhesi; Zhang, Boyu; Wang, Wen-Xu; Cressman, Ross; Stanley, H Eugene
2017-03-14
Communities are common in complex networks and play a significant role in the functioning of social, biological, economic, and technological systems. Despite widespread interest in detecting community structures in complex networks and exploring the effect of communities on collective dynamics, a deep understanding of the emergence and prevalence of communities in social networks is still lacking. Addressing this fundamental problem is of paramount importance in understanding, predicting, and controlling a variety of collective behaviors in society. An elusive question is how communities with common internal properties arise in social networks with great individual diversity. Here, we answer this question using the ultimatum game, which has been a paradigm for characterizing altruism and fairness. We experimentally show that stable local communities with different internal agreements emerge spontaneously and induce social diversity into networks, which is in sharp contrast to populations with random interactions. Diverse communities and social norms come from the interaction between responders with inherent heterogeneous demands and rational proposers via local connections, where the former eventually become the community leaders. This result indicates that networks are significant in the emergence and stabilization of communities and social diversity. Our experimental results also provide valuable information about strategies for developing network models and theories of evolutionary games and social dynamics.
A Deep Stochastic Model for Detecting Community in Complex Networks
NASA Astrophysics Data System (ADS)
Fu, Jingcheng; Wu, Jianliang
2017-01-01
Discovering community structures is an important step to understanding the structure and dynamics of real-world networks in social science, biology and technology. In this paper, we develop a deep stochastic model based on non-negative matrix factorization to identify communities, in which there are two sets of parameters. One is the community membership matrix, of which the elements in a row correspond to the probabilities of the given node belongs to each of the given number of communities in our model, another is the community-community connection matrix, of which the element in the i-th row and j-th column represents the probability of there being an edge between a randomly chosen node from the i-th community and a randomly chosen node from the j-th community. The parameters can be evaluated by an efficient updating rule, and its convergence can be guaranteed. The community-community connection matrix in our model is more precise than the community-community connection matrix in traditional non-negative matrix factorization methods. Furthermore, the method called symmetric nonnegative matrix factorization, is a special case of our model. Finally, based on the experiments on both synthetic and real-world networks data, it can be demonstrated that our algorithm is highly effective in detecting communities.
Richard A. MacKenzie; Nicole Cormier
2012-01-01
Structurally complex mangrove roots are thought to provide foraging habitat, predation refugia, and typhoon protection for resident fish, shrimp, and crabs. The spatially compact nature of Micronesian mangroves results in model ecosystems to test these ideas. Tidal creek nekton assemblages were compared among mangrove forests impacted by Typhoon Sudal and differing in...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hempling, Scott
2006-08-15
The repeal of PUHCA has occasioned important questions on the appropriate role for regulation in the area of utility corporate structure, including complex process and jurisdictional issues. There is a disproportionality between the importance of these questions and the lack of attention that has been given them by our regulatory and political communities. (author)
Hajjar, David J; McCarthy, John W; Benigno, Joann P; Chabot, Jennifer
2016-06-01
Recreation is an essential part of life that provides enriching experiences that may define one's life course similar to careers or other interests. An understanding of the role of volunteers in active community-based recreational programs can help to generate ways to enhance participation and contribute to additional communication opportunities with people who have complex communication needs. Nine volunteers from two adaptive ski programs and one therapeutic horseback-riding program in the Northeast region of the United States participated in semi-structured interviews. Audio-recordings were transcribed and analyzed and resulted in five thematic areas: (a) benefits, (b) why individuals volunteer, (c) barriers, (d) successful program supports, and (e) who are the riders and skiers using AAC. The findings provided insight to support the notion that active community-based recreational activities foster an environment for communication, meaningful engagement, and social relationships between volunteers and people with complex communication needs.
Local community detection as pattern restoration by attractor dynamics of recurrent neural networks.
Okamoto, Hiroshi
2016-08-01
Densely connected parts in networks are referred to as "communities". Community structure is a hallmark of a variety of real-world networks. Individual communities in networks form functional modules of complex systems described by networks. Therefore, finding communities in networks is essential to approaching and understanding complex systems described by networks. In fact, network science has made a great deal of effort to develop effective and efficient methods for detecting communities in networks. Here we put forward a type of community detection, which has been little examined so far but will be practically useful. Suppose that we are given a set of source nodes that includes some (but not all) of "true" members of a particular community; suppose also that the set includes some nodes that are not the members of this community (i.e., "false" members of the community). We propose to detect the community from this "imperfect" and "inaccurate" set of source nodes using attractor dynamics of recurrent neural networks. Community detection by the proposed method can be viewed as restoration of the original pattern from a deteriorated pattern, which is analogous to cue-triggered recall of short-term memory in the brain. We demonstrate the effectiveness of the proposed method using synthetic networks and real social networks for which correct communities are known. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Ransome, E. J.; Timmers, M.; Hartmann, A.; Collins, A.; Meyer, C.
2016-02-01
Coral reefs harbor diverse and distinct eukaryotic, bacterial and viral communities, which are critically important for their success. The lack of standardized measures for comprehensively assessing reef diversity has been a major obstacle in understanding the complexity of eukaryotic and microbial associations, and the processes that drive ecosystem shifts on reefs. ARMS, which mimic the structural complexity of the reef using artificial settlement plates, were used to systematically measure reef biodiversity across the Indo-Pacific. This device allows for standardized sampling of reef microbes to metazoans, providing the opportunity to investigate the fundamental links between these groups at an ecosystem level. We integrate the use of traditional ecology methods with metagenomics and metabolomics (metabolic predictors) to quantify the taxonomic composition of one of the planet's most diverse ecosystems and to assess the fundamental links between these cryptic communities and ecosystem function along geographical and anthropogenic stress gradients.
Judge, Jenna; Barry, James P
2016-11-01
Environmental filtering, including the influence of environmental constraints and biological interactions on species' survival, is known to significantly affect patterns of community assembly in terrestrial ecosystems. However, its role in regulating patterns and processes of community assembly in deep-sea environments is poorly studied. Here we investigated the role of wood characteristics in the assembly of deep-sea wood fall communities. Ten different wood species (substrata) that varied in structural complexity were sunk to a depth of 3,100 m near Monterey Bay, CA. In total, 28 wood parcels were deployed on the deep-sea bed. After 2 yr, the wood parcels were recovered with over 7,000 attached or colonizing macroinvertebrates. All macroinvertebrates were identified to the lowest taxonomic level possible, and included several undescribed species. Diversity indices and multivariate analyses of variance detected significant variation in the colonizing community assemblages among different wood substrata. Structural complexity seemed to be the primary factor altering community composition between wood substrata. For example, wood-boring clams were most abundant on solid logs, while small arthropods and limpets were more abundant on bundles of branches that provided more surface area and small, protected spaces to occupy. Other factors such as chemical defenses, the presence of bark, and wood hardness likely also played a role. Our finding that characteristics of woody debris entering the marine realm can have significant effects on community assembly supports the notion of ecological and perhaps evolutionarily significant links between land and sea. © 2016 by the Ecological Society of America.
Emslie, Michael J.; Cheal, Alistair J.; Johns, Kerryn A.
2014-01-01
High biodiversity ecosystems are commonly associated with complex habitats. Coral reefs are highly diverse ecosystems, but are under increasing pressure from numerous stressors, many of which reduce live coral cover and habitat complexity with concomitant effects on other organisms such as reef fishes. While previous studies have highlighted the importance of habitat complexity in structuring reef fish communities, they employed gradient or meta-analyses which lacked a controlled experimental design over broad spatial scales to explicitly separate the influence of live coral cover from overall habitat complexity. Here a natural experiment using a long term (20 year), spatially extensive (∼115,000 kms2) dataset from the Great Barrier Reef revealed the fundamental importance of overall habitat complexity for reef fishes. Reductions of both live coral cover and habitat complexity had substantial impacts on fish communities compared to relatively minor impacts after major reductions in coral cover but not habitat complexity. Where habitat complexity was substantially reduced, species abundances broadly declined and a far greater number of fish species were locally extirpated, including economically important fishes. This resulted in decreased species richness and a loss of diversity within functional groups. Our results suggest that the retention of habitat complexity following disturbances can ameliorate the impacts of coral declines on reef fishes, so preserving their capacity to perform important functional roles essential to reef resilience. These results add to a growing body of evidence about the importance of habitat complexity for reef fishes, and represent the first large-scale examination of this question on the Great Barrier Reef. PMID:25140801
Emslie, Michael J; Cheal, Alistair J; Johns, Kerryn A
2014-01-01
High biodiversity ecosystems are commonly associated with complex habitats. Coral reefs are highly diverse ecosystems, but are under increasing pressure from numerous stressors, many of which reduce live coral cover and habitat complexity with concomitant effects on other organisms such as reef fishes. While previous studies have highlighted the importance of habitat complexity in structuring reef fish communities, they employed gradient or meta-analyses which lacked a controlled experimental design over broad spatial scales to explicitly separate the influence of live coral cover from overall habitat complexity. Here a natural experiment using a long term (20 year), spatially extensive (∼ 115,000 kms(2)) dataset from the Great Barrier Reef revealed the fundamental importance of overall habitat complexity for reef fishes. Reductions of both live coral cover and habitat complexity had substantial impacts on fish communities compared to relatively minor impacts after major reductions in coral cover but not habitat complexity. Where habitat complexity was substantially reduced, species abundances broadly declined and a far greater number of fish species were locally extirpated, including economically important fishes. This resulted in decreased species richness and a loss of diversity within functional groups. Our results suggest that the retention of habitat complexity following disturbances can ameliorate the impacts of coral declines on reef fishes, so preserving their capacity to perform important functional roles essential to reef resilience. These results add to a growing body of evidence about the importance of habitat complexity for reef fishes, and represent the first large-scale examination of this question on the Great Barrier Reef.
Lin, Huirong; Zhang, Shuting; Gong, Song; Zhang, Shenghua; Yu, Xin
2015-01-01
The composition and microbial community structure of the drinking water system biofilms were investigated using microstructure analysis and 454 pyrosequencing technique in Xiamen city, southeast of China. SEM (scanning electron microscope) results showed different features of biofilm morphology in different fields of PVC pipe. Extracellular matrix material and sparse populations of bacteria (mainly rod-shaped and coccoid) were observed. CLSM (confocal laser scanning microscope) revealed different distributions of attached cells, extracellular proteins, α-polysaccharides, and β-polysaccharides. The biofilms had complex bacterial compositions. Differences in bacteria diversity and composition from different tap materials and ages were observed. Proteobacteria was the common and predominant group in all biofilms samples. Some potential pathogens (Legionellales, Enterobacteriales, Chromatiales, and Pseudomonadales) and corrosive microorganisms were also found in the biofilms. This study provides the information of characterization and visualization of the drinking water biofilms matrix, as well as the microbial community structure and opportunistic pathogens occurrence. PMID:26273617
Stability-to-instability transition in the structure of large-scale networks
NASA Astrophysics Data System (ADS)
Hu, Dandan; Ronhovde, Peter; Nussinov, Zohar
2012-12-01
We examine phase transitions between the “easy,” “hard,” and “unsolvable” phases when attempting to identify structure in large complex networks (“community detection”) in the presence of disorder induced by network “noise” (spurious links that obscure structure), heat bath temperature T, and system size N. The partition of a graph into q optimally disjoint subgraphs or “communities” inherently requires Potts-type variables. In earlier work [Philos. Mag.1478-643510.1080/14786435.2011.616547 92, 406 (2012)], when examining power law and other networks (and general associated Potts models), we illustrated that transitions in the computational complexity of the community detection problem typically correspond to spin-glass-type transitions (and transitions to chaotic dynamics in mechanical analogs) at both high and low temperatures and/or noise. The computationally “hard” phase exhibits spin-glass type behavior including memory effects. The region over which the hard phase extends in the noise and temperature phase diagram decreases as N increases while holding the average number of nodes per community fixed. This suggests that in the thermodynamic limit a direct sharp transition may occur between the easy and unsolvable phases. When present, transitions at low temperature or low noise correspond to entropy driven (or “order by disorder”) annealing effects, wherein stability may initially increase as temperature or noise is increased before becoming unsolvable at sufficiently high temperature or noise. Additional transitions between contending viable solutions (such as those at different natural scales) are also possible. Identifying community structure via a dynamical approach where “chaotic-type” transitions were found earlier. The correspondence between the spin-glass-type complexity transitions and transitions into chaos in dynamical analogs might extend to other hard computational problems. In this work, we examine large networks (with a power law distribution in cluster size) that have a large number of communities (q≫1). We infer that large systems at a constant ratio of q to the number of nodes N asymptotically tend towards insolvability in the limit of large N for any positive T. The asymptotic behavior of temperatures below which structure identification might be possible, T×=O[1/lnq], decreases slowly, so for practical system sizes, there remains an accessible, and generally easy, global solvable phase at low temperature. We further employ multivariate Tutte polynomials to show that increasing q emulates increasing T for a general Potts model, leading to a similar stability region at low T. Given the relation between Tutte and Jones polynomials, our results further suggest a link between the above complexity transitions and transitions associated with random knots.
NASA Astrophysics Data System (ADS)
Young, C.; Blomberg, B.; Kolker, A.; Nguyen, U.; Page, C. M.; Sherchan, S. P.; Tobias, V. D.; Wu, H.
2017-12-01
Coastal communities in the Gulf of Mexico are facing new and complex challenges as their physical environment is altered by climate warming and sea level rise. To effectively prepare for environmental changes, coastal communities must build resilience in both physical structures and social structures. One measure of social structure resilience is how much social capital a community possesses. Social capital is defined as the connections among individuals which result in networks with shared norms, values and understandings that facilitate cooperation within or among groups. Social capital exists in three levels; bonding, bridging and linking. Bonding social capital is a measure of the strength of relationships amongst members of a network who are similar in some form. Bridging social capital is a measure of relationships amongst people who are dissimilar in some way, such as age, education, or race/ethnicity. Finally Linking social capital measures the extent to which individuals build relationships with institutions and individuals who have relative power over them (e.g local government, educational institutions). Using census and American Community Survey data, we calculated a Social Capital index value for bonding, bridging and linking for 60 Gulf of Mexico coastal counties for the years 2000, and 2010 to 2015. To investigate the impact of social capital on community resilience we coupled social capital index values with physical datasets of land-use/land cover, sea level change, climate, elevation and surface water quality for each coastal county in each year. Preliminary results indicate that in Gulf of Mexico coastal counties, increased bonding social capital results in decreased population change. In addition, we observed a multi-year time lag in the effect of increased bridging social capital on population stability, potentially suggesting key linkages between the physical and social environment in this complex coupled-natural human system. This transdisciplinary study integrated physical and social open science data and provides a better understanding on how increased social capital improves resilience to changes in the physical environment. Thus, by investing in social capital, local governments may have a low cost and non-structural way of increasing community resilience.
Wang, Feng; Liang, Yuting; Jiang, Yuji; Yang, Yunfeng; Xue, Kai; Xiong, Jinbo; Zhou, Jizhong; Sun, Bo
2015-01-01
Plants have an important impact on soil microbial communities and their functions. However, how plants determine the microbial composition and network interactions is still poorly understood. During a four-year field experiment, we investigated the functional gene composition of three types of soils (Phaeozem, Cambisols and Acrisol) under maize planting and bare fallow regimes located in cold temperate, warm temperate and subtropical regions, respectively. The core genes were identified using high-throughput functional gene microarray (GeoChip 3.0), and functional molecular ecological networks (fMENs) were subsequently developed with the random matrix theory (RMT)-based conceptual framework. Our results demonstrated that planting significantly (P < 0.05) increased the gene alpha-diversity in terms of richness and Shannon – Simpson’s indexes for all three types of soils and 83.5% of microbial alpha-diversity can be explained by the plant factor. Moreover, planting had significant impacts on the microbial community structure and the network interactions of the microbial communities. The calculated network complexity was higher under maize planting than under bare fallow regimes. The increase of the functional genes led to an increase in both soil respiration and nitrification potential with maize planting, indicating that changes in the soil microbial communities and network interactions influenced ecological functioning. PMID:26396042
Wielgoss, Arno; Tscharntke, Teja; Rumede, Alfianus; Fiala, Brigitte; Seidel, Hannes; Shahabuddin, Saleh; Clough, Yann
2014-01-01
Owing to complex direct and indirect effects, impacts of higher trophic levels on plants is poorly understood. In tropical agroecosystems, ants interact with crop mutualists and antagonists, but little is known about how this integrates into the final ecosystem service, crop yield. We combined ant exclusion and introduction of invasive and native-dominant species in cacao agroecosystems to test whether (i) ant exclusion reduces yield, (ii) dominant species maximize certain intermediate ecosystem services (e.g. control of specific pests) rather than yield, which depends on several, cascading intermediate services and (iii) even, species-rich ant communities result in highest yields. Ants provided services, including reduced leaf herbivory and fruit pest damage and indirect pollination facilitation, but also disservices, such as increased mealybug density, phytopathogen dissemination and indirect pest damage enhancement. Yields were highest with unmanipulated, species-rich, even communities, whereas ant exclusion decreased yield by 27%. Introduction of an invasive-dominant ant decreased species density and evenness and resulted in 34% lower yields, whereas introduction of a non-invasive-dominant species resulted in similar species density and yields as in the unmanipulated control. Species traits and ant community structure affect services and disservices for agriculture in surprisingly complex ways, with species-rich and even communities promoting highest yield. PMID:24307667
The optimal community detection of software based on complex networks
NASA Astrophysics Data System (ADS)
Huang, Guoyan; Zhang, Peng; Zhang, Bing; Yin, Tengteng; Ren, Jiadong
2016-02-01
The community structure is important for software in terms of understanding the design patterns, controlling the development and the maintenance process. In order to detect the optimal community structure in the software network, a method Optimal Partition Software Network (OPSN) is proposed based on the dependency relationship among the software functions. First, by analyzing the information of multiple execution traces of one software, we construct Software Execution Dependency Network (SEDN). Second, based on the relationship among the function nodes in the network, we define Fault Accumulation (FA) to measure the importance of the function node and sort the nodes with measure results. Third, we select the top K(K=1,2,…) nodes as the core of the primal communities (only exist one core node). By comparing the dependency relationships between each node and the K communities, we put the node into the existing community which has the most close relationship. Finally, we calculate the modularity with different initial K to obtain the optimal division. With experiments, the method OPSN is verified to be efficient to detect the optimal community in various softwares.
Cahuas, Madelaine C; Wakefield, Sarah; Peng, Yun
2015-05-01
There is a renewed interest in the potential of municipal governments working collaboratively with local communities to address health inequities. A growing body of literature has also highlighted the benefits and limitations of participatory approaches in neighbourhood interventions initiated by municipal governments. However, few studies have investigated how neighbourhood interventions tackling health inequities work in real-time and in context, from the perspectives of Community Developers (CDs) who promote community participation. This study uses a process evaluation approach and semi-structured interviews with CDs to explore the challenges they face in implementing a community development, participatory process in the City of Hamilton's strategy to reduce health inequities - Neighbourhood Action. Findings demonstrate that municipal government can facilitate and suppress community participation in complex ways. CDs serve as significant but conflicted intermediaries as they negotiate and navigate power differentials between city and community actors, while also facing structural challenges. We conclude that community participation is important to bottom-up, resident-led social change, and that CDs are central to this work. Copyright © 2014 Elsevier Ltd. All rights reserved.
Brawner, Bridgette M.; Reason, Janaiya L.; Goodman, Bridget A.; Schensul, Jean J.; Guthrie, Barbara
2014-01-01
Background Unequal HIV/AIDS distribution is influenced by certain social and structural contexts that facilitate HIV transmission and concentrate HIV in disease epicenters. Thus, one of the first steps in designing effective community-level HIV/AIDS initiatives is to disentangle the influence of individual, social, and structural factors on HIV risk. Combining ethnographic methodology with geographic information systems (GIS) mapping can allow for a complex exploration of multilevel factors within communities that facilitate HIV transmission in highly affected areas. Objectives We present the formative comparative community-based case study findings of an investigation of individual-, social- , and structural-level factors that contribute to the HIV/AIDS epidemic among Black Philadelphians. Methods Communities were defined using census tracts. The methodology included ethnographic and GIS mapping, observation, informal conversations with residents and business owners, and secondary analyses of census tract-level data in four Philadelphia neighborhoods. Results Factors such as overcrowding, disadvantage, permeability in community boundaries, and availability and accessibility of health-related resources varied significantly. Further, HIV/AIDS trended with social and structural inequities above and beyond the community’s racial composition. Discussion This study was a first step to disentangle relationships between community-level factors and potential risk for HIV in an HIV epicenter. The findings also highlight stark sociodemographic differences within and across racial groups, and further substantiate the need for comprehensive, community-level HIV prevention interventions. These findings from targeted United States urban communities have potential applicability for examining the distribution of HIV/AIDS in broader national and international geosocial contexts. PMID:25738621
Constant Communities in Complex Networks
NASA Astrophysics Data System (ADS)
Chakraborty, Tanmoy; Srinivasan, Sriram; Ganguly, Niloy; Bhowmick, Sanjukta; Mukherjee, Animesh
2013-05-01
Identifying community structure is a fundamental problem in network analysis. Most community detection algorithms are based on optimizing a combinatorial parameter, for example modularity. This optimization is generally NP-hard, thus merely changing the vertex order can alter their assignments to the community. However, there has been less study on how vertex ordering influences the results of the community detection algorithms. Here we identify and study the properties of invariant groups of vertices (constant communities) whose assignment to communities are, quite remarkably, not affected by vertex ordering. The percentage of constant communities can vary across different applications and based on empirical results we propose metrics to evaluate these communities. Using constant communities as a pre-processing step, one can significantly reduce the variation of the results. Finally, we present a case study on phoneme network and illustrate that constant communities, quite strikingly, form the core functional units of the larger communities.
NASA Astrophysics Data System (ADS)
Ma, Xiaoke; Wang, Bingbo; Yu, Liang
2018-01-01
Community detection is fundamental for revealing the structure-functionality relationship in complex networks, which involves two issues-the quantitative function for community as well as algorithms to discover communities. Despite significant research on either of them, few attempt has been made to establish the connection between the two issues. To attack this problem, a generalized quantification function is proposed for community in weighted networks, which provides a framework that unifies several well-known measures. Then, we prove that the trace optimization of the proposed measure is equivalent with the objective functions of algorithms such as nonnegative matrix factorization, kernel K-means as well as spectral clustering. It serves as the theoretical foundation for designing algorithms for community detection. On the second issue, a semi-supervised spectral clustering algorithm is developed by exploring the equivalence relation via combining the nonnegative matrix factorization and spectral clustering. Different from the traditional semi-supervised algorithms, the partial supervision is integrated into the objective of the spectral algorithm. Finally, through extensive experiments on both artificial and real world networks, we demonstrate that the proposed method improves the accuracy of the traditional spectral algorithms in community detection.
Aquatic-macroinvertebrate communities of Prairie-Pothole wetlands and lakes under a changed climate
McLean, Kyle I.; Mushet, David M.; Renton, David A.; Stockwell, Craig A.
2016-01-01
Understanding how aquatic-macroinvertebrate communities respond to changes in climate is important for biodiversity conservation in the Prairie Pothole Region and other wetland-rich landscapes. We sampled macroinvertebrate communities of 162 wetlands and lakes previously sampled from 1966 to 1976, a much drier period compared to our 2012–2013 sampling timeframe. To identify possible influences of a changed climate and predation pressures on macroinvertebrates, we compared two predictors of aquatic-macroinvertebrate communities: ponded-water dissolved-ion concentration and vertebrate-predator presence/abundance. Further, we make inferences of how macroinvertebrate communities were structured during the drier period when the range of dissolved-ion concentrations was much greater and fish occurrence in aquatic habitats was rare. We found that aquatic-macroinvertebrate community structure was influenced by dissolved-ion concentrations through a complex combination of direct and indirect relationships. Ion concentrations also influenced predator occurrence and abundance, which indirectly affected macroinvertebrate communities. It is important to consider both abiotic and biotic gradients when predicting how invertebrate communities will respond to climate change. Generally, in the wetlands and lakes we studied, freshening of ponded water resulted in more homogenous communities than occurred during a much drier period when salinity range among sites was greater.
The ground truth about metadata and community detection in networks
Peel, Leto; Larremore, Daniel B.; Clauset, Aaron
2017-01-01
Across many scientific domains, there is a common need to automatically extract a simplified view or coarse-graining of how a complex system’s components interact. This general task is called community detection in networks and is analogous to searching for clusters in independent vector data. It is common to evaluate the performance of community detection algorithms by their ability to find so-called ground truth communities. This works well in synthetic networks with planted communities because these networks’ links are formed explicitly based on those known communities. However, there are no planted communities in real-world networks. Instead, it is standard practice to treat some observed discrete-valued node attributes, or metadata, as ground truth. We show that metadata are not the same as ground truth and that treating them as such induces severe theoretical and practical problems. We prove that no algorithm can uniquely solve community detection, and we prove a general No Free Lunch theorem for community detection, which implies that there can be no algorithm that is optimal for all possible community detection tasks. However, community detection remains a powerful tool and node metadata still have value, so a careful exploration of their relationship with network structure can yield insights of genuine worth. We illustrate this point by introducing two statistical techniques that can quantify the relationship between metadata and community structure for a broad class of models. We demonstrate these techniques using both synthetic and real-world networks, and for multiple types of metadata and community structures. PMID:28508065
NASA Astrophysics Data System (ADS)
Roopnarine, P. D.; Weik, A.; Dineen, A.; Angielczyk, K.
2016-12-01
The Permian-Triassic mass extinction (PTME) is the most severe mass extinction recorded in Earth's history. Effects on the biosphere were complicated and often contradictory, e.g. selective species extinctions and exceptional species survival; prolonged miniaturization of some Early Triassic clades but rapid increases of size in others; and both simplified and complex trophic structures in various E. Triassic ecosystems. Here we present the results of a new generalized model of paleocommunity global stability (number of species capable of persistent coexistence in the absence of external perturbation), suggesting that community dynamics in response to species extinction, and the addition of new species in the aftermath of the PTME, is best understood as a complex outcome of predictable community dynamics and contingent, unpredictable evolutionary pathways. We applied the model to the best known PTME transitional terrestrial ecosystem, the Karoo Basin of South Africa. The model verifies previous claims that global stability scales negatively with increasing species richness and the strength of interspecific interactions. We also show that global stability scales negatively with intrinsic population growth rates. Taxon-rich Permian communities could therefore have persisted only under a restricted range of those parameters. Communities during three phases of the PTME, however, exhibited greater global stability than would be predicted from the pre-PTME communities. Those communities could therefore have maintained relative stabilities under a broader range of parameters, implying that species could have adapted by modifying life history and ecological traits with lesser negative consequences to community stability. The earliest post-PTME community with increased species richness, however, was less stable than would be predicted from pre-PTME communities. In both the extinction and aftermath communities, nonlinear deviations from the general scaling of stability result from structural features unique to those communities, perhaps limiting our ability to forecast biospheric responses to extreme perturbations.
Milferstedt, Kim; Santa-Catalina, Gaëlle; Godon, Jean-Jacques; Escudié, Renaud; Bernet, Nicolas
2013-01-01
Many natural and engineered biofilm systems periodically face disturbances. Here we present how the recovery time of a biofilm between disturbances (expressed as disturbance frequency) shapes the development of morphology and community structure in a multi-species biofilm at the landscape scale. It was hypothesized that a high disturbance frequency favors the development of a stable adapted biofilm system while a low disturbance frequency promotes a dynamic biofilm response. Biofilms were grown in laboratory-scale reactors over a period of 55-70 days and exposed to the biocide monochloramine at two frequencies: daily or weekly pulse injections. One untreated reactor served as control. Biofilm morphology and community structure were followed on comparably large biofilm areas at the landscape scale using automated image analysis (spatial gray level dependence matrices) and community fingerprinting (single-strand conformation polymorphisms). We demonstrated that a weekly disturbed biofilm developed a resilient morphology and community structure. Immediately after the disturbance, the biofilm simplified but recovered its initial complex morphology and community structure between two biocide pulses. In the daily treated reactor, one organism largely dominated a morphologically simple and stable biofilm. Disturbances primarily affected the abundance distribution of already present bacterial taxa but did not promote growth of previously undetected organisms. Our work indicates that disturbances can be used as lever to engineer biofilms by maintaining a biofilm between two developmental states. PMID:24303024
Quantifying the Adaptive Cycle | Science Inventory | US EPA
The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994–2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and
Urbach, E.; Vergin, K.L.; Larson, G.L.; Giovannoni, S.J.
2007-01-01
The distribution of bacterial and archaeal species in Crater Lake plankton varies dramatically over depth and with time, as assessed by hybridization of group-specific oligonucleotides to RNA extracted from lakewater. Nonmetric, multidimensional scaling (MDS) analysis of relative bacterial phylotype densities revealed complex relationships among assemblages sampled from depth profiles in July, August and September of 1997 through 1999. CL500-11 green nonsulfur bacteria (Phylum Chloroflexi) and marine Group I crenarchaeota are consistently dominant groups in the oxygenated deep waters at 300 and 500 m. Other phylotypes found in the deep waters are similar to surface and mid-depth populations and vary with time. Euphotic zone assemblages are dominated either by ??-proteobacteria or CL120-10 verrucomicrobia, and ACK4 actinomycetes. MDS analyses of euphotic zone populations in relation to environmental variables and phytoplankton and zooplankton population structures reveal apparent links between Daphnia pulicaria zooplankton population densities and microbial community structure. These patterns may reflect food web interactions that link kokanee salmon population densities to community structure of the bacterioplankton, via fish predation on Daphnia with cascading consequences to Daphnia bacterivory and predation on bacterivorous protists. These results demonstrate a stable bottom-water microbial community. They also extend previous observations of food web-driven changes in euphotic zone bacterioplankton community structure to an oligotrophic setting. ?? 2007 Springer Science+Business Media B.V.
Critical slowing down as early warning for the onset of collapse in mutualistic communities.
Dakos, Vasilis; Bascompte, Jordi
2014-12-09
Tipping points are crossed when small changes in external conditions cause abrupt unexpected responses in the current state of a system. In the case of ecological communities under stress, the risk of approaching a tipping point is unknown, but its stakes are high. Here, we test recently developed critical slowing-down indicators as early-warning signals for detecting the proximity to a potential tipping point in structurally complex ecological communities. We use the structure of 79 empirical mutualistic networks to simulate a scenario of gradual environmental change that leads to an abrupt first extinction event followed by a sequence of species losses until the point of complete community collapse. We find that critical slowing-down indicators derived from time series of biomasses measured at the species and community level signal the proximity to the onset of community collapse. In particular, we identify specialist species as likely the best-indicator species for monitoring the proximity of a community to collapse. In addition, trends in slowing-down indicators are strongly correlated to the timing of species extinctions. This correlation offers a promising way for mapping species resilience and ranking species risk to extinction in a given community. Our findings pave the road for combining theory on tipping points with patterns of network structure that might prove useful for the management of a broad class of ecological networks under global environmental change.
Taking a systems approach to ecological systems
Grace, James B.
2015-01-01
Increasingly, there is interest in a systems-level understanding of ecological problems, which requires the evaluation of more complex, causal hypotheses. In this issue of the Journal of Vegetation Science, Soliveres et al. use structural equation modeling to test a causal network hypothesis about how tree canopies affect understorey communities. Historical analysis suggests structural equation modeling has been under-utilized in ecology.
Human and Environmental Impacts on River Sediment Microbial Communities
Gibbons, Sean M.; Jones, Edwin; Bearquiver, Angelita; ...
2014-05-19
Sediment microbial communities are responsible for a majority of the metabolic activity in river and stream ecosystems. Understanding the dynamics in community structure and function across freshwater environments will help us to predict how these ecosystems will change in response to human land-use practices. Here we present a spatiotemporal study of sediments in the Tongue River (Montana, USA), comprising six sites along 134 km of river sampled in both spring and fall for two years. Sequencing of 16S rRNA amplicons and shotgun metagenomes revealed that these sediments are the richest (~65,000 microbial ‘species’ identified) and most novel (93% of OTUsmore » do not match known microbial diversity) ecosystems analyzed by the Earth Microbiome Project to date, and display more functional diversity than was detected in a recent review of global soil metagenomes. Community structure and functional potential have been significantly altered by anthropogenic drivers, including increased pathogenicity and antibiotic metabolism markers near towns and metabolic signatures of coal and coalbed methane extraction byproducts. The core (OTUs shared across all samples) and the overall microbial community exhibited highly similar structure, and phylogeny was weakly coupled with functional potential. Together, these results suggest that microbial community structure is shaped by environmental drivers and niche filtering, though stochastic assembly processes likely play a role as well. These results indicate that sediment microbial communities are highly complex and sensitive to changes in land use practices.« less
Structural Biology of Proteins of the Multi-enzyme Assembly Human Pyruvate Dehydrogenase Complex
NASA Technical Reports Server (NTRS)
2003-01-01
Objectives and research challenges of this effort include: 1. Need to establish Human Pyruvate Dehydrogenase Complex protein crystals; 2. Need to test value of microgravity for improving crystal quality of Human Pyruvate Dehydrogenase Complex protein crystals; 3. Need to improve flight hardware in order to control and understand the effects of microgravity on crystallization of Human Pyruvate Dehydrogenase Complex proteins; 4. Need to integrate sets of national collaborations with the restricted and specific requirements of flight experiments; 5. Need to establish a highly controlled experiment in microgravity with a rigor not yet obtained; 6. Need to communicate both the rigor of microgravity experiments and the scientific value of results obtained from microgravity experiments to the national community; and 7. Need to advance the understanding of Human Pyruvate Dehydrogenase Complex structures so that scientific and commercial advance is identified for these proteins.
Community Care for People with Complex Care Needs: Bridging the Gap between Health and Social Care
Ho, Julia W.; Hans, Parminder Kaur; Nelson, Michelle LA
2017-01-01
Introduction: A growing number of people are living with complex care needs characterized by multimorbidity, mental health challenges and social deprivation. Required is the integration of health and social care, beyond traditional health care services to address social determinants. This study investigates key care components to support complex patients and their families in the community. Methods: Expert panel focus groups with 24 care providers, working in health and social care sectors across Toronto, Ontario, Canada were conducted. Patient vignettes illustrating significant health and social care needs were presented to participants. The vignettes prompted discussions on i) how best to meet complex care needs in the community and ii) the barriers to delivering care to this population. Results: Categories to support care needs of complex patients and their families included i) relationships as the foundation for care, ii) desired processes and structures of care, and iii) barriers and workarounds for desired care. Discussion and Conclusions: Meeting the needs of the population who require health and social care requires time to develop authentic relationships, broadening the membership of the care team, communicating across sectors, co-locating health and social care, and addressing the barriers that prevent providers from engaging in these required practices. PMID:28970760
Lohse, Christian; Bassett, Danielle S; Lim, Kelvin O; Carlson, Jean M
2014-10-01
Human brain anatomy and function display a combination of modular and hierarchical organization, suggesting the importance of both cohesive structures and variable resolutions in the facilitation of healthy cognitive processes. However, tools to simultaneously probe these features of brain architecture require further development. We propose and apply a set of methods to extract cohesive structures in network representations of brain connectivity using multi-resolution techniques. We employ a combination of soft thresholding, windowed thresholding, and resolution in community detection, that enable us to identify and isolate structures associated with different weights. One such mesoscale structure is bipartivity, which quantifies the extent to which the brain is divided into two partitions with high connectivity between partitions and low connectivity within partitions. A second, complementary mesoscale structure is modularity, which quantifies the extent to which the brain is divided into multiple communities with strong connectivity within each community and weak connectivity between communities. Our methods lead to multi-resolution curves of these network diagnostics over a range of spatial, geometric, and structural scales. For statistical comparison, we contrast our results with those obtained for several benchmark null models. Our work demonstrates that multi-resolution diagnostic curves capture complex organizational profiles in weighted graphs. We apply these methods to the identification of resolution-specific characteristics of healthy weighted graph architecture and altered connectivity profiles in psychiatric disease.
Zhang, Lai; Andersen, Ken H; Dieckmann, Ulf; Brännström, Åke
2015-09-07
We investigate how four types of interference competition - which alternatively affect foraging, metabolism, survival, and reproduction - impact the ecology and evolution of size-structured populations. Even though all four types of interference competition reduce population biomass, interference competition at intermediate intensity sometimes significantly increases the abundance of adult individuals and the population׳s reproduction rate. We find that foraging and metabolic interference evolutionarily favor smaller maturation size when interference is weak and larger maturation size when interference is strong. The evolutionary response to survival interference and reproductive interference is always larger maturation size. We also investigate how the four types of interference competition impact the evolutionary dynamics and resultant diversity and trophic structure of size-structured communities. Like other types of trait-mediated competition, all four types of interference competition can induce disruptive selection and thus promote initial diversification. Even though foraging interference and reproductive interference are more potent in promoting initial diversification, they catalyze the formation of diverse communities with complex trophic structure only at high levels of interference intensity. By contrast, survival interference does so already at intermediate levels, while reproductive interference can only support relatively smaller communities with simpler trophic structure. Taken together, our results show how the type and intensity of interference competition jointly affect coexistence patterns in structured population models. Copyright © 2015 Elsevier Ltd. All rights reserved.
Gunda, Thushara; Turner, B. L.; Tidwell, Vincent C.
2018-03-14
Sociohydrological studies use interdisciplinary approaches to explore the complex interactions between physical and social water systems and increase our understanding of emergent and paradoxical system behaviors. The dynamics of community values and social cohesion, however, have received little attention in modeling studies due to quantification challenges. Social structures associated with community-managed irrigation systems around the world, in particular, reflect these communities' experiences with a multitude of natural and social shocks. Using the Valdez acequia (a communally-managed irrigation community in northern New Mexico) as a simulation case study, we evaluate the impact of that community's social structure in governing its responsesmore » to water availability stresses posed by climate change. Specifically, a system dynamics model (developed using insights from community stakeholders and multiple disciplines that captures biophysical, socioeconomic, and sociocultural dynamics of acequia systems) was used to generate counterfactual trajectories to explore how the community would behave with streamflow conditions expected under climate change. We found that earlier peak flows, combined with adaptive measures of shifting crop selection, allowed for greater production of higher value crops and fewer people leaving the acequia. The economic benefits were lost, however, if downstream water pressures increased. Even with significant reductions in agricultural profitability, feedbacks associated with community cohesion buffered the community's population and land parcel sizes from more detrimental impacts, indicating the community's resilience under natural and social stresses. In conclusion, continued exploration of social structures is warranted to better understand these systems' responses to stress and identify possible leverage points for strengthening community resilience.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gunda, Thushara; Turner, B. L.; Tidwell, Vincent C.
Sociohydrological studies use interdisciplinary approaches to explore the complex interactions between physical and social water systems and increase our understanding of emergent and paradoxical system behaviors. The dynamics of community values and social cohesion, however, have received little attention in modeling studies due to quantification challenges. Social structures associated with community-managed irrigation systems around the world, in particular, reflect these communities' experiences with a multitude of natural and social shocks. Using the Valdez acequia (a communally-managed irrigation community in northern New Mexico) as a simulation case study, we evaluate the impact of that community's social structure in governing its responsesmore » to water availability stresses posed by climate change. Specifically, a system dynamics model (developed using insights from community stakeholders and multiple disciplines that captures biophysical, socioeconomic, and sociocultural dynamics of acequia systems) was used to generate counterfactual trajectories to explore how the community would behave with streamflow conditions expected under climate change. We found that earlier peak flows, combined with adaptive measures of shifting crop selection, allowed for greater production of higher value crops and fewer people leaving the acequia. The economic benefits were lost, however, if downstream water pressures increased. Even with significant reductions in agricultural profitability, feedbacks associated with community cohesion buffered the community's population and land parcel sizes from more detrimental impacts, indicating the community's resilience under natural and social stresses. In conclusion, continued exploration of social structures is warranted to better understand these systems' responses to stress and identify possible leverage points for strengthening community resilience.« less
NASA Astrophysics Data System (ADS)
Gunda, T.; Turner, B. L.; Tidwell, V. C.
2018-04-01
Sociohydrological studies use interdisciplinary approaches to explore the complex interactions between physical and social water systems and increase our understanding of emergent and paradoxical system behaviors. The dynamics of community values and social cohesion, however, have received little attention in modeling studies due to quantification challenges. Social structures associated with community-managed irrigation systems around the world, in particular, reflect these communities' experiences with a multitude of natural and social shocks. Using the Valdez acequia (a communally-managed irrigation community in northern New Mexico) as a simulation case study, we evaluate the impact of that community's social structure in governing its responses to water availability stresses posed by climate change. Specifically, a system dynamics model (developed using insights from community stakeholders and multiple disciplines that captures biophysical, socioeconomic, and sociocultural dynamics of acequia systems) was used to generate counterfactual trajectories to explore how the community would behave with streamflow conditions expected under climate change. We found that earlier peak flows, combined with adaptive measures of shifting crop selection, allowed for greater production of higher value crops and fewer people leaving the acequia. The economic benefits were lost, however, if downstream water pressures increased. Even with significant reductions in agricultural profitability, feedbacks associated with community cohesion buffered the community's population and land parcel sizes from more detrimental impacts, indicating the community's resilience under natural and social stresses. Continued exploration of social structures is warranted to better understand these systems' responses to stress and identify possible leverage points for strengthening community resilience.
Beckett, Stephen J.; Williams, Hywel T. P.
2013-01-01
Phage and their bacterial hosts are the most diverse and abundant biological entities in the oceans, where their interactions have a major impact on marine ecology and ecosystem function. The structure of interaction networks for natural phage–bacteria communities offers insight into their coevolutionary origin. At small phylogenetic scales, observed communities typically show a nested structure, in which both hosts and phages can be ranked by their range of resistance and infectivity, respectively. A qualitatively different multi-scale structure is seen at larger phylogenetic scales; a natural assemblage sampled from the Atlantic Ocean displays large-scale modularity and local nestedness within each module. Here, we show that such ‘nested-modular’ interaction networks can be produced by a simple model of host–phage coevolution in which infection depends on genetic matching. Negative frequency-dependent selection causes diversification of hosts (to escape phages) and phages (to track their evolving hosts). This creates a diverse community of bacteria and phage, maintained by kill-the-winner ecological dynamics. When the resulting communities are visualized as bipartite networks of who infects whom, they show the nested-modular structure characteristic of the Atlantic sample. The statistical significance and strength of this observation varies depending on whether the interaction networks take into account the density of the interacting strains, with implications for interpretation of interaction networks constructed by different methods. Our results suggest that the apparently complex community structures associated with marine bacteria and phage may arise from relatively simple coevolutionary origins. PMID:24516719
Wendu, Ri-le; Li, Gang; Yang, Dian-lin; Zhang, Jing-ni; Yi, Jin
2011-04-01
By the methods of polymerase chain reaction-denaturing gradient gel electrophoresis and sequence analysis, a comparative study was conducted on the diversity and community structure of soil ammonia-oxidizing bacteria in the Filifolium sibiricum steppe, Stipa baicalensis steppe, Leymus chinensis steppe, Stipa grandis steppe, and Stipa kryrowi steppe in Hulunbeier Grassland, Inner Mongolia. A significant difference was observed in the community structure of soil ammonia-oxidizing bacteria among the five steppes, with the similarity lower than 50%. The diversity of soil ammonia-oxidizing bacteria was the highest in F. sibiricum steppe, followed by in S. baicalensis steppe, L. chinensis steppe, S. kryrowi steppe, and S. grandis steppe. In the five steppes, Nitrosospira cluster 3 was the dominant group, and the Nitrosospira cluster 1, 2, and 4 as well as Nitrosomonas were also found. The community structure of soil ammonia oxidizing bacteria in F. sibiricum steppe was most complex, while that in L. chinensis steppe and S. grandis steppe was relatively simple. Correlation analysis indicated that there existed significant positive correlations between the diversity of soil ammonia-oxidizing bacteria and the soil moisture, total nitrogen, total organic carbon, and C/N ratio (P<0.05).
Stable isotope probing to study functional components of complex microbial ecosystems.
Mazard, Sophie; Schäfer, Hendrik
2014-01-01
This protocol presents a method of dissecting the DNA or RNA of key organisms involved in a specific biochemical process within a complex ecosystem. Stable isotope probing (SIP) allows the labelling and separation of nucleic acids from community members that are involved in important biochemical transformations, yet are often not the most numerically abundant members of a community. This pure culture-independent technique circumvents limitations of traditional microbial isolation techniques or data mining from large-scale whole-community metagenomic studies to tease out the identities and genomic repertoires of microorganisms participating in biological nutrient cycles. SIP experiments can be applied to virtually any ecosystem and biochemical pathway under investigation provided a suitable stable isotope substrate is available. This versatile methodology allows a wide range of analyses to be performed, from fatty-acid analyses, community structure and ecology studies, and targeted metagenomics involving nucleic acid sequencing. SIP experiments provide an effective alternative to large-scale whole-community metagenomic studies by specifically targeting the organisms or biochemical transformations of interest, thereby reducing the sequencing effort and time-consuming bioinformatics analyses of large datasets.
Su, Xiaoquan; Wang, Xuetao; Jing, Gongchao; Ning, Kang
2014-04-01
The number of microbial community samples is increasing with exponential speed. Data-mining among microbial community samples could facilitate the discovery of valuable biological information that is still hidden in the massive data. However, current methods for the comparison among microbial communities are limited by their ability to process large amount of samples each with complex community structure. We have developed an optimized GPU-based software, GPU-Meta-Storms, to efficiently measure the quantitative phylogenetic similarity among massive amount of microbial community samples. Our results have shown that GPU-Meta-Storms would be able to compute the pair-wise similarity scores for 10 240 samples within 20 min, which gained a speed-up of >17 000 times compared with single-core CPU, and >2600 times compared with 16-core CPU. Therefore, the high-performance of GPU-Meta-Storms could facilitate in-depth data mining among massive microbial community samples, and make the real-time analysis and monitoring of temporal or conditional changes for microbial communities possible. GPU-Meta-Storms is implemented by CUDA (Compute Unified Device Architecture) and C++. Source code is available at http://www.computationalbioenergy.org/meta-storms.html.
Diverse, high-quality test set for the validation of protein-ligand docking performance.
Hartshorn, Michael J; Verdonk, Marcel L; Chessari, Gianni; Brewerton, Suzanne C; Mooij, Wijnand T M; Mortenson, Paul N; Murray, Christopher W
2007-02-22
A procedure for analyzing and classifying publicly available crystal structures has been developed. It has been used to identify high-resolution protein-ligand complexes that can be assessed by reconstructing the electron density for the ligand using the deposited structure factors. The complexes have been clustered according to the protein sequences, and clusters have been discarded if they do not represent proteins thought to be of direct interest to the pharmaceutical or agrochemical industry. Rules have been used to exclude complexes containing non-drug-like ligands. One complex from each cluster has been selected where a structure of sufficient quality was available. The final Astex diverse set contains 85 diverse, relevant protein-ligand complexes, which have been prepared in a format suitable for docking and are to be made freely available to the entire research community (http://www.ccdc.cam.ac.uk). The performance of the docking program GOLD against the new set is assessed using a variety of protocols. Relatively unbiased protocols give success rates of approximately 80% for redocking into native structures, but it is possible to get success rates of over 90% with some protocols.
Matrix composition and community structure analysis of a novel bacterial pyrite leaching community.
Ziegler, Sibylle; Ackermann, Sonia; Majzlan, Juraj; Gescher, Johannes
2009-09-01
Here we describe a novel bacterial community that is embedded in a matrix of carbohydrates and bio/geochemical products of pyrite (FeS(2)) oxidation. This community grows in stalactite-like structures--snottites--on the ceiling of an abandoned pyrite mine at pH values of 2.2-2.6. The aqueous phase in the matrix contains 200 mM of sulfate and total iron concentrations of 60 mM. Micro-X-ray diffraction analysis showed that jarosite [(K,Na,H(3)O)Fe(3)(SO(4))(2)(OH)(6)] is the major mineral embedded in the snottites. X-ray absorption near-edge structure experiments revealed three different sulfur species. The major signal can be ascribed to sulfate, and the other two features may correspond to thiols and sulfoxides. Arabinose was detected as the major sugar component in the extracellular polymeric substance. Via restriction fragment length polymorphism analysis, a community was found that mainly consists of iron oxidizing Leptospirillum and Ferrovum species but also of bacteria that could be involved in dissimilatory sulfate and dissimilatory iron reduction. Each snottite can be regarded as a complex, self-contained consortium of bacterial species fuelled by the decomposition of pyrite.
Wang, Mian; Chen, Mingna; Yang, Zhen; Chen, Na; Chi, Xiaoyuan; Pan, Lijuan; Wang, Tong; Yu, Shanlin; Guo, Xingqi
2017-12-01
Peanut yield and quality are seriously affected by pod rot pathogens worldwide, especially in China in recent years. The goals of this study are to analyze the structure of fungal communities of peanut pod rot in soil in three peanut cultivars and the correlation of pod rot with environmental variables using 454 pyrosequencing. A total of 46,723 internal transcribed spacer high-quality sequences were obtained and grouped into 1,706 operational taxonomic units at the 97% similarity cut-off level. The coverage, rank abundance, and the Chao 1 and Shannon diversity indices of the operational taxonomic units were analyzed. Members of the phylum Ascomycota were dominant, such as Fusarium , Chaetomium , Alternaria , and Sordariomycetes , followed by Basidiomycota. The results of the heatmap and redundancy analysis revealed significant variation in the composition of the fungal community among the three cultivar samples. The environmental conditions in different peanut cultivars may also influence on the structure of the fungal community. The results of this study suggest that the causal agent of peanut pod rot may be more complex, and cultivars and environmental conditions are both important contributors to the community structure of peanut pod rot fungi.
Lipsewers, Yvonne A.; Vasquez-Cardenas, Diana; Seitaj, Dorina; Schauer, Regina; Hidalgo-Martinez, Silvia; Meysman, Filip J. R.
2017-01-01
ABSTRACT Seasonal hypoxia in coastal systems drastically changes the availability of electron acceptors in bottom water, which alters the sedimentary reoxidation of reduced compounds. However, the effect of seasonal hypoxia on the chemolithoautotrophic community that catalyzes these reoxidation reactions is rarely studied. Here, we examine the changes in activity and structure of the sedimentary chemolithoautotrophic bacterial community of a seasonally hypoxic saline basin under oxic (spring) and hypoxic (summer) conditions. Combined 16S rRNA gene amplicon sequencing and analysis of phospholipid-derived fatty acids indicated a major temporal shift in community structure. Aerobic sulfur-oxidizing Gammaproteobacteria (Thiotrichales) and Epsilonproteobacteria (Campylobacterales) were prevalent during spring, whereas Deltaproteobacteria (Desulfobacterales) related to sulfate-reducing bacteria prevailed during summer hypoxia. Chemolithoautotrophy rates in the surface sediment were three times higher in spring than in summer. The depth distribution of chemolithoautotrophy was linked to the distinct sulfur oxidation mechanisms identified through microsensor profiling, i.e., canonical sulfur oxidation, electrogenic sulfur oxidation by cable bacteria, and sulfide oxidation coupled to nitrate reduction by Beggiatoaceae. The metabolic diversity of the sulfur-oxidizing bacterial community suggests a complex niche partitioning within the sediment, probably driven by the availability of reduced sulfur compounds (H2S, S0, and S2O32−) and electron acceptors (O2 and NO3−) regulated by seasonal hypoxia. IMPORTANCE Chemolithoautotrophic microbes in the seafloor are dependent on electron acceptors, like oxygen and nitrate, that diffuse from the overlying water. Seasonal hypoxia, however, drastically changes the availability of these electron acceptors in the bottom water; hence, one expects a strong impact of seasonal hypoxia on sedimentary chemolithoautotrophy. A multidisciplinary investigation of the sediments in a seasonally hypoxic coastal basin confirms this hypothesis. Our data show that bacterial community structure and chemolithoautotrophic activity varied with the seasonal depletion of oxygen. Unexpectedly, the dark carbon fixation was also dependent on the dominant microbial pathway of sulfur oxidation occurring in the sediment (i.e., canonical sulfur oxidation, electrogenic sulfur oxidation by cable bacteria, and sulfide oxidation coupled to nitrate reduction by Beggiatoaceae). These results suggest that a complex niche partitioning within the sulfur-oxidizing bacterial community additionally affects the chemolithoautotrophic community of seasonally hypoxic sediments. PMID:28314724
Lipsewers, Yvonne A; Vasquez-Cardenas, Diana; Seitaj, Dorina; Schauer, Regina; Hidalgo-Martinez, Silvia; Sinninghe Damsté, Jaap S; Meysman, Filip J R; Villanueva, Laura; Boschker, Henricus T S
2017-05-15
Seasonal hypoxia in coastal systems drastically changes the availability of electron acceptors in bottom water, which alters the sedimentary reoxidation of reduced compounds. However, the effect of seasonal hypoxia on the chemolithoautotrophic community that catalyzes these reoxidation reactions is rarely studied. Here, we examine the changes in activity and structure of the sedimentary chemolithoautotrophic bacterial community of a seasonally hypoxic saline basin under oxic (spring) and hypoxic (summer) conditions. Combined 16S rRNA gene amplicon sequencing and analysis of phospholipid-derived fatty acids indicated a major temporal shift in community structure. Aerobic sulfur-oxidizing Gammaproteobacteria ( Thiotrichales ) and Epsilonproteobacteria ( Campylobacterales ) were prevalent during spring, whereas Deltaproteobacteria ( Desulfobacterales ) related to sulfate-reducing bacteria prevailed during summer hypoxia. Chemolithoautotrophy rates in the surface sediment were three times higher in spring than in summer. The depth distribution of chemolithoautotrophy was linked to the distinct sulfur oxidation mechanisms identified through microsensor profiling, i.e., canonical sulfur oxidation, electrogenic sulfur oxidation by cable bacteria, and sulfide oxidation coupled to nitrate reduction by Beggiatoaceae The metabolic diversity of the sulfur-oxidizing bacterial community suggests a complex niche partitioning within the sediment, probably driven by the availability of reduced sulfur compounds (H 2 S, S 0 , and S 2 O 3 2- ) and electron acceptors (O 2 and NO 3 - ) regulated by seasonal hypoxia. IMPORTANCE Chemolithoautotrophic microbes in the seafloor are dependent on electron acceptors, like oxygen and nitrate, that diffuse from the overlying water. Seasonal hypoxia, however, drastically changes the availability of these electron acceptors in the bottom water; hence, one expects a strong impact of seasonal hypoxia on sedimentary chemolithoautotrophy. A multidisciplinary investigation of the sediments in a seasonally hypoxic coastal basin confirms this hypothesis. Our data show that bacterial community structure and chemolithoautotrophic activity varied with the seasonal depletion of oxygen. Unexpectedly, the dark carbon fixation was also dependent on the dominant microbial pathway of sulfur oxidation occurring in the sediment (i.e., canonical sulfur oxidation, electrogenic sulfur oxidation by cable bacteria, and sulfide oxidation coupled to nitrate reduction by Beggiatoaceae ). These results suggest that a complex niche partitioning within the sulfur-oxidizing bacterial community additionally affects the chemolithoautotrophic community of seasonally hypoxic sediments. Copyright © 2017 American Society for Microbiology.
Delparte, D; Gates, RD; Takabayashi, M
2015-01-01
The structural complexity of coral reefs plays a major role in the biodiversity, productivity, and overall functionality of reef ecosystems. Conventional metrics with 2-dimensional properties are inadequate for characterization of reef structural complexity. A 3-dimensional (3D) approach can better quantify topography, rugosity and other structural characteristics that play an important role in the ecology of coral reef communities. Structure-from-Motion (SfM) is an emerging low-cost photogrammetric method for high-resolution 3D topographic reconstruction. This study utilized SfM 3D reconstruction software tools to create textured mesh models of a reef at French Frigate Shoals, an atoll in the Northwestern Hawaiian Islands. The reconstructed orthophoto and digital elevation model were then integrated with geospatial software in order to quantify metrics pertaining to 3D complexity. The resulting data provided high-resolution physical properties of coral colonies that were then combined with live cover to accurately characterize the reef as a living structure. The 3D reconstruction of reef structure and complexity can be integrated with other physiological and ecological parameters in future research to develop reliable ecosystem models and improve capacity to monitor changes in the health and function of coral reef ecosystems. PMID:26207190
Valdivia, Abel; Cox, Courtney E.; Silbiger, Nyssa J.; Bruno, John F.
2017-01-01
Invasive lionfish are assumed to significantly affect Caribbean reef fish communities. However, evidence of lionfish effects on native reef fishes is based on uncontrolled observational studies or small-scale, unrepresentative experiments, with findings ranging from no effect to large effects on prey density and richness. Moreover, whether lionfish affect populations and communities of native reef fishes at larger, management-relevant scales is unknown. The purpose of this study was to assess the effects of lionfish on coral reef prey fish communities in a natural complex reef system. We quantified lionfish and the density, richness, and composition of native prey fishes (0–10 cm total length) at sixteen reefs along ∼250 km of the Belize Barrier Reef from 2009 to 2013. Lionfish invaded our study sites during this four-year longitudinal study, thus our sampling included fish community structure before and after our sites were invaded, i.e., we employed a modified BACI design. We found no evidence that lionfish measurably affected the density, richness, or composition of prey fishes. It is possible that higher lionfish densities are necessary to detect an effect of lionfish on prey populations at this relatively large spatial scale. Alternatively, negative effects of lionfish on prey could be small, essentially undetectable, and ecologically insignificant at our study sites. Other factors that influence the dynamics of reef fish populations including reef complexity, resource availability, recruitment, predation, and fishing could swamp any effects of lionfish on prey populations. PMID:28560093
Hackerott, Serena; Valdivia, Abel; Cox, Courtney E; Silbiger, Nyssa J; Bruno, John F
2017-01-01
Invasive lionfish are assumed to significantly affect Caribbean reef fish communities. However, evidence of lionfish effects on native reef fishes is based on uncontrolled observational studies or small-scale, unrepresentative experiments, with findings ranging from no effect to large effects on prey density and richness. Moreover, whether lionfish affect populations and communities of native reef fishes at larger, management-relevant scales is unknown. The purpose of this study was to assess the effects of lionfish on coral reef prey fish communities in a natural complex reef system. We quantified lionfish and the density, richness, and composition of native prey fishes (0-10 cm total length) at sixteen reefs along ∼250 km of the Belize Barrier Reef from 2009 to 2013. Lionfish invaded our study sites during this four-year longitudinal study, thus our sampling included fish community structure before and after our sites were invaded, i.e., we employed a modified BACI design. We found no evidence that lionfish measurably affected the density, richness, or composition of prey fishes. It is possible that higher lionfish densities are necessary to detect an effect of lionfish on prey populations at this relatively large spatial scale. Alternatively, negative effects of lionfish on prey could be small, essentially undetectable, and ecologically insignificant at our study sites. Other factors that influence the dynamics of reef fish populations including reef complexity, resource availability, recruitment, predation, and fishing could swamp any effects of lionfish on prey populations.
Sun, Yu; Li, Junhua; Suckling, John; Feng, Lei
2017-01-01
Human brain is structurally and functionally asymmetrical and the asymmetries of brain phenotypes have been shown to change in normal aging. Recent advances in graph theoretical analysis have showed topological lateralization between hemispheric networks in the human brain throughout the lifespan. Nevertheless, apparent discrepancies of hemispheric asymmetry were reported between the structural and functional brain networks, indicating the potentially complex asymmetry patterns between structural and functional networks in aging population. In this study, using multimodal neuroimaging (resting-state fMRI and structural diffusion tensor imaging), we investigated the characteristics of hemispheric network topology in 76 (male/female = 15/61, age = 70.08 ± 5.30 years) community-dwelling older adults. Hemispheric functional and structural brain networks were obtained for each participant. Graph theoretical approaches were then employed to estimate the hemispheric topological properties. We found that the optimal small-world properties were preserved in both structural and functional hemispheric networks in older adults. Moreover, a leftward asymmetry in both global and local levels were observed in structural brain networks in comparison with a symmetric pattern in functional brain network, suggesting a dissociable process of hemispheric asymmetry between structural and functional connectome in healthy older adults. Finally, the scores of hemispheric asymmetry in both structural and functional networks were associated with behavioral performance in various cognitive domains. Taken together, these findings provide new insights into the lateralized nature of multimodal brain connectivity, highlight the potentially complex relationship between structural and functional brain network alterations, and augment our understanding of asymmetric structural and functional specializations in normal aging. PMID:29209197
Thompson, C.; Beringer, J.; Chapin, F. S.; McGuire, A.D.
2004-01-01
Question: Current climate changes in the Alaskan Arctic, which are characterized by increases in temperature and length of growing season, could alter vegetation structure, especially through increases in shrub cover or the movement of treeline. These changes in vegetation structure have consequences for the climate system. What is the relationship between structural complexity and partitioning of surface energy along a gradient from tundra through shrub tundra to closed canopy forest? Location: Arctic tundra-boreal forest transition in the Alaskan Arctic. Methods: Along this gradient of increasing canopy complexity, we measured key vegetation characteristics, including community composition, biomass, cover, height, leaf area index and stem area index. We relate these vegetation characteristics to albedo and the partitioning of net radiation into ground, latent, and sensible heating fluxes. Results: Canopy complexity increased along the sequence from tundra to forest due to the addition of new plant functional types. This led to non-linear changes in biomass, cover, and height in the understory. The increased canopy complexity resulted in reduced ground heat fluxes, relatively conserved latent heat fluxes and increased sensible heat fluxes. The localized warming associated with increased sensible heating over more complex canopies may amplify regional warming, causing further vegetation change in the Alaskan Arctic.
The Influence of Heating Mains on Yeast Communities in Urban Soils
NASA Astrophysics Data System (ADS)
Tepeeva, A. N.; Glushakova, A. M.; Kachalkin, A. V.
2018-04-01
The number and species diversity of yeasts in urban soils (urbanozems) affected by heating mains and in epiphytic yeast complexes of grasses growing above them were studied. The number of yeasts in the soil reached 103-104 CFU/g; on the plants, 107 CFU/g. Significant (by an order of magnitude) increase in the total number of soil yeasts in the zone of heating mains in comparison with the surrounding soil was found in winter period. Overall, 25 species of yeasts were isolated in our study. Yeast community of studied urbanozems was dominated by the Candida sake, an eurybiont of the temperate zone and other natural ecotopes with relatively low temperatures, but its share was minimal in the zone of heating mains. In general, the structure of soil and epiphytic yeast complexes in the zones of heating mains differed from that in the surrounding area by higher species diversity and a lower share of pigmented species among the epiphytic yeasts. The study demonstrated that the number and species structure of soil yeast communities in urban soils change significantly under the influence of the temperature factor and acquire a mosaic distribution pattern.
NASA Astrophysics Data System (ADS)
Song, H. S.; Li, M.; Qian, W.; Song, X.; Chen, X.; Scheibe, T. D.; Fredrickson, J.; Zachara, J. M.; Liu, C.
2016-12-01
Modeling environmental microbial communities at individual organism level is currently intractable due to overwhelming structural complexity. Functional guild-based approaches alleviate this problem by lumping microorganisms into fewer groups based on their functional similarities. This reduction may become ineffective, however, when individual species perform multiple functions as environmental conditions vary. In contrast, the functional enzyme-based modeling approach we present here describes microbial community dynamics based on identified functional enzymes (rather than individual species or their groups). Previous studies in the literature along this line used biomass or functional genes as surrogate measures of enzymes due to the lack of analytical methods for quantifying enzymes in environmental samples. Leveraging our recent development of a signature peptide-based technique enabling sensitive quantification of functional enzymes in environmental samples, we developed a genetically structured microbial community model (GSMCM) to incorporate enzyme concentrations and various other omics measurements (if available) as key modeling input. We formulated the GSMCM based on the cybernetic metabolic modeling framework to rationally account for cellular regulation without relying on empirical inhibition kinetics. In the case study of modeling denitrification process in Columbia River hyporheic zone sediments collected from the Hanford Reach, our GSMCM provided a quantitative fit to complex experimental data in denitrification, including the delayed response of enzyme activation to the change in substrate concentration. Our future goal is to extend the modeling scope to the prediction of carbon and nitrogen cycles and contaminant fate. Integration of a simpler version of the GSMCM with PFLOTRAN for multi-scale field simulations is in progress.
Wheat landraces: A mini review
USDA-ARS?s Scientific Manuscript database
Farmers developed and utilized diverse wheat landraces to meet the complexity of a multitude of spatio-temporal, agro-ecological systems and to provide reliable sustenance and a sustainable food source to local communities. The genetic structure of wheat landraces is an evolutionary approach to surv...
Pec, Gregory J; Karst, Justine; Taylor, D Lee; Cigan, Paul W; Erbilgin, Nadir; Cooke, Janice E K; Simard, Suzanne W; Cahill, James F
2017-01-01
Western North American landscapes are rapidly being transformed by forest die-off caused by mountain pine beetle (Dendroctonus ponderosae), with implications for plant and soil communities. The mechanisms that drive changes in soil community structure, particularly for the highly prevalent ectomycorrhizal fungi in pine forests, are complex and intertwined. Critical to enhancing understanding will be disentangling the relative importance of host tree mortality from changes in soil chemistry following tree death. Here, we used a recent bark beetle outbreak in lodgepole pine (Pinus contorta) forests of western Canada to test whether the effects of tree mortality altered the richness and composition of belowground fungal communities, including ectomycorrhizal and saprotrophic fungi. We also determined the effects of environmental factors (i.e. soil nutrients, moisture, and phenolics) and geographical distance, both of which can influence the richness and composition of soil fungi. The richness of both groups of soil fungi declined and the overall composition was altered by beetle-induced tree mortality. Soil nutrients, soil phenolics and geographical distance influenced the community structure of soil fungi; however, the relative importance of these factors differed between ectomycorrhizal and saprotrophic fungi. The independent effects of tree mortality, soil phenolics and geographical distance influenced the community composition of ectomycorrhizal fungi, while the community composition of saprotrophic fungi was weakly but significantly correlated with the geographical distance of plots. Taken together, our results indicate that both deterministic and stochastic processes structure soil fungal communities following landscape-scale insect outbreaks and reflect the independent roles tree mortality, soil chemistry and geographical distance play in regulating the community composition of soil fungi. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.
A multistate dynamic site occupancy model for spatially aggregated sessile communities
Fukaya, Keiichi; Royle, J. Andrew; Okuda, Takehiro; Nakaoka, Masahiro; Noda, Takashi
2017-01-01
Estimation of transition probabilities of sessile communities seems easy in principle but may still be difficult in practice because resampling error (i.e. a failure to resample exactly the same location at fixed points) may cause significant estimation bias. Previous studies have developed novel analytical methods to correct for this estimation bias. However, they did not consider the local structure of community composition induced by the aggregated distribution of organisms that is typically observed in sessile assemblages and is very likely to affect observations.We developed a multistate dynamic site occupancy model to estimate transition probabilities that accounts for resampling errors associated with local community structure. The model applies a nonparametric multivariate kernel smoothing methodology to the latent occupancy component to estimate the local state composition near each observation point, which is assumed to determine the probability distribution of data conditional on the occurrence of resampling error.By using computer simulations, we confirmed that an observation process that depends on local community structure may bias inferences about transition probabilities. By applying the proposed model to a real data set of intertidal sessile communities, we also showed that estimates of transition probabilities and of the properties of community dynamics may differ considerably when spatial dependence is taken into account.Results suggest the importance of accounting for resampling error and local community structure for developing management plans that are based on Markovian models. Our approach provides a solution to this problem that is applicable to broad sessile communities. It can even accommodate an anisotropic spatial correlation of species composition, and may also serve as a basis for inferring complex nonlinear ecological dynamics.
NASA Astrophysics Data System (ADS)
Falconer, R.; Radoslow, P.; Grinev, D.; Otten, W.
2009-04-01
Fungi play a pivital role in soil ecosystems contributing to plant productivity. The underlying soil physical and biological processes responsible for community dynamics are interrelated and, at present, poorly understood. If these complex processes can be understood then this knowledge can be managed with an aim to providing more sustainable agriculture. Our understanding of microbial dynamics in soil has long been hampered by a lack of a theoretical framework and difficulties in observation and quantification. We will demonstrate how the spatial and temporal dynamics of fungi in soil can be understood by linking mathematical modelling with novel techniques that visualise the complex structure of the soil. The combination of these techniques and mathematical models opens up new possibilities to understand how the physical structure of soil affects fungal colony dynamics and also how fungal dynamics affect soil structure. We will quantify, using X ray tomography, soil structure for a range of artificially prepared microcosms. We characterise the soil structures using soil metrics such as porosity, fractal dimension, and the connectivity of the pore volume. Furthermore we will use the individual based fungal colony growth model of Falconer et al. 2005, which is based on the physiological processes of fungi, to assess the effect of soil structure on microbial dynamics by qualifying biomass abundances and distributions. We demonstrate how soil structure can critically affect fungal species interactions with consequences for biological control and fungal biodiversity.
NASA Astrophysics Data System (ADS)
Hardy, S. M.; Bik, H.; Walker, A.; Sharma, J.; Blanchard, A.
2016-02-01
Rapid change is occurring in the Arctic concurrently with increased human activity, yet our knowledge of the structure and function of high-Arctic sediment communities is still rudimentary. The Beaufort Sea is particularly poorly sampled, and largely unexplored at slope depths, providing little information with which to assess the impacts of petroleum exploration activities now beginning in this area. We are investigating diversity and community structure of meio- and macrobenthic infauna on the continental shelf and slope of the Beaufort Sea across a range of depths (50 to 1000 m) using traditional taxonomic and environmental DNA sequencing approaches, and comparing results to additional sites in the adjacent NE Chukchi Sea petroleum lease-sale area. The Beaufort slope is topographically complex and characterized by an east-west gradient in benthic habitat characteristics, with heavy input of terrestrial organic matter particularly in the region of the Mackenzie River delta. Warmer, saltier subsurface Atlantic water masses impact benthic communities at mid-slope depths, likely influencing turnover in community structure observed with depth. Food resources are variable across the region, with very high sediment chlorophyll concentrations at 350 m depth in some areas. Differences in nematode assemblages were detected across the Beaufort Sea shelf/slope, across depths within the Beaufort Sea, and between the Beaufort and adjacent NE Chukchi Sea. These differences were apparent in both morphological and environmental sequencing data. Macrofaunal communities showed variable community structure among transects, with high abundance and high dominance in polychaete assemblages coincident with the chlorophyll maximum. Sequencing data also revealed an abundance of protists in sediments which have been mostly ignored in studies of ecosystem dynamics in this region, and may represent an important component of the food web.
Community evolution mining and analysis in social network
NASA Astrophysics Data System (ADS)
Liu, Hongtao; Tian, Yuan; Liu, Xueyan; Jian, Jie
2017-03-01
With the development of digital and network technology, various social platforms emerge. These social platforms have greatly facilitated access to information, attracting more and more users. They use these social platforms every day to work, study and communicate, so every moment social platforms are generating massive amounts of data. These data can often be modeled as complex networks, making large-scale social network analysis possible. In this paper, the existing evolution classification model of community has been improved based on community evolution relationship over time in dynamic social network, and the Evolution-Tree structure is proposed which can show the whole life cycle of the community more clearly. The comparative test result shows that the improved model can excavate the evolution relationship of the community well.
You, Yeming; Wang, Juan; Huang, Xueman; Tang, Zuoxin; Liu, Shirong; Sun, Osbert J
2014-03-01
Forest soils store vast amounts of terrestrial carbon, but we are still limited in mechanistic understanding on how soil organic carbon (SOC) stabilization or turnover is controlled by biotic and abiotic factors in forest ecosystems. We used phospholipid fatty acids (PLFAs) as biomarker to study soil microbial community structure and measured activities of five extracellular enzymes involved in the degradation of cellulose (i.e., β-1,4-glucosidase and cellobiohydrolase), chitin (i.e., β-1,4-N-acetylglucosaminidase), and lignin (i.e., phenol oxidase and peroxidase) as indicators of soil microbial functioning in carbon transformation or turnover across varying biotic and abiotic conditions in a typical temperate forest ecosystem in central China. Redundancy analysis (RDA) was performed to determine the interrelationship between individual PFLAs and biotic and abiotic site factors as well as the linkage between soil microbial structure and function. Path analysis was further conducted to examine the controls of site factors on soil microbial community structure and the regulatory pathway of changes in SOC relating to microbial community structure and function. We found that soil microbial community structure is strongly influenced by water, temperature, SOC, fine root mass, clay content, and C/N ratio in soils and that the relative abundance of Gram-negative bacteria, saprophytic fungi, and actinomycetes explained most of the variations in the specific activities of soil enzymes involved in SOC transformation or turnover. The abundance of soil bacterial communities is strongly linked with the extracellular enzymes involved in carbon transformation, whereas the abundance of saprophytic fungi is associated with activities of extracellular enzymes driving carbon oxidation. Findings in this study demonstrate the complex interactions and linkage among plant traits, microenvironment, and soil physiochemical properties in affecting SOC via microbial regulations.
[Rapid ecological assessment of tropical fish communities in a gold mine area of Costa Rica].
Espinoza Mendiola, Mario
2008-12-01
Gold mining impacts have generated a great concern regarding aquatic systems and habitat fragmentation. Anthropogenic disturbances on the structure and heterogeneity of a system can have an important effect on aquatic community stability. Ecological rapid assessments (1996, 2002, and 2007) were employed to determine the structure, composition and distribution of tropical fish communities in several rivers and smaller creeks from a gold mining area in Cerro Crucitas, Costa Rica. In addition, species composition and relative abundance were related with habitat structure. A total of 35 species were registered, among which sardine Astyanax aeneus (Characidae) and livebearer Alfaro cultratus (Poeciliidae) were the most abundant fish (71%). The highest species richness was observed in Caño Crucitas (s=19) and Minas Creek (s=18). Significant differences in fish communities structure and composition from Infiernillo river and Minas creek were observed (lamda = 0.0, F(132, 66) = 2.24, p < 0.001). Presence and/or absence of certain species such as Dormitor gobiomorus, Rhamdia nicaraguensis, Parachromis loiseillei and Atractosteus tropicus explained most of the spatial variation among sites. Habitat structure also contributed to explain differences among sites (lamda = 0.004, F(60.183) = 5.52, p < 0.001). Substratum (soft and hard bottom types) and habitat attributes (elevation, width and depth) explained most of the variability observed in Infiernillo River, Caño Crucitas and Tamagá Creek. In addition, a significant association between fish species and habitat structure was observed. This study reveals a high complexity in tropical fish communities that inhabit a gold mine area. Furthermore, it highlights the importance of habitat heterogeneity in fish community dynamics. The loss and degradation of aquatic systems in Cerro Crucitas can have a strong negative effect on fish community structure and composition of local species. A better understanding of the use of specific habitats that serve as essential fish habitats can improve tropical fish conservation and management strategies, thus increasing local diversity, and thereby, the biological importance of the area.
Socio-cultural impacts of contemporary tourism.
Jovicić, Dobrica
2011-06-01
The topic of the paper is devoted to analysis of socio-cultural impacts of tourism, as effects on the people of host communities resulting from their direct and indirect associations with tourists. The social and cultural impacts of tourism are the ways in which tourism is contributing to changes in value systems, individual behavior, family structure and relationships, collective lifestyles, safety levels, moral conduct, traditional ceremonies and community organizations. Special attention is devoted to considering complexity of tourists/host interrelationships and discussing the techniques for appraisal of quality and quantity of socio-cultural changes which tourism provokes in local communities.
Uncovering the overlapping community structure of complex networks by maximal cliques
NASA Astrophysics Data System (ADS)
Li, Junqiu; Wang, Xingyuan; Cui, Yaozu
2014-12-01
In this paper, a unique algorithm is proposed to detect overlapping communities in the un-weighted and weighted networks with considerable accuracy. The maximal cliques, overlapping vertex, bridge vertex and isolated vertex are introduced. First, all the maximal cliques are extracted by the algorithm based on the deep and bread searching. Then two maximal cliques can be merged into a larger sub-graph by some given rules. In addition, the proposed algorithm successfully finds overlapping vertices and bridge vertices between communities. Experimental results using some real-world networks data show that the performance of the proposed algorithm is satisfactory.
An edge-centric perspective on the human connectome: link communities in the brain.
de Reus, Marcel A; Saenger, Victor M; Kahn, René S; van den Heuvel, Martijn P
2014-10-05
Brain function depends on efficient processing and integration of information within a complex network of neural interactions, known as the connectome. An important aspect of connectome architecture is the existence of community structure, providing an anatomical basis for the occurrence of functional specialization. Typically, communities are defined as groups of densely connected network nodes, representing clusters of brain regions. Looking at the connectome from a different perspective, instead focusing on the interconnecting links or edges, we find that the white matter pathways between brain regions also exhibit community structure. Eleven link communities were identified: five spanning through the midline fissure, three through the left hemisphere and three through the right hemisphere. We show that these link communities are consistently identifiable and investigate the network characteristics of their underlying white matter pathways. Furthermore, examination of the relationship between link communities and brain regions revealed that the majority of brain regions participate in multiple link communities. In particular, the highly connected and central hub regions showed a rich level of community participation, supporting the notion that these hubs play a pivotal role as confluence zones in which neural information from different domains merges. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Logue, Jürg B; Stedmon, Colin A; Kellerman, Anne M; Nielsen, Nikoline J; Andersson, Anders F; Laudon, Hjalmar; Lindström, Eva S; Kritzberg, Emma S
2016-01-01
Bacteria play a central role in the cycling of carbon, yet our understanding of the relationship between the taxonomic composition and the degradation of dissolved organic matter (DOM) is still poor. In this experimental study, we were able to demonstrate a direct link between community composition and ecosystem functioning in that differently structured aquatic bacterial communities differed in their degradation of terrestrially derived DOM. Although the same amount of carbon was processed, both the temporal pattern of degradation and the compounds degraded differed among communities. We, moreover, uncovered that low-molecular-weight carbon was available to all communities for utilisation, whereas the ability to degrade carbon of greater molecular weight was a trait less widely distributed. Finally, whereas the degradation of either low- or high-molecular-weight carbon was not restricted to a single phylogenetic clade, our results illustrate that bacterial taxa of similar phylogenetic classification differed substantially in their association with the degradation of DOM compounds. Applying techniques that capture the diversity and complexity of both bacterial communities and DOM, our study provides new insight into how the structure of bacterial communities may affect processes of biogeochemical significance. PMID:26296065
An ant colony based algorithm for overlapping community detection in complex networks
NASA Astrophysics Data System (ADS)
Zhou, Xu; Liu, Yanheng; Zhang, Jindong; Liu, Tuming; Zhang, Di
2015-06-01
Community detection is of great importance to understand the structures and functions of networks. Overlap is a significant feature of networks and overlapping community detection has attracted an increasing attention. Many algorithms have been presented to detect overlapping communities. In this paper, we present an ant colony based overlapping community detection algorithm which mainly includes ants' location initialization, ants' movement and post processing phases. An ants' location initialization strategy is designed to identify initial location of ants and initialize label list stored in each node. During the ants' movement phase, the entire ants move according to the transition probability matrix, and a new heuristic information computation approach is redefined to measure similarity between two nodes. Every node keeps a label list through the cooperation made by ants until a termination criterion is reached. A post processing phase is executed on the label list to get final overlapping community structure naturally. We illustrate the capability of our algorithm by making experiments on both synthetic networks and real world networks. The results demonstrate that our algorithm will have better performance in finding overlapping communities and overlapping nodes in synthetic datasets and real world datasets comparing with state-of-the-art algorithms.
NASA Astrophysics Data System (ADS)
Karkarey, R.; Kelkar, N.; Lobo, A. Savio; Alcoverro, T.; Arthur, R.
2014-06-01
Benthic recovery from climate-related disturbances does not always warrant a commensurate functional recovery for reef-associated fish communities. Here, we examine the distribution of benthic groupers (family Serranidae) in coral reef communities from the Lakshadweep archipelago (Arabian Sea) in response to structural complexity and long-term habitat stability. These coral reefs that have been subject to two major El Niño Southern Oscillation-related coral bleaching events in the last decades (1998 and 2010). First, we employ a long-term (12-yr) benthic-monitoring dataset to track habitat structural stability at twelve reef sites in the archipelago. Structural stability of reefs was strongly driven by exposure to monsoon storms and depth, which made deeper and more sheltered reefs on the eastern aspect more stable than the more exposed (western) and shallower reefs. We surveyed groupers (species richness, abundance, biomass) in 60 sites across the entire archipelago, representing both exposures and depths. Sites were selected along a gradient of structural complexity from very low to high. Grouper biomass appeared to vary with habitat stability with significant differences between depth and exposure; sheltered deep reefs had a higher grouper biomass than either sheltered shallow or exposed (deep and shallow) reefs. Species richness and abundance showed similar (though not significant) trends. More interestingly, average grouper biomass increased exponentially with structural complexity, but only at the sheltered deep (high stability) sites, despite the availability of recovered structure at exposed deep and shallow sites (lower-stability sites). This trend was especially pronounced for long-lived groupers (life span >10 yrs). These results suggest that long-lived groupers may prefer temporally stable reefs, independent of the local availability of habitat structure. In reefs subject to repeated disturbances, the presence of structurally stable reefs may be critical as refuges for functionally important, long-lived species like groupers.
Power, Eileen F.; Kelly, Daniel L.; Stout, Jane C.
2012-01-01
Parallel declines in insect-pollinated plants and their pollinators have been reported as a result of agricultural intensification. Intensive arable plant communities have previously been shown to contain higher proportions of self-pollinated plants compared to natural or semi-natural plant communities. Though intensive grasslands are widespread, it is not known whether they show similar patterns to arable systems nor whether local and/or landscape factors are influential. We investigated plant community composition in 10 pairs of organic and conventional dairy farms across Ireland in relation to the local and landscape context. Relationships between plant groups and local factors (farming system, position in field and soil parameters) and landscape factors (e.g. landscape complexity) were investigated. The percentage cover of unimproved grassland was used as an inverse predictor of landscape complexity, as it was negatively correlated with habitat-type diversity. Intensive grasslands (organic and conventional) contained more insect-pollinated forbs than non-insect pollinated forbs. Organic field centres contained more insect-pollinated forbs than conventional field centres. Insect-pollinated forb richness in field edges (but not field centres) increased with increasing landscape complexity (% unimproved grassland) within 1, 3, 4 and 5km radii around sites, whereas non-insect pollinated forb richness was unrelated to landscape complexity. Pollination systems within intensive grassland communities may be different from those in arable systems. Our results indicate that organic management increases plant richness in field centres, but that landscape complexity exerts strong influences in both organic and conventional field edges. Insect-pollinated forb richness, unlike that for non-insect pollinated forbs, showed positive relationships to landscape complexity reflecting what has been documented for bees and other pollinators. The insect-pollinated forbs, their pollinators and landscape context are clearly linked. This needs to be taken into account when managing and conserving insect-pollinated plant and pollinator communities. PMID:22666450
LIPID ANALYSIS TO DETERMINE THE EFFECT OF A SOURCE REMEDIAL TECHNOLOGY IN MICROBIAL ECOLOGY
Microbial community structures and related changes in the subsurface environment were investigated following in situ chemical oxidation (ISCO) treatment at Launch Complex 34, Cape Canaveral Air Station, Florida. The site has dense non-aqueous phase (DNAPL) concentrations of TCE ...
NATURE OF CUMULATIVE IMPACTS ON BIOTIC DIVERSITY OF WETLAND VERTEBRATES
There is no longer any doubt that cumulative impacts have important effects on wetland vertebrates. he interactions of species diversity and community structure produce a complex pattern in which environmental impacts can play a highly significant role. ariety of examples shows h...
Beyond the continuum: a multi-dimensional phase space for neutral-niche community assembly.
Latombe, Guillaume; Hui, Cang; McGeoch, Melodie A
2015-12-22
Neutral and niche processes are generally considered to interact in natural communities along a continuum, exhibiting community patterns bounded by pure neutral and pure niche processes. The continuum concept uses niche separation, an attribute of the community, to test the hypothesis that communities are bounded by pure niche or pure neutral conditions. It does not accommodate interactions via feedback between processes and the environment. By contrast, we introduce the Community Assembly Phase Space (CAPS), a multi-dimensional space that uses community processes (such as dispersal and niche selection) to define the limiting neutral and niche conditions and to test the continuum hypothesis. We compare the outputs of modelled communities in a heterogeneous landscape, assembled by pure neutral, pure niche and composite processes. Differences in patterns under different combinations of processes in CAPS reveal hidden complexity in neutral-niche community dynamics. The neutral-niche continuum only holds for strong dispersal limitation and niche separation. For weaker dispersal limitation and niche separation, neutral and niche processes amplify each other via feedback with the environment. This generates patterns that lie well beyond those predicted by a continuum. Inferences drawn from patterns about community assembly processes can therefore be misguided when based on the continuum perspective. CAPS also demonstrates the complementary information value of different patterns for inferring community processes and captures the complexity of community assembly. It provides a general tool for studying the processes structuring communities and can be applied to address a range of questions in community and metacommunity ecology. © 2015 The Author(s).
Beyond the continuum: a multi-dimensional phase space for neutral–niche community assembly
Latombe, Guillaume; McGeoch, Melodie A.
2015-01-01
Neutral and niche processes are generally considered to interact in natural communities along a continuum, exhibiting community patterns bounded by pure neutral and pure niche processes. The continuum concept uses niche separation, an attribute of the community, to test the hypothesis that communities are bounded by pure niche or pure neutral conditions. It does not accommodate interactions via feedback between processes and the environment. By contrast, we introduce the Community Assembly Phase Space (CAPS), a multi-dimensional space that uses community processes (such as dispersal and niche selection) to define the limiting neutral and niche conditions and to test the continuum hypothesis. We compare the outputs of modelled communities in a heterogeneous landscape, assembled by pure neutral, pure niche and composite processes. Differences in patterns under different combinations of processes in CAPS reveal hidden complexity in neutral–niche community dynamics. The neutral–niche continuum only holds for strong dispersal limitation and niche separation. For weaker dispersal limitation and niche separation, neutral and niche processes amplify each other via feedback with the environment. This generates patterns that lie well beyond those predicted by a continuum. Inferences drawn from patterns about community assembly processes can therefore be misguided when based on the continuum perspective. CAPS also demonstrates the complementary information value of different patterns for inferring community processes and captures the complexity of community assembly. It provides a general tool for studying the processes structuring communities and can be applied to address a range of questions in community and metacommunity ecology. PMID:26702047
Kittelmann, Sandra; Seedorf, Henning; Walters, William A.; Clemente, Jose C.; Knight, Rob; Gordon, Jeffrey I.; Janssen, Peter H.
2013-01-01
Ruminants rely on a complex rumen microbial community to convert dietary plant material to energy-yielding products. Here we developed a method to simultaneously analyze the community's bacterial and archaeal 16S rRNA genes, ciliate 18S rRNA genes and anaerobic fungal internal transcribed spacer 1 genes using 12 DNA samples derived from 11 different rumen samples from three host species (Ovis aries, Bos taurus, Cervus elephas) and multiplex 454 Titanium pyrosequencing. We show that the mixing ratio of the group-specific DNA templates before emulsion PCR is crucial to compensate for differences in amplicon length. This method, in contrast to using a non-specific universal primer pair, avoids sequencing non-targeted DNA, such as plant- or endophyte-derived rRNA genes, and allows increased or decreased levels of community structure resolution for each microbial group as needed. Communities analyzed with different primers always grouped by sample origin rather than by the primers used. However, primer choice had a greater impact on apparent archaeal community structure than on bacterial community structure, and biases for certain methanogen groups were detected. Co-occurrence analysis of microbial taxa from all three domains of life suggested strong within- and between-domain correlations between different groups of microorganisms within the rumen. The approach used to simultaneously characterize bacterial, archaeal and eukaryotic components of a microbiota should be applicable to other communities occupying diverse habitats. PMID:23408926
Kittelmann, Sandra; Seedorf, Henning; Walters, William A; Clemente, Jose C; Knight, Rob; Gordon, Jeffrey I; Janssen, Peter H
2013-01-01
Ruminants rely on a complex rumen microbial community to convert dietary plant material to energy-yielding products. Here we developed a method to simultaneously analyze the community's bacterial and archaeal 16S rRNA genes, ciliate 18S rRNA genes and anaerobic fungal internal transcribed spacer 1 genes using 12 DNA samples derived from 11 different rumen samples from three host species (Ovis aries, Bos taurus, Cervus elephas) and multiplex 454 Titanium pyrosequencing. We show that the mixing ratio of the group-specific DNA templates before emulsion PCR is crucial to compensate for differences in amplicon length. This method, in contrast to using a non-specific universal primer pair, avoids sequencing non-targeted DNA, such as plant- or endophyte-derived rRNA genes, and allows increased or decreased levels of community structure resolution for each microbial group as needed. Communities analyzed with different primers always grouped by sample origin rather than by the primers used. However, primer choice had a greater impact on apparent archaeal community structure than on bacterial community structure, and biases for certain methanogen groups were detected. Co-occurrence analysis of microbial taxa from all three domains of life suggested strong within- and between-domain correlations between different groups of microorganisms within the rumen. The approach used to simultaneously characterize bacterial, archaeal and eukaryotic components of a microbiota should be applicable to other communities occupying diverse habitats.
Temperate Snake Community in South America: Is Diet Determined by Phylogeny or Ecology?
Etchepare, Eduardo G.
2015-01-01
Communities are complex and dynamic systems that change with time. The first attempts to explain how they were structured involve contemporary phenomena like ecological interactions between species (e.g., competition and predation) and led to the competition-predation hypothesis. Recently, the deep history hypothesis has emerged, which suggests that profound differences in the evolutionary history of organisms resulted in a number of ecological features that remain largely on species that are part of existing communities. Nevertheless, both phylogenetic structure and ecological interactions can act together to determine the structure of a community. Because diet is one of the main niche axes, in this study we evaluated, for the first time, the impact of ecological and phylogenetic factors on the diet of Neotropical snakes from the subtropical-temperate region of South America. Additionally, we studied their relationship with morphological and environmental aspects to understand the natural history and ecology of this community. A canonical phylogenetical ordination analysis showed that phylogeny explained most of the variation in diet, whereas ecological characters explained very little of this variation. Furthermore, some snakes that shared the habitat showed some degree of diet convergence, in accordance with the competition-predation hypothesis, although phylogeny remained the major determinant in structuring this community. The clade with the greatest variability was the subfamily Dipsadinae, whose members had a very different type of diet, based on soft-bodied invertebrates. Our results are consistent with the deep history hypothesis, and we suggest that the community under study has a deep phylogenetic effect that explains most of the variation in the diet. PMID:25945501
Stage structure alters how complexity affects stability of ecological networks
Rudolf, V.H.W.; Lafferty, Kevin D.
2011-01-01
Resolving how complexity affects stability of natural communities is of key importance for predicting the consequences of biodiversity loss. Central to previous stability analysis has been the assumption that the resources of a consumer are substitutable. However, during their development, most species change diets; for instance, adults often use different resources than larvae or juveniles. Here, we show that such ontogenetic niche shifts are common in real ecological networks and that consideration of these shifts can alter which species are predicted to be at risk of extinction. Furthermore, niche shifts reduce and can even reverse the otherwise stabilizing effect of complexity. This pattern arises because species with several specialized life stages appear to be generalists at the species level but act as sequential specialists that are hypersensitive to resource loss. These results suggest that natural communities are more vulnerable to biodiversity loss than indicated by previous analyses.
Adam, Thomas C; Brooks, Andrew J; Holbrook, Sally J; Schmitt, Russell J; Washburn, Libe; Bernardi, Giacomo
2014-09-01
Global climate change is rapidly altering disturbance regimes in many ecosystems including coral reefs, yet the long-term impacts of these changes on ecosystem structure and function are difficult to predict. A major ecosystem service provided by coral reefs is the provisioning of physical habitat for other organisms, and consequently, many of the effects of climate change on coral reefs will be mediated by their impacts on habitat structure. Therefore, there is an urgent need to understand the independent and combined effects of coral mortality and loss of physical habitat on reef-associated biota. Here, we use a unique series of events affecting the coral reefs around the Pacific island of Moorea, French Polynesia to differentiate between the impacts of coral mortality and the degradation of physical habitat on the structure of reef fish communities. We found that, by removing large amounts of physical habitat, a tropical cyclone had larger impacts on reef fish communities than an outbreak of coral-eating sea stars that caused widespread coral mortality but left the physical structure intact. In addition, the impacts of declining structural complexity on reef fish assemblages accelerated as structure became increasingly rare. Structure provided by dead coral colonies can take up to decades to erode following coral mortality, and, consequently, our results suggest that predictions based on short-term studies are likely to grossly underestimate the long-term impacts of coral decline on reef fish communities.
High pressure and multiferroics materials: a happy marriage
Gilioli, Edmondo; Ehm, Lars
2014-01-01
The community of material scientists is strongly committed to the research area of multiferroic materials, both for the understanding of the complex mechanisms supporting the multiferroism and for the fabrication of new compounds, potentially suitable for technological applications. The use of high pressure is a powerful tool in synthesizing new multiferroic, in particular magneto-electric phases, where the pressure stabilization of otherwise unstable perovskite-based structural distortions may lead to promising novel metastable compounds. The in situ investigation of the high-pressure behavior of multiferroic materials has provided insight into the complex interplay between magnetic and electronic properties and the coupling to structural instabilities. PMID:25485138
Is benthic food web structure related to diversity of marine macrobenthic communities?
NASA Astrophysics Data System (ADS)
Sokołowski, A.; Wołowicz, M.; Asmus, H.; Asmus, R.; Carlier, A.; Gasiunaité, Z.; Grémare, A.; Hummel, H.; Lesutiené, J.; Razinkovas, A.; Renaud, P. E.; Richard, P.; Kędra, M.
2012-08-01
Numerical structure and the organisation of food webs within macrozoobenthic communities has been assessed in the European waters (Svalbard, Barents Sea, Baltic Sea, North Sea, Atlantic Ocean and the Mediterranean Sea) to address the interactions between biodiversity and ecosystem functioning. Abundance and classical species diversity indices (S, H', J) of macrofaunal communities were related to principal attributes of food webs (relative trophic level and food chain length, FCL) that were determined from carbon and nitrogen stable isotope values. Structure of marine macrobenthos varies substantially at a geographical scale; total abundance ranges from 63 ind. m-2 to 34,517 ind. m-2, species richness varies from 3 to 166 and the Shannon-Weaver diversity index from 0.26 to 3.26 while Pielou's evenness index is below 0.73. The major source of energy for macrobenthic communities is suspended particulate organic matter, consisting of phytoplankton and detrital particles, sediment particulate organic matter, and microphytobenthos in varying proportions. These food sources support the presence of suspension- and deposit-feeding communities, which dominate numerically on the sea floor. Benthic food webs include usually four to five trophic levels (FCL varies from 3.08 to 4.86). Most species are assigned to the second trophic level (primary consumers), fewer species are grouped in the third trophic level (secondary consumers), and benthic top predators are the least numerous. Most species cluster primarily at the lowest trophic level that is consistent with the typical organization of pyramidal food webs. Food chain length increases with biodiversity, highlighting a positive effect of more complex community structure on food web organisation. In more diverse benthic communities, energy is transferred through more trophic levels while species-poor communities sustain a shorter food chain.
Underwood, Carlisa M; Hayne, Arlene N
The purpose was to identify and describe structures and processes of best practices for system-level shared governance in healthcare systems. Currently, more than 64.6% of US community hospitals are part of a system. System chief nurse executives (SCNEs) are challenged to establish leadership structures and processes that effectively and efficiently disseminate best practices for patients and staff across complex organizations, geographically dispersed locations, and populations. Eleven US healthcare SCNEs from the American Nurses Credentialing Center's repository of Magnet®-designated facilities participated in a 35-multiquestion interview based on Kanter's Theory of Organizational Empowerment. Most SCNEs reported the presence of more than 50% of the empowerment structures and processes in system-level shared governance. Despite the difficulties and complexities of growing health systems, SCNEs have replicated empowerment characteristics of hospital shared governance structures and processes at the system level.
Structure of local interactions in complex financial dynamics
Jiang, X. F.; Chen, T. T.; Zheng, B.
2014-01-01
With the network methods and random matrix theory, we investigate the interaction structure of communities in financial markets. In particular, based on the random matrix decomposition, we clarify that the local interactions between the business sectors (subsectors) are mainly contained in the sector mode. In the sector mode, the average correlation inside the sectors is positive, while that between the sectors is negative. Further, we explore the time evolution of the interaction structure of the business sectors, and observe that the local interaction structure changes dramatically during a financial bubble or crisis. PMID:24936906
Wang, Yong-Feng; Zhang, Fang-Qiu; Gu, Ji-Dong
2014-06-01
Denaturing gradient gel electrophoresis (DGGE) is a powerful technique to reveal the community structures and composition of microorganisms in complex natural environments and samples. However, positive and reproducible polymerase chain reaction (PCR) products, which are difficult to acquire for some specific samples due to low abundance of the target microorganisms, significantly impair the effective applications of DGGE. Thus, nested PCR is often introduced to generate positive PCR products from the complex samples, but one problem is also introduced: The total number of thermocycling in nested PCR is usually unacceptably high, which results in skewed community structures by generation of random or mismatched PCR products on the DGGE gel, and this was demonstrated in this study. Furthermore, nested PCR could not resolve the uneven representative issue with PCR products of complex samples with unequal richness of microbial population. In order to solve the two problems in nested PCR, the general protocol was modified and improved in this study. Firstly, a general PCR procedure was used to amplify the target genes with the PCR primers without any guanine cytosine (GC) clamp, and then, the resultant PCR products were purified and diluted to 0.01 μg ml(-1). Subsequently, the diluted PCR products were utilized as templates to amplify again with the same PCR primers with the GC clamp for 17 cycles, and the products were finally subjected to DGGE analysis. We demonstrated that this is a much more reliable approach to obtain a high quality DGGE profile with high reproducibility. Thus, we recommend the adoption of this improved protocol in analyzing microorganisms of low abundance in complex samples when applying the DGGE fingerprinting technique to avoid biased results.
The role of banks in the Brazilian interbank market: Does bank type matter?
NASA Astrophysics Data System (ADS)
Cajueiro, Daniel O.; Tabak, Benjamin M.
2008-12-01
This paper analyzes the Brazilian interbank network structure using a complex network-based approach. Results suggest a weak evidence of community structure, high heterogeneity of the network and that this market is characterized by money centers having exposures to many banks. Furthermore, we go beyond the structure of the network using information about the characteristics of the nodes and a non-parametric test in order to understand the role of the banks in the interbanking market.
Young, Jean-Gabriel; Allard, Antoine; Hébert-Dufresne, Laurent; Dubé, Louis J.
2015-01-01
Community detection is the process of assigning nodes and links in significant communities (e.g. clusters, function modules) and its development has led to a better understanding of complex networks. When applied to sizable networks, we argue that most detection algorithms correctly identify prominent communities, but fail to do so across multiple scales. As a result, a significant fraction of the network is left uncharted. We show that this problem stems from larger or denser communities overshadowing smaller or sparser ones, and that this effect accounts for most of the undetected communities and unassigned links. We propose a generic cascading approach to community detection that circumvents the problem. Using real and artificial network datasets with three widely used community detection algorithms, we show how a simple cascading procedure allows for the detection of the missing communities. This work highlights a new detection limit of community structure, and we hope that our approach can inspire better community detection algorithms. PMID:26461919
NASA Astrophysics Data System (ADS)
Gui, Chun; Zhang, Ruisheng; Zhao, Zhili; Wei, Jiaxuan; Hu, Rongjing
In order to deal with stochasticity in center node selection and instability in community detection of label propagation algorithm, this paper proposes an improved label propagation algorithm named label propagation algorithm based on community belonging degree (LPA-CBD) that employs community belonging degree to determine the number and the center of community. The general process of LPA-CBD is that the initial community is identified by the nodes with the maximum degree, and then it is optimized or expanded by community belonging degree. After getting the rough structure of network community, the remaining nodes are labeled by using label propagation algorithm. The experimental results on 10 real-world networks and three synthetic networks show that LPA-CBD achieves reasonable community number, better algorithm accuracy and higher modularity compared with other four prominent algorithms. Moreover, the proposed algorithm not only has lower algorithm complexity and higher community detection quality, but also improves the stability of the original label propagation algorithm.
Hödl, Iris; Mari, Lorenzo; Bertuzzo, Enrico; Suweis, Samir; Besemer, Katharina; Rinaldo, Andrea; Battin, Tom J
2014-01-01
Ecology, with a traditional focus on plants and animals, seeks to understand the mechanisms underlying structure and dynamics of communities. In microbial ecology, the focus is changing from planktonic communities to attached biofilms that dominate microbial life in numerous systems. Therefore, interest in the structure and function of biofilms is on the rise. Biofilms can form reproducible physical structures (i.e. architecture) at the millimetre-scale, which are central to their functioning. However, the spatial dynamics of the clusters conferring physical structure to biofilms remains often elusive. By experimenting with complex microbial communities forming biofilms in contrasting hydrodynamic microenvironments in stream mesocosms, we show that morphogenesis results in ‘ripple-like’ and ‘star-like’ architectures – as they have also been reported from monospecies bacterial biofilms, for instance. To explore the potential contribution of demographic processes to these architectures, we propose a size-structured population model to simulate the dynamics of biofilm growth and cluster size distribution. Our findings establish that basic physical and demographic processes are key forces that shape apparently universal biofilm architectures as they occur in diverse microbial but also in single-species bacterial biofilms. PMID:23879839
Insensitive dependence of delay-induced oscillation death on complex networks
NASA Astrophysics Data System (ADS)
Zou, Wei; Zheng, Xing; Zhan, Meng
2011-06-01
Oscillation death (also called amplitude death), a phenomenon of coupling induced stabilization of an unstable equilibrium, is studied for an arbitrary symmetric complex network with delay-coupled oscillators, and the critical conditions for its linear stability are explicitly obtained. All cases including one oscillator, a pair of oscillators, regular oscillator networks, and complex oscillator networks with delay feedback coupling, can be treated in a unified form. For an arbitrary symmetric network, we find that the corresponding smallest eigenvalue of the Laplacian λN (0 >λN ≥ -1) completely determines the death island, and as λN is located within the insensitive parameter region for nearly all complex networks, the death island keeps nearly the largest and does not sensitively depend on the complex network structures. This insensitivity effect has been tested for many typical complex networks including Watts-Strogatz (WS) and Newman-Watts (NW) small world networks, general scale-free (SF) networks, Erdos-Renyi (ER) random networks, geographical networks, and networks with community structures and is expected to be helpful for our understanding of dynamics on complex networks.
Experimental manipulation of spatial heterogeneity in Douglas-fir forests: effects on squirrels.
A.B. Carey
2001-01-01
Squirrel communities simultaneously composed of abundant populations of Glaucomys, Tamias, and Tamiasciurus are: (1) a result of high production of seeds and fruiting bodies by forest plants and fungi and complexity of ecosystem structure, composition, and function; (2) indicative of high carrying capacity...
ERIC Educational Resources Information Center
Yee, Roger
1974-01-01
A young, St. Louis, Missouri, architectural firm, seeking a personal style of practice, has succeeded in creating structures that reveal client input, and which are sensitive, articulate, and at ease with complexity. Describes an elementary school, a condominium, a shopping mall, a high school, and a "community mall." Illustrated with photographs…
Carbon and nitrogen inputs affect soil microbial community structure and function
NASA Astrophysics Data System (ADS)
Liu, X. J. A.; Mau, R. L.; Hayer, M.; Finley, B. K.; Schwartz, E.; Dijkstra, P.; Hungate, B. A.
2016-12-01
Climate change has been projected to increase energy and nutrient inputs to soils, affecting soil organic matter (SOM) decomposition (priming effect) and microbial communities. However, many important questions remain: how do labile C and/or N inputs affect priming and microbial communities? What is the relationship between them? To address these questions, we applied N (NH4NO3 ; 100 µg N g-1 wk-1), C (13C glucose; 1000 µg C g-1 wk-1), C+N to four different soils for five weeks. We found: 1) N showed no effect, whereas C induced the greatest priming, and C+N had significantly lower priming than C. 2) C and C+N additions increased the relative abundance of actinobacteria, proteobacteria, and firmicutes, but reduced relative abundance of acidobacteria, chloroflexi, verrucomicrobia, planctomycetes, and gemmatimonadetes. 3) Actinobacteria and proteobacteria increased relative abundance over time, but most others decreased over time. 4) substrate additions (N, C, C+N) significantly reduced microbial alpha diversity, which also decreased over time. 5) For beta diversity, C and C+N formed significantly different communities compare to the control and N treatments. Overtime, microbial community structure significantly altered. Four soils have drastically different community structures. These results indicate amounts of substrate C were determinant factors in modulating the rate of SOM decomposition and microbial communities. Variable responses of different microbial communities to labile C and N inputs indicate that complex relationships between priming and microbial functions. In general, we demonstrate that energy inputs can quickly accelerate SOM decomposition whereas extra N input can slow this process, though both had similar microbial community responses.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Perelson, Alan S; Gerrish, Philip J
The constructive creativity of natural selection originates from its paradoxical ability to foster cooperation through competition. Cooperating communities ranging from complex societies to somatic tissue are constantly under attack, however, by non-cooperating mutants or transformants, called 'cheaters'. Structure in these communities promotes the formation of cooperating clusters whose competitive superiority can alone be sufficient to thwart outgrowths of cheaters and thereby maintain cooperation. But we find that when cheaters appear too frequently -- exceeding a threshold mutation or transformation rate -- their scattered outgrowths infiltrate and break up cooperating clusters, resulting in a cascading loss of community integrity, a switchmore » to net positive selection for cheaters, and ultimately in the loss of cooperation. We find that this threshold mutation rate is directly proportional to the fitness support received from each cooperating neighbor minus the individual fitness benefit of cheating. When mutation rate also evolves, this threshold is crossed spontaneously after thousands of generations, at which point cheaters rapidly invade. In a structured community, cooperation can persist only if the mutation rate remains below a critical value.« less
Quantifying the adaptive cycle
Angeler, David G.; Allen, Craig R.; Garmestani, Ahjond S.; Gunderson, Lance H.; Hjerne, Olle; Winder, Monika
2015-01-01
The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994–2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.
Quantifying the Adaptive Cycle.
Angeler, David G; Allen, Craig R; Garmestani, Ahjond S; Gunderson, Lance H; Hjerne, Olle; Winder, Monika
2015-01-01
The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994-2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.
Verma, Sushant Kumar; Murmu, Thakur Das
2015-01-01
Gradient pattern analysis was used to investigate the impact of environmental and disturbance variables on species richness, species diversity, abundance and seasonal variation of birds in and around Jamshedpur, which is one of the fastest growing cities of India. It was observed that avian community structure is highly influenced by the vegetation habitat variables, food availability and human-related disturbance variables. A total of 61 species belonging to 33 families were recorded from the suburban area. 55 species belonging to 32 families were observed in nearby wildland habitat consisting of natural vegetation whereas only 26 species belonging to 18 families were observed in urban area. Results indicated that the suburban habitat had more complex bird community structure in terms of higher species richness, higher species diversity and higher evenness in comparison to urban and wildland habitat. Bird species richness and diversity varied across seasons. Maximum species richness and diversity was observed during spring season in all type of habitat. Most of the birds observed in urban areas were found to belong to either rare or irregular category on the basis of their abundance. The observed pattern of avian community structure is due to combined effect of both environmental and human related disturbance variables. PMID:26218583
The gut eukaryotic microbiota influences the growth performance among cohabitating shrimp.
Dai, Wenfang; Yu, Weina; Zhang, Jinjie; Zhu, Jinyong; Tao, Zhen; Xiong, Jinbo
2017-08-01
Increasing evidence has revealed a close interplay between the gut bacterial communities and host growth performance. However, until recently, studies generally ignored the contribution of eukaryotes, endobiotic organisms. To fill this gap, we used Illumina sequencing technology on eukaryotic 18S rRNA gene to compare the structures of gut eukaryotic communities among cohabitating retarded, overgrown, and normal shrimp obtained from identically managed ponds. Results showed that a significant difference between gut eukaryotic communities differed significantly between water and intestine and among three shrimp categories. Structural equation modeling revealed that changes in the gut eukaryotic community were positively related to digestive enzyme activities, which in turn influenced shrimp growth performance (λ = 0.97, P < 0.001). Overgrown shrimp exhibited a more complex and cooperative gut eukaryotic interspecies interaction than retarded and normal shrimp, which may facilitate their nutrient acquisition efficiency. Notably, the distribution of dominant eukaryotic genera and shifts in keystone species were closely concordant with shrimp growth performance. In summary, this study provides an integrated overview on direct roles of gut eukaryotic communities in shrimp growth performance instead of well-studied bacterial assembly.
López-Carretero, Antonio; Díaz-Castelazo, Cecilia; Boege, Karina; Rico-Gray, Víctor
2014-01-01
Despite the dynamic nature of ecological interactions, most studies on species networks offer static representations of their structure, constraining our understanding of the ecological mechanisms involved in their spatio-temporal stability. This is the first study to evaluate plant-herbivore interaction networks on a small spatio-temporal scale. Specifically, we simultaneously assessed the effect of host plant availability, habitat complexity and seasonality on the structure of plant-herbivore networks in a coastal tropical ecosystem. Our results revealed that changes in the host plant community resulting from seasonality and habitat structure are reflected not only in the herbivore community, but also in the emergent properties (network parameters) of the plant-herbivore interaction network such as connectance, selectiveness and modularity. Habitat conditions and periods that are most stressful favored the presence of less selective and susceptible herbivore species, resulting in increased connectance within networks. In contrast, the high degree of selectivennes (i.e. interaction specialization) and modularity of the networks under less stressful conditions was promoted by the diversification in resource use by herbivores. By analyzing networks at a small spatio-temporal scale we identified the ecological factors structuring this network such as habitat complexity and seasonality. Our research offers new evidence on the role of abiotic and biotic factors in the variation of the properties of species interaction networks. PMID:25340790
Chusova, Olga; Nolvak, Hiie; Nehrenheim, Emma; Truu, Jaak; Odlare, Monica; Oopkaup, Kristjan; Truu, Marika
2014-01-01
Pine bark, a low-cost industrial residue, has been suggested as a promising substitute for granular activated carbon in the on-site treatment of water contaminated with 2,4,6-trinitrotoluene (TNT). However, the complex organic structure and indigenous microbial community of pine bark have thus far not been thoroughly described in the context of TNT-contaminated water treatment. This two-week batch study examined the removal efficiency ofTNT from water by (1) adsorption on pine bark and (2) simultaneous adsorption on pine bark and biotransformation by specialized TNT-biotransforming microbial inocula. The bacterial community composition of experimental batches, inocula and pine bark, was profiled by Illumina sequencing of the V6 region of the 16S rRNA gene. The results revealed that the inocula and experimental batches were dominated by phylotypes belonging to the Enterobacteriaceae family and that the tested inocula had good potential for TNT biotransformation. The type of applied inocula had the most profound effect on the TNT-transforming bacterial community structure in the experimental batches. The indigenous microbial community of pine bark harboured phylotypes that also have a potential to degrade TNT. Altogether, the combination of a specialized inoculum and pine bark proved to be the most efficient treatment option for TNT-contaminated water.
Hanif, Muhammad; Atsuta, Yoichi; Fujie, Koichi; Daimon, Hiroyuki
2012-03-05
Microbial community structure plays a significant role in environmental assessment and animal health management. The development of a superior analytical strategy for the characterization of microbial community structure is an ongoing challenge. In this study, we developed an effective supercritical fluid extraction (SFE) and ultra performance liquid chromatography (UPLC) method for the analysis of bacterial respiratory quinones (RQ) in environmental and biological samples. RQ profile analysis is one of the most widely used culture-independent tools for characterizing microbial community structure. A UPLC equipped with a photo diode array (PDA) detector was successfully applied to the simultaneous determination of ubiquinones (UQ) and menaquinones (MK) without tedious pretreatment. Supercritical carbon dioxide (scCO(2)) extraction with the solid-phase cartridge trap proved to be a more effective and rapid method for extracting respiratory quinones, compared to a conventional organic solvent extraction method. This methodology leads to a successful analytical procedure that involves a significant reduction in the complexity and sample preparation time. Application of the optimized methodology to characterize microbial communities based on the RQ profile was demonstrated for a variety of environmental samples (activated sludge, digested sludge, and compost) and biological samples (swine and Japanese quail feces).
Phylogenetic structure of soil bacterial communities predicts ecosystem functioning.
Pérez-Valera, Eduardo; Goberna, Marta; Verdú, Miguel
2015-05-01
Quantifying diversity with phylogeny-informed metrics helps understand the effects of diversity on ecosystem functioning (EF). The sign of these effects remains controversial because phylogenetic diversity and taxonomic identity may interactively influence EF. Positive relationships, traditionally attributed to complementarity effects, seem unimportant in natural soil bacterial communities. Negative relationships could be attributed to fitness differences leading to the overrepresentation of few productive clades, a mechanism recently invoked to assemble soil bacteria communities. We tested in two ecosystems contrasting in terms of environmental heterogeneity whether two metrics of phylogenetic community structure, a simpler measure of phylogenetic diversity (NRI) and a more complex metric incorporating taxonomic identity (PCPS), correctly predict microbially mediated EF. We show that the relationship between phylogenetic diversity and EF depends on the taxonomic identity of the main coexisting lineages. Phylogenetic diversity was negatively related to EF in soils where a marked fertility gradient exists and a single and productive clade (Proteobacteria) outcompete other clades in the most fertile plots. However, phylogenetic diversity was unrelated to EF in soils where the fertility gradient is less marked and Proteobacteria coexist with other abundant lineages. Including the taxonomic identity of bacterial lineages in metrics of phylogenetic community structure allows the prediction of EF in both ecosystems. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Liu, Jun; Chen, Xi; Shu, Hao-Yue; Lin, Xue-Rui; Zhou, Qi-Xing; Bramryd, Torleif; Shu, Wen-Sheng; Huang, Li-Nan
2018-04-01
The release of toxic organic pollutants and heavy metals by primitive electronic waste (e-waste) processing to waterways has raised significant concerns, but little is known about their potential ecological effects on aquatic biota especially microorganisms. We characterized the microbial community composition and diversity in sediments sampled along two rivers consistently polluted by e-waste, and explored how community functions may respond to the complex combined pollution. High-throughput 16S rRNA gene sequencing showed that Proteobacteria (particularly Deltaproteobacteria) dominated the sediment microbial assemblages followed by Bacteroidetes, Acidobacteria, Chloroflexi and Firmicutes. PICRUSt metagenome inference provided an initial insight into the metabolic potentials of these e-waste affected communities, speculating that organic pollutants degradation in the sediment might be mainly performed by some of the dominant genera (such as Sulfuricurvum, Thiobacillus and Burkholderia) detected in situ. Statistical analyses revealed that toxic organic compounds contributed more to the observed variations in sediment microbial community structure and predicted functions (24.68% and 8.89%, respectively) than heavy metals (12.18% and 4.68%), and Benzo(a)pyrene, bioavailable lead and electrical conductivity were the key contributors. These results have shed light on the microbial assemblages in e-waste contaminated river sediments, indicating a potential influence of e-waste pollution on the microbial community structure and function in aquatic ecosystems. Copyright © 2017 Elsevier Ltd. All rights reserved.
Mobberley, Jennifer M; Ortega, Maya C; Foster, Jamie S
2012-01-01
Thrombolites are unlaminated carbonate structures that form as a result of the metabolic interactions of complex microbial mat communities. Thrombolites have a long geological history; however, little is known regarding the microbes associated with modern structures. In this study, we use a barcoded 16S rRNA gene-pyrosequencing approach coupled with morphological analysis to assess the bacterial, cyanobacterial and archaeal diversity associated with actively forming thrombolites found in Highborne Cay, Bahamas. Analyses revealed four distinct microbial mat communities referred to as black, beige, pink and button mats on the surfaces of the thrombolites. At a coarse phylogenetic resolution, the domain bacterial sequence libraries from the four mats were similar, with Proteobacteria and Cyanobacteria being the most abundant. At the finer resolution of the rRNA gene sequences, significant differences in community structure were observed, with dramatically different cyanobacterial communities. Of the four mat types, the button mats contained the highest diversity of Cyanobacteria, and were dominated by two sequence clusters with high similarity to the genus Dichothrix, an organism associated with the deposition of carbonate. Archaeal diversity was low, but varied in all mat types, and the archaeal community was predominately composed of members of the Thaumarchaeota and Euryarchaeota. The morphological and genetic data support the hypothesis that the four mat types are distinctive thrombolitic mat communities. © 2011 Society for Applied Microbiology and Blackwell Publishing Ltd.
Nematodes as bioindicators of soil degradation due to heavy metals.
Šalamún, Peter; Renčo, Marek; Kucanová, Eva; Brázová, Tímea; Papajová, Ingrid; Miklisová, Dana; Hanzelová, Vladimíra
2012-11-01
The effect of distance from a heavy metal pollution source on the soil nematode community was investigated on four sampling sites along an 4 km transect originating at the Kovohuty a.s. Krompachy (pollution source). The soil nematode communities were exposed to heavy metal influence directly and through soil properties changes. We quantified the relative effects of total and mobile fraction of metals (As, Cd, Cr, Cu, Pb, and Zn) on soil ecosystem using the nematode community structure (trophic and c-p groups,) and ecological indices (Richness of genera, H', MI2-5, etc.). Pollution effects on the community structure of soil free living nematodes was found to be the highest near the pollution source, with relatively low population density and domination of insensitive taxa. A decrease in heavy metals contents along the transect was linked with an increase in complexity of nematode community. The majority of used indices (MI2-5, SI, H') negatively correlated (P < 0.05 or P < 0.01) with heavy metals content and were sensitive to soil ecosystem disturbance. Contamination by heavy metals has negatively affected the soil environment, which resulted in nematode community structure and ecological indices changes. Results showed that the free-living nematodes are useful tools for bioindication of contamination and could be used as an alternative to the common approaches based on chemical methods.
Xie, Wan-Ying; Su, Jian-Qiang; Zhu, Yong-Guan
2015-01-01
The phyllosphere of floating macrophytes in paddy soil ecosystems, a unique habitat, may support large microbial communities but remains largely unknown. We took Wolffia australiana as a representative floating plant and investigated its phyllosphere bacterial community and the underlying driving forces of community modulation in paddy soil ecosystems using Illumina HiSeq 2000 platform-based 16S rRNA gene sequence analysis. The results showed that the phyllosphere of W. australiana harbored considerably rich communities of bacteria, with Proteobacteria and Bacteroidetes as the predominant phyla. The core microbiome in the phyllosphere contained genera such as Acidovorax, Asticcacaulis, Methylibium, and Methylophilus. Complexity of the phyllosphere bacterial communities in terms of class number and α-diversity was reduced compared to those in corresponding water and soil. Furthermore, the bacterial communities exhibited structures significantly different from those in water and soil. These findings and the following redundancy analysis (RDA) suggest that species sorting played an important role in the recruitment of bacterial species in the phyllosphere. The compositional structures of the phyllosphere bacterial communities were modulated predominantly by water physicochemical properties, while the initial soil bacterial communities had limited impact. Taken together, the findings from this study reveal the diversity and uniqueness of the phyllosphere bacterial communities associated with the floating macrophytes in paddy soil environments. Copyright © 2015, American Society for Microbiology. All Rights Reserved.
Xie, Wan-Ying
2014-01-01
The phyllosphere of floating macrophytes in paddy soil ecosystems, a unique habitat, may support large microbial communities but remains largely unknown. We took Wolffia australiana as a representative floating plant and investigated its phyllosphere bacterial community and the underlying driving forces of community modulation in paddy soil ecosystems using Illumina HiSeq 2000 platform-based 16S rRNA gene sequence analysis. The results showed that the phyllosphere of W. australiana harbored considerably rich communities of bacteria, with Proteobacteria and Bacteroidetes as the predominant phyla. The core microbiome in the phyllosphere contained genera such as Acidovorax, Asticcacaulis, Methylibium, and Methylophilus. Complexity of the phyllosphere bacterial communities in terms of class number and α-diversity was reduced compared to those in corresponding water and soil. Furthermore, the bacterial communities exhibited structures significantly different from those in water and soil. These findings and the following redundancy analysis (RDA) suggest that species sorting played an important role in the recruitment of bacterial species in the phyllosphere. The compositional structures of the phyllosphere bacterial communities were modulated predominantly by water physicochemical properties, while the initial soil bacterial communities had limited impact. Taken together, the findings from this study reveal the diversity and uniqueness of the phyllosphere bacterial communities associated with the floating macrophytes in paddy soil environments. PMID:25362067
Prospects and limitations of full-text index structures in genome analysis
Vyverman, Michaël; De Baets, Bernard; Fack, Veerle; Dawyndt, Peter
2012-01-01
The combination of incessant advances in sequencing technology producing large amounts of data and innovative bioinformatics approaches, designed to cope with this data flood, has led to new interesting results in the life sciences. Given the magnitude of sequence data to be processed, many bioinformatics tools rely on efficient solutions to a variety of complex string problems. These solutions include fast heuristic algorithms and advanced data structures, generally referred to as index structures. Although the importance of index structures is generally known to the bioinformatics community, the design and potency of these data structures, as well as their properties and limitations, are less understood. Moreover, the last decade has seen a boom in the number of variant index structures featuring complex and diverse memory-time trade-offs. This article brings a comprehensive state-of-the-art overview of the most popular index structures and their recently developed variants. Their features, interrelationships, the trade-offs they impose, but also their practical limitations, are explained and compared. PMID:22584621
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thompson, Andrew J.; Cuskin, Fiona; Spears, Richard J.
A high-resolution structure of a noncanonical α-mannanase relevant to human health and nutrition has been solved via heavy-atom phasing of a selenomethionine derivative. The large bowel microbiota, a complex ecosystem resident within the gastrointestinal tract of all human beings and large mammals, functions as an essential, nonsomatic metabolic organ, hydrolysing complex dietary polysaccharides and modulating the host immune system to adequately tolerate ingested antigens. A significant member of this community, Bacteroides thetaiotaomicron, has evolved a complex system for sensing and processing a wide variety of natural glycoproducts in such a way as to provide maximum benefit to itself, the widermore » microbial community and the host. The immense ability of B. thetaiotaomicron as a ‘glycan specialist’ resides in its enormous array of carbohydrate-active enzymes, many of which are arranged into polysaccharide-utilization loci (PULs) that are able to degrade sugar polymers that are often inaccessible to other gut residents, notably α-mannan. The B. thetaiotaomicron genome encodes ten putative α-mannanases spread across various PULs; however, little is known about the activity of these enzymes or the wider implications of α-mannan metabolism for the health of both the microbiota and the host. In this study, SAD phasing of a selenomethionine derivative has been used to investigate the structure of one such B. thetaiotaomicron enzyme, BT2949, which belongs to the GH76 family of α-mannanases. BT2949 presents a classical (α/α){sub 6}-barrel structure comprising a large extended surface cleft common to other GH76 family members. Analysis of the structure in conjunction with sequence alignments reveals the likely location of the catalytic active site of this noncanonical GH76.« less
Community detection in complex networks using link prediction
NASA Astrophysics Data System (ADS)
Cheng, Hui-Min; Ning, Yi-Zi; Yin, Zhao; Yan, Chao; Liu, Xin; Zhang, Zhong-Yuan
2018-01-01
Community detection and link prediction are both of great significance in network analysis, which provide very valuable insights into topological structures of the network from different perspectives. In this paper, we propose a novel community detection algorithm with inclusion of link prediction, motivated by the question whether link prediction can be devoted to improving the accuracy of community partition. For link prediction, we propose two novel indices to compute the similarity between each pair of nodes, one of which aims to add missing links, and the other tries to remove spurious edges. Extensive experiments are conducted on benchmark data sets, and the results of our proposed algorithm are compared with two classes of baselines. In conclusion, our proposed algorithm is competitive, revealing that link prediction does improve the precision of community detection.
Seasonal variation in functional properties of microbial communities in beech forest soil
Koranda, Marianne; Kaiser, Christina; Fuchslueger, Lucia; Kitzler, Barbara; Sessitsch, Angela; Zechmeister-Boltenstern, Sophie; Richter, Andreas
2013-01-01
Substrate quality and the availability of nutrients are major factors controlling microbial decomposition processes in soils. Seasonal alteration in resource availability, which is driven by plants via belowground C allocation, nutrient uptake and litter fall, also exerts effects on soil microbial community composition. Here we investigate if seasonal and experimentally induced changes in microbial community composition lead to alterations in functional properties of microbial communities and thus microbial processes. Beech forest soils characterized by three distinct microbial communities (winter and summer community, and summer community from a tree girdling plot, in which belowground carbon allocation was interrupted) were incubated with different 13C-labeled substrates with or without inorganic N supply and analyzed for substrate use and various microbial processes. Our results clearly demonstrate that the three investigated microbial communities differed in their functional response to addition of various substrates. The winter communities revealed a higher capacity for degradation of complex C substrates (cellulose, plant cell walls) than the summer communities, indicated by enhanced cellulase activities and reduced mineralization of soil organic matter. In contrast, utilization of labile C sources (glucose) was lower in winter than in summer, demonstrating that summer and winter community were adapted to the availability of different substrates. The saprotrophic community established in girdled plots exhibited a significantly higher utilization of complex C substrates than the more plant root associated community in control plots if additional nitrogen was provided. In this study we were able to demonstrate experimentally that variation in resource availability as well as seasonality in temperate forest soils cause a seasonal variation in functional properties of soil microorganisms, which is due to shifts in community structure and physiological adaptations of microbial communities to altered resource supply. PMID:23645937
Hakkenberg, C R; Peet, R K; Urban, D L; Song, C
2018-01-01
In light of the need to operationalize the mapping of forest composition at landscape scales, this study uses multi-scale nested vegetation sampling in conjunction with LiDAR-hyperspectral remotely sensed data from the G-LiHT airborne sensor to map vascular plant compositional turnover in a compositionally and structurally complex North Carolina Piedmont forest. Reflecting a shift in emphasis from remotely sensing individual crowns to detecting aggregate optical-structural properties of forest stands, predictive maps reflect the composition of entire vascular plant communities, inclusive of those species smaller than the resolution of the remotely sensed imagery, intertwined with proximate taxa, or otherwise obscured from optical sensors by dense upper canopies. Stand-scale vascular plant composition is modeled as community continua: where discrete community-unit classes at different compositional resolutions provide interpretable context for continuous gradient maps that depict n-dimensional compositional complexity as a single, consistent RGB color combination. In total, derived remotely sensed predictors explain 71%, 54%, and 48% of the variation in the first three components of vascular plant composition, respectively. Among all remotely sensed environmental gradients, topography derived from LiDAR ground returns, forest structure estimated from LiDAR all returns, and morphological-biochemical traits determined from hyperspectral imagery each significantly correspond to the three primary axes of floristic composition in the study site. Results confirm the complementarity of LiDAR and hyperspectral sensors for modeling the environmental gradients constraining landscape turnover in vascular plant composition and hold promise for predictive mapping applications spanning local land management to global ecosystem modeling. © 2017 by the Ecological Society of America.
Song, Woojin; Kim, Mincheol; Tripathi, Binu M; Kim, Hyoki; Adams, Jonathan M
2016-06-01
It is difficult to understand the processes that structure immensely complex bacterial communities in the soil environment, necessitating a simplifying experimental approach. Here, we set up a microcosm culturing experiment with soil bacteria, at a range of nutrient concentrations, and compared these over time to understand the relationship between soil bacterial community structure and time/nutrient concentration. DNA from each replicate was analysed using HiSeq2000 Illumina sequencing of the 16S rRNA gene. We found that each nutrient treatment, and each time point during the experiment, produces characteristic bacterial communities that occur predictably between replicates. It is clear that within the context of this experiment, many soil bacteria have distinct niches from one another, in terms of both nutrient concentration, and successional time point since a resource first became available. This fine niche differentiation may in part help to explain the coexistence of a diversity of bacteria in soils. In this experiment, we show that the unimodal relationship between nutrient concentration/time and species diversity often reported in communities of larger organisms is also evident in microbial communities. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Pellissier, Loïc; Wisz, Mary S.; Strandberg, Beate; Damgaard, Christian
2014-01-01
Throughout the world, herbicides and fertilizers change species composition in agricultural communities, but how do the cumulative effects of these chemicals impact the functional and phylogenetic structure of non-targeted communities when they drift into adjacent semi-natural habitats? Based on long-term experiment we show that fertilizer and herbicides (glyphosate) have contrasting effects on functional structure, but can increase phylogenetic diversity in semi-natural plant communities. We found that an increase in nitrogen promoted an increase in the average specific leaf area and canopy height at the community level, but an increase in glyphosate promoted a decrease in those traits. Phylogenetic diversity of plant communities increased when herbicide and fertilizer were applied together, likely because functional traits facilitating plant success in those conditions were not phylogenetically conserved. Species richness also decreased with increasing levels of nitrogen and glyphosate. Our results suggest that predicting the cumulative effects of agrochemicals is more complex than anticipated due to their distinct selection of traits that may or may not be conserved phylogenetically. Precautionary efforts to mitigate drift of agricultural chemicals into semi-natural habitats are warranted to prevent unforeseeable biodiversity shifts.
Influence of geogenic factors on microbial communities in metallogenic Australian soils
Reith, Frank; Brugger, Joel; Zammit, Carla M; Gregg, Adrienne L; Goldfarb, Katherine C; Andersen, Gary L; DeSantis, Todd Z; Piceno, Yvette M; Brodie, Eoin L; Lu, Zhenmei; He, Zhili; Zhou, Jizhong; Wakelin, Steven A
2012-01-01
Links between microbial community assemblages and geogenic factors were assessed in 187 soil samples collected from four metal-rich provinces across Australia. Field-fresh soils and soils incubated with soluble Au(III) complexes were analysed using three-domain multiplex-terminal restriction fragment length polymorphism, and phylogenetic (PhyloChip) and functional (GeoChip) microarrays. Geogenic factors of soils were determined using lithological-, geomorphological- and soil-mapping combined with analyses of 51 geochemical parameters. Microbial communities differed significantly between landforms, soil horizons, lithologies and also with the occurrence of underlying Au deposits. The strongest responses to these factors, and to amendment with soluble Au(III) complexes, was observed in bacterial communities. PhyloChip analyses revealed a greater abundance and diversity of Alphaproteobacteria (especially Sphingomonas spp.), and Firmicutes (Bacillus spp.) in Au-containing and Au(III)-amended soils. Analyses of potential function (GeoChip) revealed higher abundances of metal-resistance genes in metal-rich soils. For example, genes that hybridised with metal-resistance genes copA, chrA and czcA of a prevalent aurophillic bacterium, Cupriavidus metallidurans CH34, occurred only in auriferous soils. These data help establish key links between geogenic factors and the phylogeny and function within soil microbial communities. In particular, the landform, which is a crucial factor in determining soil geochemistry, strongly affected microbial community structures. PMID:22673626
Influence of geogenic factors on microbial communities in metallogenic Australian soils.
Reith, Frank; Brugger, Joel; Zammit, Carla M; Gregg, Adrienne L; Goldfarb, Katherine C; Andersen, Gary L; DeSantis, Todd Z; Piceno, Yvette M; Brodie, Eoin L; Lu, Zhenmei; He, Zhili; Zhou, Jizhong; Wakelin, Steven A
2012-11-01
Links between microbial community assemblages and geogenic factors were assessed in 187 soil samples collected from four metal-rich provinces across Australia. Field-fresh soils and soils incubated with soluble Au(III) complexes were analysed using three-domain multiplex-terminal restriction fragment length polymorphism, and phylogenetic (PhyloChip) and functional (GeoChip) microarrays. Geogenic factors of soils were determined using lithological-, geomorphological- and soil-mapping combined with analyses of 51 geochemical parameters. Microbial communities differed significantly between landforms, soil horizons, lithologies and also with the occurrence of underlying Au deposits. The strongest responses to these factors, and to amendment with soluble Au(III) complexes, was observed in bacterial communities. PhyloChip analyses revealed a greater abundance and diversity of Alphaproteobacteria (especially Sphingomonas spp.), and Firmicutes (Bacillus spp.) in Au-containing and Au(III)-amended soils. Analyses of potential function (GeoChip) revealed higher abundances of metal-resistance genes in metal-rich soils. For example, genes that hybridised with metal-resistance genes copA, chrA and czcA of a prevalent aurophillic bacterium, Cupriavidus metallidurans CH34, occurred only in auriferous soils. These data help establish key links between geogenic factors and the phylogeny and function within soil microbial communities. In particular, the landform, which is a crucial factor in determining soil geochemistry, strongly affected microbial community structures.
Kuehl, Carole J.; Wood, Heather D.; Marsh, Terence L.; Schmidt, Thomas M.; Young, Vincent B.
2005-01-01
Establishment of mucosal and/or luminal colonization is the first step in the pathogenesis of many gastrointestinal bacterial pathogens. The pathogen must be able to establish itself in the face of competition from the complex microbial community that is already in place. We used culture-independent methods to monitor the colonization of the cecal mucosa of Helicobacter-free mice following experimental infection with the pathogen Helicobacter hepaticus. Two days after infection, H. hepaticus comprised a minor component of the mucosa-associated microbiota, but within 14 days, it became the dominant member of the community. Colonization of the mucosa by H. hepaticus was associated with a decrease in the overall diversity of the microbial community, in large part due to changes in evenness resulting from the relative dominance of H. hepaticus as a member of the community. Our results demonstrate that invasion of the complex gastrointestinal microbial community by a pathogenic microorganism causes reproducible and significant disturbances in the community structure. The use of non-culture-based methods to monitor these changes should lead to a greater understanding of the ecological principles that govern pathogen invasion and may lead to novel methods for the prevention and control of gastrointestinal pathogens. PMID:16177375
Microbial Herd Protection Mediated by Antagonistic Interaction in Polymicrobial Communities
Wong, Megan J. Q.; Liang, Xiaoye; Smart, Matt; Tang, Le; Moore, Richard; Ingalls, Brian
2016-01-01
ABSTRACT In host and natural environments, microbes often exist in complex multispecies communities. The molecular mechanisms through which such communities develop and persist, despite significant antagonistic interactions between species, are not well understood. The type VI secretion system (T6SS) is a lethal weapon commonly employed by Gram-negative bacteria to inhibit neighboring species through the delivery of toxic effectors. It is well established that intraspecies protection is conferred by immunity proteins that neutralize effector toxicities. In contrast, the mechanisms for interspecies protection are not clear. Here we use two T6SS-active antagonistic bacterial species, Aeromonas hydrophila and Vibrio cholerae, to demonstrate that interspecies protection is dependent on effectors. A. hydrophila and V. cholerae do not share conserved immunity genes but could coexist equally in a mixture. However, mutants lacking the T6SS or effectors were effectively eliminated by the competing wild-type strain. Time-lapse microscopic analyses showed that mutually lethal interactions drive the segregation of mixed species into distinct single-species clusters by eliminating interspersed single cells. Cluster formation provides herd protection by abolishing lethal interactions inside each cluster and restricting the interactions to the boundary. Using an agent-based modeling approach, we simulated the antagonistic interactions of two hypothetical species. The resulting simulations recapitulated our experimental observations. These results provide mechanistic insights regarding the general role of microbial weapons in determining the structures of complex multispecies communities. IMPORTANCE Investigating the warfare of microbes allows us to better understand the ecological relationships in complex microbial communities such as the human microbiota. Here we use the T6SS, a deadly bacterial weapon, as a model to demonstrate the importance of lethal interactions in determining community structures and the exchange of genetic materials. This simplified model elucidates a mechanism of microbial herd protection by which competing antagonistic species can coexist in the same niche, despite their diverse mutually destructive activities. Our results also suggest that antagonistic interactions impose strong selection that could promote multicellular organism-like social behaviors and contribute to the transition to multicellularity during evolution. PMID:27637882
Microbial herd protection mediated by antagonistic interaction in polymicrobial communities.
Wong, Megan; Liang, Xiaoye; Smart, Matt; Tang, Le; Moore, Richard; Ingalls, Brian; Dong, Tao G
2016-09-16
In the host and natural environments, microbes often exist in complex multispecies communities. The molecular mechanisms through which such communities develop and persist - despite significant antagonistic interactions between species - are not well understood. The type VI secretion system (T6SS) is a lethal weapon commonly employed by Gram-negative bacteria to inhibit neighboring species through delivery of toxic effectors. It is well established that intra-species protection is conferred by immunity proteins that neutralize effector toxicities. By contrast, the mechanisms for interspecies protection are not clear. Here we use two T6SS active antagonistic bacteria, Aeromonas hydrophila (AH) and Vibrio cholerae (VC), to demonstrate that interspecies protection is dependent on effectors. AH and VC do not share conserved immunity genes but could equally co-exist in a mixture. However, mutants lacking the T6SS or effectors were effectively eliminated by the other competing wild type. Time-lapse microscopy analyses show that mutually lethal interactions drive the segregation of mixed species into distinct single-species clusters by eliminating interspersed single cells. Cluster formation provides herd protection by abolishing lethal interaction inside each cluster and restricting it to the boundary. Using an agent-based modeling approach, we simulated the antagonistic interactions of two hypothetical species. The resulting simulations recapitulate our experimental observation. These results provide mechanistic insights for the general role of microbial weapons in determining the structures of complex multispecies communities. Investigating the warfare of microbes allows us to better understand the ecological relationships in complex microbial communities such as the human microbiota. Here we use the T6SS, a deadly bacterial weapon, as a model to demonstrate the importance of lethal interactions in determining community structures and exchange of genetic materials. This simplified model elucidates a mechanism of microbial herd protection by which competing antagonistic species coexist in the same niche despite their diverse mutually destructive activities. Our results also suggest that antagonistic interaction imposes a strong selection that could promote multicellular like social behaviors and contribute to the transition to multicellularity during evolution. Copyright © 2016, American Society for Microbiology. All Rights Reserved.
Query-Time Optimization Techniques for Structured Queries in Information Retrieval
ERIC Educational Resources Information Center
Cartright, Marc-Allen
2013-01-01
The use of information retrieval (IR) systems is evolving towards larger, more complicated queries. Both the IR industrial and research communities have generated significant evidence indicating that in order to continue improving retrieval effectiveness, increases in retrieval model complexity may be unavoidable. From an operational perspective,…
Organizational Structures and Data Use in Volunteer Monitoring Organizations (VMOs)
ERIC Educational Resources Information Center
Laird, Shelby Gull; Nelson, Stacy A. C.; Stubbs, Harriett S.; James, April L.; Menius, Erika
2012-01-01
Complex environmental problems call for unique solutions to monitoring efforts alongside developing a more environmentally literate citizenry. Community-based monitoring (CBM) through the use of volunteer monitoring organizations helps to provide a part of the solution, particularly when CBM groups work with research scientists or government…
Prions: Introducing a Complex Scientific Controversy to a Biology Classroom
ERIC Educational Resources Information Center
Zaitsev, Igor V.
2009-01-01
Thomas Kuhn, in "The Structure of Scientific Revolutions," posited that science does not progress by the steady accumulation of knowledge, but rather by a system of competition among paradigms. They vie for supremacy through greater parsimony, explanatory power, and popularity among the community of scientists (Kuhn, 1962). The current…
The Campus as a Total Community.
ERIC Educational Resources Information Center
Hunt, Robert E.
The myriad and complex health and safety needs of a college or university campus are discussed. Consideration is given to the demands of fire prevention, accident prevention, food service standards, and the mental and physical well-being of students, faculty, and staff. Structural and architectural concerns of the well-designed campus are…
The United States’ water and wastewater infrastructure is large (i.e., 16,000 publicly owned treatment works, 59,000 community water supplies, 600,000 miles of sewer, 1,000,000 miles of drinking water distribution piping), complex and expensive. The reliable and efficient functio...
Emergence Shapes the Structure of the Seed Microbiota
Briand, Martial; Bonneau, Sophie; Préveaux, Anne; Valière, Sophie; Bouchez, Olivier; Hunault, Gilles; Simoneau, Philippe; Jacques, Marie-Agnès
2014-01-01
Seeds carry complex microbial communities, which may exert beneficial or deleterious effects on plant growth and plant health. To date, the composition of microbial communities associated with seeds has been explored mainly through culture-based diversity studies and therefore remains largely unknown. In this work, we analyzed the structures of the seed microbiotas of different plants from the family Brassicaceae and their dynamics during germination and emergence through sequencing of three molecular markers: the ITS1 region of the fungal internal transcribed spacer, the V4 region of 16S rRNA gene, and a species-specific bacterial marker based on a fragment of gyrB. Sequence analyses revealed important variations in microbial community composition between seed samples. Moreover, we found that emergence strongly influences the structure of the microbiota, with a marked reduction of bacterial and fungal diversity. This shift in the microbial community composition is mostly due to an increase in the relative abundance of some bacterial and fungal taxa possessing fast-growing abilities. Altogether, our results provide an estimation of the role of the seed as a source of inoculum for the seedling, which is crucial for practical applications in developing new strategies of inoculation for disease prevention. PMID:25501471
Emergence shapes the structure of the seed microbiota.
Barret, Matthieu; Briand, Martial; Bonneau, Sophie; Préveaux, Anne; Valière, Sophie; Bouchez, Olivier; Hunault, Gilles; Simoneau, Philippe; Jacquesa, Marie-Agnès
2015-02-01
Seeds carry complex microbial communities, which may exert beneficial or deleterious effects on plant growth and plant health. To date, the composition of microbial communities associated with seeds has been explored mainly through culture-based diversity studies and therefore remains largely unknown. In this work, we analyzed the structures of the seed microbiotas of different plants from the family Brassicaceae and their dynamics during germination and emergence through sequencing of three molecular markers: the ITS1 region of the fungal internal transcribed spacer, the V4 region of 16S rRNA gene, and a species-specific bacterial marker based on a fragment of gyrB. Sequence analyses revealed important variations in microbial community composition between seed samples. Moreover, we found that emergence strongly influences the structure of the microbiota, with a marked reduction of bacterial and fungal diversity. This shift in the microbial community composition is mostly due to an increase in the relative abundance of some bacterial and fungal taxa possessing fast-growing abilities. Altogether, our results provide an estimation of the role of the seed as a source of inoculum for the seedling, which is crucial for practical applications in developing new strategies of inoculation for disease prevention.
Diversity and food web structure of nematode communities under high soil salinity and alkaline pH.
Salamún, Peter; Kucanová, Eva; Brázová, Tímea; Miklisová, Dana; Renčo, Marek; Hanzelová, Vladimíra
2014-10-01
A long-term and intensive magnesium (Mg) ore processing in Slovenské Magnezitové Závody a.s. in Jelšava has resulted in a high Mg content and alkaline pH of the soil environment, noticeable mainly in the close vicinity of the smelter. Nematode communities strongly reacted to the contamination mostly by a decrease in abundance of the sensitive groups. Nematodes from c-p 1 group and bacterivores, tolerant to pollution played a significant role in establishing the dominance at all sites. With increasing distance from the pollution source, the nematode communities were more structured and complex, with an increase in proportion of sensitive c-p 4 and 5 nematodes, composed mainly of carnivores and omnivores. Various ecological indices (e.g. MI2-5, SI, H') indicated similar improvement of farther soil ecosystems.
Understanding parenting in Manitoba First nations: implications for program development.
Eni, Rachel; Rowe, Gladys
2011-01-01
This qualitative study introduced the "Manitoba First Nation Strengthening Families Maternal Child Health Pilot Project" program and evaluation methodologies. The study provided a knowledge base for programmers, evaluators, and communities to develop relevant health promotion, prevention, and intervention programming to assist in meeting health needs of pregnant women and young families. Sixty-five open-ended, semistructured interviews were completed in 13 communities. Data analysis was through grounded theory. Three major themes emerged from the data: interpersonal support and relationships; socioeconomic factors; and community initiatives. Complex structural, historical events compromise parenting; capacity and resilience are supported through informal and formal health and social supports.
Organisms as cooperative ecosystem engineers in intertidal flats
NASA Astrophysics Data System (ADS)
Passarelli, Claire; Olivier, Frédéric; Paterson, David M.; Meziane, Tarik; Hubas, Cédric
2014-09-01
The importance of facilitative interactions and organismal ecosystem engineering for establishing the structure of communities is increasingly being recognised for many different ecosystems. For example, soft-bottom tidal flats host a wide range of ecosystem engineers, probably because the harsh physico-chemical environmental conditions render these species of particular importance for community structure and function. These environments are therefore interesting when focusing on how ecosystem engineers interact and the consequences of these interactions on community dynamics. In this review, we initially detail the influence on benthic systems of two kinds of ecosystem engineers that are particularly common in tidal flats. Firstly, we examine species providing biogenic structures, which are often the only source of habitat complexity in these environments. Secondly, we focus on species whose activities alter sediment stability, which is a crucial feature structuring the dynamics of communities in tidal flats. The impacts of these engineers on both environment and communities were assessed but in addition the interaction between ecosystem engineers was examined. Habitat cascades occur when one engineer favours the development of another, which in turn creates or modifies and improves habitat for other species. Non-hierarchical interactions have often been shown to display non-additive effects, so that the effects of the association cannot be predicted from the effects of individual organisms. Here we propose the term of “cooperative ecosystem engineering” when two species interact in a way which enhances habitat suitability as a result of a combined engineering effect. Finally, we conclude by describing the potential threats for ecosystem engineers in intertidal areas, potential effects on their interactions and their influence on communities and ecosystem function.
Mendonça, Ana; Arístegui, Javier; Vilas, Juan Carlos; Montero, Maria Fernanda; Ojeda, Alicia; Espino, Minerva; Martins, Ana
2012-01-01
Seamounts are considered to be "hotspots" of marine life but, their role in oceans primary productivity is still under discussion. We have studied the microbial community structure and biomass of the epipelagic zone (0-150 m) at two northeast Atlantic seamounts (Seine and Sedlo) and compared those with the surrounding ocean. Results from two cruises to Sedlo and three to Seine are presented. Main results show large temporal and spatial microbial community variability on both seamounts. Both Seine and Sedlo heterotrophic community (abundance and biomass) dominate during winter and summer months, representing 75% (Sedlo, July) to 86% (Seine, November) of the total plankton biomass. In Seine, during springtime the contribution to total plankton biomass is similar (47% autotrophic and 53% heterotrophic). Both seamounts present an autotrophic community structure dominated by small cells (nano and picophytoplankton). It is also during spring that a relatively important contribution (26%) of large cells to total autotrophic biomass is found. In some cases, a "seamount effect" is observed on Seine and Sedlo microbial community structure and biomass. In Seine this is only observed during spring through enhancement of large autotrophic cells at the summit and seamount stations. In Sedlo, and despite the observed low biomasses, some clear peaks of picoplankton at the summit or at stations within the seamount area are also observed during summer. Our results suggest that the dominance of heterotrophs is presumably related to the trapping effect of organic matter by seamounts. Nevertheless, the complex circulation around both seamounts with the presence of different sources of mesoscale variability (e.g. presence of meddies, intrusion of African upwelling water) may have contributed to the different patterns of distribution, abundances and also changes observed in the microbial community.
1992-04-01
Derivabl, from Concentrated Conceotual Analysis Obviously, there is a prima facie medical relevance to studying concepts judged by the medical community... consumers of research, e.g., students, see and are affected only by the partial products of the overall quest, without access to the "big picture...in a number of studies that the learning of complex content materia ! in ill-structured domains requires multiple representations -- multiple
A cooperative game framework for detecting overlapping communities in social networks
NASA Astrophysics Data System (ADS)
Jonnalagadda, Annapurna; Kuppusamy, Lakshmanan
2018-02-01
Community detection in social networks is a challenging and complex task, which received much attention from researchers of multiple domains in recent years. The evolution of communities in social networks happens merely due to the self-interest of the nodes. The interesting feature of community structure in social networks is the multi membership of the nodes resulting in overlapping communities. Assuming the nodes of the social network as self-interested players, the dynamics of community formation can be captured in the form of a game. In this paper, we propose a greedy algorithm, namely, Weighted Graph Community Game (WGCG), in order to model the interactions among the self-interested nodes of the social network. The proposed algorithm employs the Shapley value mechanism to discover the inherent communities of the underlying social network. The experimental evaluation on the real-world and synthetic benchmark networks demonstrates that the performance of the proposed algorithm is superior to the state-of-the-art overlapping community detection algorithms.
The structure of parasite communities in fish hosts: ecology meets geography and climate.
Poulin, R
2007-09-01
Parasite communities in fish hosts are not uniform in space: their diversity, composition and abundance vary across the geographical range of a host species. Increasingly urgently, we need to understand the geographic component of parasite communities to better predict how they will respond to global climate change. Patterns of geographical variation in the abundance of parasite populations, and in the diversity and composition of parasite communities, are explored here, and the ways in which they may be affected by climate change are discussed. The time has come to transform fish parasite ecology from a mostly descriptive discipline into a predictive science, capable of integrating complex ecological data to generate forecasts about the future state of host-parasite systems.
Complexity of Bacterial Communities in a River-Floodplain System (Danube, Austria)
Besemer, Katharina; Moeseneder, Markus M.; Arrieta, Jesus M.; Herndl, Gerhard J.; Peduzzi, Peter
2005-01-01
Natural floodplains play an essential role in the processing and decomposition of organic matter and in the self-purification ability of rivers, largely due to the activity of bacteria. Knowledge about the composition of bacterial communities and its impact on organic-matter cycling is crucial for the understanding of ecological processes in river-floodplain systems. Particle-associated and free-living bacterial assemblages from the Danube River and various floodplain pools with different hydrological characteristics were investigated using terminal restriction fragment length polymorphism analysis. The particle-associated bacterial community exhibited a higher number of operational taxonomic units (OTUs) and was more heterogeneous in time and space than the free-living community. The temporal dynamics of the community structure were generally higher in isolated floodplain pools. The community structures of the river and the various floodplain pools, as well as those of the particle-associated and free-living bacteria, differed significantly. The compositional dynamics of the planktonic bacterial communities were related to changes in the algal biomass, temperature, and concentrations of organic and inorganic nutrients. The OTU richness of the free-living community was correlated with the concentration and origin of organic matter and the concentration of inorganic nutrients, while no correlation with the OTU richness of the particle-associated assemblage was found. Our results demonstrate the importance of the river-floodplain interactions and the influence of damming and regulation on the bacterial-community composition. PMID:15691909
Xie, Yuwei; Wang, Jizhong; Yang, Jianghua; Giesy, John P; Yu, Hongxia; Zhang, Xiaowei
2017-04-01
Land-use intensification threatens freshwater biodiversity. Freshwater eukaryotic communities are affected by multiple chemical contaminants with a land-use specific manner. However, biodiversities of eukaryotes and their associations with multiple chemical contaminants are largely unknown. This study characterized in situ eukaryotic communities in sediments exposed to mixtures of chemical contaminants and assessed relationships between various environmental variables and eukaryotic communities in sediments from the Nanfei River. Eukaryotic communities in the sediment samples were dominated by Annelida, Arthropoda, Rotifera, Ochrophyta, Chlorophyta and Ciliophora. Alpha-diversities (Shannon entropy) and structures of eukaryotic communities were significantly different between land-use types. According to the results of multiple statistical tests (PCoA, distLM, Mantel and network analysis), dissimilarity of eukaryotic community structures revealed the key effects of pyrethroid insecticides, manganese, zinc, lead, chromium and polycyclic aromatic hydrocarbons (PAHs) on eukaryotic communities in the sediment samples from the Nanfei River. Furthermore, taxa associated with land-use types were identified and several sensitive eukaryotic taxa to some of the primary contaminants were identified as potential indicators to monitor effects of the primary chemical contaminants. Overall, environmental DNA metabarcoding on in situ eukaryotic communities provided a powerful tool for biomonitoring and identifying primary contaminants and their complex effects on benthic eukaryotic communities in freshwater sediments. Copyright © 2016 Elsevier Ltd. All rights reserved.
Two decades of warming increases diversity of a potentially lignolytic bacterial community
Pold, Grace; Melillo, Jerry M.; DeAngelis, Kristen M.
2015-01-01
As Earth's climate warms, the massive stores of carbon found in soil are predicted to become depleted, and leave behind a smaller carbon pool that is less accessible to microbes. At a long-term forest soil-warming experiment in central Massachusetts, soil respiration and bacterial diversity have increased, while fungal biomass and microbially-accessible soil carbon have decreased. Here, we evaluate how warming has affected the microbial community's capability to degrade chemically-complex soil carbon using lignin-amended BioSep beads. We profiled the bacterial and fungal communities using PCR-based methods and completed extracellular enzyme assays as a proxy for potential community function. We found that lignin-amended beads selected for a distinct community containing bacterial taxa closely related to known lignin degraders, as well as members of many genera not previously noted as capable of degrading lignin. Warming tended to drive bacterial community structure more strongly in the lignin beads, while the effect on the fungal community was limited to unamended beads. Of those bacterial operational taxonomic units (OTUs) enriched by the warming treatment, many were enriched uniquely on lignin-amended beads. These taxa may be contributing to enhanced soil respiration under warming despite reduced readily available C availability. In aggregate, these results suggest that there is genetic potential for chemically complex soil carbon degradation that may lead to extended elevated soil respiration with long-term warming. PMID:26042112
Activity and stability of a complex bacterial soil community under simulated Martian conditions
NASA Astrophysics Data System (ADS)
Hansen, Aviaja Anna; Merrison, Jonathan; Nørnberg, Per; Aagaard Lomstein, Bente; Finster, Kai
2005-04-01
A simulation experiment with a complex bacterial soil community in a Mars simulation chamber was performed to determine the effect of Martian conditions on community activity, stability and survival. At three different depths in the soil core short-term effects of Martian conditions with and without ultraviolet (UV) exposure corresponding to 8 Martian Sol were compared. Community metabolic activities and functional diversity, measured as glucose respiration and versatility in substrate utilization, respectively, decreased after UV exposure, whereas they remained unaffected by Martian conditions without UV exposure. In contrast, the numbers of culturable bacteria and the genetic diversity were unaffected by the simulated Martian conditions both with and without UV exposure. The genetic diversity of the soil community and of the colonies grown on agar plates were evaluated by denaturant gradient gel electrophoresis (DGGE) on DNA extracts. Desiccation of the soil prior to experimentation affected the functional diversity by decreasing the versatility in substrate utilization. The natural dominance of endospores and Gram-positive bacteria in the investigated Mars-analogue soil may explain the limited effect of the Mars incubations on the survival and community structure. Our results suggest that UV radiation and desiccation are major selecting factors on bacterial functional diversity in terrestrial bacterial communities incubated under simulated Martian conditions. Furthermore, these results suggest that forward contamination of Mars is a matter of great concern in future space missions.
Stergiopoulos, Vicky; Saab, Dima; Francombe Pridham, Kate; Aery, Anjana; Nakhost, Arash
2018-01-24
Across many jurisdictions, adults with complex mental health and social needs face challenges accessing appropriate supports due to system fragmentation and strict eligibility criteria of existing services. To support this underserviced population, Toronto's local health authority launched two novel community mental health models in 2014, inspired by Flexible Assertive Community Team principles. This study explores service user and provider perspectives on the acceptability of these services, and lessons learned during early implementation. We purposively sampled 49 stakeholders (staff, physicians, service users, health systems stakeholders) and conducted 17 semi-structured qualitative interviews and 5 focus groups between October 23, 2014 and March 2, 2015, exploring stakeholder perspectives on the newly launched team based models, as well as activities and strategies employed to support early implementation. Interviews and focus groups were audio recorded, transcribed verbatim and analyzed using thematic analysis. Findings revealed wide-ranging endorsement for the two team-based models' success in engaging the target population of adults with complex service needs. Implementation strengths included the broad recognition of existing service gaps, the use of interdisciplinary teams and experienced service providers, broad partnerships and collaboration among various service sectors, training and team building activities. Emerging challenges included lack of complementary support services such as suitable housing, organizational contexts reluctant to embrace change and risk associated with complexity, as well as limited service provider and organizational capacity to deliver evidence-based interventions. Findings identified implementation drivers at the practitioner, program, and system levels, specific to the implementation of community mental health interventions for adults with complex health and social needs. These can inform future efforts to address the health and support needs of this vulnerable population.
Geng, Haifeng; Tran-Gyamfi, Mary B.; Lane, Todd W.; Sale, Kenneth L.; Yu, Eizadora T.
2016-01-01
Open microalgae cultures host a myriad of bacteria, creating a complex system of interacting species that influence algal growth and health. Many algal microbiota studies have been conducted to determine the relative importance of bacterial taxa to algal culture health and physiological states, but these studies have not characterized the interspecies relationships in the microbial communities. We subjected Nanochroloropsis salina cultures to multiple chemical treatments (antibiotics and quorum sensing compounds) and obtained dense time-series data on changes to the microbial community using 16S gene amplicon metagenomic sequencing (21,029,577 reads for 23 samples) to measure microbial taxa-taxa abundance correlations. Short-term treatment with antibiotics resulted in substantially larger shifts in the microbiota structure compared to changes observed following treatment with signaling compounds and glucose. We also calculated operational taxonomic unit (OTU) associations and generated OTU correlation networks to provide an overview of possible bacterial OTU interactions. This analysis identified five major cohesive modules of microbiota with similar co-abundance profiles across different chemical treatments. The Eigengenes of OTU modules were examined for correlation with different external treatment factors. This correlation-based analysis revealed that culture age (time) and treatment types have primary effects on forming network modules and shaping the community structure. Additional network analysis detected Alteromonadeles and Alphaproteobacteria as having the highest centrality, suggesting these species are “keystone” OTUs in the microbial community. Furthermore, we illustrated that the chemical tropodithietic acid, which is secreted by several species in the Alphaproteobacteria taxon, is able to drastically change the structure of the microbiota within 3 h. Taken together, these results provide valuable insights into the structure of the microbiota associated with N. salina cultures and how these structures change in response to chemical perturbations. PMID:27507966
Physical structure and algae community of summer upwelling off eastern Hainan
NASA Astrophysics Data System (ADS)
Xu, H.; Liu, S.; Xie, Q.; Hong, B.; Long, T.
2017-12-01
The upwelling system is the most productive ecosystem along the continental shelf of the northern South China Sea Shelf. It brings nutrient from bottom to surface and blooms biotic community driven by summer monsoon. In this study, we present observed results of physical and biotic community structures during August, 2015 in the upwelling system along Hainan eastern coast, which is one the strongest upwelling systems in the northern South China Sea. By using hydrological data collected by CTD, we found a significant cold water tongue with high salinity which extended from offshore to 100 m isobaths. However, dissolved oxygen (DO) showed a sandwich structure in which high core of DO concentration appeared at the layer from 5 m to 30 m. It possibly was caused by the advection transport of high DO from adjacent area. Basically, this upwelling system was constrained at northern area of 18.8ºN in horizontal due to the weakening summer monsoon in August. In addition, we collected water sample at the upwelling area and measured algae categories and concentration by high performance liquid chromatography (HPLC). Results show the biotic community was dominated by five types of algae mainly, they were diatoms, dinoflagellates, green algae, prokaryotes and prochlorococcus. And different patterns of different algae were demonstrated. In the upwelling area, diatoms and prokaryotes show opposite structures, and more complex pattern for the rest three algae indicating an active biotic community in the upwelling system.
High pressure and Multiferroics materials. A happy marriage
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gilioli, Edmondo; Ehm, Lars
2014-10-31
We found that the community of material scientists is strongly committed to the research area of multiferroic materials, both for the understanding of the complex mechanisms supporting the multiferroism and for the fabrication of new compounds, potentially suitable for technological applications. The use of high pressure is a powerful tool in synthesizing new multiferroic, in particular magneto-electric phases, where the pressure stabilization of otherwise unstable perovskite-based structural distortions may lead to promising novel metastable compounds. Moreover, the in situ investigation of the high-pressure behavior of multiferroic materials has provided insight into the complex interplay between magnetic and electronic properties andmore » the coupling to structural instabilities.« less
Food-web complexity, meta-community complexity and community stability.
Mougi, A; Kondoh, M
2016-04-13
What allows interacting, diverse species to coexist in nature has been a central question in ecology, ever since the theoretical prediction that a complex community should be inherently unstable. Although the role of spatiality in species coexistence has been recognized, its application to more complex systems has been less explored. Here, using a meta-community model of food web, we show that meta-community complexity, measured by the number of local food webs and their connectedness, elicits a self-regulating, negative-feedback mechanism and thus stabilizes food-web dynamics. Moreover, the presence of meta-community complexity can give rise to a positive food-web complexity-stability effect. Spatiality may play a more important role in stabilizing dynamics of complex, real food webs than expected from ecological theory based on the models of simpler food webs.
Landscape moderation of biodiversity patterns and processes - eight hypotheses.
Tscharntke, Teja; Tylianakis, Jason M; Rand, Tatyana A; Didham, Raphael K; Fahrig, Lenore; Batáry, Péter; Bengtsson, Janne; Clough, Yann; Crist, Thomas O; Dormann, Carsten F; Ewers, Robert M; Fründ, Jochen; Holt, Robert D; Holzschuh, Andrea; Klein, Alexandra M; Kleijn, David; Kremen, Claire; Landis, Doug A; Laurance, William; Lindenmayer, David; Scherber, Christoph; Sodhi, Navjot; Steffan-Dewenter, Ingolf; Thies, Carsten; van der Putten, Wim H; Westphal, Catrin
2012-08-01
Understanding how landscape characteristics affect biodiversity patterns and ecological processes at local and landscape scales is critical for mitigating effects of global environmental change. In this review, we use knowledge gained from human-modified landscapes to suggest eight hypotheses, which we hope will encourage more systematic research on the role of landscape composition and configuration in determining the structure of ecological communities, ecosystem functioning and services. We organize the eight hypotheses under four overarching themes. Section A: 'landscape moderation of biodiversity patterns' includes (1) the landscape species pool hypothesis-the size of the landscape-wide species pool moderates local (alpha) biodiversity, and (2) the dominance of beta diversity hypothesis-landscape-moderated dissimilarity of local communities determines landscape-wide biodiversity and overrides negative local effects of habitat fragmentation on biodiversity. Section B: 'landscape moderation of population dynamics' includes (3) the cross-habitat spillover hypothesis-landscape-moderated spillover of energy, resources and organisms across habitats, including between managed and natural ecosystems, influences landscape-wide community structure and associated processes and (4) the landscape-moderated concentration and dilution hypothesis-spatial and temporal changes in landscape composition can cause transient concentration or dilution of populations with functional consequences. Section C: 'landscape moderation of functional trait selection' includes (5) the landscape-moderated functional trait selection hypothesis-landscape moderation of species trait selection shapes the functional role and trajectory of community assembly, and (6) the landscape-moderated insurance hypothesis-landscape complexity provides spatial and temporal insurance, i.e. high resilience and stability of ecological processes in changing environments. Section D: 'landscape constraints on conservation management' includes (7) the intermediate landscape-complexity hypothesis-landscape-moderated effectiveness of local conservation management is highest in structurally simple, rather than in cleared (i.e. extremely simplified) or in complex landscapes, and (8) the landscape-moderated biodiversity versus ecosystem service management hypothesis-landscape-moderated biodiversity conservation to optimize functional diversity and related ecosystem services will not protect endangered species. Shifting our research focus from local to landscape-moderated effects on biodiversity will be critical to developing solutions for future biodiversity and ecosystem service management. © 2012 The Authors. Biological Reviews © 2012 Cambridge Philosophical Society.
Ocean acidification can mediate biodiversity shifts by changing biogenic habitat
NASA Astrophysics Data System (ADS)
Sunday, Jennifer M.; Fabricius, Katharina E.; Kroeker, Kristy J.; Anderson, Kathryn M.; Brown, Norah E.; Barry, James P.; Connell, Sean D.; Dupont, Sam; Gaylord, Brian; Hall-Spencer, Jason M.; Klinger, Terrie; Milazzo, Marco; Munday, Philip L.; Russell, Bayden D.; Sanford, Eric; Thiyagarajan, Vengatesen; Vaughan, Megan L. H.; Widdicombe, Stephen; Harley, Christopher D. G.
2017-01-01
The effects of ocean acidification (OA) on the structure and complexity of coastal marine biogenic habitat have been broadly overlooked. Here we explore how declining pH and carbonate saturation may affect the structural complexity of four major biogenic habitats. Our analyses predict that indirect effects driven by OA on habitat-forming organisms could lead to lower species diversity in coral reefs, mussel beds and some macroalgal habitats, but increases in seagrass and other macroalgal habitats. Available in situ data support the prediction of decreased biodiversity in coral reefs, but not the prediction of seagrass bed gains. Thus, OA-driven habitat loss may exacerbate the direct negative effects of OA on coastal biodiversity; however, we lack evidence of the predicted biodiversity increase in systems where habitat-forming species could benefit from acidification. Overall, a combination of direct effects and community-mediated indirect effects will drive changes in the extent and structural complexity of biogenic habitat, which will have important ecosystem effects.
The methodology of multi-viewpoint clustering analysis
NASA Technical Reports Server (NTRS)
Mehrotra, Mala; Wild, Chris
1993-01-01
One of the greatest challenges facing the software engineering community is the ability to produce large and complex computer systems, such as ground support systems for unmanned scientific missions, that are reliable and cost effective. In order to build and maintain these systems, it is important that the knowledge in the system be suitably abstracted, structured, and otherwise clustered in a manner which facilitates its understanding, manipulation, testing, and utilization. Development of complex mission-critical systems will require the ability to abstract overall concepts in the system at various levels of detail and to consider the system from different points of view. Multi-ViewPoint - Clustering Analysis MVP-CA methodology has been developed to provide multiple views of large, complicated systems. MVP-CA provides an ability to discover significant structures by providing an automated mechanism to structure both hierarchically (from detail to abstract) and orthogonally (from different perspectives). We propose to integrate MVP/CA into an overall software engineering life cycle to support the development and evolution of complex mission critical systems.
Animal diversity and ecosystem functioning in dynamic food webs
NASA Astrophysics Data System (ADS)
Schneider, Florian D.; Brose, Ulrich; Rall, Björn C.; Guill, Christian
2016-10-01
Species diversity is changing globally and locally, but the complexity of ecological communities hampers a general understanding of the consequences of animal species loss on ecosystem functioning. High animal diversity increases complementarity of herbivores but also increases feeding rates within the consumer guild. Depending on the balance of these counteracting mechanisms, species-rich animal communities may put plants under top-down control or may release them from grazing pressure. Using a dynamic food-web model with body-mass constraints, we simulate ecosystem functions of 20,000 communities of varying animal diversity. We show that diverse animal communities accumulate more biomass and are more exploitative on plants, despite their higher rates of intra-guild predation. However, they do not reduce plant biomass because the communities are composed of larger, and thus energetically more efficient, plant and animal species. This plasticity of community body-size structure reconciles the debate on the consequences of animal species loss for primary productivity.
Chen, Heng; Chen, Xinying
2018-01-01
Language is a complex adaptive system, but how does it change? For investigating this process, four diachronic Chinese word co-occurrence networks have been built based on texts that were written during the last 2,000 years. By comparing the network indicators that are associated with the hierarchical features in language networks, we learn that the hierarchy of Chinese lexical networks has indeed evolved over time at three different levels. The connections of words at the micro level are continually weakening; the number of words in the meso-level communities has increased significantly; and the network is expanding at the macro level. This means that more and more words tend to be connected to medium-central words and form different communities. Meanwhile, fewer high-central words link these communities into a highly efficient small-world network. Understanding this process may be crucial for understanding the increasing structural complexity of the language system. PMID:29489837
Zhou, Jizhong; He, Zhili; Yang, Yunfeng; Deng, Ye; Tringe, Susannah G; Alvarez-Cohen, Lisa
2015-01-27
Understanding the structure, functions, activities and dynamics of microbial communities in natural environments is one of the grand challenges of 21st century science. To address this challenge, over the past decade, numerous technologies have been developed for interrogating microbial communities, of which some are amenable to exploratory work (e.g., high-throughput sequencing and phenotypic screening) and others depend on reference genes or genomes (e.g., phylogenetic and functional gene arrays). Here, we provide a critical review and synthesis of the most commonly applied "open-format" and "closed-format" detection technologies. We discuss their characteristics, advantages, and disadvantages within the context of environmental applications and focus on analysis of complex microbial systems, such as those in soils, in which diversity is high and reference genomes are few. In addition, we discuss crucial issues and considerations associated with applying complementary high-throughput molecular technologies to address important ecological questions. Copyright © 2015 Zhou et al.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jeffries, H P
The principal hypothesis addressed in this study states that community variability is related to fatty acid structure. As a test of this idea, the zooplankton in three regimes of increasing physical severity (Block Island Sound, Narragansett Bay and Green Hill Pond) are being compared. Measurements were made on the physical environment, on standing crop and on fatty acid composition in both the phytoplankton-microzooplankton and macrozooplankton. Fatty acid variation in these communities displays a unique trajectory in time at each location. Environmental change and biochemical variability are directly related. The resulting biochemical message is complex but apparently highly informative. Patterns ofmore » variation in some fatty acids are affected most strongly by physical environmental parameters whereas the variation of other fatty acids is more responsive to differences in species composition, diversity and food web relationships. Taken together, these two aspects of biochemical pattern appear to characterize complex species assemblages. The result offers a new strategem for convenient assessment of the ever changing state in a natural community.« less
He, Zhili; Yang, Yunfeng; Deng, Ye; Tringe, Susannah G.; Alvarez-Cohen, Lisa
2015-01-01
ABSTRACT Understanding the structure, functions, activities and dynamics of microbial communities in natural environments is one of the grand challenges of 21st century science. To address this challenge, over the past decade, numerous technologies have been developed for interrogating microbial communities, of which some are amenable to exploratory work (e.g., high-throughput sequencing and phenotypic screening) and others depend on reference genes or genomes (e.g., phylogenetic and functional gene arrays). Here, we provide a critical review and synthesis of the most commonly applied “open-format” and “closed-format” detection technologies. We discuss their characteristics, advantages, and disadvantages within the context of environmental applications and focus on analysis of complex microbial systems, such as those in soils, in which diversity is high and reference genomes are few. In addition, we discuss crucial issues and considerations associated with applying complementary high-throughput molecular technologies to address important ecological questions. PMID:25626903
Chen, Heng; Chen, Xinying; Liu, Haitao
2018-01-01
Language is a complex adaptive system, but how does it change? For investigating this process, four diachronic Chinese word co-occurrence networks have been built based on texts that were written during the last 2,000 years. By comparing the network indicators that are associated with the hierarchical features in language networks, we learn that the hierarchy of Chinese lexical networks has indeed evolved over time at three different levels. The connections of words at the micro level are continually weakening; the number of words in the meso-level communities has increased significantly; and the network is expanding at the macro level. This means that more and more words tend to be connected to medium-central words and form different communities. Meanwhile, fewer high-central words link these communities into a highly efficient small-world network. Understanding this process may be crucial for understanding the increasing structural complexity of the language system.
Zhou, Jizhong; He, Zhili; Yang, Yunfeng; ...
2015-01-27
Understanding the structure, functions, activities and dynamics of microbial communities in natural environments is one of the grand challenges of 21st century science. To address this challenge, over the past decade, numerous technologies have been developed for interrogating microbial communities, of which some are amenable to exploratory work (e.g., high-throughput sequencing and phenotypic screening) and others depend on reference genes or genomes (e.g., phylogenetic and functional gene arrays). Here, we provide a critical review and synthesis of the most commonly applied “open-format” and “closed-format” detection technologies. We discuss their characteristics, advantages, and disadvantages within the context of environmental applications andmore » focus on analysis of complex microbial systems, such as those in soils, in which diversity is high and reference genomes are few. In addition, we discuss crucial issues and considerations associated with applying complementary high-throughput molecular technologies to address important ecological questions.« less
Parasites, ecosystems and sustainability: an ecological and complex systems perspective.
Horwitz, Pierre; Wilcox, Bruce A
2005-06-01
Host-parasite relationships can be conceptualised either narrowly, where the parasite is metabolically dependent on the host, or more broadly, as suggested by an ecological-evolutionary and complex systems perspective. In this view Host-parasite relationships are part of a larger set of ecological and co-evolutionary interdependencies and a complex adaptive system. These interdependencies affect not just the hosts, vectors, parasites, the immediate agents, but also those indirectly or consequentially affected by the relationship. Host-parasite relationships also can be viewed as systems embedded within larger systems represented by ecological communities and ecosystems. So defined, it can be argued that Host-parasite relationships may often benefit their hosts and contribute significantly to the structuring of ecological communities. The broader, complex adaptive system view also contributes to understanding the phenomenon of disease emergence, the ecological and evolutionary mechanisms involved, and the role of parasitology in research and management of ecosystems in light of the apparently growing problem of emerging infectious diseases in wildlife and humans. An expanded set of principles for integrated parasite management is suggested by this perspective.
Puspitasari, Hanni P.; Aslani, Parisa; Krass, Ines
2014-01-01
Background As primary healthcare professionals, community pharmacists have both opportunity and potential to contribute to the prevention and progression of chronic diseases. Using cardiovascular disease (CVD) as a case study, we explored factors that influence community pharmacists’ everyday practice in this area. We also propose a model to best illustrate relationships between influencing factors and the scope of community pharmacy practice in the care of clients with established CVD. Methods In-depth, semi-structured interviews were conducted with 21 community pharmacists in New South Wales, Australia. All interviews were audio-recorded, transcribed ad verbatim, and analysed using a “grounded-theory” approach. Results Our model shows that community pharmacists work within a complex system and their practice is influenced by interactions between three main domains: the “people” factors, including their own attitudes and beliefs as well as those of clients and doctors; the “environment” within and beyond the control of community pharmacy; and outcomes of their professional care. Despite the complexity of factors and interactions, our findings shed some light on the interrelationships between these various influences. The overarching obstacle to maximizing the community pharmacists’ contribution is the lack of integration within health systems. However, achieving better integration of community pharmacists in primary care is a challenge since the systems of remuneration for healthcare professional services do not currently support this integration. Conclusion Tackling chronic diseases such as CVD requires mobilization of all sources of support in the community through innovative policies which facilitate inter-professional collaboration and team care to achieve the best possible healthcare outcomes for society. PMID:25409194
Puspitasari, Hanni P; Aslani, Parisa; Krass, Ines
2014-01-01
As primary healthcare professionals, community pharmacists have both opportunity and potential to contribute to the prevention and progression of chronic diseases. Using cardiovascular disease (CVD) as a case study, we explored factors that influence community pharmacists' everyday practice in this area. We also propose a model to best illustrate relationships between influencing factors and the scope of community pharmacy practice in the care of clients with established CVD. In-depth, semi-structured interviews were conducted with 21 community pharmacists in New South Wales, Australia. All interviews were audio-recorded, transcribed ad verbatim, and analysed using a "grounded-theory" approach. Our model shows that community pharmacists work within a complex system and their practice is influenced by interactions between three main domains: the "people" factors, including their own attitudes and beliefs as well as those of clients and doctors; the "environment" within and beyond the control of community pharmacy; and outcomes of their professional care. Despite the complexity of factors and interactions, our findings shed some light on the interrelationships between these various influences. The overarching obstacle to maximizing the community pharmacists' contribution is the lack of integration within health systems. However, achieving better integration of community pharmacists in primary care is a challenge since the systems of remuneration for healthcare professional services do not currently support this integration. Tackling chronic diseases such as CVD requires mobilization of all sources of support in the community through innovative policies which facilitate inter-professional collaboration and team care to achieve the best possible healthcare outcomes for society.
Microbial bebop: creating music from complex dynamics in microbial ecology.
Larsen, Peter; Gilbert, Jack
2013-01-01
In order for society to make effective policy decisions on complex and far-reaching subjects, such as appropriate responses to global climate change, scientists must effectively communicate complex results to the non-scientifically specialized public. However, there are few ways however to transform highly complicated scientific data into formats that are engaging to the general community. Taking inspiration from patterns observed in nature and from some of the principles of jazz bebop improvisation, we have generated Microbial Bebop, a method by which microbial environmental data are transformed into music. Microbial Bebop uses meter, pitch, duration, and harmony to highlight the relationships between multiple data types in complex biological datasets. We use a comprehensive microbial ecology, time course dataset collected at the L4 marine monitoring station in the Western English Channel as an example of microbial ecological data that can be transformed into music. Four compositions were generated (www.bio.anl.gov/MicrobialBebop.htm.) from L4 Station data using Microbial Bebop. Each composition, though deriving from the same dataset, is created to highlight different relationships between environmental conditions and microbial community structure. The approach presented here can be applied to a wide variety of complex biological datasets.
Lewin, Gina R.; Johnson, Amanda L.; Soto, Rolando D. Moreira; ...
2016-03-21
Deconstruction of the cellulose in plant cell walls is critical for carbon flow through ecosystems and for the production of sustainable cellulosic biofuels. Our understanding of cellulose deconstruction is largely limited to the study of microbes in isolation, but in nature, this process is driven by microbes within complex communities. In Neotropical forests, microbes in leaf-cutter ant refuse dumps are important for carbon turnover. These dumps consist of decaying plant material and a diverse bacterial community, as shown here by electron microscopy. To study the portion of the community capable of cellulose degradation, we performed enrichments on cellulose using materialmore » from five Atta colombica refuse dumps. The ability of enriched communities to degrade cellulose varied significantly across refuse dumps. 16S rRNA gene amplicon sequencing of enriched samples identified that the community structure correlated with refuse dump and with degradation ability. Overall, samples were dominated by Bacteroidetes, Gammaproteobacteria, and Betaproteobacteria. Half of abundant operational taxonomic units (OTUs) across samples were classified within general containing known cellulose degraders, including Acidovorax, the most abundant OTU detected across samples, which was positively correlated with cellulolytic ability. Lastly, a representative Acidovorax strain was isolated, but did not grow on cellulose alone. Phenotypic and compositional analyses of enrichment cultures, such as those presented here, help link community composition with cellulolytic ability and provide insight into the complexity of community-based cellulose degradation.« less
Lewin, Gina R.; Johnson, Amanda L.; Soto, Rolando D. Moreira; Perry, Kailene; Book, Adam J.; Horn, Heidi A.; Pinto-Tomás, Adrián A.; Currie, Cameron R.
2016-01-01
Deconstruction of the cellulose in plant cell walls is critical for carbon flow through ecosystems and for the production of sustainable cellulosic biofuels. Our understanding of cellulose deconstruction is largely limited to the study of microbes in isolation, but in nature, this process is driven by microbes within complex communities. In Neotropical forests, microbes in leaf-cutter ant refuse dumps are important for carbon turnover. These dumps consist of decaying plant material and a diverse bacterial community, as shown here by electron microscopy. To study the portion of the community capable of cellulose degradation, we performed enrichments on cellulose using material from five Atta colombica refuse dumps. The ability of enriched communities to degrade cellulose varied significantly across refuse dumps. 16S rRNA gene amplicon sequencing of enriched samples identified that the community structure correlated with refuse dump and with degradation ability. Overall, samples were dominated by Bacteroidetes, Gammaproteobacteria, and Betaproteobacteria. Half of abundant operational taxonomic units (OTUs) across samples were classified within genera containing known cellulose degraders, including Acidovorax, the most abundant OTU detected across samples, which was positively correlated with cellulolytic ability. A representative Acidovorax strain was isolated, but did not grow on cellulose alone. Phenotypic and compositional analyses of enrichment cultures, such as those presented here, help link community composition with cellulolytic ability and provide insight into the complexity of community-based cellulose degradation. PMID:26999749
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lewin, Gina R.; Johnson, Amanda L.; Soto, Rolando D. Moreira
Deconstruction of the cellulose in plant cell walls is critical for carbon flow through ecosystems and for the production of sustainable cellulosic biofuels. Our understanding of cellulose deconstruction is largely limited to the study of microbes in isolation, but in nature, this process is driven by microbes within complex communities. In Neotropical forests, microbes in leaf-cutter ant refuse dumps are important for carbon turnover. These dumps consist of decaying plant material and a diverse bacterial community, as shown here by electron microscopy. To study the portion of the community capable of cellulose degradation, we performed enrichments on cellulose using materialmore » from five Atta colombica refuse dumps. The ability of enriched communities to degrade cellulose varied significantly across refuse dumps. 16S rRNA gene amplicon sequencing of enriched samples identified that the community structure correlated with refuse dump and with degradation ability. Overall, samples were dominated by Bacteroidetes, Gammaproteobacteria, and Betaproteobacteria. Half of abundant operational taxonomic units (OTUs) across samples were classified within general containing known cellulose degraders, including Acidovorax, the most abundant OTU detected across samples, which was positively correlated with cellulolytic ability. Lastly, a representative Acidovorax strain was isolated, but did not grow on cellulose alone. Phenotypic and compositional analyses of enrichment cultures, such as those presented here, help link community composition with cellulolytic ability and provide insight into the complexity of community-based cellulose degradation.« less
Microbial diversity and interactions in subgingival biofilm communities.
Diaz, Patricia I
2012-01-01
The human subgingival environment is a complex environmental niche where microorganisms from the three domains of life meet to form diverse biofilm communities that exist in close proximity to the host. Bacteria constitute the most abundant, diverse and ultimately well-studied component of these communities with about 500 bacterial taxa reported to occur in this niche. Cultivation and molecular approaches are revealing the breadth and depth of subgingival biofilm diversity as part of an effort to understand the subgingival microbiome, the collection of microorganisms that inhabit the gingival crevices. Although these investigations are constructing a pretty detailed taxonomical census of subgingival microbial communities, including inter-subject and temporal variability in community structure, as well as differences according to periodontal health status, we are still at the front steps in terms of understanding community function. Clinical studies that evaluate community structure need to be coupled with biologically relevant models that allow evaluation of the ecological determinants of subgingival biofilm maturation. Functional characteristics of subgingival biofilm communities that still need to be clarified include main metabolic processes that support microbial communities, identification of keystone species, microbial interactions and signaling events that lead to community maturation and the relationship of different communities with the host. This manuscript presents a summary of our current understanding of subgingival microbial diversity and an overview of experimental models used to dissect the functional characteristics of subgingival communities. Future coupling of 'omics'-based approaches with such models will facilitate a better understanding of subgingival ecology opening opportunities for community manipulation. Copyright © 2012 S. Karger AG, Basel.
Microbial community pattern detection in human body habitats via ensemble clustering framework.
Yang, Peng; Su, Xiaoquan; Ou-Yang, Le; Chua, Hon-Nian; Li, Xiao-Li; Ning, Kang
2014-01-01
The human habitat is a host where microbial species evolve, function, and continue to evolve. Elucidating how microbial communities respond to human habitats is a fundamental and critical task, as establishing baselines of human microbiome is essential in understanding its role in human disease and health. Recent studies on healthy human microbiome focus on particular body habitats, assuming that microbiome develop similar structural patterns to perform similar ecosystem function under same environmental conditions. However, current studies usually overlook a complex and interconnected landscape of human microbiome and limit the ability in particular body habitats with learning models of specific criterion. Therefore, these methods could not capture the real-world underlying microbial patterns effectively. To obtain a comprehensive view, we propose a novel ensemble clustering framework to mine the structure of microbial community pattern on large-scale metagenomic data. Particularly, we first build a microbial similarity network via integrating 1920 metagenomic samples from three body habitats of healthy adults. Then a novel symmetric Nonnegative Matrix Factorization (NMF) based ensemble model is proposed and applied onto the network to detect clustering pattern. Extensive experiments are conducted to evaluate the effectiveness of our model on deriving microbial community with respect to body habitat and host gender. From clustering results, we observed that body habitat exhibits a strong bound but non-unique microbial structural pattern. Meanwhile, human microbiome reveals different degree of structural variations over body habitat and host gender. In summary, our ensemble clustering framework could efficiently explore integrated clustering results to accurately identify microbial communities, and provide a comprehensive view for a set of microbial communities. The clustering results indicate that structure of human microbiome is varied systematically across body habitats and host genders. Such trends depict an integrated biography of microbial communities, which offer a new insight towards uncovering pathogenic model of human microbiome.
Microbial community pattern detection in human body habitats via ensemble clustering framework
2014-01-01
Background The human habitat is a host where microbial species evolve, function, and continue to evolve. Elucidating how microbial communities respond to human habitats is a fundamental and critical task, as establishing baselines of human microbiome is essential in understanding its role in human disease and health. Recent studies on healthy human microbiome focus on particular body habitats, assuming that microbiome develop similar structural patterns to perform similar ecosystem function under same environmental conditions. However, current studies usually overlook a complex and interconnected landscape of human microbiome and limit the ability in particular body habitats with learning models of specific criterion. Therefore, these methods could not capture the real-world underlying microbial patterns effectively. Results To obtain a comprehensive view, we propose a novel ensemble clustering framework to mine the structure of microbial community pattern on large-scale metagenomic data. Particularly, we first build a microbial similarity network via integrating 1920 metagenomic samples from three body habitats of healthy adults. Then a novel symmetric Nonnegative Matrix Factorization (NMF) based ensemble model is proposed and applied onto the network to detect clustering pattern. Extensive experiments are conducted to evaluate the effectiveness of our model on deriving microbial community with respect to body habitat and host gender. From clustering results, we observed that body habitat exhibits a strong bound but non-unique microbial structural pattern. Meanwhile, human microbiome reveals different degree of structural variations over body habitat and host gender. Conclusions In summary, our ensemble clustering framework could efficiently explore integrated clustering results to accurately identify microbial communities, and provide a comprehensive view for a set of microbial communities. The clustering results indicate that structure of human microbiome is varied systematically across body habitats and host genders. Such trends depict an integrated biography of microbial communities, which offer a new insight towards uncovering pathogenic model of human microbiome. PMID:25521415
Architecture of the human interactome defines protein communities and disease networks
Huttlin, Edward L.; Bruckner, Raphael J.; Paulo, Joao A.; Cannon, Joe R.; Ting, Lily; Baltier, Kurt; Colby, Greg; Gebreab, Fana; Gygi, Melanie P.; Parzen, Hannah; Szpyt, John; Tam, Stanley; Zarraga, Gabriela; Pontano-Vaites, Laura; Swarup, Sharan; White, Anne E.; Schweppe, Devin K.; Rad, Ramin; Erickson, Brian K.; Obar, Robert A.; Guruharsha, K.G.; Li, Kejie; Artavanis-Tsakonas, Spyros; Gygi, Steven P.; Harper, J. Wade
2017-01-01
The physiology of a cell can be viewed as the product of thousands of proteins acting in concert to shape the cellular response. Coordination is achieved in part through networks of protein-protein interactions that assemble functionally related proteins into complexes, organelles, and signal transduction pathways. Understanding the architecture of the human proteome has the potential to inform cellular, structural, and evolutionary mechanisms and is critical to elucidation of how genome variation contributes to disease1–3. Here, we present BioPlex 2.0 (Biophysical Interactions of ORFEOME-derived complexes), which employs robust affinity purification-mass spectrometry (AP-MS) methodology4 to elucidate protein interaction networks and co-complexes nucleated by more than 25% of protein coding genes from the human genome, and constitutes the largest such network to date. With >56,000 candidate interactions, BioPlex 2.0 contains >29,000 previously unknown co-associations and provides functional insights into hundreds of poorly characterized proteins while enhancing network-based analyses of domain associations, subcellular localization, and co-complex formation. Unsupervised Markov clustering (MCL)5 of interacting proteins identified more than 1300 protein communities representing diverse cellular activities. Genes essential for cell fitness6,7 are enriched within 53 communities representing central cellular functions. Moreover, we identified 442 communities associated with more than 2000 disease annotations, placing numerous candidate disease genes into a cellular framework. BioPlex 2.0 exceeds previous experimentally derived interaction networks in depth and breadth, and will be a valuable resource for exploring the biology of incompletely characterized proteins and for elucidating larger-scale patterns of proteome organization. PMID:28514442
NASA Astrophysics Data System (ADS)
Lukacheva, Evgeniya; Natalia, Manucharova
2016-04-01
Chitin is a naturally occurring fibre-forming polymer that plays a protective role in many lower animals similar to that of cellulose in plants. Also it's a compound of cell walls of fungi. Chemically it is a long-chain unbranched polysaccharide made of N-acetylglucosamine residues; it is the second most abundant organic compound in nature, after cellulose. Pectin is a structural heteropolysaccharide contained in the primary cell walls of terrestrial plants. Roots of the plants and root crops contain pectin. Chitin and pectin are widely distributed throughout the natural world. Structural and functional features of the complex microbial degradation of biopolymers one of the most important direction in microbial ecology. But there is no a lot of data concerns degradation in vertical structure of terrestrial ecosystems and detailed studies concerning certain abiotic features as pH. Microbial complexes of natural areas were analyzed only as humus horizons (A1) of the soil profile. Only small part of microbial community could be studied with this approach. It is known that ecosystems have their own structure. It is possible to allocate some vertical tiers: phylloplane, litter (soil covering), soil. We investigated chitinolytic and pectinolytic microbial communities dedicated to different layers of the ecosystems. Also it was described depending on pH dominated in certain ecosystem with certain conditions. Quantity of eukaryote and procaryote organisms increased in the test samples with chitin and pectin. Increasing of eukaryote in samples with pectin was more then in samples with chitin. Also should be noted the significant increasing of actinomycet's quantity in the samples with chitin in comparison with samples with pectin. The variety and abundance of bacteria in the litter samples increased an order of magnitude as compared to other probes. Further prokaryote community was investigated by method FISH (fluorescence in situ hybridization). FISH is a cytogenetic technique developed that is used to detect and localize the presence or absence of specific DNA sequences on chromosomes. pH as one of the factors which can have influence on degradation of biopolymers was studied for chitiolytic communities of different zones. And results were compared with direct studyings by method of "sowing" on a Petri dishes. Thus, we compared old classical methods with modern molecular studies. The difference between climatic zones was studied and the mathematical model was created. The mathematic model could be use in different aims, such as prognosis of microbial community composition and their classification.
Leaders, Leveraging, and Abundance: Competencies for the Future
ERIC Educational Resources Information Center
Alfred, Richard L.
2012-01-01
Leadership, as it is practiced today in community colleges, has taken three brilliant ideas to excess and made them into guiding ideologies. The first is "growth," a means for gauging organizational legitimacy and success that has eclipsed other means. The second is "complexity," which has gained acceptance as a structural necessity for managing…
Ulyshen Michael
2011-01-01
Studies on the vertical distribution patterns of arthropods in temperate deciduous forests reveal highly stratified (i.e., unevenly vertically distributed) communities. These patterns are determined by multiple factors acting simultaneously, including: (1) time (forest age, season, time of day); (2) forest structure (height, vertical foliage complexity, plant surface...
ERIC Educational Resources Information Center
Tull, Ashley, Ed.; Kuk, Linda, Ed.
2012-01-01
Student affairs organizations are at a crossroads. They face expanding enrollments; a concomitant increase need for often more complex services; changing demographics; a growing cohort of non-traditional and first-generation students; shifting and more demanding responsibilities; and increased expectations from the greater campus community,…
Dai, Tianjiao; Zhang, Yan; Tang, Yushi; Bai, Yaohui; Tao, Yile; Huang, Bei; Wen, Donghui
2016-10-01
Coastal areas are land-sea transitional zones with complex natural and anthropogenic disturbances. Microorganisms in coastal sediments adapt to such disturbances both individually and as a community. The microbial community structure changes spatially and temporally under environmental stress. In this study, we investigated the microbial community structure in the sediments of Hangzhou Bay, a seriously polluted bay in China. In order to identify the roles and contribution of all microbial taxa, we set thresholds as 0.1% for rare taxa and 1% for abundant taxa, and classified all operational taxonomic units into six exclusive categories based on their abundance. The results showed that the key taxa in differentiating the communities are abundant taxa (AT), conditionally abundant taxa (CAT), and conditionally rare or abundant taxa (CRAT). A large population in conditionally rare taxa (CRT) made this category collectively significant in differentiating the communities. Both bacteria and archaea demonstrated a distance decay pattern of community similarity in the bay, and this pattern was strengthened by rare taxa, CRT and CRAT, but weakened by AT and CAT. This implied that the low abundance taxa were more deterministically distributed, while the high abundance taxa were more ubiquitously distributed. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Detectability Thresholds and Optimal Algorithms for Community Structure in Dynamic Networks
NASA Astrophysics Data System (ADS)
Ghasemian, Amir; Zhang, Pan; Clauset, Aaron; Moore, Cristopher; Peel, Leto
2016-07-01
The detection of communities within a dynamic network is a common means for obtaining a coarse-grained view of a complex system and for investigating its underlying processes. While a number of methods have been proposed in the machine learning and physics literature, we lack a theoretical analysis of their strengths and weaknesses, or of the ultimate limits on when communities can be detected. Here, we study the fundamental limits of detecting community structure in dynamic networks. Specifically, we analyze the limits of detectability for a dynamic stochastic block model where nodes change their community memberships over time, but where edges are generated independently at each time step. Using the cavity method, we derive a precise detectability threshold as a function of the rate of change and the strength of the communities. Below this sharp threshold, we claim that no efficient algorithm can identify the communities better than chance. We then give two algorithms that are optimal in the sense that they succeed all the way down to this threshold. The first uses belief propagation, which gives asymptotically optimal accuracy, and the second is a fast spectral clustering algorithm, based on linearizing the belief propagation equations. These results extend our understanding of the limits of community detection in an important direction, and introduce new mathematical tools for similar extensions to networks with other types of auxiliary information.
Haack, S.K.; Fogarty, L.R.; West, T.G.; Alm, E.W.; McGuire, J.T.; Long, D.T.; Hyndman, D.W.; Forney, L.J.
2004-01-01
In a contaminated water-table aquifer, we related microbial community structure on aquifer sediments to gradients in 24 geochemical and contaminant variables at five depths, under three recharge conditions. Community amplified ribsosomal DNA restriction analysis (ARDRA) using universal 16S rDNA primers and denaturing gradient gel electrophoresis (DGGE) using bacterial 16S rDNA primers indicated: (i) communities in the anoxic, contaminated central zone were similar regardless of recharge; (ii) after recharge, communities at greatest depth were similar to those in uncontaminated zones; and (iii) after extended lack of recharge, communities at upper and lower aquifer margins differed from communities at the same depths on other dates. General aquifer geochemistry was as important as contaminant or terminal electron accepting process (TEAP) chemistry in discriminant analysis of community groups. The Shannon index of diversity (H) and the evenness index (E), based on DGGE operational taxonomic units (OTUs), were statistically different across community groups and aquifer depths. Archaea or sulphate-reducing bacteria 16S rRNA abundance was not clearly correlated with TEAP chemistry indicative of methanogenesis or sulphate reduction. Eukarya rRNA abundance varied by depth and date from 0 to 13% of the microbial community. This contaminated aquifer is a dynamic ecosystem, with complex interactions between physical, chemical and biotic components, which should be considered in the interpretation of aquifer geochemistry and in the development of conceptual or predictive models for natural attenuation or remediation.
An experimental test of a fundamental food web motif.
Rip, Jason M K; McCann, Kevin S; Lynn, Denis H; Fawcett, Sonia
2010-06-07
Large-scale changes to the world's ecosystem are resulting in the deterioration of biostructure-the complex web of species interactions that make up ecological communities. A difficult, yet crucial task is to identify food web structures, or food web motifs, that are the building blocks of this baroque network of interactions. Once identified, these food web motifs can then be examined through experiments and theory to provide mechanistic explanations for how structure governs ecosystem stability. Here, we synthesize recent ecological research to show that generalist consumers coupling resources with different interaction strengths, is one such motif. This motif amazingly occurs across an enormous range of spatial scales, and so acts to distribute coupled weak and strong interactions throughout food webs. We then perform an experiment that illustrates the importance of this motif to ecological stability. We find that weak interactions coupled to strong interactions by generalist consumers dampen strong interaction strengths and increase community stability. This study takes a critical step by isolating a common food web motif and through clear, experimental manipulation, identifies the fundamental stabilizing consequences of this structure for ecological communities.
Living in the branches: population dynamics and ecological processes in dendritic networks
Grant, E.H.C.; Lowe, W.H.; Fagan, W.F.
2007-01-01
Spatial structure regulates and modifies processes at several levels of ecological organization (e.g. individual/genetic, population and community) and is thus a key component of complex systems, where knowledge at a small scale can be insufficient for understanding system behaviour at a larger scale. Recent syntheses outline potential applications of network theory to ecological systems, but do not address the implications of physical structure for network dynamics. There is a specific need to examine how dendritic habitat structure, such as that found in stream, hedgerow and cave networks, influences ecological processes. Although dendritic networks are one type of ecological network, they are distinguished by two fundamental characteristics: (1) both the branches and the nodes serve as habitat, and (2) the specific spatial arrangement and hierarchical organization of these elements interacts with a species' movement behaviour to alter patterns of population distribution and abundance, and community interactions. Here, we summarize existing theory relating to ecological dynamics in dendritic networks, review empirical studies examining the population- and community-level consequences of these networks, and suggest future research integrating spatial pattern and processes in dendritic systems.
Samuel A. Cushman; Bradley W. Compton; Kevin McGarigal
2010-01-01
Habitat loss and fragmentation are widely believed to be the most important drivers of extinction (Leakey and Lewin 1995). The habitats in which organisms live are spatially structured at a number of scales, and these patterns interact with organism perception and behavior to drive population dynamics and community structure (Johnson et al. 1992). Anthropogenic habitat...
Weighted compactness function based label propagation algorithm for community detection
NASA Astrophysics Data System (ADS)
Zhang, Weitong; Zhang, Rui; Shang, Ronghua; Jiao, Licheng
2018-02-01
Community detection in complex networks, is to detect the community structure with the internal structure relatively compact and the external structure relatively sparse, according to the topological relationship among nodes in the network. In this paper, we propose a compactness function which combines the weight of nodes, and use it as the objective function to carry out the node label propagation. Firstly, according to the node degree, we find the sets of core nodes which have great influence on the network. The more the connections between the core nodes and the other nodes are, the larger the amount of the information these kernel nodes receive and transform. Then, according to the similarity of the nodes between the core nodes sets and the nodes degree, we assign weights to the nodes in the network. So the label of the nodes with great influence will be the priority in the label propagation process, which effectively improves the accuracy of the label propagation. The compactness function between nodes and communities in this paper is based on the nodes influence. It combines the connections between nodes and communities with the degree of the node belongs to its neighbor communities based on calculating the node weight. The function effectively uses the information of nodes and connections in the network. The experimental results show that the proposed algorithm can achieve good results in the artificial network and large-scale real networks compared with the 8 contrast algorithms.
Habitat-based constraints on food web structure and parasite life cycles.
Rossiter, Wayne; Sukhdeo, Michael V K
2014-04-01
Habitat is frequently implicated as a powerful determinant of community structure and species distributions, but few studies explicitly evaluate the relationship between habitat-based patterns of species' distributions and the presence or absence of trophic interactions. The complex (multi-host) life cycles of parasites are directly affected by these factors, but almost no data exist on the role of habitat in constraining parasite-host interactions at the community level. In this study the relationship(s) between species abundances, distributions and trophic interactions (including parasitism) were evaluated in the context of habitat structure (classic geomorphic designations of pools, riffles and runs) in a riverine community (Raritan River, Hunterdon County, NJ, USA). We report 121 taxa collected over a 2-year period, and compare the observed food web patterns to null model expectations. The results show that top predators are constrained to particular habitat types, and that species' distributions are biased towards pool habitats. However, our null model (which incorporates cascade model assumptions) accurately predicts the observed patterns of trophic interactions. Thus, habitat strongly dictates species distributions, and patterns of trophic interactions arise as a consequence of these distributions. Additionally, we find that hosts utilized in parasite life cycles are more overlapping in their distributions, and this pattern is more pronounced among those involved in trophic transmission. We conclude that habitat structure may be a strong predictor of parasite transmission routes, particularly within communities that occupy heterogeneous habitats.
Ren, Ge; Ma, Anzhou; Zhang, Yanfen; Deng, Ye; Zheng, Guodong; Zhuang, Xuliang; Zhuang, Guoqiang; Fortin, Danielle
2018-04-06
Mud volcanoes (MVs) emit globally significant quantities of methane into the atmosphere, however, methane cycling in such environments is not yet fully understood, as the roles of microbes and their associated biogeochemical processes have been largely overlooked. Here, we used data from high-throughput sequencing of microbial 16S rRNA gene amplicons from six MVs in the Junggar Basin in northwest China to quantify patterns of diversity and characterize the community structure of archaea and bacteria. We found anaerobic methanotrophs and diverse sulfate- and iron-reducing microbes in all of the samples, and the diversity of both archaeal and bacterial communities was strongly linked to the concentrations of sulfate, iron and nitrate, which could act as electron acceptors in anaerobic oxidation of methane (AOM). The impacts of sulfate/iron/nitrate on AOM in the MVs were verified by microcosm experiments. Further, two representative MVs were selected to explore the microbial interactions based on phylogenetic molecular ecological networks. The sites showed distinct network structures, key species and microbial interactions, with more complex and numerous linkages between methane-cycling microbes and their partners being observed in the iron/sulfate-rich MV. These findings suggest that electron acceptors are important factors driving the structure of microbial communities in these methane-rich environments. © 2018 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.
Detecting communities in large networks
NASA Astrophysics Data System (ADS)
Capocci, A.; Servedio, V. D. P.; Caldarelli, G.; Colaiori, F.
2005-07-01
We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and link orientation. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable for the analysis of social and information networks. We test the algorithm on a large-scale data-set from a psychological experiment of word association. In this case, it proves to be successful both in clustering words, and in uncovering mental association patterns.
Spatial and successional dynamics of microbial biofilm communities in a grassland stream ecosystem
Veach, Allison M.; Stegen, James C.; Brown, Shawn P.; ...
2016-09-06
Biofilms represent a metabolically active and structurally complex component of freshwater ecosystems. Ephemeral prairie streams are hydrologically harsh and prone to frequent perturbation. Elucidating both functional and structural community changes over time within prairie streams provides a general understanding of microbial responses to environmental disturbance. In this study, we examined microbial succession of biofilm communities at three sites in a third-order stream at Konza Prairie over a 2- to 64-day period. Microbial abundance (bacterial abundance, chlorophyll a concentrations) increased and never plateaued during the experiment. Net primary productivity (net balance of oxygen consumption and production) of the developing biofilms didmore » not differ statistically from zero until 64 days suggesting a balance of the use of autochthonous and allochthonous energy sources until late succession. Bacterial communities (MiSeq analyses of the V4 region of 16S rRNA) established quickly. Bacterial richness, diversity and evenness were high after 2 days and increased over time. Several dominant bacterial phyla (Beta-, Alphaproteobacteria, Bacteroidetes, Gemmatimonadetes, Acidobacteria, Chloroflexi) and genera ( Luteolibacter, Flavobacterium, Gemmatimonas, Hydrogenophaga) differed in relative abundance over space and time. Bacterial community composition differed across both space and successional time. Pairwise comparisons of phylogenetic turnover in bacterial community composition indicated that early-stage succession (≤16 days) was driven by stochastic processes, whereas later stages were driven by deterministic selection regardless of site. Finally, our data suggest that microbial biofilms predictably develop both functionally and structurally indicating distinct successional trajectories of bacterial communities in this ecosystem.« less
Spatial and successional dynamics of microbial biofilm communities in a grassland stream ecosystem
DOE Office of Scientific and Technical Information (OSTI.GOV)
Veach, Allison M.; Stegen, James C.; Brown, Shawn P.
Biofilms represent a metabolically active and structurally complex component of freshwater ecosystems. Ephemeral prairie streams are hydrologically harsh and prone to frequent perturbation. Elucidating both functional and structural community changes over time within prairie streams provides a general understanding of microbial responses to environmental disturbance. In this study, we examined microbial succession of biofilm communities at three sites in a third-order stream at Konza Prairie over a 2- to 64-day period. Microbial abundance (bacterial abundance, chlorophyll a concentrations) increased and never plateaued during the experiment. Net primary productivity (net balance of oxygen consumption and production) of the developing biofilms didmore » not differ statistically from zero until 64 days suggesting a balance of the use of autochthonous and allochthonous energy sources until late succession. Bacterial communities (MiSeq analyses of the V4 region of 16S rRNA) established quickly. Bacterial richness, diversity and evenness were high after 2 days and increased over time. Several dominant bacterial phyla (Beta-, Alphaproteobacteria, Bacteroidetes, Gemmatimonadetes, Acidobacteria, Chloroflexi) and genera ( Luteolibacter, Flavobacterium, Gemmatimonas, Hydrogenophaga) differed in relative abundance over space and time. Bacterial community composition differed across both space and successional time. Pairwise comparisons of phylogenetic turnover in bacterial community composition indicated that early-stage succession (≤16 days) was driven by stochastic processes, whereas later stages were driven by deterministic selection regardless of site. Finally, our data suggest that microbial biofilms predictably develop both functionally and structurally indicating distinct successional trajectories of bacterial communities in this ecosystem.« less
The Influence of Coral Reef Benthic Condition on Associated Fish Assemblages
Chong-Seng, Karen M.; Mannering, Thomas D.; Pratchett, Morgan S.; Bellwood, David R.; Graham, Nicholas A. J.
2012-01-01
Accumulative disturbances can erode a coral reef’s resilience, often leading to replacement of scleractinian corals by macroalgae or other non-coral organisms. These degraded reef systems have been mostly described based on changes in the composition of the reef benthos, and there is little understanding of how such changes are influenced by, and in turn influence, other components of the reef ecosystem. This study investigated the spatial variation in benthic communities on fringing reefs around the inner Seychelles islands. Specifically, relationships between benthic composition and the underlying substrata, as well as the associated fish assemblages were assessed. High variability in benthic composition was found among reefs, with a gradient from high coral cover (up to 58%) and high structural complexity to high macroalgae cover (up to 95%) and low structural complexity at the extremes. This gradient was associated with declining species richness of fishes, reduced diversity of fish functional groups, and lower abundance of corallivorous fishes. There were no reciprocal increases in herbivorous fish abundances, and relationships with other fish functional groups and total fish abundance were weak. Reefs grouping at the extremes of complex coral habitats or low-complexity macroalgal habitats displayed markedly different fish communities, with only two species of benthic invertebrate feeding fishes in greater abundance in the macroalgal habitat. These results have negative implications for the continuation of many coral reef ecosystem processes and services if more reefs shift to extreme degraded conditions dominated by macroalgae. PMID:22870294
The influence of coral reef benthic condition on associated fish assemblages.
Chong-Seng, Karen M; Mannering, Thomas D; Pratchett, Morgan S; Bellwood, David R; Graham, Nicholas A J
2012-01-01
Accumulative disturbances can erode a coral reef's resilience, often leading to replacement of scleractinian corals by macroalgae or other non-coral organisms. These degraded reef systems have been mostly described based on changes in the composition of the reef benthos, and there is little understanding of how such changes are influenced by, and in turn influence, other components of the reef ecosystem. This study investigated the spatial variation in benthic communities on fringing reefs around the inner Seychelles islands. Specifically, relationships between benthic composition and the underlying substrata, as well as the associated fish assemblages were assessed. High variability in benthic composition was found among reefs, with a gradient from high coral cover (up to 58%) and high structural complexity to high macroalgae cover (up to 95%) and low structural complexity at the extremes. This gradient was associated with declining species richness of fishes, reduced diversity of fish functional groups, and lower abundance of corallivorous fishes. There were no reciprocal increases in herbivorous fish abundances, and relationships with other fish functional groups and total fish abundance were weak. Reefs grouping at the extremes of complex coral habitats or low-complexity macroalgal habitats displayed markedly different fish communities, with only two species of benthic invertebrate feeding fishes in greater abundance in the macroalgal habitat. These results have negative implications for the continuation of many coral reef ecosystem processes and services if more reefs shift to extreme degraded conditions dominated by macroalgae.
Compartments in a marine food web associated with phylogeny, body mass, and habitat structure.
Rezende, Enrico L; Albert, Eva M; Fortuna, Miguel A; Bascompte, Jordi
2009-08-01
A long-standing question in community ecology is whether food webs are organized in compartments, where species within the same compartment interact frequently among themselves, but show fewer interactions with species from other compartments. Finding evidence for this community organization is important since compartmentalization may strongly affect food web robustness to perturbation. However, few studies have found unequivocal evidence of compartments, and none has quantified the suite of mechanisms generating such a structure. Here, we combine computational tools from the physics of complex networks with phylogenetic statistical methods to show that a large marine food web is organized in compartments, and that body size, phylogeny, and spatial structure are jointly associated with such a compartmentalized structure. Sharks account for the majority of predatory interactions within their compartments. Phylogenetically closely related shark species tend to occupy different compartments and have divergent trophic levels, suggesting that competition may play an important role structuring some of these compartments. Current overfishing of sharks has the potential to change the structural properties, which might eventually affect the stability of the food web.
Bletz, Molly C.; Archer, Holly; Harris, Reid N.; McKenzie, Valerie J.; Rabemananjara, Falitiana C. E.; Rakotoarison, Andolalao; Vences, Miguel
2017-01-01
Host-associated microbiotas of vertebrates are diverse and complex communities that contribute to host health. In particular, for amphibians, cutaneous microbial communities likely play a significant role in pathogen defense; however, our ecological understanding of these communities is still in its infancy. Here, we take advantage of the fully endemic and locally species-rich amphibian fauna of Madagascar to investigate the factors structuring amphibian skin microbiota on a large scale. Using amplicon-based sequencing, we evaluate how multiple host species traits and site factors affect host bacterial diversity and community structure. Madagascar is home to over 400 native frog species, all of which are endemic to the island; more than 100 different species are known to occur in sympatry within multiple rainforest sites. We intensively sampled frog skin bacterial communities, from over 800 amphibians from 89 species across 30 sites in Madagascar during three field visits, and found that skin bacterial communities differed strongly from those of the surrounding environment. Richness of bacterial operational taxonomic units (OTUs) and phylogenetic diversity differed among host ecomorphs, with arboreal frogs exhibiting lower richness and diversity than terrestrial and aquatic frogs. Host ecomorphology was the strongest factor influencing microbial community structure, with host phylogeny and site parameters (latitude and elevation) explaining less but significant portions of the observed variation. Correlation analysis and topological congruency analyses revealed little to no phylosymbiosis for amphibian skin microbiota. Despite the observed geographic variation and low phylosymbiosis, we found particular OTUs that were differentially abundant between particular ecomorphs. For example, the genus Pigmentiphaga (Alcaligenaceae) was significantly enriched on arboreal frogs, Methylotenera (Methylophilaceae) was enriched on aquatic frogs, and Agrobacterium (Rhizobiaceae) was enriched on terrestrial frogs. The presence of shared bacterial OTUs across geographic regions for selected host genera suggests the presence of core microbial communities which in Madagascar, might be driven more strongly by a species’ preference for specific microhabitats than by the physical, physiological or biochemical properties of their skin. These results corroborate that both host and environmental factors are driving community assembly of amphibian cutaneous microbial communities, and provide an improved foundation for elucidating their role in disease resistance. PMID:28861051
Visibility graph analysis on quarterly macroeconomic series of China based on complex network theory
NASA Astrophysics Data System (ADS)
Wang, Na; Li, Dong; Wang, Qiwen
2012-12-01
The visibility graph approach and complex network theory provide a new insight into time series analysis. The inheritance of the visibility graph from the original time series was further explored in the paper. We found that degree distributions of visibility graphs extracted from Pseudo Brownian Motion series obtained by the Frequency Domain algorithm exhibit exponential behaviors, in which the exponential exponent is a binomial function of the Hurst index inherited in the time series. Our simulations presented that the quantitative relations between the Hurst indexes and the exponents of degree distribution function are different for different series and the visibility graph inherits some important features of the original time series. Further, we convert some quarterly macroeconomic series including the growth rates of value-added of three industry series and the growth rates of Gross Domestic Product series of China to graphs by the visibility algorithm and explore the topological properties of graphs associated from the four macroeconomic series, namely, the degree distribution and correlations, the clustering coefficient, the average path length, and community structure. Based on complex network analysis we find degree distributions of associated networks from the growth rates of value-added of three industry series are almost exponential and the degree distributions of associated networks from the growth rates of GDP series are scale free. We also discussed the assortativity and disassortativity of the four associated networks as they are related to the evolutionary process of the original macroeconomic series. All the constructed networks have “small-world” features. The community structures of associated networks suggest dynamic changes of the original macroeconomic series. We also detected the relationship among government policy changes, community structures of associated networks and macroeconomic dynamics. We find great influences of government policies in China on the changes of dynamics of GDP and the three industries adjustment. The work in our paper provides a new way to understand the dynamics of economic development.
Coastal Bacterioplankton Community Dynamics in Response to a Natural Disturbance
Rappé, Michael S.
2013-01-01
In order to characterize how disturbances to microbial communities are propagated over temporal and spatial scales in aquatic environments, the dynamics of bacterial assemblages throughout a subtropical coastal embayment were investigated via SSU rRNA gene analyses over an 8-month period, which encompassed a large storm event. During non-perturbed conditions, sampling sites clustered into three groups based on their microbial community composition: an offshore oceanic group, a freshwater group, and a distinct and persistent coastal group. Significant differences in measured environmental parameters or in the bacterial community due to the storm event were found only within the coastal cluster of sampling sites, and only at 5 of 12 locations; three of these sites showed a significant response in both environmental and bacterial community characteristics. These responses were most pronounced at sites close to the shoreline. During the storm event, otherwise common bacterioplankton community members such as marine Synechococcus sp. and members of the SAR11 clade of Alphaproteobacteria decreased in relative abundance in the affected coastal zone, whereas several lineages of Gammaproteobacteria, Betaproteobacteria, and members of the Roseobacter clade of Alphaproteobacteria increased. The complex spatial patterns in both environmental conditions and microbial community structure related to freshwater runoff and wind convection during the perturbation event leads us to conclude that spatial heterogeneity was an important factor influencing both the dynamics and the resistance of the bacterioplankton communities to disturbances throughout this complex subtropical coastal system. This heterogeneity may play a role in facilitating a rapid rebound of regions harboring distinctly coastal bacterioplankton communities to their pre-disturbed taxonomic composition. PMID:23409156
NASA Astrophysics Data System (ADS)
Dobrovol'skaya, T. G.; Khusnetdinova, K. A.
2017-11-01
The dynamics of population density and taxonomic structure of epiphytic bacterial communities on the leaves and roots of potatoes, carrots, and beets have been studied. Significant changes take place in the ontogenesis of these vegetables with substitution of hydrolytic bacteria for eccrisotrophic bacteria feeding on products of plant exosmosis. The frequency of domination of representatives of different taxa of epiphytic bacteria on the studied plants has been determined for the entire period of their growth. Bacteria of different genera have been isolated from the aboveground and underground organs of vegetables; their functions are discussed. It is shown that the taxonomic structure of bacterial communities in the soil under studied plants is not subjected to considerable changes and is characterized by the domination of typical soil bacteria— Arthrobacter and bacilli—with the appearance of Rhodococcus as a codominant at the end of the season (before harvesting).
Scientific Visualization to Study Flux Transfer Events at the Community Coordinated Modeling Center
NASA Technical Reports Server (NTRS)
Rastatter, Lutz; Kuznetsova, Maria M.; Sibeck, David G.; Berrios, David H.
2011-01-01
In this paper we present results of modeling of reconnection at the dayside magnetopause with subsequent development of flux transfer event signatures. The tools used include new methods that have been added to the suite of visualization methods that are used at the Community Coordinated Modeling Center (CCMC). Flux transfer events result from localized reconnection that connect magnetosheath magnetic field and plasma with magnetospheric fields and plasma and results in flux rope structures that span the dayside magnetopause. The onset of flux rope formation and the three-dimensional structure of flux ropes are studied as they have been modeled by high-resolution magnetohydrodynamic simulations of the dayside magnetosphere of the Earth. We show that flux transfer events are complex three-dimensional structures that require modern visualization and analysis techniques. Two suites of visualization methods are presented and we demonstrate the usefulness of those methods through the CCMC web site to the general science user.
Communities of solution: partnerships for population health.
Griswold, Kim S; Lesko, Sarah E; Westfall, John M
2013-01-01
Communities of solution (COSs) are the key principle for improving population health. The 1967 Folsom Report explains that the COS concept arose from the recognition that complex political and administrative structures often hinder problem solving by creating barriers to communication and compromise. A 2012 reexamination of the Folsom Report resurrects the idea of the COS and presents 13 grand challenges that define the critical links among community, public health, and primary care and call for ongoing demonstrations of COSs grounded in patient-centered care. In this issue, examples of COSs from around the country demonstrate core principles and propose visions of the future. Essential themes of each COS are the crossing of "jurisdictional boundaries," community-led or -oriented initiatives, measurement of outcomes, and creating durable connections with public health.
RNA-Puzzles: A CASP-like evaluation of RNA three-dimensional structure prediction
Cruz, José Almeida; Blanchet, Marc-Frédérick; Boniecki, Michal; Bujnicki, Janusz M.; Chen, Shi-Jie; Cao, Song; Das, Rhiju; Ding, Feng; Dokholyan, Nikolay V.; Flores, Samuel Coulbourn; Huang, Lili; Lavender, Christopher A.; Lisi, Véronique; Major, François; Mikolajczak, Katarzyna; Patel, Dinshaw J.; Philips, Anna; Puton, Tomasz; Santalucia, John; Sijenyi, Fredrick; Hermann, Thomas; Rother, Kristian; Rother, Magdalena; Serganov, Alexander; Skorupski, Marcin; Soltysinski, Tomasz; Sripakdeevong, Parin; Tuszynska, Irina; Weeks, Kevin M.; Waldsich, Christina; Wildauer, Michael; Leontis, Neocles B.; Westhof, Eric
2012-01-01
We report the results of a first, collective, blind experiment in RNA three-dimensional (3D) structure prediction, encompassing three prediction puzzles. The goals are to assess the leading edge of RNA structure prediction techniques; compare existing methods and tools; and evaluate their relative strengths, weaknesses, and limitations in terms of sequence length and structural complexity. The results should give potential users insight into the suitability of available methods for different applications and facilitate efforts in the RNA structure prediction community in ongoing efforts to improve prediction tools. We also report the creation of an automated evaluation pipeline to facilitate the analysis of future RNA structure prediction exercises. PMID:22361291
NASA Astrophysics Data System (ADS)
Moore, J. K.
2016-02-01
The efficiency of the biological pump is influenced by complex interactions between chemical, biological, and physical processes. The efficiency of export out of surface waters and down through the water column to the deep ocean has been linked to a number of factors including biota community composition, production of mineral ballast components, physical aggregation and disaggregation processes, and ocean oxygen concentrations. I will examine spatial patterns in the export ratio and the efficiency of the biological pump at the global scale using the Community Earth System Model (CESM). There are strong spatial variations in the export efficiency as simulated by the CESM, which are strongly correlated with new nutrient inputs to the euphotic zone and their impacts on phytoplankton community structure. I will compare CESM simulations that include dynamic, variable export ratios driven by the phytoplankton community structure, with simulations that impose a near-constant export ratio to examine the effects of export efficiency on nutrient and surface chlorophyll distributions. The model predicted export ratios will also be compared with recent satellite-based estimates.
Niederdorfer, Robert; Peter, Hannes; Battin, Tom J
2016-10-03
Small-scale hydraulics affects microbial behaviour at the cell level 1 , trophic interactions in marine aggregates 2 and the physical structure and function of stream biofilms 3,4 . However, it remains unclear how hydraulics, predictably changing from small streams to large rivers, impacts the structure and biodiversity of complex microbial communities in these ecosystems. Here, we present experimental evidence unveiling hydraulics as a hitherto poorly recognized control of microbial lifestyle differentiation in fluvial ecosystems. Exposing planktonic source communities from stream and floodplain ecosystems to different hydraulic environments revealed strong selective hydraulic pressures but only minor founder effects on the differentiation of attached biofilms and suspended aggregates and their biodiversity dynamics. Key taxa with a coherent phylogenetic underpinning drove this differentiation. Only a few resident and phylogenetically related taxa formed the backbone of biofilm communities, whereas numerous resident taxa characterized aggregate communities. Our findings unveil fundamental differences between biofilms and aggregates and build the basis for a mechanistic understanding of how hydraulics drives the distribution of microbial diversity along the fluvial continuum 5-7 .
Thrush, Simon F; Hewitt, Judi E; Lohrer, Andrew M; Chiaroni, Luca D
2013-01-01
Interaction between the diversity of local communities and the degree of connectivity between them has the potential to influence local recovery rates and thus profoundly affect community dynamics in the face of the cumulative impacts that occur across regions. Although such complex interactions have been modeled, field experiments in natural ecosystems to investigate the importance of interactions between local and regional processes are rare, especially so in coastal marine seafloor habitats subjected to many types of disturbance. We conducted a defaunation experiment at eight subtidal sites, incorporating manipulation of habitat structure, to test the relative importance of local habitat features and colonist supply in influencing macrobenthic community recovery rate. Our sites varied in community composition, habitat characteristics, and hydrodynamic conditions, and we conducted the experiment in two phases, exposing defaunated plots to colonists during periods of either high or low larval colonist supply. In both phases of the experiment, five months after disturbance, we were able to develop models that explained a large proportion of variation in community recovery rate between sites. Our results emphasize that the connectivity to the regional species pool influences recovery rate, and although local habitat effects were important, the strength of these effects was affected by broader-scale site characteristics and connectivity. Empirical evidence that cross-scale interactions are important in disturbance-recovery dynamics emphasizes the complex dynamics underlying seafloor community responses to cumulative disturbance.
BARTTest: Community-Standard Atmospheric Radiative-Transfer and Retrieval Tests
NASA Astrophysics Data System (ADS)
Harrington, Joseph; Himes, Michael D.; Cubillos, Patricio E.; Blecic, Jasmina; Challener, Ryan C.
2018-01-01
Atmospheric radiative transfer (RT) codes are used both to predict planetary and brown-dwarf spectra and in retrieval algorithms to infer atmospheric chemistry, clouds, and thermal structure from observations. Observational plans, theoretical models, and scientific results depend on the correctness of these calculations. Yet, the calculations are complex and the codes implementing them are often written without modern software-verification techniques. The community needs a suite of test calculations with analytically, numerically, or at least community-verified results. We therefore present the Bayesian Atmospheric Radiative Transfer Test Suite, or BARTTest. BARTTest has four categories of tests: analytically verified RT tests of simple atmospheres (single line in single layer, line blends, saturation, isothermal, multiple line-list combination, etc.), community-verified RT tests of complex atmospheres, synthetic retrieval tests on simulated data with known answers, and community-verified real-data retrieval tests.BARTTest is open-source software intended for community use and further development. It is available at https://github.com/ExOSPORTS/BARTTest. We propose this test suite as a standard for verifying atmospheric RT and retrieval codes, analogous to the Held-Suarez test for general circulation models. This work was supported by NASA Planetary Atmospheres grant NX12AI69G, NASA Astrophysics Data Analysis Program grant NNX13AF38G, and NASA Exoplanets Research Program grant NNX17AB62G.
Chen, Jing; Zhou, Zhichao; Gu, Ji-Dong
2015-02-01
In the present work, both 16S rRNA and pmoA gene-based PCR primers were employed successfully to study the diversity and distribution of n-damo bacteria in the surface and lower layer sediments at the coastal Mai Po wetland. The occurrence of n-damo bacteria in both the surface and subsurface sediments with high diversity was confirmed in this study. Unlike the two other known n-damo communities from coastal areas, the pmoA gene-amplified sequences in the present work clustered not only with some freshwater subclusters but also within three newly erected marine subclusters mostly, indicating the unique niche specificity of n-damo bacteria in this wetland. Results suggested vegetation affected the distribution and community structures of n-damo bacteria in the sediments and n-damo could coexist with sulfate-reducing methanotrophs in the coastal ecosystem. Community structures of the Mai Po n-damo bacteria based on 16S rRNA gene were different from those of either the freshwater or the marine. In contrast, structures of the Mai Po n-damo communities based on pmoA gene grouped with the marine ones and were clearly distinguished from the freshwater ones. The abundance of n-damo bacteria at this wetland was quantified using 16S rRNA gene PCR primers to be 2.65-6.71 × 10(5) copies/g dry sediment. Ammonium and nitrite strongly affected the community structures and distribution of n-damo bacteria in the coastal Mai Po wetland sediments.
Benthic megafaunal community structure of cobalt-rich manganese crusts on Necker Ridge
NASA Astrophysics Data System (ADS)
Morgan, Nicole B.; Cairns, Stephen; Reiswig, Henry; Baco, Amy R.
2015-10-01
In the North Pacific Ocean, the seamounts of the Hawaiian Archipelago and the Mid-Pacific Mountains are connected by Necker Ridge, a 600 km-long feature spanning a depth range of 1400-4000 m. The Necker Ridge is a part of a large area of the central and western Pacific under consideration for cobalt-rich manganese crust mining. We describe the fauna and community structure of the previously unsampled Necker Ridge based on explorations with the submersible Pisces IV. On five pinnacles and a portion of the Ridge ranging from 1400 to 2000 m deep, 27 transects were recorded using HD video, and voucher specimens were collected to aid in species identification. The video was analyzed to identify and count the megafauna found on each transect and to characterize the substrate. Diversity increased from south to north along the feature. There was a significant difference in community structure between southern and northern pinnacles, with southern pinnacles dominated by crinoids of the Family Charitometridae and northern pinnacles dominated by octocorals, especially the Families Isididae and Chrysogorgiidae. DistLM demonstrated a correlation between community structure on the pinnacles and at least six environmental variables, including latitude, sediment cover, and oxygen concentration, but not including depth. The discontinuous and patchy nature of these distinct megafaunal communities highlights growing evidence that cobalt-rich seamounts are highly heterogeneous habitats, and that managing seamounts may require more complex regulations than treating them as a single ecological unit. These results suggest that extensive community analysis should occur at a given site to determine management priority areas, prior to consideration of that site for exploitation of natural resources.
Revealing and analyzing networks of environmental systems
NASA Astrophysics Data System (ADS)
Eveillard, D.; Bittner, L.; Chaffron, S.; Guidi, L.; Raes, J.; Karsenti, E.; Bowler, C.; Gorsky, G.
2015-12-01
Understanding the interactions between microbial communities and their environment well enough to be able to predict diversity on the basis of physicochemical parameters is a fundamental pursuit of microbial ecology that still eludes us. However, modeling microbial communities is a complicated task, because (i) communities are complex, (ii) most are described qualitatively, and (iii) quantitative understanding of the way communities interacts with their surroundings remains incomplete. Within this seminar, we will illustrate two complementary approaches that aim to overcome these points in different manners. First, we will present a network analysis that focus on the biological carbon pump in the global ocean. The biological carbon pump is the process by which photosynthesis transforms CO2 to organic carbon sinking to the deep-ocean as particles where it is sequestered. While the intensity of the pump correlate to plankton community composition, the underlying ecosystem structure and interactions driving this process remain largely uncharacterized Here we use environmental and metagenomic data gathered during the Tara Oceans expedition to improve understanding of these drivers. We show that specific plankton communities correlate with carbon export and highlight unexpected and overlooked taxa such as Radiolaria, alveolate parasites and bacterial pathogens, as well as Synechococcus and their phages, as key players in the biological pump. Additionally, we show that the abundances of just a few bacterial and viral genes predict most of the global ocean carbon export's variability. Together these findings help elucidate ecosystem drivers of the biological carbon pump and present a case study for scaling from genes-to-ecosystems. Second, we will show preliminary results on a probabilistic modeling that predicts microbial community structure across observed physicochemical data, from a putative network and partial quantitative knowledge. This modeling shows that, despite distinct quantitative environmental perturbations, the constraints on community structure could remain stable.
Dias, Armando Cavalcante Franco; Taketani, Rodrigo Gouveia; Andreote, Fernando Dini; Luvizotto, Danice Mazzer; da Silva, João Luis; Nascimento, Rosely dos Santos; de Melo, Itamar Soares
2012-01-01
Mangrove forests encompass a group of trees species that inhabit the intertidal zones, where soil is characterized by the high salinity and low availability of oxygen. The phyllosphere of these trees represent the habitat provided on the aboveground parts of plants, supporting in a global scale, a large and complex microbial community. The structure of phyllosphere communities reflects immigration, survival and growth of microbial colonizers, which is influenced by numerous environmental factors in addition to leaf physical and chemical properties. Here, a combination of culture-base methods with PCR-DGGE was applied to test whether local or plant specific factors shape the bacterial community of the phyllosphere from three plant species (Avicenia shaueriana, Laguncularia racemosa and Rhizophora mangle), found in two mangroves. The number of bacteria in the phyllosphere of these plants varied between 3.62 x 104 in A. schaeriana and 6.26 x 103 in R. mangle. The results obtained by PCR-DGGE and isolation approaches were congruent and demonstrated that each plant species harbor specific bacterial communities in their leaves surfaces. Moreover, the ordination of environmental factors (mangrove and plant species), by redundancy analysis (RDA), also indicated that the selection exerted by plant species is higher than mangrove location on bacterial communities at phyllosphere. PMID:24031877
2017-01-01
The authors use four criteria to examine a novel community detection algorithm: (a) effectiveness in terms of producing high values of normalized mutual information (NMI) and modularity, using well-known social networks for testing; (b) examination, meaning the ability to examine mitigating resolution limit problems using NMI values and synthetic networks; (c) correctness, meaning the ability to identify useful community structure results in terms of NMI values and Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks; and (d) scalability, or the ability to produce comparable modularity values with fast execution times when working with large-scale real-world networks. In addition to describing a simple hierarchical arc-merging (HAM) algorithm that uses network topology information, we introduce rule-based arc-merging strategies for identifying community structures. Five well-studied social network datasets and eight sets of LFR benchmark networks were employed to validate the correctness of a ground-truth community, eight large-scale real-world complex networks were used to measure its efficiency, and two synthetic networks were used to determine its susceptibility to two resolution limit problems. Our experimental results indicate that the proposed HAM algorithm exhibited satisfactory performance efficiency, and that HAM-identified and ground-truth communities were comparable in terms of social and LFR benchmark networks, while mitigating resolution limit problems. PMID:29121100
Dias, Armando Cavalcante Franco; Taketani, Rodrigo Gouveia; Andreote, Fernando Dini; Luvizotto, Danice Mazzer; da Silva, João Luis; Nascimento, Rosely Dos Santos; de Melo, Itamar Soares
2012-04-01
Mangrove forests encompass a group of trees species that inhabit the intertidal zones, where soil is characterized by the high salinity and low availability of oxygen. The phyllosphere of these trees represent the habitat provided on the aboveground parts of plants, supporting in a global scale, a large and complex microbial community. The structure of phyllosphere communities reflects immigration, survival and growth of microbial colonizers, which is influenced by numerous environmental factors in addition to leaf physical and chemical properties. Here, a combination of culture-base methods with PCR-DGGE was applied to test whether local or plant specific factors shape the bacterial community of the phyllosphere from three plant species (Avicenia shaueriana, Laguncularia racemosa and Rhizophora mangle), found in two mangroves. The number of bacteria in the phyllosphere of these plants varied between 3.62 x 10(4) in A. schaeriana and 6.26 x 10(3) in R. mangle. The results obtained by PCR-DGGE and isolation approaches were congruent and demonstrated that each plant species harbor specific bacterial communities in their leaves surfaces. Moreover, the ordination of environmental factors (mangrove and plant species), by redundancy analysis (RDA), also indicated that the selection exerted by plant species is higher than mangrove location on bacterial communities at phyllosphere.
Brown, B.L.; Swan, C.M.; Auerbach, D.A.; Campbell, Grant E.H.; Hitt, N.P.; Maloney, K.O.; Patrick, C.
2011-01-01
Explaining the mechanisms underlying patterns of species diversity and composition in riverine networks is challenging. Historically, community ecologists have conceived of communities as largely isolated entities and have focused on local environmental factors and interspecific interactions as the major forces determining species composition. However, stream ecologists have long embraced a multiscale approach to studying riverine ecosystems and have studied both local factors and larger-scale regional factors, such as dispersal and disturbance. River networks exhibit a dendritic spatial structure that can constrain aquatic organisms when their dispersal is influenced by or confined to the river network. We contend that the principles of metacommunity theory would help stream ecologists to understand how the complex spatial structure of river networks mediates the relative influences of local and regional control on species composition. From a basic ecological perspective, the concept is attractive because new evidence suggests that the importance of regional processes (dispersal) depends on spatial structure of habitat and on connection to the regional species pool. The role of local factors relative to regional factors will vary with spatial position in a river network. From an applied perspective, the long-standing view in ecology that local community composition is an indicator of habitat quality may not be uniformly applicable across a river network, but the strength of such bioassessment approaches probably will depend on spatial position in the network. The principles of metacommunity theory are broadly applicable across taxa and systems but seem of particular consequence to stream ecology given the unique spatial structure of riverine systems. By explicitly embracing processes at multiple spatial scales, metacommunity theory provides a foundation on which to build a richer understanding of stream communities.
Broadhurst, Melanie; Orme, C David L
2014-08-01
The addition of man-made structures to the marine environment is known to increase the physical complexity of the seafloor, which can influence benthic species community patterns and habitat structure. However, knowledge of how deployed tidal energy device structures influence benthic communities is currently lacking. Here we examined species biodiversity, composition and habitat type surrounding a tidal energy device within the European Marine Energy Centre test site, Orkney. Commercial fishing and towed video camera techniques were used over three temporal periods, from 2009 to 2010. Our results showed increased species biodiversity and compositional differences within the device site, compared to a control site. Both sites largely comprised of crustacean species, omnivore or predatory feeding regimes and marine tide-swept EUNIS habitat types, which varied over the time. We conclude that the device could act as a localised artificial reef structure, but that further in-depth investigations are required. Copyright © 2014 Elsevier Ltd. All rights reserved.
Grassroots Participation, Peer Education, and HIV Prevention by Sex Workers in South Africa
Campbell, Catherine; Mzaidume, Zodwa
2001-01-01
Objectives. This microqualitative case study of a community-based peer education program led by sex workers at a South African mine examined the role of grassroots participation in sexual health promotion. Methods. The study involved in-depth interviews with 30 members of the target community. The interviews were analyzed in terms of social capital, empowerment, and identity. Results. The study yielded a detailed analysis of the way in which community dynamics have shaped the peer education program's development in a deprived, violent community where existing norms and networks are inconsistent with ideal criteria for participatory health promotion. Conclusions. Much remains to be learned about the complexities of translating theoretically and politically vital notions of “community participation” into practice among hard-to-reach groups. The fabric of local community life is shaped by nonlocal structural conditions of poverty and sexual inequality in ways that challenge those seeking to theorize the role of social capital in community development in general and in sexual health promotion in particular. PMID:11726380
Defining dysbiosis and its influence on host immunity and disease
Petersen, Charisse; Round, June L
2014-01-01
Mammalian immune system development depends on instruction from resident commensal microorganisms. Diseases associated with abnormal immune responses towards environmental and self antigens have been rapidly increasing over the last 50 years. These diseases include inflammatory bowel disease (IBD), multiple sclerosis (MS), type I diabetes (T1D), allergies and asthma. The observation that people with immune mediated diseases house a different microbial community when compared to healthy individuals suggests that pathogenesis arises from improper training of the immune system by the microbiota. However, with hundreds of different microorganisms on our bodies it is hard to know which of these contribute to health and more importantly how? Microbiologists studying pathogenic organisms have long adhered to Koch's postulates to directly relate a certain disease to a specific microbe, raising the question of whether this might be true of commensal–host relationships as well. Emerging evidence supports that rather than one or two dominant organisms inducing host health, the composition of the entire community of microbial residents influences a balanced immune response. Thus, perturbations to the structure of complex commensal communities (referred to as dysbiosis) can lead to deficient education of the host immune system and subsequent development of immune mediated diseases. Here we will overview the literature that describes the causes of dysbiosis and the mechanisms evolved by the host to prevent these changes to community structure. Building off these studies, we will categorize the different types of dysbiosis and define how collections of microorganisms can influence the host response. This research has broad implications for future therapies that go beyond the introduction of a single organism to induce health. We propose that identifying mechanisms to re-establish a healthy complex microbiota after dysbiosis has occurred, a process we will refer to as rebiosis, will be fundamental to treating complex immune diseases. PMID:24798552
Relating geomorphic change and grazing to avian communities in riparian forests
Scott, M.L.; Skagen, S.K.; Merligliano, M.F.
2003-01-01
Avian conservation in riparian or bottomland forests requires an understanding of the physical and biotic factors that sustain the structural complexity of riparian vegetation. Riparian forests of western North America are dependent upon flow-related geomorphic processes necessary for establishment of new cottonwood and willow patches. In June 1995, we examined how fluvial geomorphic processes and long-term grazing influence the structural complexity of riparian vegetation and the abundance and diversity of breeding birds along the upper Missouri River in central Montana, a large, flow-regulated, and geomorphically constrained reach. Use by breeding birds was linked to fluvial geomorphic processes that influence the structure of these patches. Species richness and bird diversity increased with increasing structural complexity of vegetation (F1,32 = 75.49, p < 0.0001; F1,32 = 79.76, p < 0.0001, respectively). Bird species composition was significantly correlated with vegetation strata diversity (rs,33 = 0.98, p < 0.0001). Bird abundance in canopy and tall-shrub foraging guilds increased significantly with increasing tree cover and tall-shrub cover (F1,22 = 34.68, p < 0.0001; F1,20 = 22.22, p < 0.0001, respectively). Seventeen bird species, including five species of concern (e.g., Red-eyed Vireo [Vireo olivaceus]), were significantly associated (p < 0.10) with structurally complex forest patches, whereas only six bird species were significantly associated with structurally simple forest patches. We related the structural complexity of 34 riparian vegetation patches to geomorphic change, woody vegetation establishment, and grazing history over a 35-year post-dam period (1953–1988). The structural complexity of habitat patches was positively related to recent sediment accretion (t33 = 3.31, p = 0.002) and vegetation establishment (t20.7 = −3.63, p = 0.002) and negatively related to grazing activity (t19.6 = 3.75, p = 0.001). Avian conservation along rivers like the upper Missouri requires maintenance of the geomorphic processes responsible for tree establishment and management of land-use activities in riparian forests.
Bacterial Associates Modify Growth Dynamics of the Dinoflagellate Gymnodinium catenatum
Bolch, Christopher J. S.; Bejoy, Thaila A.; Green, David H.
2017-01-01
Marine phytoplankton cells grow in close association with a complex microbial associate community known to affect the growth, behavior, and physiology of the algal host. The relative scale and importance these effects compared to other major factors governing algal cell growth remain unclear. Using algal-bacteria co-culture models based on the toxic dinoflagellate Gymnodinium catenatum, we tested the hypothesis that associate bacteria exert an independent effect on host algal cell growth. Batch co-cultures of G. catenatum were grown under identical environmental conditions with simplified bacterial communities composed of one-, two-, or three-bacterial associates. Modification of the associate community membership and complexity induced up to four-fold changes in dinoflagellate growth rate, equivalent to the effect of a 5°C change in temperature or an almost six-fold change in light intensity (20–115 moles photons PAR m-2 s-1). Almost three-fold changes in both stationary phase cell concentration and death rate were also observed. Co-culture with Roseobacter sp. DG874 reduced dinoflagellate exponential growth rate and led to a more rapid death rate compared with mixed associate community controls or co-culture with either Marinobacter sp. DG879, Alcanivorax sp. DG881. In contrast, associate bacteria concentration was positively correlated with dinoflagellate cell concentration during the exponential growth phase, indicating growth was limited by supply of dinoflagellate-derived carbon. Bacterial growth increased rapidly at the onset of declining and stationary phases due to either increasing availability of algal-derived carbon induced by nutrient stress and autolysis, or at mid-log phase in Roseobacter co-cultures potentially due to the onset of bacterial-mediated cell lysis. Co-cultures with the three bacterial associates resulted in dinoflagellate and bacterial growth dynamics very similar to more complex mixed bacterial community controls, suggesting that three-way co-cultures are sufficient to model interaction and growth dynamics of more complex communities. This study demonstrates that algal associate bacteria independently modify the growth of the host cell under non-limiting growth conditions and supports the concept that algal–bacterial interactions are an important structuring mechanism in phytoplankton communities. PMID:28469613
From complexity to reality: providing useful frameworks for defining systems of care.
Levison-Johnson, Jody; Wenz-Gross, Melodie
2010-02-01
Because systems of care are not uniform across communities, there is a need to better document the process of system development, define the complexity, and describe the development of the structures, processes, and relationships within communities engaged in system transformation. By doing so, we begin to identify the necessary and sufficient components that, at minimum, move us from usual care within a naturally occurring system to a true system of care. Further, by documenting and measuring the degree to which key components are operating, we may be able to identify the most successful strategies in creating system reform. The theory of change and logic model offer a useful framework for communities to begin the adaptive work necessary to effect true transformation. Using the experience of two system of care communities, this new definition and the utility of a theory of change and logic model framework for defining local system transformation efforts will be discussed. Implications for the field, including the need to further examine the natural progression of systems change and to create quantifiable measures of transformation, will be raised as new challenges for the evolving system of care movement.
Moniz, Marcela de Abreu; Sabóia, Vera Maria; Carmo, Cleber Nascimento do; Hacon, Sandra de Souza
2017-11-01
The aim of this study was to diagnose the priority socio environmental problems and the health risks from the surrounding communities the Petrochemical Complex of Rio de Janeiro. Characterized by a participatory approach, the action research has led to the application of interviews, focal groups, meetings and workshop with social actors of Porto das Caixas and Sambaetiba districts, located in Itaboraí city/RJ from November 2013 to December 2014. A structural analysis of the problems prioritized by the communities (water supply, sewage treatment and risk of transmissible diseases; risk of air pollution and respiratory diseases; absence of public security and risk of violence) sketched out the cause-effect-intervention relationship, on the basis of the Protocol for Assessing Community Excellence in Environmental Health. The process revealed the absence of representativity of the social actors of the studied localities in spaces of decision-making on the environmental issue. Educational actions with professionals and inhabitants that aim to promote the formation of collective movements urge, indispensable to guarantee the rights of mitigation of situations of contamination of air and access to sanitation services and public security and thus of conditions of lower risk to health.
Network Analysis Highlights Complex Interactions between Pathogen, Host and Commensal Microbiota
Boutin, Sébastien; Bernatchez, Louis; Audet, Céline; Derôme, Nicolas
2013-01-01
Interactions between bacteria and their host represent a full continuum from pathogenicity to mutualism. From an evolutionary perspective, host-bacteria relationships are no longer considered a two-component system but rather a complex network. In this study, we focused on the relationship between brook charr (Salvelinus fontinalis) and bacterial communities developing on skin mucus. We hypothesized that stressful conditions such as those occurring in aquaculture production induce shifts in the bacterial community of healthy fish, thus allowing pathogens to cause infections. The results showed that fish skin mucus microbiota taxonomical structure is highly specific, its diversity being partly influenced by the surrounding water bacterial community. Two types of taxonomic co-variation patterns emerged across 121 contrasted communities’ samples: one encompassing four genera well known for their probiotic properties, the other harboring five genera mostly associated with pathogen species. The homeostasis of fish bacterial community was extensively disturbed by induction of physiological stress in that both: 1) the abundance of probiotic-like bacteria decreased after stress exposure; and 2) pathogenic bacteria increased following stress exposure. This study provides further insights regarding the role of mutualistic bacteria as a primary host protection barrier. PMID:24376845
Alignment and integration of complex networks by hypergraph-based spectral clustering
NASA Astrophysics Data System (ADS)
Michoel, Tom; Nachtergaele, Bruno
2012-11-01
Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.
Alignment and integration of complex networks by hypergraph-based spectral clustering.
Michoel, Tom; Nachtergaele, Bruno
2012-11-01
Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.
Textures on Mars: evidences of a biogenic environment
NASA Astrophysics Data System (ADS)
Rizzo, V.; Cantasano, N.
Sediments on Mars could be explained as the result of simple coalescing structures having the ability to produce oriented concretions and more complex forms, as are intertwined filaments of microspherules, laminae and "blueberries", growing from a microscopic scale to a macroscopic one. Of which we have examples in some terrestrial microbial community, especially in regards to cyanobacteria and their organosedimentary products named stromatolites. This study aims to describe the most-often structural features that occur, showing their mutual relations in passing from simple to complex forms. These relationships could explain the genesis and the funny shapes of "blueberries" as the result of two different processes: by an enrolling sheet of microspherules or by an internal growing of minor spherule aggregates.
[Green space vegetation quantity in workshop area of Wuhan Iron and Steel Company].
Chen, Fang; Zhou, Zhixiang; Wang, Pengcheng; Li, Haifang; Zhong, Yingfei
2006-04-01
Aimed at the complex community structure and higher fragmentation of urban green space, and based on the investigation of synusia structure and its coverage, this paper studied the vegetation quantity of ornamental green space in the workshop area of Wuhan Iron and Steel Company, with the help of GIS. The results showed that different life forms of ornamental plants in this area had a greater difference in their single leaf area and leaf area index (LAI), and the LAI was not only depended on single leaf area, but also governed by the shape of tree crown and the intensive degree of branches and leaves. The total vegetation quantity was 1 694.2 hm2, with the average LAI being 7.75, and the vegetation quantity of arbor-shrub-herb and arbor-shrub communities accounted for 79.7% and 92.3% of the total, respectively, reflecting that the green space structure was dominated by arbor species and by arbor-shrub-herb and arbor-shrub community types. Single layer-structured lawn had a less percentage, while the vegetation quantity of herb synusia accounted for 22.9% of the total, suggesting an afforestation characteristic of "making use of every bit of space" in the workshop area. The vegetation quantity of urban ornamental green space depended on the area of green space, its synusia structure, and the LAI and coverage of ornamental plants. In enlarging urban green space, ornamental plant species with high LAI should be selected, and community structure should be improved to have a higher vegetation quantity in urban area. To quantify the vegetation quantity of urban ornamental green space more accurately, synusia should be taken as the unit to measure the LAI of typical species, and the synusia structure and its coverage of different community types should be investigated with the help of remote sensing images and GIS.
Ajemian, Matthew J.; Wetz, Jennifer J.; Shipley-Lozano, Brooke; Shively, J. Dale; Stunz, Gregory W.
2015-01-01
Artificial structures are the dominant complex marine habitat type along the northwestern Gulf of Mexico (GOM) shelf. These habitats can consist of a variety of materials, but in this region are primarily comprised of active and reefed oil and gas platforms. Despite being established for several decades, the fish communities inhabiting these structures remain poorly investigated. Between 2012 and 2013 we assessed fish communities at 15 sites using remotely operated vehicles (ROVs). Fish assemblages were quantified from standing platforms and an array of artificial reef types (Liberty Ships and partially removed or toppled platforms) distributed over the Texas continental shelf. The depth gradient covered by the surveys (30–84 m) and variability in structure density and relief also permitted analyses of the effects of these characteristics on fish richness, diversity, and assemblage composition. ROVs captured a variety of species inhabiting these reefs from large transient piscivores to small herbivorous reef fishes. While structure type and relief were shown to influence species richness and community structure, major trends in species composition were largely explained by the bottom depth where these structures occurred. We observed a shift in fish communities and relatively high diversity at approximately 60 m bottom depth, confirming trends observed in previous studies of standing platforms. This depth was also correlated with some of the largest Red Snapper captured on supplementary vertical longline surveys. Our work indicates that managers of artificial reefing programs (e.g., Rigs-to-Reefs) in the GOM should carefully consider the ambient environmental conditions when designing reef sites. For the Texas continental shelf, reefing materials at a 50–60 m bottom depth can serve a dual purpose of enhancing diving experiences and providing the best potential habitat for relatively large Red Snapper. PMID:25954943
NASA Astrophysics Data System (ADS)
Luek, Andreas; Rasmussen, Joseph B.
2017-04-01
Aquatic invertebrates form the base of the consumer food web in lakes. In coal-mining end-pit lakes, invertebrates are exposed to an environment with potentially challenging physical and chemical features. We hypothesized that the physical and chemical features of end-pit lakes reduce critical littoral habitat and thus reduce invertebrate diversity, thereby limiting the potential for these lakes to be naturalized. We used a multivariate approach using principle component analysis and redundancy analysis to study relationships between invertebrate community structure, habitat features, and water quality in five end-pit lakes and five natural lakes in the Rocky Mountain foothills of west-central Alberta, Canada. Results show a significantly different invertebrate community structure was present in end-pit lakes as compared with reference lakes in the same region, which could be accounted for by water hardness, conductivity, slope of the littoral zone, and phosphorus concentrations. Habitat diversity in end-pit lakes was also limited, cover provided by macrophytes was scarce, and basin slopes were significantly steeper in pit lakes. Although water chemistry is currently the strongest influencing factor on the invertebrate community, physical challenges of habitat homogeneity and steep slopes in the littoral zones were identified as major drivers of invertebrate community structure. The addition of floating wetlands to the littoral zone of existing pit lakes can add habitat complexity without the need for large-scale alterations to basing morphology, while impermeable capping of waste-rock and the inclusion of littoral habitat in the planning process of new pit lakes can improve the success of integrating new pit lakes into the landscape.
[Fleas on small mammals in the surrounding area of Erhai Lake].
Dong, Wen-Ge; Guo, Xian-Guo; Men, Xing-Yuan; Gong, Zheng-Da; Wu, Dian; Zhang, Zheng-Kun; Zhang, Li-Yun
2009-12-01
To investigate the distribution pattern, species diversity and community structure of fleas on small mammals in the surrounding area of Erhai Lake, and the relationship between fleas and their hosts. Different geographical areas surrounding the Erhai Lake in Yunnan were selected as investigated spots. Small mammals were captured with baited cages. The cage-traps were examined and re-baited each morning. All fleas on the hosts were collected and identified. The richness (S), evenness (J'), diversity index (H'), dominance index (C'), total ectoparasite infestation rate (Rpt), total ectoparasite infestation index (Ipt), and constituent ratio (Cr) were used to measure the community structure. Altogether, 3,303 small mammals and 3,243 fleas were collected. From the 21 species of small mammal hosts, 13 species of fleas were identified. In southern area of the Lake, the species richness (21 species of small mammals & 12 species of fleas) was highest among the three selected areas. Seventeen species of small mammals and 8 species of fleas were found in eastern area, and only 13 species of small mammals and 7 species of fleas found in the west. This implied the probable influences of ecological environments on the fleas and their corresponding hosts. The community structure of fleas on small mammals was complex. The species diversity, species composition, community structure and distribution pattern of fleas were simultaneously influenced by the hosts' body surface microenvironment and the macroenvironment (habitat). The fleas are commonly distributed in small mammals in the areas and their communities are related to host species and the habitats.
Luek, Andreas; Rasmussen, Joseph B
2017-04-01
Aquatic invertebrates form the base of the consumer food web in lakes. In coal-mining end-pit lakes, invertebrates are exposed to an environment with potentially challenging physical and chemical features. We hypothesized that the physical and chemical features of end-pit lakes reduce critical littoral habitat and thus reduce invertebrate diversity, thereby limiting the potential for these lakes to be naturalized. We used a multivariate approach using principle component analysis and redundancy analysis to study relationships between invertebrate community structure, habitat features, and water quality in five end-pit lakes and five natural lakes in the Rocky Mountain foothills of west-central Alberta, Canada. Results show a significantly different invertebrate community structure was present in end-pit lakes as compared with reference lakes in the same region, which could be accounted for by water hardness, conductivity, slope of the littoral zone, and phosphorus concentrations. Habitat diversity in end-pit lakes was also limited, cover provided by macrophytes was scarce, and basin slopes were significantly steeper in pit lakes. Although water chemistry is currently the strongest influencing factor on the invertebrate community, physical challenges of habitat homogeneity and steep slopes in the littoral zones were identified as major drivers of invertebrate community structure. The addition of floating wetlands to the littoral zone of existing pit lakes can add habitat complexity without the need for large-scale alterations to basing morphology, while impermeable capping of waste-rock and the inclusion of littoral habitat in the planning process of new pit lakes can improve the success of integrating new pit lakes into the landscape.
Unintended consequences of conservation actions: managing disease in complex ecosystems.
Chauvenet, Aliénor L M; Durant, Sarah M; Hilborn, Ray; Pettorelli, Nathalie
2011-01-01
Infectious diseases are increasingly recognised to be a major threat to biodiversity. Disease management tools such as control of animal movements and vaccination can be used to mitigate the impact and spread of diseases in targeted species. They can reduce the risk of epidemics and in turn the risks of population decline and extinction. However, all species are embedded in communities and interactions between species can be complex, hence increasing the chance of survival of one species can have repercussions on the whole community structure. In this study, we use an example from the Serengeti ecosystem in Tanzania to explore how a vaccination campaign against Canine Distemper Virus (CDV) targeted at conserving the African lion (Panthera leo), could affect the viability of a coexisting threatened species, the cheetah (Acinonyx jubatus). Assuming that CDV plays a role in lion regulation, our results suggest that a vaccination programme, if successful, risks destabilising the simple two-species system considered, as simulations show that vaccination interventions could almost double the probability of extinction of an isolated cheetah population over the next 60 years. This work uses a simple example to illustrate how predictive modelling can be a useful tool in examining the consequence of vaccination interventions on non-target species. It also highlights the importance of carefully considering linkages between human-intervention, species viability and community structure when planning species-based conservation actions.
Predator-prey trophic relationships in response to organic management practices.
Schmidt, Jason M; Barney, Sarah K; Williams, Mark A; Bessin, Ricardo T; Coolong, Timothy W; Harwood, James D
2014-08-01
A broad range of environmental conditions likely regulate predator-prey population dynamics and impact the structure of these communities. Central to understanding the interplay between predator and prey populations and their importance is characterizing the corresponding trophic interactions. Here, we use a well-documented molecular approach to examine the structure of the community of natural enemies preying upon the squash bug, Anasa tristis, a herbivorous cucurbit pest that severely hinders organic squash and pumpkin production in the United States. Primer pairs were designed to examine the effects of organic management practices on the strength of these trophic connections and link this metric to measures of the arthropod predator complex density and diversity within an experimental open-field context. Replicated plots of butternut squash were randomly assigned to three treatments and were sampled throughout a growing season. Row-cover treatments had significant negative effects on squash bug and predator communities. In total, 640 predators were tested for squash bug molecular gut-content, of which 11% were found to have preyed on squash bugs, but predation varied over the season between predator groups (coccinellids, geocorids, nabids, web-building spiders and hunting spiders). Through the linking of molecular gut-content analysis to changes in diversity and abundance, these data delineate the complexity of interaction pathways on a pest that limits the profitability of organic squash production. © 2014 John Wiley & Sons Ltd.
Unintended Consequences of Conservation Actions: Managing Disease in Complex Ecosystems
Chauvenet, Aliénor L. M.; Durant, Sarah M.; Hilborn, Ray; Pettorelli, Nathalie
2011-01-01
Infectious diseases are increasingly recognised to be a major threat to biodiversity. Disease management tools such as control of animal movements and vaccination can be used to mitigate the impact and spread of diseases in targeted species. They can reduce the risk of epidemics and in turn the risks of population decline and extinction. However, all species are embedded in communities and interactions between species can be complex, hence increasing the chance of survival of one species can have repercussions on the whole community structure. In this study, we use an example from the Serengeti ecosystem in Tanzania to explore how a vaccination campaign against Canine Distemper Virus (CDV) targeted at conserving the African lion (Panthera leo), could affect the viability of a coexisting threatened species, the cheetah (Acinonyx jubatus). Assuming that CDV plays a role in lion regulation, our results suggest that a vaccination programme, if successful, risks destabilising the simple two-species system considered, as simulations show that vaccination interventions could almost double the probability of extinction of an isolated cheetah population over the next 60 years. This work uses a simple example to illustrate how predictive modelling can be a useful tool in examining the consequence of vaccination interventions on non-target species. It also highlights the importance of carefully considering linkages between human-intervention, species viability and community structure when planning species-based conservation actions. PMID:22163323
Fish, K; Osborn, A M; Boxall, J B
2017-09-01
High-quality drinking water from treatment works is degraded during transport to customer taps through the Drinking Water Distribution System (DWDS). Interactions occurring at the pipe wall-water interface are central to this degradation and are often dominated by complex microbial biofilms that are not well understood. This study uses novel application of confocal microscopy techniques to quantify the composition of extracellular polymeric substances (EPS) and cells of DWDS biofilms together with concurrent evaluation of the bacterial community. An internationally unique, full-scale, experimental DWDS facility was used to investigate the impact of three different hydraulic patterns upon biofilms and subsequently assess their response to increases in shear stress, linking biofilms to water quality impacts such as discolouration. Greater flow variation during growth was associated with increased cell quantity but was inversely related to EPS-to-cell volume ratios and bacterial diversity. Discolouration was caused and EPS was mobilised during flushing of all conditions. Ultimately, biofilms developed under low-varied flow conditions had lowest amounts of biomass, the greatest EPS volumes per cell and the lowest discolouration response. This research shows that the interactions between hydraulics and biofilm physical and community structures are complex but critical to managing biofilms within ageing DWDS infrastructure to limit water quality degradation and protect public health. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
Hydrolytic microbial communities in terrestrial ecosystems
NASA Astrophysics Data System (ADS)
Manucharova, Natalia; Chernov, Timofey; Kolcova, Ekaterina; Zelezova, Alena; Lukacheva, Euhenia; Zenova, Galina
2014-05-01
Hydrolytic microbial communities in terrestrial ecosystems Manucharova N.A., Chernov T.I., Kolcova E.M., Zelezova A.D., Lukacheva E.G. Lomonosov Moscow State University, Russia Vertical differentiation of terrestrial biogeocenoses is conditioned by the formation of vertical tiers that differ considerably in the composition and structure of microbial communities. All the three tiers, phylloplane, litter and soil, are united by a single flow of organic matter, and are spatially separated successional stages of decomposition of organic substances. Decomposition of organic matter is mainly due to the activity of microorganisms producing enzymes - hydrolase and lyase - which destroy complex organic compounds. Application of molecular biological techniques (FISH) in environmental studies provides a more complete information concerning the taxonomic diversity and potential hydrolytic activity of microbial complexes of terrestrial ecosystems that exist in a wide range of environmental factors (moisture, temperature, redox potential, organic matter). The combination of two molecular biological techniques (FISH and DGGE-analysis of fragments of gene 16S rRNA total amplificate) enables an informative assessment of the differences in the structure of dominant and minor components of hydrolytic complexes formed in different tiers of terrestrial ecosystems. The functional activity of hydrolytic microbial complexes of terrestrial ecosystems is determined by the activity of dominant and minor components, which also have a high gross enzymatic activity. Degradation of biopolymers in the phylloplane is mainly due to the representatives of the Proteobacteria phylogenetic group (classes alpha and beta). In mineral soil horizons, the role of hydrolytic representatives of Firmicutes and Actinobacteria increases. Among the key environmental parameters that determine the functional activity of the hydrolytic (chitinolytic) complex of soil layer (moisture, nutrient supply, successional time), the most significant one is moisture. Moisture levels providing maximum activity of a hydrolytic microbial complex depend on the soil type. Development of a hydrolytic microbial complex occurs in a very wide moisture range - from values close to field capacity to those close to the wilting moisture point. The functional role of mycelial actinobacteria in the metabolism of chitin consists, on the one hand, in active decomposition of this biopolymer, and on the other hand, in the regulation of microbial hydrolytic complex activity through the production of biologically active regulatory metabolites, which occurs in a wide range of environmental parameters (moisture, temperature, organic matter, successional time). Experimental design is applicable to identify in situ optimal values of environmental factors that considerably affect the functional parameters of hydrolytic microbial complexes.
Ferrera, Isabel; Mas, Jordi; Taberna, Elisenda; Sanz, Joan; Sánchez, Olga
2015-01-01
The diversity of the bacterial community developed in different stages of two reverse osmosis (RO) water reclamation demonstration plants designed in a wastewater treatment plant (WWTP) in Tarragona (Spain) was characterized by applying 454-pyrosequencing of the 16S rRNA gene. The plants were fed by secondary treated effluent to a conventional pretreatment train prior to the two-pass RO system. Plants differed in the material used in the filtration process, which was sand in one demonstration plant and Scandinavian schists in the second plant. The results showed the presence of a highly diverse and complex community in the biofilms, mainly composed of members of the Betaproteobacteria and Bacteroidetes in all stages, with the presence of some typical wastewater bacteria, suggesting a feed water origin. Community similarities analyses revealed that samples clustered according to filter type, highlighting the critical influence of the biological supporting medium in biofilm community structure.
Phylogeny, phylogeography, phylobetadiversity and the molecular analysis of biological communities
Emerson, Brent C.; Cicconardi, Francesco; Fanciulli, Pietro P.; Shaw, Peter J. A.
2011-01-01
There has been much recent interest and progress in the characterization of community structure and community assembly processes through the application of phylogenetic methods. To date most focus has been on groups of taxa for which some relevant detail of their ecology is known, for which community composition is reasonably easily quantified and where the temporal scale is such that speciation is not likely to feature. Here, we explore how we might apply a molecular genetic approach to investigate community structure and assembly at broad taxonomic and geographical scales, where we have little knowledge of species ecology, where community composition is not easily quantified, and where speciation is likely to be of some importance. We explore these ideas using the class Collembola as a focal group. Gathering molecular evidence for cryptic diversity suggests that the ubiquity of many species of Collembola across the landscape may belie greater community complexity than would otherwise be assumed. However, this morphologically cryptic species-level diversity poses a challenge for attempts to characterize diversity both within and among local species assemblages. Recent developments in high throughput parallel sequencing technology, combined with mtDNA barcoding, provide an advance that can bring together the fields of phylogenetic and phylogeographic analysis to bear on this problem. Such an approach could be standardized for analyses at any geographical scale for a range of taxonomic groups to quantify the formation and composition of species assemblages. PMID:21768154
Taucher, Jan; Haunost, Mathias; Boxhammer, Tim; Bach, Lennart T.; Algueró-Muñiz, María; Riebesell, Ulf
2017-01-01
Plankton communities play a key role in the marine food web and are expected to be highly sensitive to ongoing environmental change. Oceanic uptake of anthropogenic carbon dioxide (CO2) causes pronounced shifts in marine carbonate chemistry and a decrease in seawater pH. These changes–summarized by the term ocean acidification (OA)–can significantly affect the physiology of planktonic organisms. However, studies on the response of entire plankton communities to OA, which also include indirect effects via food-web interactions, are still relatively rare. Thus, it is presently unclear how OA could affect the functioning of entire ecosystems and biogeochemical element cycles. In this study, we report from a long-term in situ mesocosm experiment, where we investigated the response of natural plankton communities in temperate waters (Gullmarfjord, Sweden) to elevated CO2 concentrations and OA as expected for the end of the century (~760 μatm pCO2). Based on a plankton-imaging approach, we examined size structure, community composition and food web characteristics of the whole plankton assemblage, ranging from picoplankton to mesozooplankton, during an entire winter-to-summer succession. The plankton imaging system revealed pronounced temporal changes in the size structure of the copepod community over the course of the plankton bloom. The observed shift towards smaller individuals resulted in an overall decrease of copepod biomass by 25%, despite increasing numerical abundances. Furthermore, we observed distinct effects of elevated CO2 on biomass and size structure of the entire plankton community. Notably, the biomass of copepods, dominated by Pseudocalanus acuspes, displayed a tendency towards elevated biomass by up to 30–40% under simulated ocean acidification. This effect was significant for certain copepod size classes and was most likely driven by CO2-stimulated responses of primary producers and a complex interplay of trophic interactions that allowed this CO2 effect to propagate up the food web. Such OA-induced shifts in plankton community structure could have far-reaching consequences for food-web interactions, biomass transfer to higher trophic levels and biogeochemical cycling of marine ecosystems. PMID:28178268
Fernandez, Adria L; Sheaffer, Craig C; Wyse, Donald L; Staley, Christopher; Gould, Trevor J; Sadowsky, Michael J
2016-10-01
Agricultural management practices can produce changes in soil microbial populations whose functions are crucial to crop production and may be detectable using high-throughput sequencing of bacterial 16S rRNA. To apply sequencing-derived bacterial community structure data to on-farm decision-making will require a better understanding of the complex associations between soil microbial community structure and soil function. Here 16S rRNA sequencing was used to profile soil bacterial communities following application of cover crops and organic fertilizer treatments in certified organic field cropping systems. Amendment treatments were hairy vetch (Vicia villosa), winter rye (Secale cereale), oilseed radish (Raphanus sativus), buckwheat (Fagopyrum esculentum), beef manure, pelleted poultry manure, Sustane(®) 8-2-4, and a no-amendment control. Enzyme activities, net N mineralization, soil respiration, and soil physicochemical properties including nutrient levels, organic matter (OM) and pH were measured. Relationships between these functional and physicochemical parameters and soil bacterial community structure were assessed using multivariate methods including redundancy analysis, discriminant analysis, and Bayesian inference. Several cover crops and fertilizers affected soil functions including N-acetyl-β-d-glucosaminidase and β-glucosidase activity. Effects, however, were not consistent across locations and sampling timepoints. Correlations were observed among functional parameters and relative abundances of individual bacterial families and phyla. Bayesian analysis inferred no directional relationships between functional activities, bacterial families, and physicochemical parameters. Soil functional profiles were more strongly predicted by location than by treatment, and differences were largely explained by soil physicochemical parameters. Composition of soil bacterial communities was predictive of soil functional profiles. Differences in soil function were better explained using both soil physicochemical test values and bacterial community structure data than using soil tests alone. Pursuing a better understanding of bacterial community composition and how it is affected by farming practices is a promising avenue for increasing our ability to predict the impact of management practices on important soil functions. Copyright © 2016. Published by Elsevier B.V.
Predicting community composition from pairwise interactions
NASA Astrophysics Data System (ADS)
Friedman, Jonathan; Higgins, Logan; Gore, Jeff
The ability to predict the structure of complex, multispecies communities is crucial for understanding the impact of species extinction and invasion on natural communities, as well as for engineering novel, synthetic communities. Communities are often modeled using phenomenological models, such as the classical generalized Lotka-Volterra (gLV) model. While a lot of our intuition comes from such models, their predictive power has rarely been tested experimentally. To directly assess the predictive power of this approach, we constructed synthetic communities comprised of up to 8 soil bacteria. We measured the outcome of competition between all species pairs, and used these measurements to predict the composition of communities composed of more than 2 species. The pairwise competitions resulted in a diverse set of outcomes, including coexistence, exclusion, and bistability, and displayed evidence for both interference and facilitation. Most pair outcomes could be captured by the gLV framework, and the composition of multispecies communities could be predicted for communities composed solely of such pairs. Our results demonstrate the predictive ability and utility of simple phenomenology, which enables accurate predictions in the absence of mechanistic details.
ERIC Educational Resources Information Center
Samier, Eugenie
2015-01-01
The United Arab Emirates (UAE) is a small state transitioning from traditional communities into a modern society. This is a complex process: it involves instilling a national identity over tribal structures; modernising and technologising while retaining Islam; ensuring a high level of security while allowing for a liberal and relatively free…
ERIC Educational Resources Information Center
Chen, Katherine Hoi Ying
2008-01-01
Li Wei (1995) notes that relatively little sociolinguistic work on bilingualism has attempted to analyze and compare the complex relationships between aspects of language choice and code-switching among subgroups of the same community. This study aims to investigate the co-existence of two structurally different Cantonese-English code-switching…
Margaret W. Roberts; Anthony W. D' Amato; Christel C. Kern; Brian J. Palik; Lorenzo Marini
2016-01-01
Concerns about loss of biodiversity and structural complexity in managed forests have recently increased and led to the development of new management strategies focused on restoring or maintaining ecosystem functions while also providing wood outputs. Variable retention harvest (VRH) systems, in which mature overstorey trees are retained in various spatial arrangements...
Friendship Concept and Community Network Structure among Elementary School and University Students.
Hernández-Hernández, Ana María; Viga-de Alva, Dolores; Huerta-Quintanilla, Rodrigo; Canto-Lugo, Efrain; Laviada-Molina, Hugo; Molina-Segui, Fernanda
2016-01-01
We use complex network theory to study the differences between the friendship concepts in elementary school and university students. Four friendship networks were identified from surveys. Three of these networks are from elementary schools; two are located in the rural area of Yucatán and the other is in the urban area of Mérida, Yucatán. We analyzed the structure and the communities of these friendship networks and found significant differences among those at the elementary schools compared with those at the university. In elementary schools, the students make friends mainly in the same classroom, but there are also links among different classrooms because of the presence of siblings and relatives in the schools. These kinds of links (sibling-friend or relative-friend) are called, in this work, "mixed links". The classification of the communities is based on their similarity with the classroom composition. If the community is composed principally of students in different classrooms, the community is classified as heterogeneous. These kinds of communities appear in the elementary school friendship networks mainly because of the presence of relatives and siblings. Once the links between siblings and relatives are removed, the communities resembled the classroom composition. On the other hand, the university students are more selective in choosing friends and therefore, even when they have friends in the same classroom, those communities are quite different to the classroom composition. Also, in the university network, we found heterogeneous communities even when the presence of sibling and relatives is negligible. These differences made up a topological structure quite different at different academic levels. We also found differences in the network characteristics. Once these differences are understood, the topological structure of the friendship network and the communities shaped in an elementary school could be predicted if we know the total number of students and the ties between siblings and relatives. However, at the university, we cannot do the same. This discovery implies that friendship is a dynamic concept that produces several changes in the friendship network structure and the way that people make groups of friends; it provides the opportunity to give analytic support to observational studies. Communities were also studied by gender and we found that when the links among relatives and siblings were removed, the number of communities formed by one gender alone increased. At the university, many communities formed by students of the same gender were also found.
Metamorphosis of a Scleractinian Coral in Response to Microbial Biofilms
Webster, Nicole S.; Smith, Luke D.; Heyward, Andrew J.; Watts, Joy E. M.; Webb, Richard I.; Blackall, Linda L.; Negri, Andrew P.
2004-01-01
Microorganisms have been reported to induce settlement and metamorphosis in a wide range of marine invertebrate species. However, the primary cue reported for metamorphosis of coral larvae is calcareous coralline algae (CCA). Herein we report the community structure of developing coral reef biofilms and the potential role they play in triggering the metamorphosis of a scleractinian coral. Two-week-old biofilms induced metamorphosis in less than 10% of larvae, whereas metamorphosis increased significantly on older biofilms, with a maximum of 41% occurring on 8-week-old microbial films. There was a significant influence of depth in 4- and 8-week biofilms, with greater levels of metamorphosis occurring in response to shallow-water communities. Importantly, larvae were found to settle and metamorphose in response to microbial biofilms lacking CCA from both shallow and deep treatments, indicating that microorganisms not associated with CCA may play a significant role in coral metamorphosis. A polyphasic approach consisting of scanning electron microscopy, fluorescence in situ hybridization (FISH), and denaturing gradient gel electrophoresis (DGGE) revealed that coral reef biofilms were comprised of complex bacterial and microalgal communities which were distinct at each depth and time. Principal-component analysis of FISH data showed that the Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, and Cytophaga-Flavobacterium of Bacteroidetes had the largest influence on overall community composition. A low abundance of Archaea was detected in almost all biofilms, providing the first report of Archaea associated with coral reef biofilms. No differences in the relative densities of each subdivision of Proteobacteria were observed between slides that induced larval metamorphosis and those that did not. Comparative cluster analysis of bacterial DGGE patterns also revealed that there were clear age and depth distinctions in biofilm community structure; however, no difference was detected in banding profiles between biofilms which induced larval metamorphosis and those where no metamorphosis occurred. This investigation demonstrates that complex microbial communities can induce coral metamorphosis in the absence of CCA. PMID:14766608
Yu, Ermeng; Xie, Jun; Wang, Jinlin; Ako, Harry; Wang, Guangjun; Chen, Zhanghe; Liu, Yongfeng
2016-07-01
Bacteria play crucial roles in the combined system of substrate addition and C/N control, which has been demonstrated to improve aquaculture production. However, the complexity of surface-attached bacteria on substrates and suspended bacteria in the water column hamper further application of this system. This study firstly applied this combined system into the culture of grass carp, and then explored the relationship between microbial complexes from surface-attached and suspended bacteria in this system and the production of grass carp. In addition, this study investigated bacterial community structures as affected by four C/N ratios using Illumina sequencing technology. The results demonstrated that the weight gain rate and specific growth rate of grass carp in the CN20 group (C/N ratio 20:1) were the highest (P < 0.05), and dietary supplementation of the microbial complex had positive effects on the growth of grass carp (P < 0.05). Sequencing data revealed that, (1) the proportions of Verrucomicrobiae and Rhodobacter (surface-attached), sediminibacterium (suspended), and emticicia (surface-attached and suspended) were much higher in the CN20 group compared with those in the other groups (P < 0.05); (2) Rhodobacter, Flavobacterium, Acinetobacter, Pseudomonas, Planctomyces, and Cloacibacterium might be important for the microbial colonization on substrates; (3) as the C/N ratio increased, proportions of Hydrogenophaga (surface-attached and suspended), Zoogloea, and Flectobacillus (suspended) increased, but proportions of Bacillus, Clavibacter, and Cellvibro (surface-attached and suspended) decreased. In summary, a combined system of substrate addition and C/N control increased the production of grass carp, and Verrucomicrobiae and Rhodobacter in the surface-attached bacterial community were potential probiotic bacteria that contributed to the enhanced growth of grass carp.
Shi, Y.; Zwolinski, M. D.; Schreiber, M. E.; Bahr, J. M.; Sewell, G. W.; Hickey, W. J.
1999-01-01
This study used phylogenetic probes in hybridization analysis to (i) determine in situ microbial community structures in regions of a shallow sand aquifer that were oxygen depleted and fuel contaminated (FC) or aerobic and noncontaminated (NC) and (ii) examine alterations in microbial community structures resulting from exposure to toluene and/or electron acceptor supplementation (nitrate). The latter objective was addressed by using the NC and FC aquifer materials for anaerobic microcosm studies in which phylogenetic probe analysis was complemented by microbial activity assays. Domain probe analysis of the aquifer samples showed that the communities were predominantly Bacteria; Eucarya and Archaea were not detectable. At the phylum and subclass levels, the FC and NC aquifer material had similar relative abundance distributions of 43 to 65% β- and γ-Proteobacteria (B+G), 31 to 35% α-Proteobacteria (ALF), 15 to 18% sulfate-reducing bacteria, and 5 to 10% high G+C gram positive bacteria. Compared to that of the NC region, the community structure of the FC material differed mainly in an increased abundance of B+G relative to that of ALF. The microcosm communities were like those of the field samples in that they were predominantly Bacteria (83 to 101%) and lacked detectable Archaea but differed in that a small fraction (2 to 8%) of Eucarya was detected regardless of the treatment applied. The latter result was hypothesized to reflect enrichment of anaerobic protozoa. Addition of nitrate and/or toluene stimulated microbial activity in the microcosms, but only supplementation of toluene alone significantly altered community structures. For the NC material, the dominant subclass shifted from B+G to ALF, while in the FC microcosms 55 to 65% of the Bacteria community was no longer identifiable by the phylum or subclass probes used. The latter result suggested that toluene exposure fostered the proliferation of phylotype(s) that were otherwise minor constituents of the FC aquifer community. These studies demonstrated that alterations in aquifer microbial communities resulting from specific anthropogenic perturbances can be inferred from microcosm studies integrating chemical and phylogenetic probe analysis and in the case of hydrocarbon contamination may facilitate the identification of organisms important for in situ biodegradation processes. Further work integrating and coordinating microcosm and field experiments is needed to explore how differences in scale, substrate complexity, and other hydrogeological conditions may affect patterns observed in these systems. PMID:10224013
Farr, Deeonna E; Brandt, Heather M; Comer, Kimberly D; Jackson, Dawnyéa D; Pandya, Kinjal; Friedman, Daniela B; Ureda, John R; Williams, Deloris G; Scott, Dolores B; Green, Wanda; Hébert, James R
2015-09-01
Increasing the participation of Blacks in cancer research is a vital component of a strategy to reduce racial inequities in cancer burden. Community-based participatory research (CBPR) is especially well-suited to advancing our knowledge of factors that influence research participation to ultimately address cancer-related health inequities. A paucity of literature focuses on the role of structural factors limiting participation in cancer research. As part of a larger CBPR project, we used survey data from a statewide cancer needs assessment of a Black faith community to examine the influence of structural factors on attitudes toward research and the contributions of both structural and attitudinal factors on whether individuals participate in research. Regression analyses and non-parametric statistics were conducted on data from 727 adult survey respondents. Structural factors, such as having health insurance coverage, experiencing discrimination during health care encounters, and locale, predicted belief in the benefits, but not the risks, of research participation. Positive attitudes toward research predicted intention to participate in cancer research. Significant differences in structural and attitudinal factors were found between cancer research participants and non-participants; however, directionality is confounded by the cross-sectional survey design and causality cannot be determined. This study points to complex interplay of structural and attitudinal factors on research participation as well as need for additional quantitative examinations of the various types of factors that influence research participation in Black communities.
Feasibility and coexistence of large ecological communities.
Grilli, Jacopo; Adorisio, Matteo; Suweis, Samir; Barabás, György; Banavar, Jayanth R; Allesina, Stefano; Maritan, Amos
2017-02-24
The role of species interactions in controlling the interplay between the stability of ecosystems and their biodiversity is still not well understood. The ability of ecological communities to recover after small perturbations of the species abundances (local asymptotic stability) has been well studied, whereas the likelihood of a community to persist when the conditions change (structural stability) has received much less attention. Our goal is to understand the effects of diversity, interaction strengths and ecological network structure on the volume of parameter space leading to feasible equilibria. We develop a geometrical framework to study the range of conditions necessary for feasible coexistence. We show that feasibility is determined by few quantities describing the interactions, yielding a nontrivial complexity-feasibility relationship. Analysing more than 100 empirical networks, we show that the range of coexistence conditions in mutualistic systems can be analytically predicted. Finally, we characterize the geometric shape of the feasibility domain, thereby identifying the direction of perturbations that are more likely to cause extinctions.
Modeling Global Spatial-Temporal Evolution of Society: Hyperbolic Growth and Historical Cycles
NASA Astrophysics Data System (ADS)
Kurkina, E. S.
2011-09-01
The global historical processes are under consideration; and laws of global evolution of the world community are studied. The world community is considered as a united complex self-developing and self-organizing system. It supposed that the main driving force of social-economical evolution was the positive feedback between the population size and the level of technological development, which was a cause of growth in blow-up regime both of population and of global economic indexes. The study is supported by the results of mathematical modeling founded on a nonlinear heat equation with a source. Every social-economical epoch characterizes by own specific spatial distributed structures. So the global dynamics of world community during the whole history is investigated throughout the prism of the developing of spatial-temporal structures. The model parameters have been chosen so that 1) total population follows stable hyperbolic growth, consistently with the demographic data; 2) the evolution of the World-System goes through 11 stages corresponding to the main historical epochs.
Ouyang, Erming; Lu, Yao; Ouyang, Jiating; Wang, Lele; Wang, Xiaohui
2017-01-01
Gibberellin wastewater cannot be directly discharged without treatment due to its high concentrations of sulfate and organic compounds and strong acidity. Therefore, multi-stage anaerobic bioreactor + micro-aerobic+ anoxic/aeration (A/O) + biological contact oxidation combined processes are used to treat gibberellin wastewater. However, knowledge of the treatment effects of the A/O process and bacterial community structure in the aeration tank reactors of such systems is sparse. Therefore, this study was conducted to investigate the treatment effects and operation of the A/O process on gibberellin wastewater, as well as changes in the bacterial community structure of activated sludge in the aeration tank during treatment. Moreover, removal was examined based on evaluation of effluent after A/O treatment. Although influent chemical oxygen demand (COD), NH3-N and total phosphorus (TP) fluctuated, effluent COD, NH3-N and TP remained stable. Moreover, average COD, NH3-N and TP removal efficiency were 68.41%, 93.67% and 45.82%, respectively, during the A/O process. At the phylum level, Proteobacteria was the dominant phylum in all samples, followed by Chloroflexi, Bacteroidetes and Actinobacteria. Proteobacteria played an important role in the removal of organic matter. Chloroflexi was found to be responsible for the degradation of carbohydrates and Bacteroidetes also had been found to be responsible for the degradation of complex organic matters. Actinobacteria are able to degrade a variety of environmental chemicals. Additionally, Anaerolineaceae_uncultured was the major genus in samples collected on May 25, 2015, while Novosphingobium and Nitrospira were dominant in most samples. Nitrosomonas are regarded as the dominant ammonia-oxidizing bacteria, while Nitrospira are the main nitrite-oxidizing bacteria. Bacterial community structure varied considerably with time, and a partial Mantel test showed a highly significant positive correlation between bacterial community structure and DO. The bacterial community structure was also positively correlated with temperature and SO42-. PMID:29053751
Fish-derived nutrient hotspots shape coral reef benthic communities.
Shantz, Andrew A; Ladd, Mark C; Schrack, Elizabeth; Burkepile, Deron E
2015-12-01
Animal-derived nutrients play an important role in structuring nutrient regimes within and between ecosystems. When animals undergo repetitive, aggregating behavior through time, they can create nutrient hotspots where rates of biogeochemical activity are higher than those found in the surrounding environment. In turn, these hotspots can influence ecosystem processes and community structure. We examined the potential for reef fishes from the family Haemulidae (grunts) to create nutrient hotspots and the potential impact of these hotspots on reef communities. To do so, we tracked the schooling locations of diurnally migrating grunts, which shelter at reef sites during the day but forage off reef each night, and measured the impact of these fish schools on benthic communities. We found that grunt schools showed a high degree of site fidelity, repeatedly returning to the same coral heads. These aggregations created nutrient hotspots around coral heads where nitrogen and phosphorus delivery was roughly 10 and 7 times the respective rates of delivery to structurally similar sites that lacked schools of these fishes. In turn, grazing rates of herbivorous fishes at grunt-derived hotspots were approximately 3 times those of sites where grunts were rare. These differences in nutrient delivery and grazing led to distinct benthic communities with higher cover of crustose coralline algae and less total algal abundance at grunt aggregation sites. Importantly, coral growth was roughly 1.5 times greater at grunt hotspots, likely due to the important nutrient subsidy. Our results suggest that schooling reef fish and their nutrient subsidies play an important role in mediating community structure on coral reefs and that overfishing may have important negative consequences on ecosystem functions. As such, management strategies must consider mesopredatory fishes in addition to current protection often offered to herbivores and top-tier predators. Furthermore, our results suggest that restoration strategies may benefit from focusing on providing structure for aggregating fishes on reefs with low topographic complexity or focusing the restoration of nursery raised corals around existing nutrient hotspots.
Burman, Christopher J; Aphane, Marota; Mtapuri, Oliver; Delobelle, Peter
2015-01-01
The article describes a design journey that culminated in an HIV-Conversant Community Framework that is now being piloted in the Limpopo Province of South Africa. The objective of the initiative is to reduce the aggregate community viral load by building capacity at multiple scales that strengthens peoples' HIV-related navigational skill sets-while simultaneously opening a 'chronic situation' schema. The framework design is based upon a transdisciplinary methodological combination that synthesises ideas and constructs from complexity science and the management sciences as a vehicle through which to re-conceptualise HIV prevention. This resulted in a prototype that included the following constructs: managing HIV-prevention in a complex, adaptive epidemiological landscape; problematising and increasing the scope of the HIV knowledge armamentarium through education that focuses on the viral load and Langerhans cells; disruptive innovation and safe-fail probes followed by the facilitation of path creations and pattern management implementation techniques. These constructs are underpinned by a 'middle-ground' prevention approach which is designed to bridge the prevention 'fault line', enabling a multi-ontology conceptualisation of the challenge to be developed. The article concludes that stepping outside of the 'ordered' epistemological parameters of the existing prevention 'messaging' mind-set towards a more systemic approach that emphasises agency, structure and social practices as a contribution to 'ending AIDS by 2030' is worthy of further attention if communities are to engage more adaptively with the dynamic HIV landscape in South Africa.
Structural complexities in the active layers of organic electronics.
Lee, Stephanie S; Loo, Yueh-Lin
2010-01-01
The field of organic electronics has progressed rapidly in recent years. However, understanding the direct structure-function relationships between the morphology in electrically active layers and the performance of devices composed of these materials has proven difficult. The morphology of active layers in organic electronics is inherently complex, with heterogeneities existing across multiple length scales, from subnanometer to micron and millimeter range. A major challenge still facing the organic electronics community is understanding how the morphology across all of the length scales in active layers collectively determines the device performance of organic electronics. In this review we highlight experiments that have contributed to the elucidation of structure-function relationships in organic electronics and also point to areas in which knowledge of such relationships is still lacking. Such knowledge will lead to the ability to select active materials on the basis of their inherent properties for the fabrication of devices with prespecified characteristics.
The structure of the microbial communities in low-moor and high-moor peat bogs of Tomsk oblast
NASA Astrophysics Data System (ADS)
Dobrovol'skaya, T. G.; Golovchenko, A. V.; Kukharenko, O. S.; Yakushev, A. V.; Semenova, T. A.; Inisheva, L. A.
2012-03-01
The number, structure, and physical state of the microbial communities in high-moor and low-moor peat bogs were compared. Distinct differences in these characteristics were revealed. The microbial biomass in the high-moor peat exceeded that in the low-moor peat by 2-9 times. Fungi predominated in the high-moor peat, whereas bacteria were the dominant microorganisms in the low-moor peat. The micromycetal complexes of the high-moor peat were characterized by a high portion of dark-colored representatives; the complexes of the low-moor peat were dominated by fast-growing fungi. The species of the Penicillum genus were dominant in the high-moor peat; the species of Trichoderma were abundant in the low-moor peat. In the former, the bacteria were distinguished as minor components; in the latter, they predominated in the saprotrophic bacterial complex. In the high-moor peat, the microorganisms were represented by bacilli, while, in the low-moor peat, by cytophages, myxobacteria, and actinobacteria. The different physiological states of the bacteria in the studied objects reflecting the duration of the lag phase and the readiness of the metabolic system to consume different substrates were demonstrated for the first time. The relationships between the trophic characteristics of bacterial habitats and the capacity of the bacteria to consume substrates were established.
Kohout, Petr; Doubková, Pavla; Bahram, Mohammad; Suda, Jan; Tedersoo, Leho; Voříšková, Jana; Sudová, Radka
2015-04-01
Arbuscular mycorrhizal fungi (AMF) represent an important soil microbial group playing a fundamental role in many terrestrial ecosystems. We explored the effects of deterministic (soil characteristics, host plant life stage, neighbouring plant communities) and stochastic processes on AMF colonization, richness and community composition in roots of Knautia arvensis (Dipsacaceae) plants from three serpentine grasslands and adjacent nonserpentine sites. Methodically, the study was based on 454-sequencing of the ITS region of rDNA. In total, we detected 81 molecular taxonomical operational units (MOTUs) belonging to the Glomeromycota. Serpentine character of the site negatively influenced AMF root colonization, similarly as higher Fe concentration. AMF MOTUs richness linearly increased along a pH gradient from 3.5 to 5.8. Contrary, K and Cr soil concentration had a negative influence on AMF MOTUs richness. We also detected a strong relation between neighbouring plant community composition and AMF MOTUs richness. Although spatial distance between the sampled sites (c. 0.3-3 km) contributed to structuring AMF communities in K. arvensis roots, environmental parameters were key factors in this respect. In particular, the composition of AMF communities was shaped by the complex of serpentine conditions, pH and available soil Ni concentration. The composition of AMF communities was also dependent on host plant life stage (vegetative vs. generative). Our study supports the dominance of deterministic factors in structuring AMF communities in heterogeneous environment composed of an edaphic mosaic of serpentine and nonserpentine soils. © 2015 John Wiley & Sons Ltd.
Architectural design influences the diversity and structure of the built environment microbiome
Kembel, Steven W; Jones, Evan; Kline, Jeff; Northcutt, Dale; Stenson, Jason; Womack, Ann M; Bohannan, Brendan JM; Brown, G Z; Green, Jessica L
2012-01-01
Buildings are complex ecosystems that house trillions of microorganisms interacting with each other, with humans and with their environment. Understanding the ecological and evolutionary processes that determine the diversity and composition of the built environment microbiome—the community of microorganisms that live indoors—is important for understanding the relationship between building design, biodiversity and human health. In this study, we used high-throughput sequencing of the bacterial 16S rRNA gene to quantify relationships between building attributes and airborne bacterial communities at a health-care facility. We quantified airborne bacterial community structure and environmental conditions in patient rooms exposed to mechanical or window ventilation and in outdoor air. The phylogenetic diversity of airborne bacterial communities was lower indoors than outdoors, and mechanically ventilated rooms contained less diverse microbial communities than did window-ventilated rooms. Bacterial communities in indoor environments contained many taxa that are absent or rare outdoors, including taxa closely related to potential human pathogens. Building attributes, specifically the source of ventilation air, airflow rates, relative humidity and temperature, were correlated with the diversity and composition of indoor bacterial communities. The relative abundance of bacteria closely related to human pathogens was higher indoors than outdoors, and higher in rooms with lower airflow rates and lower relative humidity. The observed relationship between building design and airborne bacterial diversity suggests that we can manage indoor environments, altering through building design and operation the community of microbial species that potentially colonize the human microbiome during our time indoors. PMID:22278670
Energy Transformations of Soil Organic Matter in a Changing World
NASA Astrophysics Data System (ADS)
Herrmann, A. M.; Coucheney, E.; Grice, S. M.; Ritz, K.; Harris, J.
2011-12-01
The role of soils in governing the terrestrial carbon balance is acknowledged as being important but remains poorly understood within the context of climate change. Soils exchange energy with their surroundings and are therefore open systems thermodynamically, but little is known how energy transformations of decomposition processes are affected by temperature. Soil organic matter and the soil biomass can be conceptualised as analogous to the 'fuel' and 'biological engine' of the earth, respectively, and are pivotal in driving the belowground carbon cycle. Thermodynamic principles of soil organic matter decomposition were evaluated by means of isothermal microcalorimetry (TAM Air, TA Instruments, Sollentuna Sweden: (i) Mineral forest soils from the Flakaliden long-term nitrogen fertilisation experiment (Sweden) were amended with a range of different substrates representing structurally simple to complex, ecologically pertinent organic matter and heat signatures were determined at temperatures between 5 and 25°C. (ii) Thermodynamic and resource-use efficiencies of the biomass were determined in arable soils which received contrasting long-term management regimes with respect to organic matter and nitrogen since 1956. The work showed that (i) structurally labile components have higher activation energy and temperature dependence than structurally more complex organic components. This is, however, in contrast to the thermodynamic argument which suggests the opposite that reactions metabolising structurally complex, aromatic components have higher temperature dependence than reactions metabolising structurally more labile components. (ii) Microbial communities exposed to long-term stress by heavy metal and low pH were less thermodynamic efficient and showed a decrease in resource-use efficiency in comparison with conventional input regimes. Differences in efficiencies were mirrored in both the phenotypic and functional profiles of the communities. We will present our findings illustrating the capacity of isothermal microcalorimetry to evaluate temperature dependencies of soil organic matter decomposition, associated energy transformations and thermodynamic principles in soil ecosystems.
Mosier, Annika C; Justice, Nicholas B; Bowen, Benjamin P; Baran, Richard; Thomas, Brian C; Northen, Trent R; Banfield, Jillian F
2013-03-12
Microorganisms grow under a remarkable range of extreme conditions. Environmental transcriptomic and proteomic studies have highlighted metabolic pathways active in extremophilic communities. However, metabolites directly linked to their physiology are less well defined because metabolomics methods lag behind other omics technologies due to a wide range of experimental complexities often associated with the environmental matrix. We identified key metabolites associated with acidophilic and metal-tolerant microorganisms using stable isotope labeling coupled with untargeted, high-resolution mass spectrometry. We observed >3,500 metabolic features in biofilms growing in pH ~0.9 acid mine drainage solutions containing millimolar concentrations of iron, sulfate, zinc, copper, and arsenic. Stable isotope labeling improved chemical formula prediction by >50% for larger metabolites (>250 atomic mass units), many of which were unrepresented in metabolic databases and may represent novel compounds. Taurine and hydroxyectoine were identified and likely provide protection from osmotic stress in the biofilms. Community genomic, transcriptomic, and proteomic data implicate fungi in taurine metabolism. Leptospirillum group II bacteria decrease production of ectoine and hydroxyectoine as biofilms mature, suggesting that biofilm structure provides some resistance to high metal and proton concentrations. The combination of taurine, ectoine, and hydroxyectoine may also constitute a sulfur, nitrogen, and carbon currency in the communities. Microbial communities are central to many critical global processes and yet remain enigmatic largely due to their complex and distributed metabolic interactions. Metabolomics has the possibility of providing mechanistic insights into the function and ecology of microbial communities. However, our limited knowledge of microbial metabolites, the difficulty of identifying metabolites from complex samples, and the inability to link metabolites directly to community members have proven to be major limitations in developing advances in systems interactions. Here, we show that combining stable-isotope-enabled metabolomics with genomics, transcriptomics, and proteomics can illuminate the ecology of microorganisms at the community scale.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cole, Jessica K.; Hutchison, Janine R.; Renslow, Ryan S.
2014-04-07
Though microbial autotroph-heterotroph interactions influence biogeochemical cycles on a global scale, the diversity and complexity of natural systems and their intractability to in situ environmental manipulation makes elucidation of the principles governing these interactions challenging. Examination of primary succession during phototrophic biofilm assembly provides a robust means by which to elucidate the dynamics of such interactions and determine their influence upon recruitment and maintenance of phylogenetic and functional diversity in microbial communities. We isolated and characterized two unicyanobacterial consortia from the Hot Lake phototrophic mat, quantifying the structural and community composition of their assembling biofilms. The same heterotrophs were retainedmore » in both consortia and included members of Alphaproteobacteria, Gammaproteobacteria, and Bacteroidetes, taxa frequently reported as consorts of microbial photoautotrophs. Cyanobacteria led biofilm assembly, eventually giving way to a late heterotrophic bloom. The consortial biofilms exhibited similar patterns of assembly, with the relative abundances of members of Bacteroidetes and Alphaproteobacteria increasing and members of Gammaproteobacteria decreasing as colonization progressed. Despite similar trends in assembly at higher taxa, the consortia exhibited substantial differences in community structure at the species level. These similar patterns of assembly with divergent community structures suggest that, while similar niches are created by the metabolism of the cyanobacteria, the resultant webs of autotroph-heterotroph and heterotroph-heterotroph interactions driving metabolic exchange are specific to each primary producer. Altogether, our data support these Hot Lake unicyanobacterial consortia as generalizable model systems whose simplicity and tractability permit the deciphering of community assembly principles relevant to natural microbial communities.« less
Influence of plankton community structure on the sinking velocity of marine aggregates
NASA Astrophysics Data System (ADS)
Bach, L. T.; Boxhammer, T.; Larsen, A.; Hildebrandt, N.; Schulz, K. G.; Riebesell, U.
2016-08-01
About 50 Gt of carbon is fixed photosynthetically by surface ocean phytoplankton communities every year. Part of this organic matter is reprocessed within the plankton community to form aggregates which eventually sink and export carbon into the deep ocean. The fraction of organic matter leaving the surface ocean is partly dependent on aggregate sinking velocity which accelerates with increasing aggregate size and density, where the latter is controlled by ballast load and aggregate porosity. In May 2011, we moored nine 25 m deep mesocosms in a Norwegian fjord to assess on a daily basis how plankton community structure affects material properties and sinking velocities of aggregates (Ø 80-400 µm) collected in the mesocosms' sediment traps. We noted that sinking velocity was not necessarily accelerated by opal ballast during diatom blooms, which could be due to relatively high porosity of these rather fresh aggregates. Furthermore, estimated aggregate porosity (Pestimated) decreased as the picoautotroph (0.2-2 µm) fraction of the phytoplankton biomass increased. Thus, picoautotroph-dominated communities may be indicative for food webs promoting a high degree of aggregate repackaging with potential for accelerated sinking. Blooms of the coccolithophore Emiliania huxleyi revealed that cell concentrations of 1500 cells/mL accelerate sinking by about 35-40%, which we estimate (by one-dimensional modeling) to elevate organic matter transfer efficiency through the mesopelagic from 14 to 24%. Our results indicate that sinking velocities are influenced by the complex interplay between the availability of ballast minerals and aggregate packaging; both of which are controlled by plankton community structure.
Chaos, Complexity, and Earning Community: What Do They Mean for Education?
ERIC Educational Resources Information Center
Pouravood, Roland C.
1997-01-01
Ponders possible explanations for the connections among chaos, complexity, and a learning community. Challenges the Newtonian world model, suggests that the world operates in a complex, nonlinear, unpredictable pattern, and calls for a new science to understand this complexity. A true learning community values individual autonomy, risk taking,…
Raguideau, Sébastien; Plancade, Sandra; Pons, Nicolas; Leclerc, Marion; Laroche, Béatrice
2016-12-01
Whole Genome Shotgun (WGS) metagenomics is increasingly used to study the structure and functions of complex microbial ecosystems, both from the taxonomic and functional point of view. Gene inventories of otherwise uncultured microbial communities make the direct functional profiling of microbial communities possible. The concept of community aggregated trait has been adapted from environmental and plant functional ecology to the framework of microbial ecology. Community aggregated traits are quantified from WGS data by computing the abundance of relevant marker genes. They can be used to study key processes at the ecosystem level and correlate environmental factors and ecosystem functions. In this paper we propose a novel model based approach to infer combinations of aggregated traits characterizing specific ecosystemic metabolic processes. We formulate a model of these Combined Aggregated Functional Traits (CAFTs) accounting for a hierarchical structure of genes, which are associated on microbial genomes, further linked at the ecosystem level by complex co-occurrences or interactions. The model is completed with constraints specifically designed to exploit available genomic information, in order to favor biologically relevant CAFTs. The CAFTs structure, as well as their intensity in the ecosystem, is obtained by solving a constrained Non-negative Matrix Factorization (NMF) problem. We developed a multicriteria selection procedure for the number of CAFTs. We illustrated our method on the modelling of ecosystemic functional traits of fiber degradation by the human gut microbiota. We used 1408 samples of gene abundances from several high-throughput sequencing projects and found that four CAFTs only were needed to represent the fiber degradation potential. This data reduction highlighted biologically consistent functional patterns while providing a high quality preservation of the original data. Our method is generic and can be applied to other metabolic processes in the gut or in other ecosystems.
Campos, Raúl E.
2013-01-01
In order to determine if phytotelmata in sympatric bamboos of the genus Guadua might be colonized by different types of arthropods and contain communities of different complexities, the following objectives were formulated: (1) to analyze the structure and species richness of the aquatic macroinvertebrate communities, (2) to comparatively analyze co-occurrences; and (3) to identify the main predators. Field studies were conducted in a subtropical forest in Argentina, where 80 water-filled bamboo internodes of Guadua chacoensis (Rojas Acosta) Londoño and Peterson (Poales: Poaceae) and G. trinii (Nees) Nees and Rupr. were sampled. Morphological measurements indicated that G. chacoensis held more fluid than G. trinii. The communities differed between Guadua species, but many macroinvertebrate species used both bamboo species. The phytotelmata were mainly colonized by Diptera of the families Culicidae and Ceratopogonidae. PMID:24224775
"Rebuilding our community": hearing silenced voices on Aboriginal youth suicide.
Walls, Melissa L; Hautala, Dane; Hurley, Jenna
2014-02-01
This paper brings forth the voices of adult Aboriginal First Nations community members who gathered in focus groups to discuss the problem of youth suicide on their reserves. Our approach emphasizes multilevel (e.g., individual, family, and broader ecological systems) factors viewed by participants as relevant to youth suicide. Wheaton's conceptualization of stressors and Evans-Campbell's multilevel classification of the impacts of historical trauma are used as theoretical and analytic guides. Thematic analysis of qualitative data transcripts revealed a highly complex intersection of stressors, traumas, and social problems seen by community members as underlying mechanisms influencing heightened levels of Aboriginal youth suicidality. Our multilevel coding approach revealed that suicidal behaviors were described by community members largely as a problem with deep historical and contemporary structural roots, as opposed to being viewed as individualized pathology.
Rúa, Megan A.; Wilson, Emily C.; Steele, Sarah; Munters, Arielle R.; Hoeksema, Jason D.; Frank, Anna C.
2016-01-01
Studies of the ecological and evolutionary relationships between plants and their associated microbes have long been focused on single microbes, or single microbial guilds, but in reality, plants associate with a diverse array of microbes from a varied set of guilds. As such, multitrophic interactions among plant-associated microbes from multiple guilds represent an area of developing research, and can reveal how complex microbial communities are structured around plants. Interactions between coniferous plants and their associated microbes provide a good model system for such studies, as conifers host a suite of microorganisms including mutualistic ectomycorrhizal (ECM) fungi and foliar bacterial endophytes. To investigate the potential role ECM fungi play in structuring foliar bacterial endophyte communities, we sampled three isolated, native populations of Monterey pine (Pinus radiata), and used constrained analysis of principal coordinates to relate the community matrices of the ECM fungi and bacterial endophytes. Our results suggest that ECM fungi may be important factors for explaining variation in bacterial endophyte communities but this effect is influenced by population and environmental characteristics, emphasizing the potential importance of other factors — biotic or abiotic — in determining the composition of bacterial communities. We also classified ECM fungi into categories based on known fungal traits associated with substrate exploration and nutrient mobilization strategies since variation in these traits allows the fungi to acquire nutrients across a wide range of abiotic conditions and may influence the outcome of multi-species interactions. Across populations and environmental factors, none of the traits associated with fungal foraging strategy types significantly structured bacterial assemblages, suggesting these ECM fungal traits are not important for understanding endophyte-ECM interactions. Overall, our results suggest that both biotic species interactions and environmental filtering are important for structuring microbial communities but emphasize the need for more research into these interactions. PMID:27065966
Inferring the relative resilience of alternative states
Angeler, David G.; Allen, Craig R.; Rojo, Carmen; Alvarez-Cobelas, Miguel; Rodrigo, Maria A.; Sanchez-Carrillo, Salvador
2013-01-01
Ecological systems may occur in alternative states that differ in ecological structures, functions and processes. Resilience is the measure of disturbance an ecological system can absorb before changing states. However, how the intrinsic structures and processes of systems that characterize their states affects their resilience remains unclear. We analyzed time series of phytoplankton communities at three sites in a floodplain in central Spain to assess the dominant frequencies or “temporal scales” in community dynamics and compared the patterns between a wet and a dry alternative state. The identified frequencies and cross-scale structures are expected to arise from positive feedbacks that are thought to reinforce processes in alternative states of ecological systems and regulate emergent phenomena such as resilience. Our analyses show a higher species richness and diversity but lower evenness in the dry state. Time series modeling revealed a decrease in the importance of short-term variability in the communities, suggesting that community dynamics slowed down in the dry relative to the wet state. The number of temporal scales at which community dynamics manifested, and the explanatory power of time series models, was lower in the dry state. The higher diversity, reduced number of temporal scales and the lower explanatory power of time series models suggest that species dynamics tended to be more stochastic in the dry state. From a resilience perspective our results highlight a paradox: increasing species richness may not necessarily enhance resilience. The loss of cross-scale structure (i.e. the lower number of temporal scales) in community dynamics across sites suggests that resilience erodes during drought. Phytoplankton communities in the dry state are therefore likely less resilient than in the wet state. Our case study demonstrates the potential of time series modeling to assess attributes that mediate resilience. The approach is useful for assessing resilience of alternative states across ecological and other complex systems.
NASA Astrophysics Data System (ADS)
Orson, Richard A.; Howes, Brian L.
1992-11-01
Stochastic events relating to beach formation and inlet dynamics have been the major factors influencing the development of the Waquoit Bay tidal marshes. This results from the physical structure of the Waquoit Bay system where tidal exchange is limited to one or two small inlets and is in contrast to marsh development in nearby Barnstable Marsh where direct unrestricted exchange with Cape Cod Bay has smoothed the effects of stochastic events on vegetation development. We contend that vegetation development in salt marshes where connections to adjacent waters are restricted will be dominated by abiotic factors (e.g. storms, sedimentation rates, etc.) while those marshes directly linked to open bodies of water and where alterations to hydrodynamic factors are gradual, autecological processes (e.g. interspecific competition) will dominate long-term plant community development. The results from the five marsh systems within the Waquoit Bay complex suggest that once a vegetation change occurs the new community tended to persist for long periods of time (100's-1000's years). Stability of the 'new' community appeared to depend upon the stability of the physical structure of the system and/or time between perturbations necessary to allow the slower autecological processes to have a discernable effect. In order for the plant community to persist as long as observed, the vegetation must also be exerting an influence on the processes of development. Increased production of roots and rhizomes and growth characteristics (density of culms) are some of the factors which help to maintain long-term species dominance. It is clear from this investigation that the structure of the plant community at any one point in time is dependent upon numerous factors including historical developmental influences. To properly assess changes to the present plant community or determine recent rates of accretion, historic developmental trends must be considered. The factors that have influenced the development of marsh in the past will be important in understanding and formulating predictive models in the future.
Fahrenfeld, N.L.; Reyes, Hannah Delos; Eramo, Alessia; Akob, Denise M.; Mumford, Adam; Cozzarelli, Isabelle M.
2017-01-01
Unconventional oil and gas (UOG) production produces large quantities of wastewater with complex geochemistry and largely uncharacterized impacts on surface waters. In this study, we assessed shifts in microbial community structure and function in sediments and waters upstream and downstream from a UOG wastewater disposal facility. To do this, quantitative PCR for 16S rRNA and antibiotic resistance genes along with metagenomic sequencing were performed. Elevated conductivity and markers of UOG wastewater characterized sites sampled downstream from the disposal facility compared to background sites. Shifts in overall high level functions and microbial community structure were observed between background sites and downstream sediments. Increases in Deltaproteobacteria and Methanomicrobia and decreases in Thaumarchaeota were observed at downstream sites. Genes related to dormancy and sporulation and methanogenic respiration were 18–86 times higher at downstream, impacted sites. The potential for these sediments to serve as reservoirs of antimicrobial resistance was investigated given frequent reports of the use of biocides to control the growth of nuisance bacteria in UOG operations. A shift in resistance profiles downstream of the UOG facility was observed including increases in acrB and mexB genes encoding for multidrug efflux pumps, but not overall abundance of resistance genes. The observed shifts in microbial community structure and potential function indicate changes in respiration, nutrient cycling, and markers of stress in a stream impacted by UOG waste disposal operations.
An improved game-theoretic approach to uncover overlapping communities
NASA Astrophysics Data System (ADS)
Sun, Hong-Liang; Ch'Ng, Eugene; Yong, Xi; Garibaldi, Jonathan M.; See, Simon; Chen, Duan-Bing
How can we uncover overlapping communities from complex networks to understand the inherent structures and functions? Chen et al. firstly proposed a community game (Game) to study this problem, and the overlapping communities have been discovered when the game is convergent. It is based on the assumption that each vertex of the underlying network is a rational game player to maximize its utility. In this paper, we investigate how similar vertices affect the formation of community game. The Adamic-Adar Index (AA Index) has been employed to define the new utility function. This novel method has been evaluated on both synthetic and real-world networks. Experimental study shows that it has significant improvement of accuracy (from 4.8% to 37.6%) compared with the Game on 10 real networks. It is more efficient on Facebook networks (FN) and Amazon co-purchasing networks than on other networks. This result implicates that “friend circles of friends” of Facebook are valuable to understand the overlapping community division.
Lu, Yi; Xu, Jiuping
2015-04-01
The number of communities affected by disasters has been rising. As a result, non-governmental organisations (NGOs) that attend community post-disaster reconstruction are often unable to deliver all requirements and have to develop cooperative approaches. However, this collaboration can cause problems because of the complex environments, the fight for limited resources and uncoordinated management, all of which result in poor service delivery to the communities, adding to their woes. From extensive field research and case studies conducted in the post-Wenchuan earthquake-stricken communities, this paper introduces an integrated collaboration framework for community post-disaster reconstruction with the focus on three types of NGOs: international, government organised and civil. The proposed collaboration framework examines the three interrelated components of organisational structure, operational processes and reconstruction goals/implementation areas. Of great significance in better promoting collaborative participation between NGOs are the crucial concepts of participatory reconstruction, double-layer collaborative networks, and circular review and revision. © 2015 The Author(s). Disasters © Overseas Development Institute, 2015.
Stylized facts in social networks: Community-based static modeling
NASA Astrophysics Data System (ADS)
Jo, Hang-Hyun; Murase, Yohsuke; Török, János; Kertész, János; Kaski, Kimmo
2018-06-01
The past analyses of datasets of social networks have enabled us to make empirical findings of a number of aspects of human society, which are commonly featured as stylized facts of social networks, such as broad distributions of network quantities, existence of communities, assortative mixing, and intensity-topology correlations. Since the understanding of the structure of these complex social networks is far from complete, for deeper insight into human society more comprehensive datasets and modeling of the stylized facts are needed. Although the existing dynamical and static models can generate some stylized facts, here we take an alternative approach by devising a community-based static model with heterogeneous community sizes and larger communities having smaller link density and weight. With these few assumptions we are able to generate realistic social networks that show most stylized facts for a wide range of parameters, as demonstrated numerically and analytically. Since our community-based static model is simple to implement and easily scalable, it can be used as a reference system, benchmark, or testbed for further applications.
The impact of shrimp farming effluent on bacterial communities in mangrove waters, Ceará, Brazil.
Sousa, O V; Macrae, A; Menezes, F G R; Gomes, N C M; Vieira, R H S F; Mendonça-Hagler, L C S
2006-12-01
The effects of shrimp farm effluents on bacterial communities in mangroves have been infrequently reported. Classic and molecular biology methods were used to survey bacterial communities from four mangroves systems. Water temperature, salinity, pH, total heterotrophic bacteria and maximum probable numbers of Vibrio spp. were investigated. Genetic profiles of bacterial communities were also characterized by polymerase chain reaction (PCR) amplification of eubacterial and Vibrio 16S rDNA using denaturing gradient gel electrophoresis (DGGE). Highest heterotrophic counts were registered in the mangrove not directly polluted by shrimp farming. The Enterobacteriaceae and Chryseomonas luteola dominated the heterotrophic isolates. Vibrio spp. pathogenic to humans and shrimps were identified. Eubacterial genetic profiles suggest a shared community structure independent of mangrove system. Vibrio genetic profiles were mangrove specific. Neither microbial counts nor genetic profiling revealed a significant decrease in species richness associated with shrimp farm effluent. The complex nature of mangrove ecosystems and their microbial communities is discussed.
NASA Astrophysics Data System (ADS)
Stegmann, Patrick G.; Tang, Guanglin; Yang, Ping; Johnson, Benjamin T.
2018-05-01
A structural model is developed for the single-scattering properties of snow and graupel particles with a strongly heterogeneous morphology and an arbitrary variable mass density. This effort is aimed to provide a mechanism to consider particle mass density variation in the microwave scattering coefficients implemented in the Community Radiative Transfer Model (CRTM). The stochastic model applies a bicontinuous random medium algorithm to a simple base shape and uses the Finite-Difference-Time-Domain (FDTD) method to compute the single-scattering properties of the resulting complex morphology.
NASA Astrophysics Data System (ADS)
Hankin, S.
2004-12-01
Data management and communications within the marine environment present great challenges due in equal parts to the variety and complexity of the observations that are involved; the rapidly evolving information technology; and the complex history and relationships among community participants. At present there is no coherent Cyberinfrastructure that effectively integrates these data streams across organizations, disciplines and spatial and temporal scales. The resulting lack of integration of data denies US society important benefits, such as improved climate forecasts and more effective protection of coastal marine ecosystems. Therefore, Congress has directed the US marine science communities to come together to plan, design, and implement a sustained Integrated Ocean Observing System (IOOS). Central to the vision of the IOOS is a Data Management and Communications (DMAC) Subsystem that joins Federal, regional, state, municipal, academic and commercial partners in a seamless data sharing framework. The design of the DMAC Subsystem is made particularly challenging by three competing factors: 1) The data types to be integrated are heterogeneous and have complex structure; 2) The holdings are physically distributed and widely ranging in size and complexity; and 3) IOOS is a loose federation of many organizations, large and small, lacking a management hierarchy. Designing the DMAC Subsystem goes beyond solving problems of software engineering; the most demanding aspects of the solution lie in community behavior. An overview of the plan for the DMAC Subsystem and an outline of the next steps forward will be described.
How to Identify Success Among Networks That Promote Active Living.
Litt, Jill; Varda, Danielle; Reed, Hannah; Retrum, Jessica; Tabak, Rachel; Gustat, Jeanette; O'Hara Tompkins, Nancy
2015-11-01
We evaluated organization- and network-level factors that influence organizations' perceived success. This is important for managing interorganizational networks, which can mobilize communities to address complex health issues such as physical activity, and for achieving change. In 2011, we used structured interview and network survey data from 22 states in the United States to estimate multilevel random-intercept models to understand organization- and network-level factors that explain perceived network success. A total of 53 of 59 "whole networks" met the criteria for inclusion in the analysis (89.8%). Coordinators identified 559 organizations, with 3 to 12 organizations from each network taking the online survey (response rate = 69.7%; range = 33%-100%). Occupying a leadership position (P < .01), the amount of time with the network (P < .05), and support from community leaders (P < .05) emerged as correlates of perceived success. Organizations' perceptions of success can influence decisions about continuing involvement and investment in networks designed to promote environment and policy change for active living. Understanding these factors can help leaders manage complex networks that involve diverse memberships, varied interests, and competing community-level priorities.
[Advances in plant ecophysiological studies on re-vegetation of degraded ecosystem].
Zhao, Ping
2003-11-01
Natural force and human intervention lead to many local, regional, and sometimes global changes in plant community patterns. Regardless of the cause and intensity of these changes, ecosystem can recover most of their attributes through natural succession, or can be repaired by human assistance. The essentiality of restoration of degraded ecosystem is community succession, a process during which an ecosystem evolves from primary stage to advanced stage, and its structure and function change from simple to complex plant. Ecophysiological study could explain some macroscopical phenomena of the ecology of re-vegetation of degraded ecosystem, and provide a scientific base for assembling pioneering plant community. The advances in plant ecophysiological study on re-vegetation of degraded ecosystems were reviewed in this paper.
Network analysis shining light on parasite ecology and diversity.
Poulin, Robert
2010-10-01
The vast number of species making up natural communities, and the myriad interactions among them, pose great difficulties for the study of community structure, dynamics and stability. Borrowed from other fields, network analysis is making great inroads in community ecology and is only now being applied to host-parasite interactions. It allows a complex system to be examined in its entirety, as opposed to one or a few components at a time. This review explores what network analysis is and how it can be used to investigate parasite ecology. It also summarizes the first findings to emerge from network analyses of host-parasite interactions and identifies promising future directions made possible by this approach. Copyright © 2010 Elsevier Ltd. All rights reserved.
Detecting phenotype-driven transitions in regulatory network structure.
Padi, Megha; Quackenbush, John
2018-01-01
Complex traits and diseases like human height or cancer are often not caused by a single mutation or genetic variant, but instead arise from functional changes in the underlying molecular network. Biological networks are known to be highly modular and contain dense "communities" of genes that carry out cellular processes, but these structures change between tissues, during development, and in disease. While many methods exist for inferring networks and analyzing their topologies separately, there is a lack of robust methods for quantifying differences in network structure. Here, we describe ALPACA (ALtered Partitions Across Community Architectures), a method for comparing two genome-scale networks derived from different phenotypic states to identify condition-specific modules. In simulations, ALPACA leads to more nuanced, sensitive, and robust module discovery than currently available network comparison methods. As an application, we use ALPACA to compare transcriptional networks in three contexts: angiogenic and non-angiogenic subtypes of ovarian cancer, human fibroblasts expressing transforming viral oncogenes, and sexual dimorphism in human breast tissue. In each case, ALPACA identifies modules enriched for processes relevant to the phenotype. For example, modules specific to angiogenic ovarian tumors are enriched for genes associated with blood vessel development, and modules found in female breast tissue are enriched for genes involved in estrogen receptor and ERK signaling. The functional relevance of these new modules suggests that not only can ALPACA identify structural changes in complex networks, but also that these changes may be relevant for characterizing biological phenotypes.
Open-Source Selective Laser Sintering (OpenSLS) of Nylon and Biocompatible Polycaprolactone
Paulsen, Samantha J.; Hwang, Daniel H.; Ta, Anderson H.; Yalacki, David R.; Schmidt, Tim; Miller, Jordan S.
2016-01-01
Selective Laser Sintering (SLS) is an additive manufacturing process that uses a laser to fuse powdered starting materials into solid 3D structures. Despite the potential for fabrication of complex, high-resolution structures with SLS using diverse starting materials (including biomaterials), prohibitive costs of commercial SLS systems have hindered the wide adoption of this technology in the scientific community. Here, we developed a low-cost, open-source SLS system (OpenSLS) and demonstrated its capacity to fabricate structures in nylon with sub-millimeter features and overhanging regions. Subsequently, we demonstrated fabrication of polycaprolactone (PCL) into macroporous structures such as a diamond lattice. Widespread interest in using PCL for bone tissue engineering suggests that PCL lattices are relevant model scaffold geometries for engineering bone. SLS of materials with large powder grain size (~500 μm) leads to part surfaces with high roughness, so we further introduced a simple vapor-smoothing technique to reduce the surface roughness of sintered PCL structures which further improves their elastic modulus and yield stress. Vapor-smoothed PCL can also be used for sacrificial templating of perfusable fluidic networks within orthogonal materials such as poly(dimethylsiloxane) silicone. Finally, we demonstrated that human mesenchymal stem cells were able to adhere, survive, and differentiate down an osteogenic lineage on sintered and smoothed PCL surfaces, suggesting that OpenSLS has the potential to produce PCL scaffolds useful for cell studies. OpenSLS provides the scientific community with an accessible platform for the study of laser sintering and the fabrication of complex geometries in diverse materials. PMID:26841023
Open-Source Selective Laser Sintering (OpenSLS) of Nylon and Biocompatible Polycaprolactone.
Kinstlinger, Ian S; Bastian, Andreas; Paulsen, Samantha J; Hwang, Daniel H; Ta, Anderson H; Yalacki, David R; Schmidt, Tim; Miller, Jordan S
2016-01-01
Selective Laser Sintering (SLS) is an additive manufacturing process that uses a laser to fuse powdered starting materials into solid 3D structures. Despite the potential for fabrication of complex, high-resolution structures with SLS using diverse starting materials (including biomaterials), prohibitive costs of commercial SLS systems have hindered the wide adoption of this technology in the scientific community. Here, we developed a low-cost, open-source SLS system (OpenSLS) and demonstrated its capacity to fabricate structures in nylon with sub-millimeter features and overhanging regions. Subsequently, we demonstrated fabrication of polycaprolactone (PCL) into macroporous structures such as a diamond lattice. Widespread interest in using PCL for bone tissue engineering suggests that PCL lattices are relevant model scaffold geometries for engineering bone. SLS of materials with large powder grain size (~500 μm) leads to part surfaces with high roughness, so we further introduced a simple vapor-smoothing technique to reduce the surface roughness of sintered PCL structures which further improves their elastic modulus and yield stress. Vapor-smoothed PCL can also be used for sacrificial templating of perfusable fluidic networks within orthogonal materials such as poly(dimethylsiloxane) silicone. Finally, we demonstrated that human mesenchymal stem cells were able to adhere, survive, and differentiate down an osteogenic lineage on sintered and smoothed PCL surfaces, suggesting that OpenSLS has the potential to produce PCL scaffolds useful for cell studies. OpenSLS provides the scientific community with an accessible platform for the study of laser sintering and the fabrication of complex geometries in diverse materials.
Spatiotemporal Permutation Entropy as a Measure for Complexity of Cardiac Arrhythmia
NASA Astrophysics Data System (ADS)
Schlemmer, Alexander; Berg, Sebastian; Lilienkamp, Thomas; Luther, Stefan; Parlitz, Ulrich
2018-05-01
Permutation entropy (PE) is a robust quantity for measuring the complexity of time series. In the cardiac community it is predominantly used in the context of electrocardiogram (ECG) signal analysis for diagnoses and predictions with a major application found in heart rate variability parameters. In this article we are combining spatial and temporal PE to form a spatiotemporal PE that captures both, complexity of spatial structures and temporal complexity at the same time. We demonstrate that the spatiotemporal PE (STPE) quantifies complexity using two datasets from simulated cardiac arrhythmia and compare it to phase singularity analysis and spatial PE (SPE). These datasets simulate ventricular fibrillation (VF) on a two-dimensional and a three-dimensional medium using the Fenton-Karma model. We show that SPE and STPE are robust against noise and demonstrate its usefulness for extracting complexity features at different spatial scales.
Food-web complexity emerging from ecological dynamics on adaptive networks.
Garcia-Domingo, Josep L; Saldaña, Joan
2007-08-21
Food webs are complex networks describing trophic interactions in ecological communities. Since Robert May's seminal work on random structured food webs, the complexity-stability debate is a central issue in ecology: does network complexity increase or decrease food-web persistence? A multi-species predator-prey model incorporating adaptive predation shows that the action of ecological dynamics on the topology of a food web (whose initial configuration is generated either by the cascade model or by the niche model) render, when a significant fraction of adaptive predators is present, similar hyperbolic complexity-persistence relationships as those observed in empirical food webs. It is also shown that the apparent positive relation between complexity and persistence in food webs generated under the cascade model, which has been pointed out in previous papers, disappears when the final connection is used instead of the initial one to explain species persistence.
A probabilistic framework for identifying biosignatures using Pathway Complexity
NASA Astrophysics Data System (ADS)
Marshall, Stuart M.; Murray, Alastair R. G.; Cronin, Leroy
2017-11-01
One thing that discriminates living things from inanimate matter is their ability to generate similarly complex or non-random structures in a large abundance. From DNA sequences to folded protein structures, living cells, microbial communities and multicellular structures, the material configurations in biology can easily be distinguished from non-living material assemblies. Many complex artefacts, from ordinary bioproducts to human tools, though they are not living things, are ultimately produced by biological processes-whether those processes occur at the scale of cells or societies, they are the consequences of living systems. While these objects are not living, they cannot randomly form, as they are the product of a biological organism and hence are either technological or cultural biosignatures. A generalized approach that aims to evaluate complex objects as possible biosignatures could be useful to explore the cosmos for new life forms. However, it is not obvious how it might be possible to create such a self-contained approach. This would require us to prove rigorously that a given artefact is too complex to have formed by chance. In this paper, we present a new type of complexity measure, which we call `Pathway Complexity', that allows us not only to threshold the abiotic-biotic divide, but also to demonstrate a probabilistic approach based on object abundance and complexity which can be used to unambiguously assign complex objects as biosignatures. We hope that this approach will not only open up the search for biosignatures beyond the Earth, but also allow us to explore the Earth for new types of biology, and to determine when a complex chemical system discovered in the laboratory could be considered alive. This article is part of the themed issue 'Reconceptualizing the origins of life'.
Geng, Haifeng; Tran-Gyamfi, Mary B.; Lane, Todd W.; ...
2016-07-26
Open microalgae cultures host a myriad of bacteria, creating a complex system of interacting species that influence algal growth and health. Many algal microbiota studies have been conducted to determine the relative importance of bacterial taxa to algal culture health and physiological states, but these studies have not characterized the interspecies relationships in the microbial communities. Here we subjected Nanochroloropsis salina cultures to multiple chemical treatments (antibiotics and quorum sensing compounds) and obtained dense time-series data on changes to the microbial community using 16S gene amplicon metagenomic sequencing (21,029,577 reads for 23 samples) to measure microbial taxa-taxa abundance correlations. Short-termmore » treatment with antibiotics resulted in substantially larger shifts in the microbiota structure compared to changes observed following treatment with signaling compounds and glucose. We also calculated operational taxonomic unit (OTU) associations and generated OTU correlation networks to provide an overview of possible bacterial OTU interactions. This analysis identified five major cohesive modules of microbiota with similar co-abundance profiles across different chemical treatments. The Eigengenes of OTU modules were examined for correlation with different external treatment factors. This correlation-based analysis revealed that culture age (time) and treatment types have primary effects on forming network modules and shaping the community structure. Additional network analysis detected Alteromonadeles and Alphaproteobacteria as having the highest centrality, suggesting these species are “keystone” OTUs in the microbial community. Furthermore, we illustrated that the chemical tropodithietic acid, which is secreted by several species in the Alphaproteobacteria taxon, is able to drastically change the structure of the microbiota within 3 h. Lastly, taken together, these results provide valuable insights into the structure of the microbiota associated with N. salina cultures and how these structures change in response to chemical perturbations.« less
NASA Astrophysics Data System (ADS)
Lelièvre, Yann; Sarrazin, Jozée; Marticorena, Julien; Schaal, Gauthier; Day, Thomas; Legendre, Pierre; Hourdez, Stéphane; Matabos, Marjolaine
2018-05-01
Hydrothermal vent sites along the Juan de Fuca Ridge in the north-east Pacific host dense populations of Ridgeia piscesae tubeworms that promote habitat heterogeneity and local diversity. A detailed description of the biodiversity and community structure is needed to help understand the ecological processes that underlie the distribution and dynamics of deep-sea vent communities. Here, we assessed the composition, abundance, diversity and trophic structure of six tubeworm samples, corresponding to different successional stages, collected on the Grotto hydrothermal edifice (Main Endeavour Field, Juan de Fuca Ridge) at 2196 m depth. Including R. piscesae, a total of 36 macrofaunal taxa were identified to the species level. Although polychaetes made up the most diverse taxon, faunal densities were dominated by gastropods. Most tubeworm aggregations were numerically dominated by the gastropods Lepetodrilus fucensis and Depressigyra globulus and polychaete Amphisamytha carldarei. The highest diversities were found in tubeworm aggregations characterised by the longest tubes (18.5 ± 3.3 cm). The high biomass of grazers and high resource partitioning at a small scale illustrates the importance of the diversity of free-living microbial communities in the maintenance of food webs. Although symbiont-bearing invertebrates R. piscesae represented a large part of the total biomass, the low number of specialised predators on this potential food source suggests that its primary role lies in community structuring. Vent food webs did not appear to be organised through predator-prey relationships. For example, although trophic structure complexity increased with ecological successional stages, showing a higher number of predators in the last stages, the food web structure itself did not change across assemblages. We suggest that environmental gradients provided by the biogenic structure of tubeworm bushes generate a multitude of ecological niches and contribute to the partitioning of nutritional resources, releasing communities from competition pressure for resources and thus allowing species to coexist.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Geng, Haifeng; Tran-Gyamfi, Mary B.; Lane, Todd W.
Open microalgae cultures host a myriad of bacteria, creating a complex system of interacting species that influence algal growth and health. Many algal microbiota studies have been conducted to determine the relative importance of bacterial taxa to algal culture health and physiological states, but these studies have not characterized the interspecies relationships in the microbial communities. Here we subjected Nanochroloropsis salina cultures to multiple chemical treatments (antibiotics and quorum sensing compounds) and obtained dense time-series data on changes to the microbial community using 16S gene amplicon metagenomic sequencing (21,029,577 reads for 23 samples) to measure microbial taxa-taxa abundance correlations. Short-termmore » treatment with antibiotics resulted in substantially larger shifts in the microbiota structure compared to changes observed following treatment with signaling compounds and glucose. We also calculated operational taxonomic unit (OTU) associations and generated OTU correlation networks to provide an overview of possible bacterial OTU interactions. This analysis identified five major cohesive modules of microbiota with similar co-abundance profiles across different chemical treatments. The Eigengenes of OTU modules were examined for correlation with different external treatment factors. This correlation-based analysis revealed that culture age (time) and treatment types have primary effects on forming network modules and shaping the community structure. Additional network analysis detected Alteromonadeles and Alphaproteobacteria as having the highest centrality, suggesting these species are “keystone” OTUs in the microbial community. Furthermore, we illustrated that the chemical tropodithietic acid, which is secreted by several species in the Alphaproteobacteria taxon, is able to drastically change the structure of the microbiota within 3 h. Lastly, taken together, these results provide valuable insights into the structure of the microbiota associated with N. salina cultures and how these structures change in response to chemical perturbations.« less
Context-dependent interactions and the regulation of species richness in freshwater fish.
MacDougall, Andrew S; Harvey, Eric; McCune, Jenny L; Nilsson, Karin A; Bennett, Joseph; Firn, Jennifer; Bartley, Timothy; Grace, James B; Kelly, Jocelyn; Tunney, Tyler D; McMeans, Bailey; Matsuzaki, Shin-Ichiro S; Kadoya, Taku; Esch, Ellen; Cazelles, Kevin; Lester, Nigel; McCann, Kevin S
2018-03-06
Species richness is regulated by a complex network of scale-dependent processes. This complexity can obscure the influence of limiting species interactions, making it difficult to determine if abiotic or biotic drivers are more predominant regulators of richness. Using integrative modeling of freshwater fish richness from 721 lakes along an 11 o latitudinal gradient, we find negative interactions to be a relatively minor independent predictor of species richness in lakes despite the widespread presence of predators. Instead, interaction effects, when detectable among major functional groups and 231 species pairs, were strong, often positive, but contextually dependent on environment. These results are consistent with the idea that negative interactions internally structure lake communities but do not consistently 'scale-up' to regulate richness independently of the environment. The importance of environment for interaction outcomes and its role in the regulation of species richness highlights the potential sensitivity of fish communities to the environmental changes affecting lakes globally.
Context-dependent interactions and the regulation of species richness in freshwater fish
MacDougall, Andrew S.; Harvey, Eric; McCune, Jenny L.; Nilsson, Karin A.; Bennett, Joseph; Firn, Jennifer; Bartley, Timothy; Grace, James B.; Kelly, Jocelyn; Tunney, Tyler D.; McMeans, Bailey; Matsuzaki, Shin-Ichiro S.; Kadoya, Taku; Esch, Ellen; Cazelles, Kevin; Lester, Nigel; McCann, Kevin S.
2018-01-01
Species richness is regulated by a complex network of scale-dependent processes. This complexity can obscure the influence of limiting species interactions, making it difficult to determine if abiotic or biotic drivers are more predominant regulators of richness. Using integrative modeling of freshwater fish richness from 721 lakes along an 11olatitudinal gradient, we find negative interactions to be a relatively minor independent predictor of species richness in lakes despite the widespread presence of predators. Instead, interaction effects, when detectable among major functional groups and 231 species pairs, were strong, often positive, but contextually dependent on environment. These results are consistent with the idea that negative interactions internally structure lake communities but do not consistently ‘scale-up’ to regulate richness independently of the environment. The importance of environment for interaction outcomes and its role in the regulation of species richness highlights the potential sensitivity of fish communities to the environmental changes affecting lakes globally.