Temporal Dynamics of Abundance and Composition of Nitrogen-Fixing Communities across Agricultural Soils

PubMed Central

Pereira e Silva, Michele C.; Schloter-Hai, Brigitte; Schloter, Michael; van Elsas, Jan Dirk; Salles, Joana Falcão

2013-01-01

Background Despite the fact that the fixation of nitrogen is one of the most significant nutrient processes in the terrestrial ecosystem, a thorough study of the spatial and temporal patterns in the abundance and distribution of N-fixing communities has been missing so far. Methodology/Principal Findings In order to understand the dynamics of diazotrophic communities and their resilience to external changes, we quantified the abundance and characterized the bacterial community structures based on the nifH gene, using real-time PCR, PCR-DGGE and 454-pyrosequencing, across four representative Dutch soils during one growing season. In general, higher nifH gene copy numbers were observed in soils with higher pH than in those with lower pH, but lower numbers were related to increased nitrate and ammonium levels. Results from nifH gene pyrosequencing confirmed the observed PCR-DGGE patterns, which indicated that the N fixers are highly dynamic across time, shifting around 60%. Forward selection on CCA analysis identified N availability as the main driver of these variations, as well as of the evenness of the communities, leading to very unequal communities. Moreover, deep sequencing of the nifH gene revealed that sandy soils (B and D) had the lowest percentage of shared OTUs across time, compared with clayey soils (G and K), indicating the presence of a community under constant change. Cosmopolitan nifH species (present throughout the season) were affiliated with Bradyrhizobium , Azospirillum and Methylocistis, whereas other species increased their abundances progressively over time, when appropriate conditions were met, as was notably the case for Paenibacilus and Burkholderia. Conclusions Our study provides the first in-depth pyrosequencing analysis of the N-fixing community at both spatial and temporal scales, providing insights into the cosmopolitan and specific portions of the nitrogen fixing bacterial communities in soil. PMID:24058578

Introducing Co-Activation Pattern Metrics to Quantify Spontaneous Brain Network Dynamics

PubMed Central

Chen, Jingyuan E.; Chang, Catie; Greicius, Michael D.; Glover, Gary H.

2015-01-01

Recently, fMRI researchers have begun to realize that the brain's intrinsic network patterns may undergo substantial changes during a single resting state (RS) scan. However, despite the growing interest in brain dynamics, metrics that can quantify the variability of network patterns are still quite limited. Here, we first introduce various quantification metrics based on the extension of co-activation pattern (CAP) analysis, a recently proposed point-process analysis that tracks state alternations at each individual time frame and relies on very few assumptions; then apply these proposed metrics to quantify changes of brain dynamics during a sustained 2-back working memory (WM) task compared to rest. We focus on the functional connectivity of two prominent RS networks, the default-mode network (DMN) and executive control network (ECN). We first demonstrate less variability of global Pearson correlations with respect to the two chosen networks using a sliding-window approach during WM task compared to rest; then we show that the macroscopic decrease in variations in correlations during a WM task is also well characterized by the combined effect of a reduced number of dominant CAPs, increased spatial consistency across CAPs, and increased fractional contributions of a few dominant CAPs. These CAP metrics may provide alternative and more straightforward quantitative means of characterizing brain network dynamics than time-windowed correlation analyses. PMID:25662866

Quantifying Information Gain from Dynamic Downscaling Experiments

NASA Astrophysics Data System (ADS)

Tian, Y.; Peters-Lidard, C. D.

2015-12-01

Dynamic climate downscaling experiments are designed to produce information at higher spatial and temporal resolutions. Such additional information is generated from the low-resolution initial and boundary conditions via the predictive power of the physical laws. However, errors and uncertainties in the initial and boundary conditions can be propagated and even amplified to the downscaled simulations. Additionally, the limit of predictability in nonlinear dynamical systems will also damper the information gain, even if the initial and boundary conditions were error-free. Thus it is critical to quantitatively define and measure the amount of information increase from dynamic downscaling experiments, to better understand and appreciate their potentials and limitations. We present a scheme to objectively measure the information gain from such experiments. The scheme is based on information theory, and we argue that if a downscaling experiment is to exhibit value, it has to produce more information than what can be simply inferred from information sources already available. These information sources include the initial and boundary conditions, the coarse resolution model in which the higher-resolution models are embedded, and the same set of physical laws. These existing information sources define an "information threshold" as a function of the spatial and temporal resolution, and this threshold serves as a benchmark to quantify the information gain from the downscaling experiments, or any other approaches. For a downscaling experiment to shown any value, the information has to be above this threshold. A recent NASA-supported downscaling experiment is used as an example to illustrate the application of this scheme.

Evolution properties of the community members for dynamic networks

NASA Astrophysics Data System (ADS)

Yang, Kai; Guo, Qiang; Li, Sheng-Nan; Han, Jing-Ti; Liu, Jian-Guo

2017-03-01

The collective behaviors of community members for dynamic social networks are significant for understanding evolution features of communities. In this Letter, we empirically investigate the evolution properties of the new community members for dynamic networks. Firstly, we separate data sets into different slices, and analyze the statistical properties of new members as well as communities they joined in for these data sets. Then we introduce a parameter φ to describe community evolution between different slices and investigate the dynamic community properties of the new community members. The empirical analyses for the Facebook, APS, Enron and Wiki data sets indicate that both the number of new members and joint communities increase, the ratio declines rapidly and then becomes stable over time, and most of the new members will join in the small size communities that is s ≤ 10. Furthermore, the proportion of new members in existed communities decreases firstly and then becomes stable and relatively small for these data sets. Our work may be helpful for deeply understanding the evolution properties of community members for social networks.

Quantifying Aggregation Dynamics during Myxococcus xanthus Development▿†

PubMed Central

Zhang, Haiyang; Angus, Stuart; Tran, Michael; Xie, Chunyan; Igoshin, Oleg A.; Welch, Roy D.

2011-01-01

Under starvation conditions, a swarm of Myxococcus xanthus cells will undergo development, a multicellular process culminating in the formation of many aggregates called fruiting bodies, each of which contains up to 100,000 spores. The mechanics of symmetry breaking and the self-organization of cells into fruiting bodies is an active area of research. Here we use microcinematography and automated image processing to quantify several transient features of developmental dynamics. An analysis of experimental data indicates that aggregation reaches its steady state in a highly nonmonotonic fashion. The number of aggregates rapidly peaks at a value 2- to 3-fold higher than the final value and then decreases before reaching a steady state. The time dependence of aggregate size is also nonmonotonic, but to a lesser extent: average aggregate size increases from the onset of aggregation to between 10 and 15 h and then gradually decreases thereafter. During this process, the distribution of aggregates transitions from a nearly random state early in development to a more ordered state later in development. A comparison of experimental results to a mathematical model based on the traffic jam hypothesis indicates that the model fails to reproduce these dynamic features of aggregation, even though it accurately describes its final outcome. The dynamic features of M. xanthus aggregation uncovered in this study impose severe constraints on its underlying mechanisms. PMID:21784940

Microbial community dynamics in soil aggregates shape biogeochemical gas fluxes from soil profiles - upscaling an aggregate biophysical model.

PubMed

Ebrahimi, Ali; Or, Dani

2016-09-01

Microbial communities inhabiting soil aggregates dynamically adjust their activity and composition in response to variations in hydration and other external conditions. These rapid dynamics shape signatures of biogeochemical activity and gas fluxes emitted from soil profiles. Recent mechanistic models of microbial processes in unsaturated aggregate-like pore networks revealed a highly dynamic interplay between oxic and anoxic microsites jointly shaped by hydration conditions and by aerobic and anaerobic microbial community abundance and self-organization. The spatial extent of anoxic niches (hotspots) flicker in time (hot moments) and support substantial anaerobic microbial activity even in aerated soil profiles. We employed an individual-based model for microbial community life in soil aggregate assemblies represented by 3D angular pore networks. Model aggregates of different sizes were subjected to variable water, carbon and oxygen contents that varied with soil depth as boundary conditions. The study integrates microbial activity within aggregates of different sizes and soil depth to obtain estimates of biogeochemical fluxes from the soil profile. The results quantify impacts of dynamic shifts in microbial community composition on CO2 and N2 O production rates in soil profiles in good agreement with experimental data. Aggregate size distribution and the shape of resource profiles in a soil determine how hydration dynamics shape denitrification and carbon utilization rates. Results from the mechanistic model for microbial activity in aggregates of different sizes were used to derive parameters for analytical representation of soil biogeochemical processes across large scales of practical interest for hydrological and climate models. © 2016 John Wiley & Sons Ltd.

Quantifying ecological impacts of mass extinctions with network analysis of fossil communities

PubMed Central

Muscente, A. D.; Prabhu, Anirudh; Zhong, Hao; Eleish, Ahmed; Meyer, Michael B.; Fox, Peter; Hazen, Robert M.; Knoll, Andrew H.

2018-01-01

Mass extinctions documented by the fossil record provide critical benchmarks for assessing changes through time in biodiversity and ecology. Efforts to compare biotic crises of the past and present, however, encounter difficulty because taxonomic and ecological changes are decoupled, and although various metrics exist for describing taxonomic turnover, no methods have yet been proposed to quantify the ecological impacts of extinction events. To address this issue, we apply a network-based approach to exploring the evolution of marine animal communities over the Phanerozoic Eon. Network analysis of fossil co-occurrence data enables us to identify nonrandom associations of interrelated paleocommunities. These associations, or evolutionary paleocommunities, dominated total diversity during successive intervals of relative community stasis. Community turnover occurred largely during mass extinctions and radiations, when ecological reorganization resulted in the decline of one association and the rise of another. Altogether, we identify five evolutionary paleocommunities at the generic and familial levels in addition to three ordinal associations that correspond to Sepkoski’s Cambrian, Paleozoic, and Modern evolutionary faunas. In this context, we quantify magnitudes of ecological change by measuring shifts in the representation of evolutionary paleocommunities over geologic time. Our work shows that the Great Ordovician Biodiversification Event had the largest effect on ecology, followed in descending order by the Permian–Triassic, Cretaceous–Paleogene, Devonian, and Triassic–Jurassic mass extinctions. Despite its taxonomic severity, the Ordovician extinction did not strongly affect co-occurrences of taxa, affirming its limited ecological impact. Network paleoecology offers promising approaches to exploring ecological consequences of extinctions and radiations. PMID:29686079

Quantifying ecological impacts of mass extinctions with network analysis of fossil communities.

PubMed

Muscente, A D; Prabhu, Anirudh; Zhong, Hao; Eleish, Ahmed; Meyer, Michael B; Fox, Peter; Hazen, Robert M; Knoll, Andrew H

2018-05-15

Mass extinctions documented by the fossil record provide critical benchmarks for assessing changes through time in biodiversity and ecology. Efforts to compare biotic crises of the past and present, however, encounter difficulty because taxonomic and ecological changes are decoupled, and although various metrics exist for describing taxonomic turnover, no methods have yet been proposed to quantify the ecological impacts of extinction events. To address this issue, we apply a network-based approach to exploring the evolution of marine animal communities over the Phanerozoic Eon. Network analysis of fossil co-occurrence data enables us to identify nonrandom associations of interrelated paleocommunities. These associations, or evolutionary paleocommunities, dominated total diversity during successive intervals of relative community stasis. Community turnover occurred largely during mass extinctions and radiations, when ecological reorganization resulted in the decline of one association and the rise of another. Altogether, we identify five evolutionary paleocommunities at the generic and familial levels in addition to three ordinal associations that correspond to Sepkoski's Cambrian, Paleozoic, and Modern evolutionary faunas. In this context, we quantify magnitudes of ecological change by measuring shifts in the representation of evolutionary paleocommunities over geologic time. Our work shows that the Great Ordovician Biodiversification Event had the largest effect on ecology, followed in descending order by the Permian-Triassic, Cretaceous-Paleogene, Devonian, and Triassic-Jurassic mass extinctions. Despite its taxonomic severity, the Ordovician extinction did not strongly affect co-occurrences of taxa, affirming its limited ecological impact. Network paleoecology offers promising approaches to exploring ecological consequences of extinctions and radiations. Copyright © 2018 the Author(s). Published by PNAS.

Dynamic social community detection and its applications.

PubMed

Nguyen, Nam P; Dinh, Thang N; Shen, Yilin; Thai, My T

2014-01-01

Community structure is one of the most commonly observed features of Online Social Networks (OSNs) in reality. The knowledge of this feature is of great advantage: it not only provides helpful insights into developing more efficient social-aware solutions but also promises a wide range of applications enabled by social and mobile networking, such as routing strategies in Mobile Ad Hoc Networks (MANETs) and worm containment in OSNs. Unfortunately, understanding this structure is very challenging, especially in dynamic social networks where social interactions are evolving rapidly. Our work focuses on the following questions: How can we efficiently identify communities in dynamic social networks? How can we adaptively update the network community structure based on its history instead of recomputing from scratch? To this end, we present Quick Community Adaptation (QCA), an adaptive modularity-based framework for not only discovering but also tracing the evolution of network communities in dynamic OSNs. QCA is very fast and efficient in the sense that it adaptively updates and discovers the new community structure based on its history together with the network changes only. This flexible approach makes QCA an ideal framework applicable for analyzing large-scale dynamic social networks due to its lightweight computing-resource requirement. To illustrate the effectiveness of our framework, we extensively test QCA on both synthesized and real-world social networks including Enron, arXiv e-print citation, and Facebook networks. Finally, we demonstrate the applicability of QCA in real applications: (1) A social-aware message forwarding strategy in MANETs, and (2) worm propagation containment in OSNs. Competitive results in comparison with other methods reveal that social-based techniques employing QCA as a community detection core outperform current available methods.

Dynamic Social Community Detection and Its Applications

PubMed Central

Nguyen, Nam P.; Dinh, Thang N.; Shen, Yilin; Thai, My T.

2014-01-01

Community structure is one of the most commonly observed features of Online Social Networks (OSNs) in reality. The knowledge of this feature is of great advantage: it not only provides helpful insights into developing more efficient social-aware solutions but also promises a wide range of applications enabled by social and mobile networking, such as routing strategies in Mobile Ad Hoc Networks (MANETs) and worm containment in OSNs. Unfortunately, understanding this structure is very challenging, especially in dynamic social networks where social interactions are evolving rapidly. Our work focuses on the following questions: How can we efficiently identify communities in dynamic social networks? How can we adaptively update the network community structure based on its history instead of recomputing from scratch? To this end, we present Quick Community Adaptation (QCA), an adaptive modularity-based framework for not only discovering but also tracing the evolution of network communities in dynamic OSNs. QCA is very fast and efficient in the sense that it adaptively updates and discovers the new community structure based on its history together with the network changes only. This flexible approach makes QCA an ideal framework applicable for analyzing large-scale dynamic social networks due to its lightweight computing-resource requirement. To illustrate the effectiveness of our framework, we extensively test QCA on both synthesized and real-world social networks including Enron, arXiv e-print citation, and Facebook networks. Finally, we demonstrate the applicability of QCA in real applications: (1) A social-aware message forwarding strategy in MANETs, and (2) worm propagation containment in OSNs. Competitive results in comparison with other methods reveal that social-based techniques employing QCA as a community detection core outperform current available methods. PMID:24722164

A combinatorial framework to quantify peak/pit asymmetries in complex dynamics.

PubMed

Hasson, Uri; Iacovacci, Jacopo; Davis, Ben; Flanagan, Ryan; Tagliazucchi, Enzo; Laufs, Helmut; Lacasa, Lucas

2018-02-23

We explore a combinatorial framework which efficiently quantifies the asymmetries between minima and maxima in local fluctuations of time series. We first showcase its performance by applying it to a battery of synthetic cases. We find rigorous results on some canonical dynamical models (stochastic processes with and without correlations, chaotic processes) complemented by extensive numerical simulations for a range of processes which indicate that the methodology correctly distinguishes different complex dynamics and outperforms state of the art metrics in several cases. Subsequently, we apply this methodology to real-world problems emerging across several disciplines including cases in neurobiology, finance and climate science. We conclude that differences between the statistics of local maxima and local minima in time series are highly informative of the complex underlying dynamics and a graph-theoretic extraction procedure allows to use these features for statistical learning purposes.

Quantifying the effect of hydrogen on dislocation dynamics: A three-dimensional discrete dislocation dynamics framework

NASA Astrophysics Data System (ADS)

Gu, Yejun; El-Awady, Jaafar A.

2018-03-01

We present a new framework to quantify the effect of hydrogen on dislocations using large scale three-dimensional (3D) discrete dislocation dynamics (DDD) simulations. In this model, the first order elastic interaction energy associated with the hydrogen-induced volume change is accounted for. The three-dimensional stress tensor induced by hydrogen concentration, which is in equilibrium with respect to the dislocation stress field, is derived using the Eshelby inclusion model, while the hydrogen bulk diffusion is treated as a continuum process. This newly developed framework is utilized to quantify the effect of different hydrogen concentrations on the dynamics of a glide dislocation in the absence of an applied stress field as well as on the spacing between dislocations in an array of parallel edge dislocations. A shielding effect is observed for materials having a large hydrogen diffusion coefficient, with the shield effect leading to the homogenization of the shrinkage process leading to the glide loop maintaining its circular shape, as well as resulting in a decrease in dislocation separation distances in the array of parallel edge dislocations. On the other hand, for materials having a small hydrogen diffusion coefficient, the high hydrogen concentrations around the edge characters of the dislocations act to pin them. Higher stresses are required to be able to unpin the dislocations from the hydrogen clouds surrounding them. Finally, this new framework can open the door for further large scale studies on the effect of hydrogen on the different aspects of dislocation-mediated plasticity in metals. With minor modifications of the current formulations, the framework can also be extended to account for general inclusion-induced stress field in discrete dislocation dynamics simulations.

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.

Dynamics in microbial communities: Unraveling mechanisms to identify principles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Konopka, Allan; Lindemann, Stephen R.; Fredrickson, Jim K.

2015-07-01

Diversity begets higher order properties such as functional stability and robustness in microbial communities, but principles that inform conceptual (and eventually predictive) models of community dynamics are lacking. Recent work has shown that selection as well as dispersal and drift shape communities, but the mechanistic bases for assembly of communities and the forces that maintain their function in the face of environmental perturbation are not well understood. Conceptually, some interactions among community members could generate endogenous dynamics in composition, even in the absence of environmental changes. These endogenous dynamics are further perturbed by exogenous forcing factors to produce a richermore » network of community interactions, and it is this “system” that is the basis for higher order community properties. Elucidation of principles that follow from this conceptual model requires identifying the mechanisms that (a) optimize diversity within a community and (b) impart community stability. The network of interactions between organisms can be an important element by providing a buffer against disturbance beyond the effect of functional redundancy, as alternative pathways with different combinations of microbes can be recruited to fulfill specific functions.« less

Perspectives of Community Co-Researchers About Group Dynamics and Equitable Partnership Within a Community-Academic Research Team.

PubMed

Vaughn, Lisa M; Jacquez, Farrah; Zhen-Duan, Jenny

2018-04-01

Equitable partnership processes and group dynamics, including individual, relational, and structural factors, have been identified as key ingredients to successful community-based participatory research partnerships. The purpose of this qualitative study was to investigate the key aspects of group dynamics and partnership from the perspectives of community members serving as co-researchers. Semistructured, in-depth interviews were conducted with 15 Latino immigrant co-researchers from an intervention project with Latinos Unidos por la Salud (LU-Salud), a community research team composed of Latino immigrant community members and academic investigators working in a health research partnership. A deductive framework approach guided the interview process and qualitative data analysis. The LU-Salud co-researchers described relationships, personal growth, beliefs/identity motivation (individual dynamics), coexistence (relational dynamics), diversity, and power/resource sharing (structural dynamics) as key foundational aspects of the community-academic partnership. Building on existing CBPR and team science frameworks, these findings demonstrate that group dynamics and partnership processes are fundamental drivers of individual-level motivation and meaning making, which ultimately sustain efforts of community partners to engage with the research team and also contribute to the achievement of intended research outcomes.

Dynamic graphs, community detection, and Riemannian geometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bakker, Craig; Halappanavar, Mahantesh; Visweswara Sathanur, Arun

A community is a subset of a wider network where the members of that subset are more strongly connected to each other than they are to the rest of the network. In this paper, we consider the problem of identifying and tracking communities in graphs that change over time {dynamic community detection} and present a framework based on Riemannian geometry to aid in this task. Our framework currently supports several important operations such as interpolating between and averaging over graph snapshots. We compare these Riemannian methods with entry-wise linear interpolation and that the Riemannian methods are generally better suited tomore » dynamic community detection. Next steps with the Riemannian framework include developing higher-order interpolation methods (e.g. the analogues of polynomial and spline interpolation) and a Riemannian least-squares regression method for working with noisy data.« less

Quantifying sleep architecture dynamics and individual differences using big data and Bayesian networks

PubMed Central

Shelton, Christian; Mednick, Sara C.

2018-01-01

The pattern of sleep stages across a night (sleep architecture) is influenced by biological, behavioral, and clinical variables. However, traditional measures of sleep architecture such as stage proportions, fail to capture sleep dynamics. Here we quantify the impact of individual differences on the dynamics of sleep architecture and determine which factors or set of factors best predict the next sleep stage from current stage information. We investigated the influence of age, sex, body mass index, time of day, and sleep time on static (e.g. minutes in stage, sleep efficiency) and dynamic measures of sleep architecture (e.g. transition probabilities and stage duration distributions) using a large dataset of 3202 nights from a non-clinical population. Multi-level regressions show that sex effects duration of all Non-Rapid Eye Movement (NREM) stages, and age has a curvilinear relationship for Wake After Sleep Onset (WASO) and slow wave sleep (SWS) minutes. Bayesian network modeling reveals sleep architecture depends on time of day, total sleep time, age and sex, but not BMI. Older adults, and particularly males, have shorter bouts (more fragmentation) of Stage 2, SWS, and they transition less frequently to these stages. Additionally, we showed that the next sleep stage and its duration can be optimally predicted by the prior 2 stages and age. Our results demonstrate the potential benefit of big data and Bayesian network approaches in quantifying static and dynamic architecture of normal sleep. PMID:29641599

Quantifying sleep architecture dynamics and individual differences using big data and Bayesian networks.

PubMed

Yetton, Benjamin D; McDevitt, Elizabeth A; Cellini, Nicola; Shelton, Christian; Mednick, Sara C

2018-01-01

The pattern of sleep stages across a night (sleep architecture) is influenced by biological, behavioral, and clinical variables. However, traditional measures of sleep architecture such as stage proportions, fail to capture sleep dynamics. Here we quantify the impact of individual differences on the dynamics of sleep architecture and determine which factors or set of factors best predict the next sleep stage from current stage information. We investigated the influence of age, sex, body mass index, time of day, and sleep time on static (e.g. minutes in stage, sleep efficiency) and dynamic measures of sleep architecture (e.g. transition probabilities and stage duration distributions) using a large dataset of 3202 nights from a non-clinical population. Multi-level regressions show that sex effects duration of all Non-Rapid Eye Movement (NREM) stages, and age has a curvilinear relationship for Wake After Sleep Onset (WASO) and slow wave sleep (SWS) minutes. Bayesian network modeling reveals sleep architecture depends on time of day, total sleep time, age and sex, but not BMI. Older adults, and particularly males, have shorter bouts (more fragmentation) of Stage 2, SWS, and they transition less frequently to these stages. Additionally, we showed that the next sleep stage and its duration can be optimally predicted by the prior 2 stages and age. Our results demonstrate the potential benefit of big data and Bayesian network approaches in quantifying static and dynamic architecture of normal sleep.

Quantifying stochasticity in the dynamics of delay-coupled semiconductor lasers via forbidden patterns.

PubMed

Tiana-Alsina, Jordi; Buldú, Javier M; Torrent, M C; García-Ojalvo, Jordi

2010-01-28

We quantify the level of stochasticity in the dynamics of two mutually coupled semiconductor lasers. Specifically, we concentrate on a regime in which the lasers synchronize their dynamics with a non-zero lag time, and the leader and laggard roles alternate irregularly between the lasers. We analyse this switching dynamics in terms of the number of forbidden patterns of the alternate time series. The results reveal that the system operates in a stochastic regime, with the level of stochasticity decreasing as the lasers are pumped further away from their lasing threshold. This behaviour is similar to that exhibited by a single semiconductor laser subject to external optical feedback, as its dynamics shifts from the regime of low-frequency fluctuations to coherence collapse. This journal is © 2010 The Royal Society

Seasonal sediment dynamics shape temperate bedrock reef communities

USGS Publications Warehouse

Figurski, Jared D.; Freiwald, Jan; Lonhart, Steve I.; Storlazzi, Curt

2016-01-01

Mobilized seafloor sediment can impact benthic reef communities through burial, scour, and turbidity. These processes are ubiquitous in coastal oceans and, through their influence on the survival, fitness, and interactions of species, can alter the structure and function of benthic communities. In northern Monterey Bay, California, USA, as much as 30% of the seafloor is buried or exposed seasonally, making this an ideal location to test how subtidal temperate rocky reef communities vary in the presence and absence of chronic sediment-based disturbances. Designated dynamic plots were naturally inundated by sediment in summer (50 to 100% cover) and swept clean in winter, whereas designated stable plots remained free of sediment during our study. Multivariate analyses indicated significant differences in the structure of sessile and mobile communities between dynamic and stable reef habitats. For sessile species, community structure in disturbed plots was less variable in space and time than in stable plots due to the maintenance of an early successional state. In contrast, community structure of mobile species varied more in disturbed plots than in stable plots, reflecting how mobile species distribute in response to sediment dynamics. Some species were found only in these disturbed areas, suggesting that the spatial mosaic of disturbance could increase regional diversity. We discuss how the relative ability of species to tolerate disturbance at different life history stages and their ability to colonize habitat translate into community-level differences among habitats, and how this response varies between mobile and sessile communities.

Quantifying the Adaptive Cycle | Science Inventory | US EPA

EPA Pesticide Factsheets

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

Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities

PubMed Central

Lindegren, Martin; Denker, Tim Spaanheden; Floeter, Jens; Fock, Heino O.; Sguotti, Camilla; Stäbler, Moritz; Otto, Saskia A.; Möllmann, Christian

2017-01-01

Understanding spatio-temporal dynamics of biotic communities containing large numbers of species is crucial to guide ecosystem management and conservation efforts. However, traditional approaches usually focus on studying community dynamics either in space or in time, often failing to fully account for interlinked spatio-temporal changes. In this study, we demonstrate and promote the use of tensor decomposition for disentangling spatio-temporal community dynamics in long-term monitoring data. Tensor decomposition builds on traditional multivariate statistics (e.g. Principal Component Analysis) but extends it to multiple dimensions. This extension allows for the synchronized study of multiple ecological variables measured repeatedly in time and space. We applied this comprehensive approach to explore the spatio-temporal dynamics of 65 demersal fish species in the North Sea, a marine ecosystem strongly altered by human activities and climate change. Our case study demonstrates how tensor decomposition can successfully (i) characterize the main spatio-temporal patterns and trends in species abundances, (ii) identify sub-communities of species that share similar spatial distribution and temporal dynamics, and (iii) reveal external drivers of change. Our results revealed a strong spatial structure in fish assemblages persistent over time and linked to differences in depth, primary production and seasonality. Furthermore, we simultaneously characterized important temporal distribution changes related to the low frequency temperature variability inherent in the Atlantic Multidecadal Oscillation. Finally, we identified six major sub-communities composed of species sharing similar spatial distribution patterns and temporal dynamics. Our case study demonstrates the application and benefits of using tensor decomposition for studying complex community data sets usually derived from large-scale monitoring programs. PMID:29136658

Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities.

PubMed

Frelat, Romain; Lindegren, Martin; Denker, Tim Spaanheden; Floeter, Jens; Fock, Heino O; Sguotti, Camilla; Stäbler, Moritz; Otto, Saskia A; Möllmann, Christian

2017-01-01

Understanding spatio-temporal dynamics of biotic communities containing large numbers of species is crucial to guide ecosystem management and conservation efforts. However, traditional approaches usually focus on studying community dynamics either in space or in time, often failing to fully account for interlinked spatio-temporal changes. In this study, we demonstrate and promote the use of tensor decomposition for disentangling spatio-temporal community dynamics in long-term monitoring data. Tensor decomposition builds on traditional multivariate statistics (e.g. Principal Component Analysis) but extends it to multiple dimensions. This extension allows for the synchronized study of multiple ecological variables measured repeatedly in time and space. We applied this comprehensive approach to explore the spatio-temporal dynamics of 65 demersal fish species in the North Sea, a marine ecosystem strongly altered by human activities and climate change. Our case study demonstrates how tensor decomposition can successfully (i) characterize the main spatio-temporal patterns and trends in species abundances, (ii) identify sub-communities of species that share similar spatial distribution and temporal dynamics, and (iii) reveal external drivers of change. Our results revealed a strong spatial structure in fish assemblages persistent over time and linked to differences in depth, primary production and seasonality. Furthermore, we simultaneously characterized important temporal distribution changes related to the low frequency temperature variability inherent in the Atlantic Multidecadal Oscillation. Finally, we identified six major sub-communities composed of species sharing similar spatial distribution patterns and temporal dynamics. Our case study demonstrates the application and benefits of using tensor decomposition for studying complex community data sets usually derived from large-scale monitoring programs.

Metabolic interactions and dynamics in microbial communities

NASA Astrophysics Data System (ADS)

Segre', Daniel

Metabolism, in addition to being the engine of every living cell, plays a major role in the cell-cell and cell-environment relations that shape the dynamics and evolution of microbial communities, e.g. by mediating competition and cross-feeding interactions between different species. Despite the increasing availability of metagenomic sequencing data for numerous microbial ecosystems, fundamental aspects of these communities, such as the unculturability of many isolates, and the conditions necessary for taxonomic or functional stability, are still poorly understood. We are developing mechanistic computational approaches for studying the interactions between different organisms based on the knowledge of their entire metabolic networks. In particular, we have recently built an open source platform for the Computation of Microbial Ecosystems in Time and Space (COMETS), which combines metabolic models with convection-diffusion equations to simulate the spatio-temporal dynamics of metabolism in microbial communities. COMETS has been experimentally tested on small artificial communities, and is scalable to hundreds of species in complex environments. I will discuss recent developments and challenges towards the implementation of models for microbiomes and synthetic microbial communities.

A comparative analysis of alternative approaches for quantifying nonlinear dynamics in cardiovascular system.

PubMed

Chen, Yun; Yang, Hui

2013-01-01

Heart rate variability (HRV) analysis has emerged as an important research topic to evaluate autonomic cardiac function. However, traditional time and frequency-domain analysis characterizes and quantify only linear and stationary phenomena. In the present investigation, we made a comparative analysis of three alternative approaches (i.e., wavelet multifractal analysis, Lyapunov exponents and multiscale entropy analysis) for quantifying nonlinear dynamics in heart rate time series. Note that these extracted nonlinear features provide information about nonlinear scaling behaviors and the complexity of cardiac systems. To evaluate the performance, we used 24-hour HRV recordings from 54 healthy subjects and 29 heart failure patients, available in PhysioNet. Three nonlinear methods are evaluated not only individually but also in combination using three classification algorithms, i.e., linear discriminate analysis, quadratic discriminate analysis and k-nearest neighbors. Experimental results show that three nonlinear methods capture nonlinear dynamics from different perspectives and the combined feature set achieves the best performance, i.e., sensitivity 97.7% and specificity 91.5%. Collectively, nonlinear HRV features are shown to have the promise to identify the disorders in autonomic cardiovascular function.

Quantifying relationships between bird and butterfly community shifts and environmental change.

PubMed

Debinski, Diane M; Vannimwegen, Ron E; Jakubauskas, Mark E

2006-02-01

Quantifying the manner in which ecological communities respond during a time of decreasing precipitation is a first step in understanding how they will respond to longer-term climate change. Here we coupled analysis of interannual variability in remotely sensed data with analyses of bird and butterfly community changes in montane meadow communities of the Greater Yellowstone Ecosystem. Landsat satellite imagery was used to classify these meadows into six types along a hydrological gradient. The northern portion of the ecosystem, or Gallatin region, has smaller mean patch sizes separated by ridges of mountains, whereas the southern portion of the ecosystem, or Teton region, has much larger patches within the Jackson Hole valley. Both support a similar suite of butterfly and bird species. The Gallatin region showed more overall among-year variation in the normalized difference vegetation index (NDVI) when meadow types were pooled within regions, perhaps because the patch sizes are smaller on average. Bird and butterfly communities showed significant relationships relative to meadow type and NDVI. We identified several key species that are tightly associated with specific meadow types along the hydrological gradient. Comparing taxonomic groups, fewer birds showed specific habitat affinities than butterflies, perhaps because birds are responding to differences in habitat structure among meadow types and using the landscape at a coarser scale than the butterflies. Comparing regions, the Teton region showed higher predictability of community assemblages as compared to the Gallatin region. The Gallatin region exhibited more significant temporal trends with respect to butterflies. Butterfly communities in wet meadows showed a distinctive shift along the hydrological gradient during a drought period (1997-2000). These results imply that the larger Teton meadows will show more predictable (i.e., static) species-habitat associations over the long term, but that the smaller

Quantifying carbon footprint reduction opportunities for U.S. households and communities.

PubMed

Jones, Christopher M; Kammen, Daniel M

2011-05-01

Carbon management is of increasing interest to individuals, households, and communities. In order to effectively assess and manage their climate impacts, individuals need information on the financial and greenhouse gas benefits of effective mitigation opportunities. We use consumption-based life cycle accounting techniques to quantify the carbon footprints of typical U.S. households in 28 cities for 6 household sizes and 12 income brackets. The model includes emissions embodied in transportation, energy, water, waste, food, goods, and services. We further quantify greenhouse gas and financial savings from 13 potential mitigation actions across all household types. The model suggests that the size and composition of carbon footprints vary dramatically between geographic regions and within regions based on basic demographic characteristics. Despite these differences, large cash-positive carbon footprint reductions are evident across all household types and locations; however, realizing this potential may require tailoring policies and programs to different population segments with very different carbon footprint profiles. The results of this model have been incorporated into an open access online carbon footprint management tool designed to enable behavior change at the household level through personalized feedback.

Quantifying human response capabilities towards tsunami threats at community level

NASA Astrophysics Data System (ADS)

Post, J.; Mück, M.; Zosseder, K.; Wegscheider, S.; Taubenböck, H.; Strunz, G.; Muhari, A.; Anwar, H. Z.; Birkmann, J.; Gebert, N.

2009-04-01

Decision makers at the community level need detailed information on tsunami risks in their area. Knowledge on potential hazard impact, exposed elements such as people, critical facilities and lifelines, people's coping capacity and recovery potential are crucial to plan precautionary measures for adaptation and to mitigate potential impacts of tsunamis on society and the environment. A crucial point within a people-centred tsunami risk assessment is to quantify the human response capabilities towards tsunami threats. Based on this quantification and spatial representation in maps tsunami affected and safe areas, difficult-to-evacuate areas, evacuation target points and evacuation routes can be assigned and used as an important contribution to e.g. community level evacuation planning. Major component in the quantification of human response capabilities towards tsunami impacts is the factor time. The human response capabilities depend on the estimated time of arrival (ETA) of a tsunami, the time until technical or natural warning signs (ToNW) can be received, the reaction time (RT) of the population (human understanding of a tsunami warning and the decision to take appropriate action), the evacuation time (ET, time people need to reach a safe area) and the actual available response time (RsT = ETA - ToNW - RT). If RsT is larger than ET, people in the respective areas are able to reach a safe area and rescue themselves. Critical areas possess RsT values equal or even smaller ET and hence people whin these areas will be directly affected by a tsunami. Quantifying the factor time is challenging and an attempt to this is presented here. The ETA can be derived by analyzing pre-computed tsunami scenarios for a respective area. For ToNW we assume that the early warning center is able to fulfil the Indonesian presidential decree to issue a warning within 5 minutes. RT is difficult as here human intrinsic factors as educational level, believe, tsunami knowledge and experience

Estimating Cyanobacteria Community Dynamics and its Relationship with Environmental Factors

PubMed Central

Luo, Wenhuai; Chen, Huirong; Lei, Anping; Lu, Jun; Hu, Zhangli

2014-01-01

The cyanobacteria community dynamics in two eutrophic freshwater bodies (Tiegang Reservoir and Shiyan Reservoir) was studied with both a traditional microscopic counting method and a PCR-DGGE genotyping method. Results showed that cyanobacterium Phormidium tenue was the predominant species; twenty-six cyanobacteria species were identified in water samples collected from the two reservoirs, among which fourteen were identified with the morphological method and sixteen with the PCR-DGGE method. The cyanobacteria community composition analysis showed a seasonal fluctuation from July to December. The cyanobacteria population peaked in August in both reservoirs, with cell abundances of 3.78 × 108 cells L-1 and 1.92 × 108 cells L-1 in the Tiegang and Shiyan reservoirs, respectively. Canonical Correspondence Analysis (CCA) was applied to further investigate the correlation between cyanobacteria community dynamics and environmental factors. The result indicated that the cyanobacteria community dynamics was mostly correlated with pH, temperature and total nitrogen. This study demonstrated that data obtained from PCR-DGGE combined with a traditional morphological method could reflect cyanobacteria community dynamics and its correlation with environmental factors in eutrophic freshwater bodies. PMID:24448632

Simulating Food Web Dynamics along a Gradient: Quantifying Human Influence

PubMed Central

Jordán, Ferenc; Gjata, Nerta; Mei, Shu; Yule, Catherine M.

2012-01-01

Realistically parameterized and dynamically simulated food-webs are useful tool to explore the importance of the functional diversity of ecosystems, and in particular relations between the dynamics of species and the whole community. We present a stochastic dynamical food web simulation for the Kelian River (Borneo). The food web was constructed for six different locations, arrayed along a gradient of increasing human perturbation (mostly resulting from gold mining activities) along the river. Along the river, the relative importance of grazers, filterers and shredders decreases with increasing disturbance downstream, while predators become more dominant in governing eco-dynamics. Human activity led to increased turbidity and sedimentation which adversely impacts primary productivity. Since the main difference between the study sites was not the composition of the food webs (structure is quite similar) but the strengths of interactions and the abundance of the trophic groups, a dynamical simulation approach seemed to be useful to better explain human influence. In the pristine river (study site 1), when comparing a structural version of our model with the dynamical model we found that structurally central groups such as omnivores and carnivores were not the most important ones dynamically. Instead, primary consumers such as invertebrate grazers and shredders generated a greater dynamical response. Based on the dynamically most important groups, bottom-up control is replaced by the predominant top-down control regime as distance downstream and human disturbance increased. An important finding, potentially explaining the poor structure to dynamics relationship, is that indirect effects are at least as important as direct ones during the simulations. We suggest that our approach and this simulation framework could serve systems-based conservation efforts. Quantitative indicators on the relative importance of trophic groups and the mechanistic modeling of eco-dynamics

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

DOE PAGES

Sippel, Sebastian; Lange, Holger; Mahecha, Miguel D.; ...

2016-10-20

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observedmore » and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sippel, Sebastian; Lange, Holger; Mahecha, Miguel D.

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observedmore » and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

PubMed Central

Sippel, Sebastian; Mahecha, Miguel D.; Hauhs, Michael; Bodesheim, Paul; Kaminski, Thomas; Gans, Fabian; Rosso, Osvaldo A.

2016-01-01

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observed and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. We demonstrate here that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time

Global change and terrestrial plant community dynamics

DOE PAGES

Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.; ...

2016-02-29

Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this article, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on amore » literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Lastly, monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change.« less

Global change and terrestrial plant community dynamics

PubMed Central

Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.; Regan, Helen M.

2016-01-01

Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this paper, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on a literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change. PMID:26929338

Underrepresented Minority Dentists: Quantifying Their Numbers And Characterizing The Communities They Serve

PubMed Central

Mertz, Elizabeth A.; Wides, Cynthia; Kottek, Aubri; Calvo, Jean Marie; Gates, Paul E.

2017-01-01

The underrepresentation of Blacks, Hispanics or Latinos, and American Indians or Alaska Natives among dentists raises concerns about the diversity of the dental workforce, disparities in access to dental care and in oral health status, and social justice. We quantified the shortage of underrepresented minority dentists and examined these dentists’ practice patterns in relation to the characteristics of the communities they serve. The underrepresented minority dentist workforce is disproportionately smaller than, and unevenly distributed in relation to, minority populations in the United States. Members of minority groups represent larger shares of these dentists’ patient panels than of the populations in the communities where the dentists are located. Compared to counties with no underrepresented minority dentists, counties with one or more such dentists are more racially diverse and affluent but also have greater economic and social inequality. Current policy approaches to improve the diversity of the dental workforce are a critical first step, but more must be done to improve equity in dental health. PMID:27920306

Preliminary evaluation of an in vivo fluorometer to quantify algal periphyton biomass and community composition

USGS Publications Warehouse

Harris, Theodore D.; Graham, Jennifer L.

2015-01-01

The bbe-Moldaenke BenthoTorch (BT) is an in vivo fluorometer designed to quantify algal biomass and community composition in benthic environments. The BT quantifies total algal biomass via chlorophyll a (Chl-a) concentration and may differentiate among cyanobacteria, green algae, and diatoms based on pigment fluorescence. To evaluate how BT measurements of periphytic algal biomass (as Chl-a) compared with an ethanol extraction laboratory analysis, we collected BT- and laboratory-measured Chl-a data from 6 stream sites in the Indian Creek basin, Johnson County, Kansas, during August and September 2012. BT-measured Chl-a concentrations were positively related to laboratory-measured concentrations (R2 = 0.47); sites with abundant filamentous algae had weaker relations (R2 = 0.27). Additionally, on a single sample date, we used the BT to determine periphyton biomass and community composition upstream and downstream from 2 wastewater treatment facilities (WWTF) that discharge into Indian Creek. We found that algal biomass increased immediately downstream from the WWTF discharge then slowly decreased as distance from the WWTF increased. Changes in periphyton community structure also occurred; however, there were discrepancies between BT- and laboratory-measured community composition data. Most notably, cyanobacteria were present at all sites based on BT measurements but were present at only one site based on laboratory-analyzed samples. Overall, we found that the BT compared reasonably well with laboratory methods for relative patterns in Chl-a but not as well with absolute Chl-aconcentrations. Future studies need to test the BT over a wider range of Chl-aconcentrations, in colored waters, and across various periphyton assemblages.

Coastal oceanography sets the pace of rocky intertidal community dynamics.

PubMed

Menge, B A; Lubchenco, J; Bracken, M E S; Chan, F; Foley, M M; Freidenburg, T L; Gaines, S D; Hudson, G; Krenz, C; Leslie, H; Menge, D N L; Russell, R; Webster, M S

2003-10-14

The structure of ecological communities reflects a tension among forces that alter populations. Marine ecologists previously emphasized control by locally operating forces (predation, competition, and disturbance), but newer studies suggest that inputs from large-scale oceanographically modulated subsidies (nutrients, particulates, and propagules) can strongly influence community structure and dynamics. On New Zealand rocky shores, the magnitude of such subsidies differs profoundly between contrasting oceanographic regimes. Community structure, and particularly the pace of community dynamics, differ dramatically between intermittent upwelling regimes compared with relatively persistent down-welling regimes. We suggest that subsidy rates are a key determinant of the intensity of species interactions, and thus of structure in marine systems, and perhaps also nonmarine communities.

Dynamics of sustained use and abandonment of clean cooking systems: study protocol for community-based system dynamics modeling.

PubMed

Kumar, Praveen; Chalise, Nishesh; Yadama, Gautam N

2016-04-26

More than 3 billion of the world's population are affected by household air pollution from relying on unprocessed solid fuels for heating and cooking. Household air pollution is harmful to human health, climate, and environment. Sustained uptake and use of cleaner cooking technologies and fuels are proposed as solutions to this problem. In this paper, we present our study protocol aimed at understanding multiple interacting feedback mechanisms involved in the dynamic behavior between social, ecological, and technological systems driving sustained use or abandonment of cleaner cooking technologies among the rural poor in India. This study uses a comparative case study design to understand the dynamics of sustained use or abandonment of cleaner cooking technologies and fuels in four rural communities of Rajasthan, India. The study adopts a community based system dynamics modeling approach. We describe our approach of using community based system dynamics with rural communities to delineate the feedback mechanisms involved in the uptake and sustainment of clean cooking technologies. We develop a reference mode with communities showing the trend over time of use or abandonment of cleaner cooking technologies and fuels in these communities. Subsequently, the study develops a system dynamics model with communities to understand the complex sub-systems driving the behavior in these communities as reflected in the reference mode. We use group model building techniques to facilitate participation of relevant stakeholders in the four communities and elicit a narrative describing the feedback mechanisms underlying sustained adoption or abandonment of cleaner cooking technologies. In understanding the dynamics of feedback mechanisms in the uptake and exclusive use of cleaner cooking systems, we increase the likelihood of dissemination and implementation of efficacious interventions into everyday settings to improve the health and wellbeing of women and children most affected

Navigating the Power Dynamics between Institutions and Their Communities

ERIC Educational Resources Information Center

White, Byron P.

2009-01-01

The author's career experiences--as an impartial observer of community building, as an advocate working from within urban communities, and as a catalyst working from the outside--have given him a unique perspective into the dynamics of institutional/community engagement. "Basically, they have left me with three overriding convictions. First,…

PCB Food Web Dynamics Quantify Nutrient and Energy Flow in Aquatic Ecosystems.

PubMed

McLeod, Anne M; Paterson, Gordon; Drouillard, Ken G; Haffner, G Douglas

2015-11-03

Measuring in situ nutrient and energy flows in spatially and temporally complex aquatic ecosystems represents a major ecological challenge. Food web structure, energy and nutrient budgets are difficult to measure, and it is becoming more important to quantify both energy and nutrient flow to determine how food web processes and structure are being modified by multiple stressors. We propose that polychlorinated biphenyl (PCB) congeners represent an ideal tracer to quantify in situ energy and nutrient flow between trophic levels. Here, we demonstrate how an understanding of PCB congener bioaccumulation dynamics provides multiple direct measurements of energy and nutrient flow in aquatic food webs. To demonstrate this novel approach, we quantified nitrogen (N), phosphorus (P) and caloric turnover rates for Lake Huron lake trout, and reveal how these processes are regulated by both growth rate and fish life history. Although minimal nutrient recycling was observed in young growing fish, slow growing, older lake trout (>5 yr) recycled an average of 482 Tonnes·yr(-1) of N, 45 Tonnes·yr(-1) of P and assimilated 22 TJ yr(-1) of energy. Compared to total P loading rates of 590 Tonnes·yr(-1), the recycling of primarily bioavailable nutrients by fish plays an important role regulating the nutrient states of oligotrophic lakes.

Game theory and extremal optimization for community detection in complex dynamic networks.

PubMed

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.

Hotspots of Community Change: Temporal Dynamics Are Spatially Variable in Understory Plant Composition of a California Oak Woodland

PubMed Central

Spotswood, Erica N.; Bartolome, James W.; Allen-Diaz, Barbara

2015-01-01

Community response to external drivers such climate and disturbance can lead to fluctuations in community composition, or to directional change. Temporal dynamics can be influenced by a combination of drivers operating at multiple spatial scales, including external landscape scale drivers, local abiotic conditions, and local species pools. We hypothesized that spatial variation in these factors can create heterogeneity in temporal dynamics within landscapes. We used understory plant species composition from an 11 year dataset from a California oak woodland to compare plots where disturbance was experimentally manipulated with the removal of livestock grazing and a prescribed burn. We quantified three properties of temporal variation: compositional change (reflecting the appearance and disappearance of species), temporal fluctuation, and directional change. Directional change was related most strongly to disturbance type, and was highest at plots where grazing was removed during the study. Temporal fluctuations, compositional change, and directional change were all related to intrinsic abiotic factors, suggesting that some locations are more responsive to external drivers than others. Temporal fluctuations and compositional change were linked to local functional composition, indicating that environmental filters can create subsets of the local species pool that do not respond in the same way to external drivers. Temporal dynamics are often assumed to be relatively static at the landscape scale, provided disturbance and climate are continuous. This study shows that local and landscape scale factors jointly influence temporal dynamics creating hotspots that are particularly responsive to climate and disturbance. Thus, adequate predictions of response to disturbance or to changing climate will only be achieved by considering how factors at multiple spatial scales influence community resilience and recovery. PMID:26222069

Hotspots of Community Change: Temporal Dynamics Are Spatially Variable in Understory Plant Composition of a California Oak Woodland.

PubMed

Spotswood, Erica N; Bartolome, James W; Allen-Diaz, Barbara

2015-01-01

Community response to external drivers such climate and disturbance can lead to fluctuations in community composition, or to directional change. Temporal dynamics can be influenced by a combination of drivers operating at multiple spatial scales, including external landscape scale drivers, local abiotic conditions, and local species pools. We hypothesized that spatial variation in these factors can create heterogeneity in temporal dynamics within landscapes. We used understory plant species composition from an 11 year dataset from a California oak woodland to compare plots where disturbance was experimentally manipulated with the removal of livestock grazing and a prescribed burn. We quantified three properties of temporal variation: compositional change (reflecting the appearance and disappearance of species), temporal fluctuation, and directional change. Directional change was related most strongly to disturbance type, and was highest at plots where grazing was removed during the study. Temporal fluctuations, compositional change, and directional change were all related to intrinsic abiotic factors, suggesting that some locations are more responsive to external drivers than others. Temporal fluctuations and compositional change were linked to local functional composition, indicating that environmental filters can create subsets of the local species pool that do not respond in the same way to external drivers. Temporal dynamics are often assumed to be relatively static at the landscape scale, provided disturbance and climate are continuous. This study shows that local and landscape scale factors jointly influence temporal dynamics creating hotspots that are particularly responsive to climate and disturbance. Thus, adequate predictions of response to disturbance or to changing climate will only be achieved by considering how factors at multiple spatial scales influence community resilience and recovery.

Dynamics and control of diseases in networks with community structure.

PubMed

Salathé, Marcel; Jones, James H

2010-04-08

The dynamics of infectious diseases spread via direct person-to-person transmission (such as influenza, smallpox, HIV/AIDS, etc.) depends on the underlying host contact network. Human contact networks exhibit strong community structure. Understanding how such community structure affects epidemics may provide insights for preventing the spread of disease between communities by changing the structure of the contact network through pharmaceutical or non-pharmaceutical interventions. We use empirical and simulated networks to investigate the spread of disease in networks with community structure. We find that community structure has a major impact on disease dynamics, and we show that in networks with strong community structure, immunization interventions targeted at individuals bridging communities are more effective than those simply targeting highly connected individuals. Because the structure of relevant contact networks is generally not known, and vaccine supply is often limited, there is great need for efficient vaccination algorithms that do not require full knowledge of the network. We developed an algorithm that acts only on locally available network information and is able to quickly identify targets for successful immunization intervention. The algorithm generally outperforms existing algorithms when vaccine supply is limited, particularly in networks with strong community structure. Understanding the spread of infectious diseases and designing optimal control strategies is a major goal of public health. Social networks show marked patterns of community structure, and our results, based on empirical and simulated data, demonstrate that community structure strongly affects disease dynamics. These results have implications for the design of control strategies.

Reserve size and fragmentation alter community assembly, diversity, and dynamics.

PubMed

Lasky, Jesse R; Keitt, Timothy H

2013-11-01

Researchers have disputed whether a single large habitat reserve will support more species than many small reserves. However, relatively little is known from a theoretical perspective about how reserve size affects competitive communities structured by spatial abiotic gradients. We investigate how reserve size affects theoretical communities whose assembly is governed by dispersal limitation, abiotic niche differentiation, and source-sink dynamics. Simulations were conducted with varying scales of dispersal across landscapes with variable environmental spatial autocorrelation. Landscapes were inhabited by simulated trees with seedling and adult stages. For a fixed total area in reserves, we found that small reserve systems increased the distance between environments dominated by different species, diminishing the effects of source-sink dynamics. As reserve size decreased, environmental limitations to community assembly became stronger, α species richness decreased, and γ richness increased. When dispersal occurred across short distances, a large reserve strategy caused greater stochastic community variation, greater α richness, and lower γ richness than in small reserve systems. We found that reserve size variation trades off between preserving different aspects of natural communities, including α diversity versus γ diversity. Optimal reserve size will depend on the importance of source-sink dynamics and the value placed on different characteristics of natural communities. Anthropogenic changes to the size and separation of remnant habitats can have far-reaching effects on community structure and assembly.

Contribution of sea ice microbial production to Antarctic benthic communities is driven by sea ice dynamics and composition of functional guilds.

PubMed

Wing, Stephen R; Leichter, James J; Wing, Lucy C; Stokes, Dale; Genovese, Sal J; McMullin, Rebecca M; Shatova, Olya A

2018-04-28

Organic matter produced by the sea ice microbial community (SIMCo) is an important link between sea ice dynamics and secondary production in near-shore food webs of Antarctica. Sea ice conditions in McMurdo Sound were quantified from time series of MODIS satellite images for Sept. 1 through Feb. 28 of 2007-2015. A predictable sea ice persistence gradient along the length of the Sound and evidence for a distinct change in sea ice dynamics in 2011 were observed. We used stable isotope analysis (δ 13 C and δ 15 N) of SIMCo, suspended particulate organic matter (SPOM) and shallow water (10-20 m) macroinvertebrates to reveal patterns in trophic structure of, and incorporation of organic matter from SIMCo into, benthic communities at eight sites distributed along the sea ice persistence gradient. Mass-balance analysis revealed distinct trophic architecture among communities and large fluxes of SIMCo into the near-shore food web, with the estimates ranging from 2 to 84% of organic matter derived from SIMCo for individual species. Analysis of patterns in density, and biomass of macroinvertebrate communities among sites allowed us to model net incorporation of organic matter from SIMCo, in terms of biomass per unit area (g/m 2 ), into benthic communities. Here, organic matter derived from SIMCo supported 39 to 71 per cent of total biomass. Furthermore, for six species, we observed declines in contribution of SIMCo between years with persistent sea ice (2008-2009) and years with extensive sea ice breakout (2012-2015). Our data demonstrate the vital role of SIMCo in ecosystem function in Antarctica and strong linkages between sea ice dynamics and near-shore secondary productivity. These results have important implications for our understanding of how benthic communities will respond to changes in sea ice dynamics associated with climate change and highlight the important role of shallow water macroinvertebrate communities as sentinels of change for the Antarctic marine

Underrepresented Minority Dentists: Quantifying Their Numbers And Characterizing The Communities They Serve.

PubMed

Mertz, Elizabeth A; Wides, Cynthia D; Kottek, Aubri M; Calvo, Jean Marie; Gates, Paul E

2016-12-01

The underrepresentation of Blacks, Hispanics or Latinos, and American Indians or Alaska Natives among dentists raises concerns about the diversity of the dental workforce, disparities in access to dental care and in oral health status, and social justice. We quantified the shortage of underrepresented minority dentists and examined these dentists' practice patterns in relation to the characteristics of the communities they serve. The underrepresented minority dentist workforce is disproportionately smaller than, and unevenly distributed in relation to, minority populations in the United States. Members of minority groups represent larger shares of these dentists' patient panels than of the populations in the communities where the dentists are located. Compared to counties with no underrepresented minority dentists, counties with one or more such dentists are more racially diverse and affluent but also have greater economic and social inequality. Current policy approaches to improve the diversity of the dental workforce are a critical first step, but more must be done to improve equity in dental health. Project HOPE—The People-to-People Health Foundation, Inc.

Quantifying biological integrity of California sage scrub communities using plant life-form cover.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamada, Y.; Stow, D. A.; Franklin, J.

2010-01-01

The California sage scrub (CSS) community type in California's Mediterranean-type ecosystems supports a large number of rare, threatened, and endangered species, and is critically degraded and endangered. Monitoring ecological variables that provide information about community integrity is vital to conserving these biologically diverse communities. Fractional cover of true shrub, subshrub, herbaceous vegetation, and bare ground should fill information gaps between generalized vegetation type maps and detailed field-based plot measurements of species composition and provide an effective means for quantifying CSS community integrity. Remote sensing is the only tool available for estimating spatially comprehensive fractional cover over large extent, and fractionalmore » cover of plant life-form types is one of the measures of vegetation state that is most amenable to remote sensing. The use of remote sensing does not eliminate the need for either field surveying or vegetation type mapping; rather it will likely require a combination of approaches to reliably estimate life-form cover and to provide comprehensive information for communities. According to our review and synthesis, life-form fractional cover has strong potential for providing ecologically meaningful intermediate-scale information, which is unattainable from vegetation type maps and species-level field measurements. Thus, we strongly recommend incorporating fractional cover of true shrub, subshrub, herb, and bare ground in CSS community monitoring methods. Estimating life-form cover at a 25 m x 25 m spatial scale using remote sensing would be an appropriate approach for initial implementation. Investigation of remote sensing techniques and an appropriate spatial scale; collaboration of resource managers, biologists, and remote sensing specialists, and refinement of protocols are essential for integrating life-form fractional cover mapping into strategies for sustainable long-term CSS community management.« less

Accurate detection of hierarchical communities in complex networks based on nonlinear dynamical evolution

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

Quantifying the dynamics of emotional expressions in family therapy of patients with anorexia nervosa.

PubMed

Pezard, Laurent; Doba, Karyn; Lesne, Annick; Nandrino, Jean-Louis

2017-07-01

Emotional interactions have been considered dynamical processes involved in the affective life of humans and their disturbances may induce mental disorders. Most studies of emotional interactions have focused on dyadic behaviors or self-reports of emotional states but neglected the dynamical processes involved in family therapy. The main objective of this study is to quantify the dynamics of emotional expressions and their changes using the family therapy of patients with anorexia nervosa as an example. Nonlinear methods characterize the variability of the dynamics at the level of the whole therapeutic system and reciprocal influence between the participants during family therapy. Results show that the variability of the dynamics is higher at the end of the therapy than at the beginning. The reciprocal influences between therapist and each member of the family and between mother and patient decrease with the course of family therapy. Our results support the development of new interpersonal strategies of emotion regulation during family therapy. The quantification of emotional dynamics can help understanding the emotional processes underlying psychopathology and evaluating quantitatively the changes achieved by the therapeutic intervention. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Community helping services: dynamic of formation and expressiveness of the cultural care.

PubMed

Landim, Fátima Luna Pinheiro

2006-01-01

Community helping services is an expression used by the social movements to designate families that live in shacks installed in a public area intended for building of own house at a community helping system. Studies in ethnonursing that aimed: in order to detail dynamic configuration in a community helping service. It took place in an community helping area located in the outskirts of Fortaleza, Ceará. The community members acting as general informants from the local culture, while eight (8) women heads-of-families, working as key informers. The data collect used the Observation-Participation-Reflection Model. The analyses were processing by the time that the dates were collected, considering the categories: inserting in the community helping culture to obtain their history; community helping is not a slum -describing the formation dynamic. Established that the formation dynamic of the community helping go on the own house representation as a symbol of " a better life". To assimilate such expression introducing in own cultural universe is a challenge for the nursing to assist a care culture congruent.

A novel dynamical community detection algorithm based on weighting scheme

NASA Astrophysics Data System (ADS)

Li, Ju; Yu, Kai; Hu, Ke

2015-12-01

Network dynamics plays an important role in analyzing the correlation between the function properties and the topological structure. In this paper, we propose a novel dynamical iteration (DI) algorithm, which incorporates the iterative process of membership vector with weighting scheme, i.e. weighting W and tightness T. These new elements can be used to adjust the link strength and the node compactness for improving the speed and accuracy of community structure detection. To estimate the optimal stop time of iteration, we utilize a new stability measure which is defined as the Markov random walk auto-covariance. We do not need to specify the number of communities in advance. It naturally supports the overlapping communities by associating each node with a membership vector describing the node's involvement in each community. Theoretical analysis and experiments show that the algorithm can uncover communities effectively and efficiently.

Analyzing complex networks evolution through Information Theory quantifiers

NASA Astrophysics Data System (ADS)

Carpi, Laura C.; Rosso, Osvaldo A.; Saco, Patricia M.; Ravetti, Martín Gómez

2011-01-01

A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Niño/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution.

Belowground Controls on the Dynamics of Plant Communities

NASA Astrophysics Data System (ADS)

Sivandran, G.

2013-12-01

Arid regions are characterized by high variability in the arrival of rainfall, and species found in these areas have adapted mechanisms to ensure the capture of this scarce resource. In particular, the rooting strategies employed by vegetation can be critical to their survival. These rooting strategies also dictate the competitive outcomes within plant communities. A dynamic rooting scheme was incorporated into tRIBS+VEGGIE (a physically-based, distributed ecohydrologic model). The dynamic rooting scheme allows vegetation the freedom to alter its rooting profile in response to changes in rainfall and soil conditions, in a way that more closely mimics observed phenotypic plasticity. A simple competition-colonization model was combined with the new dynamic root scheme to explore the role of root adaptability in plant competition and landscape evolution in semi-arid environments. The influence of model representation of rooting strategy on the long term plant community composition

Quantifying archaeal community autotrophy in the mesopelagic ocean using natural radiocarbon

PubMed Central

Ingalls, Anitra E.; Shah, Sunita R.; Hansman, Roberta L.; Aluwihare, Lihini I.; Santos, Guaciara M.; Druffel, Ellen R. M.; Pearson, Ann

2006-01-01

An ammonia-oxidizing, carbon-fixing archaeon, Candidatus “Nitrosopumilus maritimus,” recently was isolated from a salt-water aquarium, definitively confirming that chemoautotrophy exists among the marine archaea. However, in other incubation studies, pelagic archaea also were capable of using organic carbon. It has remained unknown what fraction of the total marine archaeal community is autotrophic in situ. If archaea live primarily as autotrophs in the natural environment, a large ammonia-oxidizing population would play a significant role in marine nitrification. Here we use the natural distribution of radiocarbon in archaeal membrane lipids to quantify the bulk carbon metabolism of archaea at two depths in the subtropical North Pacific gyre. Our compound-specific radiocarbon data show that the archaea in surface waters incorporate modern carbon into their membrane lipids, and archaea at 670 m incorporate carbon that is slightly more isotopically enriched than inorganic carbon at the same depth. An isotopic mass balance model shows that the dominant metabolism at depth indeed is autotrophy (83%), whereas heterotrophic consumption of modern organic carbon accounts for the remainder of archaeal biomass. These results reflect the in situ production of the total community that produces tetraether lipids and are not subject to biases associated with incubation and/or culture experiments. The data suggest either that the marine archaeal community includes both autotrophs and heterotrophs or is a single population with a uniformly mixotrophic metabolism. The metabolic and phylogenetic diversity of the marine archaea warrants further exploration; these organisms may play a major role in the marine cycles of nitrogen and carbon. PMID:16614070

Jellyfish modulate bacterial dynamic and community structure.

PubMed

Tinta, Tinkara; Kogovšek, Tjaša; Malej, Alenka; Turk, Valentina

2012-01-01

Jellyfish blooms have increased in coastal areas around the world and the outbreaks have become longer and more frequent over the past few decades. The Mediterranean Sea is among the heavily affected regions and the common bloom-forming taxa are scyphozoans Aurelia aurita s.l., Pelagia noctiluca, and Rhizostoma pulmo. Jellyfish have few natural predators, therefore their carcasses at the termination of a bloom represent an organic-rich substrate that supports rapid bacterial growth, and may have a large impact on the surrounding environment. The focus of this study was to explore whether jellyfish substrate have an impact on bacterial community phylotype selection. We conducted in situ jellyfish-enrichment experiment with three different jellyfish species. Bacterial dynamic together with nutrients were monitored to assess decaying jellyfish-bacteria dynamics. Our results show that jellyfish biomass is characterized by protein rich organic matter, which is highly bioavailable to 'jellyfish-associated' and 'free-living' bacteria, and triggers rapid shifts in bacterial population dynamics and composition. Based on 16S rRNA clone libraries and denaturing gradient gel electrophoresis (DGGE) analysis, we observed a rapid shift in community composition from unculturable Alphaproteobacteria to culturable species of Gammaproteobacteria and Flavobacteria. The results of sequence analyses of bacterial isolates and of total bacterial community determined by culture independent genetic analysis showed the dominance of the Pseudoalteromonadaceae and the Vibrionaceae families. Elevated levels of dissolved proteins, dissolved organic and inorganic nutrient release, bacterial abundance and carbon production as well as ammonium concentrations characterized the degradation process. The biochemical composition of jellyfish species may influence changes in the amount of accumulated dissolved organic and inorganic nutrients. Our results can contribute insights into possible changes in

Mathematical Modeling of Microbial Community Dynamics: A Methodological Review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Hyun-Seob; Cannon, William R.; Beliaev, Alex S.

Microorganisms in nature form diverse communities that dynamically change in structure and function in response to environmental variations. As a complex adaptive system, microbial communities show higher-order properties that are not present in individual microbes, but arise from their interactions. Predictive mathematical models not only help to understand the underlying principles of the dynamics and emergent properties of natural and synthetic microbial communities, but also provide key knowledge required for engineering them. In this article, we provide an overview of mathematical tools that include not only current mainstream approaches, but also less traditional approaches that, in our opinion, can bemore » potentially useful. We discuss a broad range of methods ranging from low-resolution supra-organismal to high-resolution individual-based modeling. Particularly, we highlight the integrative approaches that synergistically combine disparate methods. In conclusion, we provide our outlook for the key aspects that should be further developed to move microbial community modeling towards greater predictive power.« less

Advances in the use of DNA barcodes to build a community phylogeny for tropical trees in a Puerto Rican forest dynamics plot.

PubMed

Kress, W John; Erickson, David L; Swenson, Nathan G; Thompson, Jill; Uriarte, Maria; Zimmerman, Jess K

2010-11-09

Species number, functional traits, and phylogenetic history all contribute to characterizing the biological diversity in plant communities. The phylogenetic component of diversity has been particularly difficult to quantify in species-rich tropical tree assemblages. The compilation of previously published (and often incomplete) data on evolutionary relationships of species into a composite phylogeny of the taxa in a forest, through such programs as Phylomatic, has proven useful in building community phylogenies although often of limited resolution. Recently, DNA barcodes have been used to construct a robust community phylogeny for nearly 300 tree species in a forest dynamics plot in Panama using a supermatrix method. In that study sequence data from three barcode loci were used to generate a well-resolved species-level phylogeny. Here we expand upon this earlier investigation and present results on the use of a phylogenetic constraint tree to generate a community phylogeny for a diverse, tropical forest dynamics plot in Puerto Rico. This enhanced method of phylogenetic reconstruction insures the congruence of the barcode phylogeny with broadly accepted hypotheses on the phylogeny of flowering plants (i.e., APG III) regardless of the number and taxonomic breadth of the taxa sampled. We also compare maximum parsimony versus maximum likelihood estimates of community phylogenetic relationships as well as evaluate the effectiveness of one- versus two- versus three-gene barcodes in resolving community evolutionary history. As first demonstrated in the Panamanian forest dynamics plot, the results for the Puerto Rican plot illustrate that highly resolved phylogenies derived from DNA barcode sequence data combined with a constraint tree based on APG III are particularly useful in comparative analysis of phylogenetic diversity and will enhance research on the interface between community ecology and evolution.

Occupancy dynamics in a tropical bird community: unexpectedly high forest use by birds classified as non-forest species

USGS Publications Warehouse

Ruiz-Gutierrez, Viviana; Zipkin, Elise F.; Dhondt, Andre A.

2010-01-01

1. Worldwide loss of biodiversity necessitates a clear understanding of the factors driving population declines as well as informed predictions about which species and populations are at greatest risk. The biggest threat to the long-term persistence of populations is the reduction and changes in configuration of their natural habitat. 2. Inconsistencies have been noted in the responses of populations to the combined effects of habitat loss and fragmentation. These have been widely attributed to the effects of the matrix habitats in which remnant focal habitats are typically embedded. 3. We quantified the potential effects of the inter-patch matrix by estimating occupancy and colonization of forest and surrounding non-forest matrix (NF). We estimated species-specific parameters using a dynamic, multi-species hierarchical model on a bird community in southwestern Costa Rica. 4. Overall, we found higher probabilities of occupancy and colonization of forest relative to the NF across bird species, including those previously categorized as open habitat generalists not needing forest to persist. Forest dependency was a poor predictor of occupancy dynamics in our study region, largely predicting occupancy and colonization of only non-forest habitats. 5. Our results indicate that the protection of remnant forest habitats is key for the long-term persistence of all members of the bird community in this fragmented landscape, including species typically associated with open, non-forest habitats. 6.Synthesis and applications. We identified 39 bird species of conservation concern defined by having high estimates of forest occupancy, and low estimates of occupancy and colonization of non-forest. These species survive in forest but are unlikely to venture out into open, non-forested habitats, therefore, they are vulnerable to the effects of habitat loss and fragmentation. Our hierarchical community-level model can be used to estimate species-specific occupancy dynamics for focal

Quantifying the Human Impacts on Papua New Guinea Reef Fish Communities across Space and Time.

PubMed

Drew, Joshua A; Amatangelo, Kathryn L; Hufbauer, Ruth A

2015-01-01

Describing the drivers of species loss and of community change are important goals in both conservation and ecology. However, it is difficult to determine whether exploited species decline due to direct effects of harvesting or due to other environmental perturbations brought about by proximity to human populations. Here we quantify differences in species richness of coral reef fish communities along a human population gradient in Papua New Guinea to understand the relative impacts of fishing and environmental perturbation. Using data from published species lists we categorize the reef fishes as either fished or non-fished based on their body size and reports from the published literature. Species diversity for both fished and non-fished groups decreases as the size of the local human population increases, and this relationship is stronger in species that are fished. Additionally, comparison of modern and museum collections show that modern reef communities have proportionally fewer fished species relative to 19th century ones. Together these findings show that the reef fish communities of Papua New Guinea experience multiple anthropogenic stressors and that even at low human population levels targeted species experience population declines across both time and space.

SCOUT: simultaneous time segmentation and community detection in dynamic networks

PubMed Central

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

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.

The Bird Community Resilience Index: a novel remote sensing-based biodiversity variable for quantifying ecological integrity

NASA Astrophysics Data System (ADS)

Michel, N. L.; Wilsey, C.; Burkhalter, C.; Trusty, B.; Langham, G.

2017-12-01

Scalable indicators of biodiversity change are critical to reporting overall progress towards national and global targets for biodiversity conservation (e.g. Aichi Targets) and sustainable development (SDGs). These essential biodiversity variables capitalize on new remote sensing technologies and growth of community science participation. Here we present a novel biodiversity metric quantifying resilience of bird communities and, by extension, of their associated ecological communities. This metric adds breadth to the community composition class of essential biodiversity variables that track trends in condition and vulnerability of ecological communities. We developed this index for use with North American grassland birds, a guild that has experienced stronger population declines than any other avian guild, in order to evaluate gains from the implementation of best management practices on private lands. The Bird Community Resilience Index was designed to incorporate the full suite of species-specific responses to management actions, and be flexible enough to work across broad climatic, land cover, and bird community gradients (i.e., grasslands from northern Mexico through Canada). The Bird Community Resilience Index consists of four components: density estimates of grassland and arid land birds; weighting based on conservation need; a functional diversity metric to incorporate resiliency of bird communities and their ecosystems; and a standardized scoring system to control for interannual variation caused by extrinsic factors (e.g., climate). We present an analysis of bird community resilience across ranches in the Northern Great Plains region of the United States. As predicted, Bird Community Resilience was higher in lands implementing best management practices than elsewhere. While developed for grassland birds, this metric holds great potential for use as an Essential Biodiversity Variable for community composition in a variety of habitat.

Quantifying long-term trajectories of plant community change with movement models: implication for ecological resilience

USDA-ARS?s Scientific Manuscript database

Quantification of rates and patterns of community dynamics is central for understanding the organization and function of ecosystems. These insights may support a greater empirical understanding of ecological resilience, and the application of resilience concepts toward ecosystem management. Distinct...

Quantifying the effects of overgrazing on mountainous watershed vegetation dynamics under a changing climate.

PubMed

Hao, Lu; Pan, Cen; Fang, Di; Zhang, Xiaoyu; Zhou, Decheng; Liu, Peilong; Liu, Yongqiang; Sun, Ge

2018-10-15

Grazing is a major ecosystem disturbance in arid regions that are increasingly threatened by climate change. Understanding the long-term impacts of grazing on rangeland vegetation dynamics in a complex terrain in mountainous regions is important for quantifying dry land ecosystem services for integrated watershed management and climate change adaptation. However, data on the detailed long-term spatial distribution of grazing activities are rare, which prevents trend detection and environmental impact assessments of grazing. This study quantified the impacts of grazing on vegetation dynamics for the period of 1983-2010 in the Upper Heihe River basin, a complex multiple-use watershed in northwestern China. We also examined the relative contributions of grazing and climate to vegetation change using a dynamic grazing pressure method. Spatial grazing patterns and temporal dynamics were mapped at a 1 km × 1 km pixel scale using satellite-derived leaf area index (LAI) data. We found that overgrazing was a dominant driver for LAI reduction in alpine grasslands and shrubs, especially for the periods of 1985-1991 and 1997-2004. Although the recent decade-long active grazing management contributed to the improvement of LAI and partially offset the negative effects of increased livestock, overgrazing has posed significant challenges to shrub-grassland ecosystem recovery in the eastern part of the study basin. We conclude that the positive effects of a warming and wetting climate on vegetation could be underestimated if the negative long-term grazing effects are not considered. Findings from the present case study show that assessing long-term climate change impacts on watersheds must include the influences of human activities. Our study provides important guidance for ecological restoration efforts in locating vulnerable areas and designing effective management practices in the study watershed. Such information is essential for natural resource management that aims

Social Information Links Individual Behavior to Population and Community Dynamics.

PubMed

Gil, Michael A; Hein, Andrew M; Spiegel, Orr; Baskett, Marissa L; Sih, Andrew

2018-05-07

When individual animals make decisions, they routinely use information produced intentionally or unintentionally by other individuals. Despite its prevalence and established fitness consequences, the effects of such social information on ecological dynamics remain poorly understood. Here, we synthesize results from ecology, evolutionary biology, and animal behavior to show how the use of social information can profoundly influence the dynamics of populations and communities. We combine recent theoretical and empirical results and introduce simple population models to illustrate how social information use can drive positive density-dependent growth of populations and communities (Allee effects). Furthermore, social information can shift the nature and strength of species interactions, change the outcome of competition, and potentially increase extinction risk in harvested populations and communities. Copyright © 2018 Elsevier Ltd. All rights reserved.

Quantifying the ecological success of a community-based wildlife conservation area in Tanzania.

PubMed

Lee, Derek E; Bond, Monica L

2018-04-03

In Tanzania, community-based natural resource management of wildlife occurs through the creation of Wildlife Management Areas (WMAs). WMAs consist of multiple villages designating land for wildlife conservation, and sharing a portion of subsequent tourism revenues. Nineteen WMAs are currently operating, encompassing 7% of Tanzania's land area, with 19 more WMAs planned. The ecological success or failure of WMAs for wildlife conservation has yet to be quantified. We defined ecological success in this case as significantly greater densities of wildlife and significantly lower densities of livestock in the WMA relative to the control site, after the WMA was established. We used 4 years of distance sampling surveys conducted 6 times per year for wild and domestic ungulates to quantify wildlife and livestock densities before and after the establishment and implementation of management efforts at Randilen WMA, relative to a control site on adjacent land of similar vegetation and habitat types. We documented similarity between the sites before WMA establishment, when both sites were managed by the same authority. After WMA establishment, we documented significantly higher densities of resident wildlife (giraffes and dik-diks) and lower densities of cattle in the WMA, relative to the control site, indicating short-term ecological success. Continued monitoring is necessary to determine longer-term effects, and to evaluate management decisions.

A multistate dynamic site occupancy model for spatially aggregated sessile communities

USGS Publications Warehouse

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.

A high-throughput assay for quantifying appetite and digestive dynamics.

PubMed

Jordi, Josua; Guggiana-Nilo, Drago; Soucy, Edward; Song, Erin Yue; Lei Wee, Caroline; Engert, Florian

2015-08-15

Food intake and digestion are vital functions, and their dysregulation is fundamental for many human diseases. Current methods do not support their dynamic quantification on large scales in unrestrained vertebrates. Here, we combine an infrared macroscope with fluorescently labeled food to quantify feeding behavior and intestinal nutrient metabolism with high temporal resolution, sensitivity, and throughput in naturally behaving zebrafish larvae. Using this method and rate-based modeling, we demonstrate that zebrafish larvae match nutrient intake to their bodily demand and that larvae adjust their digestion rate, according to the ingested meal size. Such adaptive feedback mechanisms make this model system amenable to identify potential chemical modulators. As proof of concept, we demonstrate that nicotine, l-lysine, ghrelin, and insulin have analogous impact on food intake as in mammals. Consequently, the method presented here will promote large-scale translational research of food intake and digestive function in a naturally behaving vertebrate. Copyright © 2015 the American Physiological Society.

A high-throughput assay for quantifying appetite and digestive dynamics

PubMed Central

Guggiana-Nilo, Drago; Soucy, Edward; Song, Erin Yue; Lei Wee, Caroline; Engert, Florian

2015-01-01

Food intake and digestion are vital functions, and their dysregulation is fundamental for many human diseases. Current methods do not support their dynamic quantification on large scales in unrestrained vertebrates. Here, we combine an infrared macroscope with fluorescently labeled food to quantify feeding behavior and intestinal nutrient metabolism with high temporal resolution, sensitivity, and throughput in naturally behaving zebrafish larvae. Using this method and rate-based modeling, we demonstrate that zebrafish larvae match nutrient intake to their bodily demand and that larvae adjust their digestion rate, according to the ingested meal size. Such adaptive feedback mechanisms make this model system amenable to identify potential chemical modulators. As proof of concept, we demonstrate that nicotine, l-lysine, ghrelin, and insulin have analogous impact on food intake as in mammals. Consequently, the method presented here will promote large-scale translational research of food intake and digestive function in a naturally behaving vertebrate. PMID:26108871

Quantifying the size-resolved dynamics of indoor bioaerosol transport and control.

PubMed

Kunkel, S A; Azimi, P; Zhao, H; Stark, B C; Stephens, B

2017-09-01

Understanding the bioaerosol dynamics of droplets and droplet nuclei emitted during respiratory activities is important for understanding how infectious diseases are transmitted and potentially controlled. To this end, we conducted experiments to quantify the size-resolved dynamics of indoor bioaerosol transport and control in an unoccupied apartment unit operating under four different HVAC particle filtration conditions. Two model organisms (Escherichia coli K12 and bacteriophage T4) were aerosolized under alternating low and high flow rates to roughly represent constant breathing and periodic coughing. Size-resolved aerosol sampling and settle plate swabbing were conducted in multiple locations. Samples were analyzed by DNA extraction and quantitative polymerase chain reaction (qPCR). DNA from both organisms was detected during all test conditions in all air samples up to 7 m away from the source, but decreased in magnitude with the distance from the source. A greater fraction of T4 DNA was recovered from the aerosol size fractions smaller than 1 μm than E. coli K12 at all air sampling locations. Higher efficiency HVAC filtration also reduced the amount of DNA recovered in air samples and on settle plates located 3-7 m from the source. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Decomposition-Based Multiobjective Evolutionary Algorithm for Community Detection in Dynamic Social Networks

PubMed Central

Ma, Jingjing; Liu, Jie; Ma, Wenping; Gong, Maoguo; Jiao, Licheng

2014-01-01

Community structure is one of the most important properties in social networks. In dynamic networks, there are two conflicting criteria that need to be considered. One is the snapshot quality, which evaluates the quality of the community partitions at the current time step. The other is the temporal cost, which evaluates the difference between communities at different time steps. In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. It employs the framework of multiobjective evolutionary algorithm based on decomposition to simultaneously optimize the modularity and normalized mutual information, which quantitatively measure the quality of the community partitions and temporal cost, respectively. A local search strategy dealing with the problem-specific knowledge is incorporated to improve the effectiveness of the new algorithm. Experiments on computer-generated and real-world networks demonstrate that the proposed algorithm can not only find community structure and capture community evolution more accurately, but also be steadier than the two compared algorithms. PMID:24723806

Decomposition-based multiobjective evolutionary algorithm for community detection in dynamic social networks.

PubMed

Ma, Jingjing; Liu, Jie; Ma, Wenping; Gong, Maoguo; Jiao, Licheng

2014-01-01

Community structure is one of the most important properties in social networks. In dynamic networks, there are two conflicting criteria that need to be considered. One is the snapshot quality, which evaluates the quality of the community partitions at the current time step. The other is the temporal cost, which evaluates the difference between communities at different time steps. In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. It employs the framework of multiobjective evolutionary algorithm based on decomposition to simultaneously optimize the modularity and normalized mutual information, which quantitatively measure the quality of the community partitions and temporal cost, respectively. A local search strategy dealing with the problem-specific knowledge is incorporated to improve the effectiveness of the new algorithm. Experiments on computer-generated and real-world networks demonstrate that the proposed algorithm can not only find community structure and capture community evolution more accurately, but also be steadier than the two compared algorithms.

Quantifying long-term evolution of intra-urban spatial interactions

PubMed Central

Sun, Lijun; Jin, Jian Gang; Axhausen, Kay W.; Lee, Der-Horng; Cebrian, Manuel

2015-01-01

Understanding the long-term impact that changes in a city's transportation infrastructure have on its spatial interactions remains a challenge. The difficulty arises from the fact that the real impact may not be revealed in static or aggregated mobility measures, as these are remarkably robust to perturbations. More generally, the lack of longitudinal, cross-sectional data demonstrating the evolution of spatial interactions at a meaningful urban scale also hinders us from evaluating the sensitivity of movement indicators, limiting our capacity to understand the evolution of urban mobility in depth. Using very large mobility records distributed over 3 years, we quantify the impact of the completion of a metro line extension: the Circle Line (CCL) in Singapore. We find that the commonly used movement indicators are almost identical before and after the project was completed. However, in comparing the temporal community structure across years, we do observe significant differences in the spatial reorganization of the affected geographical areas. The completion of CCL enables travellers to re-identify their desired destinations collectively with lower transport cost, making the community structure more consistent. These changes in locality are dynamic and characterized over short timescales, offering us a different approach to identify and analyse the long-term impact of new infrastructures on cities and their evolution dynamics. PMID:25551142

Targeted quantification of functional enzyme dynamics in environmental samples for microbially mediated biogeochemical processes: Targeted quantification of functional enzyme dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Minjing; Gao, Yuqian; Qian, Wei-Jun

Microbially mediated biogeochemical processes are catalyzed by enzymes that control the transformation of carbon, nitrogen, and other elements in environment. The dynamic linkage between enzymes and biogeochemical species transformation has, however, rarely been investigated because of the lack of analytical approaches to efficiently and reliably quantify enzymes and their dynamics in soils and sediments. Herein, we developed a signature peptide-based technique for sensitively quantifying dissimilatory and assimilatory enzymes using nitrate-reducing enzymes in a hyporheic zone sediment as an example. Moreover, the measured changes in enzyme concentration were found to correlate with the nitrate reduction rate in a way different frommore » that inferred from biogeochemical models based on biomass or functional genes as surrogates for functional enzymes. This phenomenon has important implications for understanding and modeling the dynamics of microbial community functions and biogeochemical processes in environments. Our results also demonstrate the importance of enzyme quantification for the identification and interrogation of those biogeochemical processes with low metabolite concentrations as a result of faster enzyme-catalyzed consumption of metabolites than their production. The dynamic enzyme behaviors provide a basis for the development of enzyme-based models to describe the relationship between the microbial community and biogeochemical processes.« less

Multimodel inference to quantify the relative importance of abiotic factors in the population dynamics of marine zooplankton

NASA Astrophysics Data System (ADS)

Everaert, Gert; Deschutter, Yana; De Troch, Marleen; Janssen, Colin R.; De Schamphelaere, Karel

2018-05-01

The effect of multiple stressors on marine ecosystems remains poorly understood and most of the knowledge available is related to phytoplankton. To partly address this knowledge gap, we tested if combining multimodel inference with generalized additive modelling could quantify the relative contribution of environmental variables on the population dynamics of a zooplankton species in the Belgian part of the North Sea. Hence, we have quantified the relative contribution of oceanographic variables (e.g. water temperature, salinity, nutrient concentrations, and chlorophyll a concentrations) and anthropogenic chemicals (i.e. polychlorinated biphenyls) to the density of Acartia clausi. We found that models with water temperature and chlorophyll a concentration explained ca. 73% of the population density of the marine copepod. Multimodel inference in combination with regression-based models are a generic way to disentangle and quantify multiple stressor-induced changes in marine ecosystems. Future-oriented simulations of copepod densities suggested increased copepod densities under predicted environmental changes.

Quantifying the impacts of vegetation changes on catchment storage-discharge dynamics using paired-catchment data

NASA Astrophysics Data System (ADS)

Cheng, Lei; Zhang, Lu; Chiew, Francis H. S.; Canadell, Josep G.; Zhao, Fangfang; Wang, Ying-Ping; Hu, Xianqun; Lin, Kairong

2017-07-01

It is widely recognized that vegetation changes can significantly affect the local water availability. Methods have been developed to predict the effects of vegetation change on water yield or total streamflow. However, it is still a challenge to predict changes in base flow following vegetation change due to limited understanding of catchment storage-discharge dynamics. In this study, the power law relationship for describing catchment storage-discharge dynamics is reformulated to quantify the changes in storage-discharge relationship resulting from vegetation changes using streamflow data from six paired-catchment experiments, of which two are deforestation catchments and four are afforestation catchments. Streamflow observations from the paired-catchment experiments clearly demonstrate that vegetation changes have led to significant changes in catchment storage-discharge relationships, accounting for about 83-128% of the changes in groundwater discharge in the treated catchments. Deforestation has led to increases in groundwater discharge (or base flow) but afforestation has resulted in decreases in groundwater discharge. Further analysis shows that the contribution of changes in groundwater discharge to the total changes in streamflow varies greatly among experimental catchments ranging from 12% to 80% with a mean of 38 ± 22% (μ ± σ). This study proposed a new method to quantify the effects of vegetation changes on groundwater discharge from catchment storage and will improve our predictability about the impacts of vegetation changes on catchment water yields.

Quantifying uncertainty due to fission-fusion dynamics as a component of social complexity.

PubMed

Ramos-Fernandez, Gabriel; King, Andrew J; Beehner, Jacinta C; Bergman, Thore J; Crofoot, Margaret C; Di Fiore, Anthony; Lehmann, Julia; Schaffner, Colleen M; Snyder-Mackler, Noah; Zuberbühler, Klaus; Aureli, Filippo; Boyer, Denis

2018-05-30

Groups of animals (including humans) may show flexible grouping patterns, in which temporary aggregations or subgroups come together and split, changing composition over short temporal scales, (i.e. fission and fusion). A high degree of fission-fusion dynamics may constrain the regulation of social relationships, introducing uncertainty in interactions between group members. Here we use Shannon's entropy to quantify the predictability of subgroup composition for three species known to differ in the way their subgroups come together and split over time: spider monkeys ( Ateles geoffroyi ), chimpanzees ( Pan troglodytes ) and geladas ( Theropithecus gelada ). We formulate a random expectation of entropy that considers subgroup size variation and sample size, against which the observed entropy in subgroup composition can be compared. Using the theory of set partitioning, we also develop a method to estimate the number of subgroups that the group is likely to be divided into, based on the composition and size of single focal subgroups. Our results indicate that Shannon's entropy and the estimated number of subgroups present at a given time provide quantitative metrics of uncertainty in the social environment (within which social relationships must be regulated) for groups with different degrees of fission-fusion dynamics. These metrics also represent an indirect quantification of the cognitive challenges posed by socially dynamic environments. Overall, our novel methodological approach provides new insight for understanding the evolution of social complexity and the mechanisms to cope with the uncertainty that results from fission-fusion dynamics. © 2017 The Author(s).

Quantifying nonergodicity in nonautonomous dissipative dynamical systems: An application to climate change

NASA Astrophysics Data System (ADS)

Drótos, Gábor; Bódai, Tamás; Tél, Tamás

2016-08-01

In nonautonomous dynamical systems, like in climate dynamics, an ensemble of trajectories initiated in the remote past defines a unique probability distribution, the natural measure of a snapshot attractor, for any instant of time, but this distribution typically changes in time. In cases with an aperiodic driving, temporal averages taken along a single trajectory would differ from the corresponding ensemble averages even in the infinite-time limit: ergodicity does not hold. It is worth considering this difference, which we call the nonergodic mismatch, by taking time windows of finite length for temporal averaging. We point out that the probability distribution of the nonergodic mismatch is qualitatively different in ergodic and nonergodic cases: its average is zero and typically nonzero, respectively. A main conclusion is that the difference of the average from zero, which we call the bias, is a useful measure of nonergodicity, for any window length. In contrast, the standard deviation of the nonergodic mismatch, which characterizes the spread between different realizations, exhibits a power-law decrease with increasing window length in both ergodic and nonergodic cases, and this implies that temporal and ensemble averages differ in dynamical systems with finite window lengths. It is the average modulus of the nonergodic mismatch, which we call the ergodicity deficit, that represents the expected deviation from fulfilling the equality of temporal and ensemble averages. As an important finding, we demonstrate that the ergodicity deficit cannot be reduced arbitrarily in nonergodic systems. We illustrate via a conceptual climate model that the nonergodic framework may be useful in Earth system dynamics, within which we propose the measure of nonergodicity, i.e., the bias, as an order-parameter-like quantifier of climate change.

Community, culture and sustainability in multilevel dynamic systems intervention science.

PubMed

Schensul, Jean J

2009-06-01

This paper addresses intertwined issues in the conceptualization, implementation and evaluation of multilevel dynamic systems intervention science (MDSIS). Interventions are systematically planned, conducted and evaluated social science-based cultural products intercepting the lives of people and institutions in the context of multiple additional events and processes (which also may be referred to as interventions) that may speed, slow or reduce change towards a desired outcome. Multilevel interventions address change efforts at multiple social levels in the hope that effects at each level will forge synergistic links, facilitating movement toward desired change. This paper utilizes an ecological framework that identifies macro (policy and regulatory institutions), meso (organizations and agencies with resources, and power) and micro (individuals, families and friends living in communities) interacting directly and indirectly. An MDSIS approach hypothesizes that change toward a goal will occur faster and more effectively when synchronized and supported across levels in a social system. MDSIS approaches by definition involve "whole" communities and cannot be implemented without the establishments of working community partnerships This paper takes a dynamic systems approach to science as conducted in communities, and discusses four concepts that are central to MDSIS--science, community, culture, and sustainability. These concepts are important in community based participatory research and to the targeting, refinement, and adaptation of enduring interventions. Consistency in their meaning and use can promote forward movement in the field of MDSIS, and in community-based prevention science.

Coastal Bacterioplankton Community Dynamics in Response to a Natural Disturbance

PubMed Central

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

Vertical and seasonal dynamics of fungal communities in boreal Scots pine forest soil.

PubMed

Santalahti, Minna; Sun, Hui; Jumpponen, Ari; Pennanen, Taina; Heinonsalo, Jussi

2016-11-01

Fungal communities are important for carbon (C) transformations in boreal forests that are one of the largest C pools in terrestrial ecosystems, warranting thus further investigation of fungal community dynamics in time and space. We investigated fungal diversity and community composition seasonally and across defined soil horizons in boreal Scots pine forest in Finland using 454 pyrosequencing. We collected a total of 120 samples from five vertical soil horizons monthly from March to October; in March, under snow. Boreal forest soil generally harbored diverse fungal communities across soil horizons. The communities shifted drastically and rapidly over time. In late winter, saprotrophs dominated the community and were replaced by ectomycorrhizal fungi during the growing season. Our studies are among the first to dissect the spatial and temporal dynamics in boreal forest ecosystems and highlights the ecological importance of vertically distinct communities and their rapid seasonal dynamics. As climate change is predicted to result in warmer and longer snow-free winter seasons, as well as increase the rooting depth of trees in boreal forest, the seasonal and vertical distribution of fungal communities may change. These changes are likely to affect the organic matter decomposition by the soil-inhabiting fungi and thus alter organic C pools. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Long-term dynamics of winter and summer annual communities in the Chihuahuan Desert

USGS Publications Warehouse

Guo, Q.; Brown, J.H.; Valone, T.J.

2002-01-01

Winter and summer annuals in the Chihuahuan Desert have been intensively studied in recent years but little is known about the similarities and differences in the dynamics between these two communities. Using 15 yr of census data from permanent quadrats, this paper compared the characteristics and temporal dynamics of these two distinct, spatially co-existent but temporally segregated communities. Although the total number of summer annual species recorded during our 15 yr of observation was higher than winter annuals, the mean number of species observed each year was higher in the winter community. The winter community exhibited lower temporal variation in total plant abundance and populations of individual species, lower species turnover rate and higher evenness than the summer community. The rank abundances of species in winter were significantly positively correlated for a period of up to 7 yr while in summer significant positive correlations in rank abundance disappeared after 2 to 3 yr. The higher seasonal species diversity (i.e. number of species observed in each season) in winter rather than the overall special pool (over 15 yr) may be responsible for the greater community stability of winter annuals. The difference in long-term community dynamics between the two communities of annual plants are likely due to the differences in total species pool, life history traits (e.g. seed size), and seasonal climatic regimes.

The dynamic bacterial communities of a melting High Arctic glacier snowpack

PubMed Central

Hell, Katherina; Edwards, Arwyn; Zarsky, Jakub; Podmirseg, Sabine M; Girdwood, Susan; Pachebat, Justin A; Insam, Heribert; Sattler, Birgit

2013-01-01

Snow environments can occupy over a third of land surface area, but little is known about the dynamics of snowpack bacteria. The effect of snow melt on bacterial community structure and diversity of surface environments of a Svalbard glacier was examined using analyses of 16S rRNA genes via T-RFLP, qPCR and 454 pyrosequencing. Distinct community structures were found in different habitat types, with changes over 1 week apparent, in particular for the dominant bacterial class present, Betaproteobacteria. The differences observed were consistent with influences from depositional mode (snowfall vs aeolian dusts), contrasting snow with dust-rich snow layers and near-surface ice. Contrary to that, slush as the decompositional product of snow harboured distinct lineages of bacteria, further implying post-depositional changes in community structure. Taxa affiliated to the betaproteobacterial genus Polaromonas were particularly dynamic, and evidence for the presence of betaproteobacterial ammonia-oxidizing bacteria was uncovered, inviting the prospect that the dynamic bacterial communities associated with snowpacks may be active in supraglacial nitrogen cycling and capable of rapid responses to changes induced by snowmelt. Furthermore the potential of supraglacial snowpack ecosystems to respond to transient yet spatially extensive melting episodes such as that observed across most of Greenland's ice sheet in 2012 merits further investigation. PMID:23552623

The dynamic bacterial communities of a melting High Arctic glacier snowpack.

PubMed

Hell, Katherina; Edwards, Arwyn; Zarsky, Jakub; Podmirseg, Sabine M; Girdwood, Susan; Pachebat, Justin A; Insam, Heribert; Sattler, Birgit

2013-09-01

Snow environments can occupy over a third of land surface area, but little is known about the dynamics of snowpack bacteria. The effect of snow melt on bacterial community structure and diversity of surface environments of a Svalbard glacier was examined using analyses of 16S rRNA genes via T-RFLP, qPCR and 454 pyrosequencing. Distinct community structures were found in different habitat types, with changes over 1 week apparent, in particular for the dominant bacterial class present, Betaproteobacteria. The differences observed were consistent with influences from depositional mode (snowfall vs aeolian dusts), contrasting snow with dust-rich snow layers and near-surface ice. Contrary to that, slush as the decompositional product of snow harboured distinct lineages of bacteria, further implying post-depositional changes in community structure. Taxa affiliated to the betaproteobacterial genus Polaromonas were particularly dynamic, and evidence for the presence of betaproteobacterial ammonia-oxidizing bacteria was uncovered, inviting the prospect that the dynamic bacterial communities associated with snowpacks may be active in supraglacial nitrogen cycling and capable of rapid responses to changes induced by snowmelt. Furthermore the potential of supraglacial snowpack ecosystems to respond to transient yet spatially extensive melting episodes such as that observed across most of Greenland's ice sheet in 2012 merits further investigation.

Quantifying the ecological success of a community-based wildlife conservation area in Tanzania

PubMed Central

Lee, Derek E

2018-01-01

Abstract In Tanzania, community-based natural resource management of wildlife occurs through the creation of Wildlife Management Areas (WMAs). WMAs consist of multiple villages designating land for wildlife conservation, and sharing a portion of subsequent tourism revenues. Nineteen WMAs are currently operating, encompassing 7% of Tanzania’s land area, with 19 more WMAs planned. The ecological success or failure of WMAs for wildlife conservation has yet to be quantified. We defined ecological success in this case as significantly greater densities of wildlife and significantly lower densities of livestock in the WMA relative to the control site, after the WMA was established. We used 4 years of distance sampling surveys conducted 6 times per year for wild and domestic ungulates to quantify wildlife and livestock densities before and after the establishment and implementation of management efforts at Randilen WMA, relative to a control site on adjacent land of similar vegetation and habitat types. We documented similarity between the sites before WMA establishment, when both sites were managed by the same authority. After WMA establishment, we documented significantly higher densities of resident wildlife (giraffes and dik-diks) and lower densities of cattle in the WMA, relative to the control site, indicating short-term ecological success. Continued monitoring is necessary to determine longer-term effects, and to evaluate management decisions. PMID:29867255

Modelling fungal growth in heterogeneous soil: analyses of the effect of soil physical structure on fungal community 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.

Quantifying Factors That Impact Riverbed Dynamic Permeability at a Riverbank Filtration Facility

NASA Astrophysics Data System (ADS)

Ulrich, C.; Hubbard, S. S.; Florsheim, J. L.; Rosenberry, D. O.; Borglin, S. E.; Zhang, Y.; Seymour, D.; Trotta, M.

2012-12-01

Previous modeling studies of the Wohler riverbank filtration system on the Russian River, California suggested that riverbed and aquifer permeability both influence the development of a pumping-induced unsaturated zone below the riverbed, which affects water produced through large radial water-supply collector wells that extend beneath and adjacent to the river. In particular, previous work suggests that riverbed permeability is influenced by interaction between pumping and river stage that is controlled by a downstream temporary inflatable dam during the summer low flow period. We hypothesize that raising the dam may instead lead to deposition of fine-grained sediment and/or accumulation of biota, both of which decrease riverbed permeability in the vicinity of the collector wells. To test this hypothesis, we are monitoring streambed permeability and seepage as a function of river stage and dam operation. We are using multiple methods to monitor the hydrological, sedimentological and geomorphic dynamics, including: seepage meters, sediment traps, cryogenic coring, ground penetrating radar, electrical resistance tomography, riverbed topography, piezometers, and thermistors. Here we discuss the use of this novel suite of methods to quantify dynamic riverbed permeability, how it relates to dam operation, and determine the key controls on permeability (i.e., biotic or abiotic). These results are expected to improve the overall understanding of riverbed permeability dynamics associated with Riverbank filtration. The results are also expected to be transferable to the project sponsors, the Sonoma County Water Agency, toward the development of an optimal pumping and dam operation schedule.

Assembly-history dynamics of a pitcher-plant protozoan community in experimental microcosms.

PubMed

Kadowaki, Kohmei; Inouye, Brian D; Miller, Thomas E

2012-01-01

History drives community assembly through differences both in density (density effects) and in the sequence in which species arrive (sequence effects). Density effects arise from predictable population dynamics, which are free of history, but sequence effects are due to a density-free mechanism, arising solely from the order and timing of immigration events. Few studies have determined how components of immigration history (timing, number of individuals, frequency) alter local dynamics to determine community assembly, beyond addressing when immigration history produces historically contingent assembly. We varied density and sequence effects independently in a two-way factorial design to follow community assembly in a three-species aquatic protozoan community. A superior competitor, Colpoda steinii, mediated alternative community states; early arrival or high introduction density allowed this species to outcompete or suppress the other competitors (Poterioochromonas malhamensis and Eimeriidae gen. sp.). Multivariate analysis showed that density effects caused greater variation in community states, whereas sequence effects altered the mean community composition. A significant interaction between density and sequence effects suggests that we should refine our understanding of priority effects. These results highlight a practical need to understand not only the "ingredients" (species) in ecological communities but their "recipes" as well.

Dynamics of microbial communities in untreated and autoclaved food waste anaerobic digesters.

PubMed

Blasco, Lucia; Kahala, Minna; Tampio, Elina; Ervasti, Satu; Paavola, Teija; Rintala, Jukka; Joutsjoki, Vesa

2014-10-01

This study describes the microbial community richness and dynamics of two semi-continuously stirred biogas reactors during a time-course study of 120 days. The reactors were fed with untreated and autoclaved (160 °C, 6.2 bar) food waste. The microbial community was analysed using a bacteria- and archaea-targeting 16S rRNA gene-based Terminal-Restriction Fragment Length Polymorphism (T-RFLP) approach. Compared with the archaeal community, the structures and functions of the bacterial community were found to be more complex and diverse. With the principal coordinates analysis it was possible to separate both microbial communities with 75 and 50% difference for bacteria and archaea, respectively, in the two reactors fed with the same waste but with different pretreatment. Despite the use of the same feeding material, anaerobic reactors showed a distinct community profile which could explain the differences in methane yield (2-17%). The community composition was highly dynamic for bacteria and archaea during the entire studied period. This study illustrates that microbial communities are dependent on feeding material and that correlations among specific bacterial and archaeal T-RFs can be established. Copyright © 2014 Elsevier Ltd. All rights reserved.

A fast community detection method in bipartite networks by distance dynamics

NASA Astrophysics Data System (ADS)

Sun, Hong-liang; Ch'ng, Eugene; Yong, Xi; Garibaldi, Jonathan M.; See, Simon; Chen, Duan-bing

2018-04-01

Many real bipartite networks are found to be divided into two-mode communities. In this paper, we formulate a new two-mode community detection algorithm BiAttractor. It is based on distance dynamics model Attractor proposed by Shao et al. with extension from unipartite to bipartite networks. Since Jaccard coefficient of distance dynamics model is incapable to measure distances of different types of vertices in bipartite networks, our main contribution is to extend distance dynamics model from unipartite to bipartite networks using a novel measure Local Jaccard Distance (LJD). Furthermore, distances between different types of vertices are not affected by common neighbors in the original method. This new idea makes clear assumptions and yields interpretable results in linear time complexity O(| E |) in sparse networks, where | E | is the number of edges. Experiments on synthetic networks demonstrate it is capable to overcome resolution limit compared with existing other methods. Further research on real networks shows that this model can accurately detect interpretable community structures in a short time.

Symbiont dynamics during ecosystem succession: co-occurring plant and arbuscular mycorrhizal fungal communities.

PubMed

García de León, David; Moora, Mari; Öpik, Maarja; Neuenkamp, Lena; Gerz, Maret; Jairus, Teele; Vasar, Martti; Bueno, C Guillermo; Davison, John; Zobel, Martin

2016-07-01

Although mycorrhizas are expected to play a key role in community assembly during ecological succession, little is known about the dynamics of the symbiotic partners in natural systems. For instance, it is unclear how efficiently plants and arbuscular mycorrhizal (AM) fungi disperse into early successional ecosystems, and which, if either, symbiotic partner drives successional dynamics. This study describes the dynamics of plant and AM fungal communities, assesses correlation in the composition of plant and AM fungal communities and compares dispersal limitation of plants and AM fungi during succession. We studied gravel pits 20 and 50 years post abandonment and undisturbed grasslands in Western Estonia. The composition of plant and AM fungal communities was strongly correlated, and the strength of the correlation remained unchanged as succession progressed, indicating a stable dependence among mycorrhizal plants and AM fungi. A relatively high proportion of the AM fungal taxon pool was present in early successional sites, in comparison with the respective fraction of plants. These results suggest that AM fungi arrived faster than plants and may thus drive vegetation dynamics along secondary vegetation succession. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Quantifying the effect of a community-based injury prevention program in Queensland using a generalized estimating equation approach.

PubMed

Yorkston, Emily; Turner, Catherine; Schluter, Philip J; McClure, Rod

2007-06-01

To develop a generalized estimating equation (GEE) model of childhood injury rates to quantify the effectiveness of a community-based injury prevention program implemented in 2 communities in Australia, in order to contribute to the discussion of community-based injury prevention program evaluation. An ecological study was conducted comparing injury rates in two intervention communities in rural and remote Queensland, Australia, with those of 16 control regions. A model of childhood injury was built using hospitalization injury rate data from 1 July 1991 to 30 June 2005 and 16 social variables. The model was built using GEE analysis and was used to estimate parameters and to test the effectiveness of the intervention. When social variables were controlled for, the intervention was associated with a decrease of 0.09 injuries/10,000 children aged 0-4 years (95% CI -0.29 to 0.11) in logarithmically transformed injury rates; however, this decrease was not significant (p = 0.36). The evaluation methods proposed in this study provide a way of determining the effectiveness of a community-based injury prevention program while considering the effect of baseline differences and secular changes in social variables.

Long-term dynamics of winter and summer annual communities in the Chihuahuan Desert

USGS Publications Warehouse

Guo, Q.; Brown, J.H.; Valone, T.J.

2002-01-01

Using 15 years of census data from permanent quadrats, this paper compared the characteristics and temporal dynamics of these two distinct, spatially coexistent but temporally segregated communities. Although the total number of summer annual species recorded during our 15 years observation was higher than winter annuals, the average number of species observed each year was higher in the winter community. The winter community exhibited lower temporal variation in total plant abundance and populations of individual species, lower species turnover rate and higher evenness than the summer community. The higher seasonal species diversity (i.e., number of species observed in each season) in winters rather than the overall special pool (over 15 yrs) may be responsible for the greater community stability of winter annuals. The difference in long-term community dynamics between the two communities of annuals plants are likely due to the differences in total species pool, life history traits (e.g., seed size), and seasonal climatic regimes.

Dynamic balance during walking adaptability tasks in individuals post-stroke.

PubMed

Vistamehr, Arian; Balasubramanian, Chitralakshmi K; Clark, David J; Neptune, Richard R; Fox, Emily J

2018-06-06

Maintaining dynamic balance during community ambulation is a major challenge post-stroke. Community ambulation requires performance of steady-state level walking as well as tasks that require walking adaptability. Prior studies on balance control post-stroke have mainly focused on steady-state walking, but walking adaptability tasks have received little attention. The purpose of this study was to quantify and compare dynamic balance requirements during common walking adaptability tasks post-stroke and in healthy adults and identify differences in underlying mechanisms used for maintaining dynamic balance. Kinematic data were collected from fifteen individuals with post-stroke hemiparesis during steady-state forward and backward walking, obstacle negotiation, and step-up tasks. In addition, data from ten healthy adults provided the basis for comparison. Dynamic balance was quantified using the peak-to-peak range of whole-body angular-momentum in each anatomical plane during the paretic, nonparetic and healthy control single-leg-stance phase of the gait cycle. To understand differences in some of the key underlying mechanisms for maintaining dynamic balance, foot placement and plantarflexor muscle activation were examined. Individuals post-stroke had significant dynamic balance deficits in the frontal plane across most tasks, particularly during the paretic single-leg-stance. Frontal plane balance deficits were associated with wider paretic foot placement, elevated body center-of-mass, and lower soleus activity. Further, the obstacle negotiation task imposed a higher balance requirement, particularly during the trailing leg single-stance. Thus, improving paretic foot placement and ankle plantarflexor activity, particularly during obstacle negotiation, may be important rehabilitation targets to enhance dynamic balance during post-stroke community ambulation. Copyright © 2018 Elsevier Ltd. All rights reserved.

Deconstructing Interaction Dynamics in Knowledge Sharing Communities

NASA Astrophysics Data System (ADS)

Aji, Ablimit; Agichtein, Eugene

Online knowledge sharing sites have recently exploded in popularity, and have began to play an important role in online information seeking. Unfortunately, many factors that influence the effectiveness of the information exchange in these communities are not well understood. This paper is an attempt to fill this gap by exploring the dynamics of information sharing in such sites - that is, identifying the factors that can explain how people respond to information requests. As a case study, we use Yahoo! Answers, one of the leading knowledge sharing portals on the web with millions of active participants. We follow the progress of thousands of questions, from posting until resolution. We examine contextual factors such as the topical area of the questions, as well as intrinsic factors of question wording, subjectivity, sentiment, and other characteristics that could influence how a community responds to an information request. Our findings could be useful for improving existing collaborative question answering systems, and for designing the next generation of knowledge sharing communities.

Microbial community dynamics in Inferno Crater Lake, a thermally fluctuating geothermal spring

PubMed Central

Ward, Laura; Taylor, Michael W; Power, Jean F; Scott, Bradley J; McDonald, Ian R; Stott, Matthew B

2017-01-01

Understanding how microbial communities respond and adjust to ecosystem perturbation is often difficult to interpret due to multiple and often simultaneous variations in observed conditions. In this research, we investigated the microbial community dynamics of Inferno Crater Lake, an acidic geothermal spring in New Zealand with a unique thermal cycle that varies between 30 and 80 °C over a period of 40–60 days. Using a combination of next-generation sequencing, geochemical analysis and quantitative PCR we found that the microbial community composition was predominantly chemolithotrophic and strongly associated with the thermal cycle. At temperatures >65 °C, the microbial community was dominated almost exclusively by sulphur-oxidising archaea (Sulfolobus-like spp.). By contrast, at mesophilic temperatures the community structure was more mixed, comprising both archaea and bacteria but dominated primarily by chemolithotrophic sulphur and hydrogen oxidisers. Multivariate analysis of physicochemical data confirmed that temperature was the only significant variable associated with community turnover. This research contributes to our understanding of microbial community dynamics in variable environments, using a naturally alternating system as a model and extends our limited knowledge of acidophile ecology in geothermal habitats. PMID:28072418

Microbial community dynamics in Inferno Crater Lake, a thermally fluctuating geothermal spring.

PubMed

Ward, Laura; Taylor, Michael W; Power, Jean F; Scott, Bradley J; McDonald, Ian R; Stott, Matthew B

2017-05-01

Understanding how microbial communities respond and adjust to ecosystem perturbation is often difficult to interpret due to multiple and often simultaneous variations in observed conditions. In this research, we investigated the microbial community dynamics of Inferno Crater Lake, an acidic geothermal spring in New Zealand with a unique thermal cycle that varies between 30 and 80 °C over a period of 40-60 days. Using a combination of next-generation sequencing, geochemical analysis and quantitative PCR we found that the microbial community composition was predominantly chemolithotrophic and strongly associated with the thermal cycle. At temperatures >65 °C, the microbial community was dominated almost exclusively by sulphur-oxidising archaea (Sulfolobus-like spp.). By contrast, at mesophilic temperatures the community structure was more mixed, comprising both archaea and bacteria but dominated primarily by chemolithotrophic sulphur and hydrogen oxidisers. Multivariate analysis of physicochemical data confirmed that temperature was the only significant variable associated with community turnover. This research contributes to our understanding of microbial community dynamics in variable environments, using a naturally alternating system as a model and extends our limited knowledge of acidophile ecology in geothermal habitats.

Dynamical origins of the community structure of an online multi-layer society

NASA Astrophysics Data System (ADS)

Klimek, Peter; Diakonova, Marina; Eguíluz, Víctor M.; San Miguel, Maxi; Thurner, Stefan

2016-08-01

Social structures emerge as a result of individuals managing a variety of different social relationships. Societies can be represented as highly structured dynamic multiplex networks. Here we study the dynamical origins of the specific community structures of a large-scale social multiplex network of a human society that interacts in a virtual world of a massive multiplayer online game. There we find substantial differences in the community structures of different social actions, represented by the various layers in the multiplex network. Community sizes distributions are either fat-tailed or appear to be centered around a size of 50 individuals. To understand these observations we propose a voter model that is built around the principle of triadic closure. It explicitly models the co-evolution of node- and link-dynamics across different layers of the multiplex network. Depending on link and node fluctuation probabilities, the model exhibits an anomalous shattered fragmentation transition, where one layer fragments from one large component into many small components. The observed community size distributions are in good agreement with the predicted fragmentation in the model. This suggests that several detailed features of the fragmentation in societies can be traced back to the triadic closure processes.

Methane Emission in a Specific Riparian-Zone Sediment Decreased with Bioelectrochemical Manipulation and Corresponded to the Microbial Community Dynamics

PubMed Central

Friedman, Elliot S.; McPhillips, Lauren E.; Werner, Jeffrey J.; Poole, Angela C.; Ley, Ruth E.; Walter, M. Todd; Angenent, Largus T.

2016-01-01

Dissimilatory metal-reducing bacteria are widespread in terrestrial ecosystems, especially in anaerobic soils and sediments. Thermodynamically, dissimilatory metal reduction is more favorable than sulfate reduction and methanogenesis but less favorable than denitrification and aerobic respiration. It is critical to understand the complex relationships, including the absence or presence of terminal electron acceptors, that govern microbial competition and coexistence in anaerobic soils and sediments, because subsurface microbial processes can effect greenhouse gas emissions from soils, possibly resulting in impacts at the global scale. Here, we elucidated the effect of an inexhaustible, ferrous-iron and humic-substance mimicking terminal electron acceptor by deploying potentiostatically poised electrodes in the sediment of a very specific stream riparian zone in Upstate New York state. At two sites within the same stream riparian zone during the course of 6 weeks in the spring of 2013, we measured CH4 and N2/N2O emissions from soil chambers containing either poised or unpoised electrodes, and we harvested biofilms from the electrodes to quantify microbial community dynamics. At the upstream site, which had a lower vegetation cover and highest soil temperatures, the poised electrodes inhibited CH4 emissions by ∼45% (when normalized to remove temporal effects). CH4 emissions were not significantly impacted at the downstream site. N2/N2O emissions were generally low at both sites and were not impacted by poised electrodes. We did not find a direct link between bioelectrochemical treatment and microbial community membership; however, we did find a correspondence between environment/function and microbial community dynamics. PMID:26793170

Astaxanthin dynamics in Baltic Sea mesozooplankton communities

NASA Astrophysics Data System (ADS)

Snoeijs, Pauline; Häubner, Norbert

2014-01-01

The red pigment astaxanthin is a powerful antioxidant, which occurs in eggs and body tissues of crustaceans and fish. It is produced by crustaceans from algal carotenoids. In a two-year field study we assessed natural concentrations and dynamics of astaxanthin in mesozooplankton communities in the brackish Baltic Sea area. Astaxanthin levels varied between 0.37 and 36 ng L- 1. They increased with salinity along the Baltic Sea gradient and were linked to zooplankton biomass and phytoplankton community composition. Astaxanthin concentrations showed typical seasonal patterns and varied from 0.2 to 5.1 ng ind- 1, 0.2 to 3.4 ng (μg C)- 1 and 6 to 100 ng mm- 3. These concentrations were inversely related to water temperature and strongly linked to zooplankton community composition. Communities dominated by the calanoid copepods Temora longicornis, Pseudocalanus acuspes and Eurytemora spp. generally held the highest concentrations. With increasing cladocerans:copepods biomass ratios community astaxanthin concentrations decreased and with higher relative biomass of Acartia spp. the proportion of astaxanthin diesters decreased. Diesters prevailed in the cold season and they are thought to improve the antioxidant protection of storage lipids during winter. Climate change causes higher temperature and lower salinity in the Baltic Sea proper. This modifies zooplankton community composition, but not necessarily into a community with lower concentrations of astaxanthin since T. longicornis (high concentrations) has been reported to increase with higher temperature. However, decreased astaxanthin production in the ecosystem is expected if a basin-wide increase in the cladocerans:copepods biomass ratios would occur with further climate change.

Consumption dynamics of the adult piscivorous fish community in Spirit Lake, Iowa

USGS Publications Warehouse

Liao, H.; Pierce, C.L.; Larscheid, J.G.

2004-01-01

At Spirit Lake, one of Iowa's most important fisheries, walleye Sander vitreus (formerly Stizostedion vitreum) is one of the most popular species with anglers. Despite a century of walleye stocking and management in Spirit Lake, walleye growth rate, size structure, and angler harvest continue to decline. Our purpose was to determine the magnitude and dynamics of walleye population consumption relative to those of other piscivorous species in Spirit Lake, which would allow managers to judge the feasibility of increasing the abundance, growth rate, and size structure of the walleye population. We quantified food consumption by the adult piscivorous fish community in Spirit Lake over a 3-year period. Data on population dynamics, diet, energy density, and water temperature from 1995 to 1997 were used in bioenergetics models to estimate total consumption by walleye, yellow perch Perca flavescens, smallmouth bass Micropterus dolomieu, largemouth bass Micropterus salmoides, black crappie Pomoxis nigromaculatus, and northern pike Esox lucius. Estimated annual consumption by the piscivorous community varied roughly fourfold, ranging from 154,752 kg in 1995 to 662,776 kg in 1997. Walleyes dominated total consumption, accounting for 68, 73, and 90% (1995-1997, respectively) of total food consumption. Walleyes were also the dominant consumers of fish, accounting for 76, 86, and 97% of piscivorous consumption; yellow perch followed, accounting for 16% of piscivorous consumption in 1995 and 12% in 1996. Yellow perch were the predominant fish prey species in all 3 years, accounting for 68, 52, and 36% of the total prey consumed. Natural reproduction is weak, so high walleye densities are maintained by intensive stocking. Walleye stocking drives piscivorous consumption in Spirit Lake, and yearly variation in the cannibalism of stocked walleye fry may be an important determinant of walleye year-class strength and angler success. Reducing walleye stocking intensity, varying stocking

Dynamics of the Fouling Layer Microbial Community in a Membrane Bioreactor

PubMed Central

Ziegler, Anja S.; McIlroy, Simon J.; Larsen, Poul; Albertsen, Mads; Hansen, Aviaja A.; Heinen, Nicolas; Nielsen, Per Halkjær

2016-01-01

Membrane fouling presents the greatest challenge to the application of membrane bioreactor (MBR) technology. Formation of biofilms on the membrane surface is the suggested cause, yet little is known of the composition or dynamics of the microbial community responsible. To gain an insight into this important question, we applied 16S rRNA gene amplicon sequencing with a curated taxonomy and fluorescent in situ hybridization to monitor the community of a pilot-scale MBR carrying out enhanced biological nitrogen and phosphorus removal with municipal wastewater. In order to track the dynamics of the fouling process, we concurrently investigated the communities of the biofilm, MBR bulk sludge, and the conventional activated sludge system used to seed the MBR system over several weeks from start-up. As the biofilm matured the initially abundant betaproteobacterial genera Limnohabitans, Hydrogenophaga and Malikia were succeeded by filamentous Chloroflexi and Gordonia as the abundant species. This study indicates that, although putative pioneer species appear, the biofilm became increasingly similar to the bulk community with time. This suggests that the microbial population in bulk water will largely determine the community structure of the mature biofilm. PMID:27399199

Next generation dynamic global vegetation models: learning from community ecology (Invited)

NASA Astrophysics Data System (ADS)

Scheiter, S.; Higgins, S.; Langan, L.

2013-12-01

Dynamic global vegetation models are a powerful tool to project past, current and future vegetation patterns and the associated biogeochemical cycles. However, most models are limited by their representation of vegetation by using static and pre-defined plant functional types and by their simplistic representation of competition. We discuss how concepts from community assembly theory and coexistence theory can help to improve dynamic vegetation models. We present a trait- and individual-based dynamic vegetation model, the aDGVM2, that allows individual plants to adopt a unique combination of trait values. These traits define how individual plants grow, compete and reproduce under the given biotic and abiotic conditions. A genetic optimization algorithm is used to simulate trait inheritance and reproductive isolation between individuals. These model properties allow the assembly of plant communities that are adapted to biotic and abiotic conditions. We show (1) that the aDGVM2 can simulate coarse vegetation patterns in Africa, (2) that changes in the environmental conditions and disturbances strongly influence trait diversity and the assembled plant communities by influencing traits such as leaf phenology and carbon allocation patterns of individual plants and (3) that communities do not necessarily return to the initial state when environmental conditions return to the initial state. The aDGVM2 deals with functional diversity and competition fundamentally differently from current models and allows novel insights as to how vegetation may respond to climate change. We believe that the aDGVM2 approach could foster collaborations between research communities that focus on functional plant ecology, plant competition, plant physiology and Earth system science.

Species composition, community and population dynamics of two gallery forests from the Brazilian Cerrado domain

PubMed Central

Almado, Roosevelt P; Miazaki, Angela S; Diniz, Écio S; Moreira, Luis C B; Meira-Neto, João A.A.

2016-01-01

Abstract Background To understand the impacts of global changes on future community compositions, knowledge of community dynamics is of crucial importance. To improve our knowledge of community composition, biomass stock and maintenance of gallery forests in the Brazilian Cerrado, we provide two datasets from the 0.5 ha Corrego Fazendinha Gallery Forest Dynamics Plot and the Corrego Fundo Gallery Forest Dynamics Plot situated in the Bom Despacho region, Minas Gerais, Southeastern Brazil. New information We report diameter at breast height, basal area and height measurements of 3417 trees and treelets identified during three censuses in both areas. PMID:27660529

Rapid and Specific Method for Evaluating Streptomyces Competitive Dynamics in Complex Soil Communities

USDA-ARS?s Scientific Manuscript database

Quantifying target microbial populations in complex communities remains a barrier to studying species interactions in soil environments. Quantitative real-time PCR (qPCR) offers a rapid and specific means to assess populations of target microorganisms. SYBR Green and TaqMan-based qPCR assays were de...

The data not collected on community forestry

PubMed Central

Oldekop, Johan A.; Cronkleton, Peter; Etue, Emily; Newton, Peter; Russel, Aaron J.M.; Tjajadi, Januarti Sinarra; Zhou, Wen; Agrawal, Arun

2016-01-01

Abstract Conservation and development practitioners increasingly promote community forestry as a way to conserve ecosystem services, consolidate resource rights, and reduce poverty. However, outcomes of community forestry have been mixed; many initiatives failed to achieve intended objectives. There is a rich literature on institutional arrangements of community forestry, but there has been little effort to examine the role of socioeconomic, market, and biophysical factors in shaping both land‐cover change dynamics and individual and collective livelihood outcomes. We systematically reviewed the peer‐reviewed literature on community forestry to examine and quantify existing knowledge gaps in the community‐forestry literature relative to these factors. In examining 697 cases of community forest management (CFM), extracted from 267 peer‐reviewed publications, we found 3 key trends that limit understanding of community forestry. First, we found substantial data gaps linking population dynamics, market forces, and biophysical characteristics to both environmental and livelihood outcomes. Second, most studies focused on environmental outcomes, and the majority of studies that assessed socioeconomic outcomes relied on qualitative data, making comparisons across cases difficult. Finally, there was a heavy bias toward studies on South Asian forests, indicating that the literature on community forestry may not be representative of decentralization policies and CFM globally. PMID:27060464

Quantifying the Dynamics of Bacterial Secondary Metabolites by Spectral Multi-Photon Microscopy

PubMed Central

Sullivan, Nora L.; Tzeranis, Dimitrios S.; Wang, Yun; So, Peter T.C.; Newman, Dianne

2011-01-01

Phenazines, a group of fluorescent small molecules produced by the bacterium Pseudomonas aeruginosa, play a role in maintaining cellular redox homeostasis. Phenazines have been challenging to study in vivo due to their redox activity, presence both intra- and extracellularly, and their diverse chemical properties. Here, we describe a non-invasive in vivo optical technique to monitor phenazine concentrations within bacterial cells using time-lapsed spectral multi-photon fluorescence microscopy. This technique enables simultaneous monitoring of multiple weakly-fluorescent molecules (phenazines, siderophores, NAD(P)H) expressed by bacteria in culture. This work provides the first in vivo measurements of reduced phenazine concentration as well as the first description of the temporal dynamics of the phenazine-NAD(P)H redox system in Pseudomonas aeruginosa, illuminating an unanticipated role for 1-hydroxyphenazine. Similar approaches could be used to study the abundance and redox dynamics of a wide range of small molecules within bacteria, both as single cells and in communities. PMID:21671613

Bacterial Community Dynamics in Full-Scale Activated Sludge Bioreactors: Operational and Ecological Factors Driving Community Assembly and Performance

PubMed Central

Valentín-Vargas, Alexis; Toro-Labrador, Gladys; Massol-Deyá, Arturo A.

2012-01-01

The assembling of bacterial communities in conventional activated sludge (CAS) bioreactors was thought, until recently, to be chaotic and mostly unpredictable. Studies done over the last decade have shown that specific, and often, predictable random and non-random factors could be responsible for that process. These studies have also motivated a “structure–function” paradigm that is yet to be resolved. Thus, elucidating the factors that affect community assembly in the bioreactors is necessary for predicting fluctuations in community structure and function. For this study activated sludge samples were collected during a one-year period from two geographically distant CAS bioreactors of different size. Combining community fingerprinting analysis and operational parameters data with a robust statistical analysis, we aimed to identify relevant links between system performance and bacterial community diversity and dynamics. In addition to revealing a significant β-diversity between the bioreactors’ communities, results showed that the largest bioreactor had a less dynamic but more efficient and diverse bacterial community throughout the study. The statistical analysis also suggests that deterministic factors, as opposed to stochastic factors, may have a bigger impact on the community structure in the largest bioreactor. Furthermore, the community seems to rely mainly on mechanisms of resistance and functional redundancy to maintain functional stability. We suggest that the ecological theories behind the Island Biogeography model and the species-area relationship were appropriate to predict the assembly of bacterial communities in these CAS bioreactors. These results are of great importance for engineers and ecologists as they reveal critical aspects of CAS systems that could be applied towards improving bioreactor design and operation. PMID:22880016

Synchronous dynamics of zooplankton competitors prevail in temperate lake ecosystems.

PubMed

Vasseur, David A; Fox, Jeremy W; Gonzalez, Andrew; Adrian, Rita; Beisner, Beatrix E; Helmus, Matthew R; Johnson, Catherine; Kratina, Pavel; Kremer, Colin; de Mazancourt, Claire; Miller, Elizabeth; Nelson, William A; Paterson, Michael; Rusak, James A; Shurin, Jonathan B; Steiner, Christopher F

2014-08-07

Although competing species are expected to exhibit compensatory dynamics (negative temporal covariation), empirical work has demonstrated that competitive communities often exhibit synchronous dynamics (positive temporal covariation). This has led to the suggestion that environmental forcing dominates species dynamics; however, synchronous and compensatory dynamics may appear at different length scales and/or at different times, making it challenging to identify their relative importance. We compiled 58 long-term datasets of zooplankton abundance in north-temperate and sub-tropical lakes and used wavelet analysis to quantify general patterns in the times and scales at which synchronous/compensatory dynamics dominated zooplankton communities in different regions and across the entire dataset. Synchronous dynamics were far more prevalent at all scales and times and were ubiquitous at the annual scale. Although we found compensatory dynamics in approximately 14% of all combinations of time period/scale/lake, there were no consistent scales or time periods during which compensatory dynamics were apparent across different regions. Our results suggest that the processes driving compensatory dynamics may be local in their extent, while those generating synchronous dynamics operate at much larger scales. This highlights an important gap in our understanding of the interaction between environmental and biotic forces that structure communities. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Spatio-temporal dynamics of species richness in coastal fish communities

USGS Publications Warehouse

Lekve, K.; Boulinier, T.; Stenseth, N.C.; Gjøsaeter, J.; Fromentin, J-M.; Hines, J.E.; Nichols, J.D.

2002-01-01

Determining patterns of change in species richness and the processes underlying the dynamics of biodiversity are of key interest within the field of ecology, but few studies have investigated the dynamics of vertebrate communities at a decadal temporal scale. Here, we report findings on the spado-temporal variability in the richness and composition of fish communities along the Norwegian Skagerrak coast having been surveyed for more than half a century. Using statistical models incorporating non-detection and associated sampling variance, we estimate local species richness and changes in species composition allowing us to compute temporal variability in species richness. We tested whether temporal variation could be related to distance to the open sea and to local levels of pollution. Clear differences in mean species richness and temporal variability are observed between fjords that were and were not exposed to the effects of pollution. Altogether this indicates that the fjord is an appropriate scale for studying changes in coastal fish communities in space and time. The year-to-year rates of local extinction and turnover were found to be smaller than spatial differences in community composition. At the regional level, exposure to the open sea plays a homogenizing role, possibly due to coastal currents and advection.

Comparing mesophilic and thermophilic anaerobic digestion of chicken manure: Microbial community dynamics and process resilience

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niu, Qigui; Takemura, Yasuyuki; Kubota, Kengo

Highlights: • Microbial community dynamics and process functional resilience were investigated. • The threshold of TAN in mesophilic reactor was higher than the thermophilic reactor. • The recoverable archaeal community dynamic sustained the process resilience. • Methanosarcina was more sensitive than Methanoculleus on ammonia inhibition. • TAN and FA effects the dynamic of hydrolytic and acidogenic bacteria obviously. - Abstract: While methane fermentation is considered as the most successful bioenergy treatment for chicken manure, the relationship between operational performance and the dynamic transition of archaeal and bacterial communities remains poorly understood. Two continuous stirred-tank reactors were investigated under thermophilic andmore » mesophilic conditions feeding with 10%TS. The tolerance of thermophilic reactor on total ammonia nitrogen (TAN) was found to be 8000 mg/L with free ammonia (FA) 2000 mg/L compared to 16,000 mg/L (FA1500 mg/L) of mesophilic reactor. Biomethane production was 0.29 L/gV S{sub in} in the steady stage and decreased following TAN increase. After serious inhibition, the mesophilic reactor was recovered successfully by dilution and washing stratagem compared to the unrecoverable of thermophilic reactor. The relationship between the microbial community structure, the bioreactor performance and inhibitors such as TAN, FA, and volatile fatty acid was evaluated by canonical correspondence analysis. The performance of methanogenic activity and substrate removal efficiency were changed significantly correlating with the community evenness and phylogenetic structure. The resilient archaeal community was found even after serious inhibition in both reactors. Obvious dynamics of bacterial communities were observed in acidogenic and hydrolytic functional bacteria following TAN variation in the different stages.« less

Postfire shrub-cover dynamics: a 70-year fire history in big sagebrush communities.

USDA-ARS?s Scientific Manuscript database

Land managers use prescribed fire to meet rangeland management objectives. This study was conducted to quantify, from present conditions, the effect of time since last burn (TSLB) on shrub cover over 70 yr of fire history. We sampled mountain big sagebrush communities at the USDA, ARS, U.S. Sheep ...

Temporal bird community dynamics are strongly affected by landscape fragmentation in a Central American tropical forest region

USGS Publications Warehouse

Blandón, A.C.; Perelman, S.B.; Ramírez, M.; López, A.; Javier, O.; Robbins, Chandler S.

2016-01-01

Habitat loss and fragmentation are considered the main causes of species extinctions, particularly in tropical ecosystems. The objective of this work was to evaluate the temporal dynamics of tropical bird communities in landscapes with different levels of fragmentation in eastern Guatemala. We evaluated five bird community dynamic parameters for forest specialists and generalists: (1) species extinction, (2) species turnover, (3) number of colonizing species, (4) relative species richness, and (5) a homogeneity index. For each of 24 landscapes, community dynamic parameters were estimated from bird point count data, for the 1998–1999 and 2008–2009 periods, accounting for species’ detection probability. Forest specialists had higher extinction rates and a smaller number of colonizing species in landscapes with higher fragmentation, thus having lower species richness in both time periods. Alternatively, forest generalists elicited a completely different pattern, showing a curvilinear association to forest fragmentation for most parameters. Thus, greater community dynamism for forest generalists was shown in landscapes with intermediate levels of fragmentation. Our study supports general theory regarding the expected negative effects of habitat loss and fragmentation on the temporal dynamics of biotic communities, particularly for forest specialists, providing strong evidence from understudied tropical bird communities.

Community dynamics and ecosystem simplification in a high-CO2 ocean.

PubMed

Kroeker, Kristy J; Gambi, Maria Cristina; Micheli, Fiorenza

2013-07-30

Disturbances are natural features of ecosystems that promote variability in the community and ultimately maintain diversity. Although it is recognized that global change will affect environmental disturbance regimes, our understanding of the community dynamics governing ecosystem recovery and the maintenance of functional diversity in future scenarios is very limited. Here, we use one of the few ecosystems naturally exposed to future scenarios of environmental change to examine disturbance and recovery dynamics. We examine the recovery patterns of marine species from a physical disturbance across different acidification regimes caused by volcanic CO2 vents. Plots of shallow rocky reef were cleared of all species in areas of ambient, low, and extreme low pH that correspond to near-future and extreme scenarios for ocean acidification. Our results illustrate how acidification decreases the variability of communities, resulting in homogenization and reduced functional diversity at a landscape scale. Whereas the recovery trajectories in ambient pH were highly variable and resulted in a diverse range of assemblages, recovery was more predictable with acidification and consistently resulted in very similar algal-dominated assemblages. Furthermore, low pH zones had fewer signs of biological disturbance (primarily sea urchin grazing) and increased recovery rates of the dominant taxa (primarily fleshy algae). Together, our results highlight how environmental change can cause ecosystem simplification via environmentally mediated changes in community dynamics in the near future, with cascading impacts on functional diversity and ecosystem function.

Moving alcohol prevention research forward-Part II: new directions grounded in community-based system dynamics modeling.

PubMed

Apostolopoulos, Yorghos; Lemke, Michael K; Barry, Adam E; Lich, Kristen Hassmiller

2018-02-01

Given the complexity of factors contributing to alcohol misuse, appropriate epistemologies and methodologies are needed to understand and intervene meaningfully. We aimed to (1) provide an overview of computational modeling methodologies, with an emphasis on system dynamics modeling; (2) explain how community-based system dynamics modeling can forge new directions in alcohol prevention research; and (3) present a primer on how to build alcohol misuse simulation models using system dynamics modeling, with an emphasis on stakeholder involvement, data sources and model validation. Throughout, we use alcohol misuse among college students in the United States as a heuristic example for demonstrating these methodologies. System dynamics modeling employs a top-down aggregate approach to understanding dynamically complex problems. Its three foundational properties-stocks, flows and feedbacks-capture non-linearity, time-delayed effects and other system characteristics. As a methodological choice, system dynamics modeling is amenable to participatory approaches; in particular, community-based system dynamics modeling has been used to build impactful models for addressing dynamically complex problems. The process of community-based system dynamics modeling consists of numerous stages: (1) creating model boundary charts, behavior-over-time-graphs and preliminary system dynamics models using group model-building techniques; (2) model formulation; (3) model calibration; (4) model testing and validation; and (5) model simulation using learning-laboratory techniques. Community-based system dynamics modeling can provide powerful tools for policy and intervention decisions that can result ultimately in sustainable changes in research and action in alcohol misuse prevention. © 2017 Society for the Study of Addiction.

Mussel dynamics model: A hydroinformatics tool for analyzing the effects of different stressors on the dynamics of freshwater mussel communities

USGS Publications Warehouse

Morales, Y.; Weber, L.J.; Mynett, A.E.; Newton, T.J.

2006-01-01

A model for simulating freshwater mussel population dynamics is presented. The model is a hydroinformatics tool that integrates principles from ecology, river hydraulics, fluid mechanics and sediment transport, and applies the individual-based modelling approach for simulating population dynamics. The general model layout, data requirements, and steps of the simulation process are discussed. As an illustration, simulation results from an application in a 10 km reach of the Upper Mississippi River are presented. The model was used to investigate the spatial distribution of mussels and the effects of food competition in native unionid mussel communities, and communities infested by Dreissena polymorpha, the zebra mussel. Simulation results were found to be realistic and coincided with data obtained from the literature. These results indicate that the model can be a useful tool for assessing the potential effects of different stressors on long-term population dynamics, and consequently, may improve the current understanding of cause and effect relationships in freshwater mussel communities. ?? 2006 Elsevier B.V. All rights reserved.

Quantifying short-term dynamics of Parkinson's disease using self-reported symptom data from an Internet social network.

PubMed

Little, Max; Wicks, Paul; Vaughan, Timothy; Pentland, Alex

2013-01-24

Parkinson's disease (PD) is an incurable neurological disease with approximately 0.3% prevalence. The hallmark symptom is gradual movement deterioration. Current scientific consensus about disease progression holds that symptoms will worsen smoothly over time unless treated. Accurate information about symptom dynamics is of critical importance to patients, caregivers, and the scientific community for the design of new treatments, clinical decision making, and individual disease management. Long-term studies characterize the typical time course of the disease as an early linear progression gradually reaching a plateau in later stages. However, symptom dynamics over durations of days to weeks remains unquantified. Currently, there is a scarcity of objective clinical information about symptom dynamics at intervals shorter than 3 months stretching over several years, but Internet-based patient self-report platforms may change this. To assess the clinical value of online self-reported PD symptom data recorded by users of the health-focused Internet social research platform PatientsLikeMe (PLM), in which patients quantify their symptoms on a regular basis on a subset of the Unified Parkinson's Disease Ratings Scale (UPDRS). By analyzing this data, we aim for a scientific window on the nature of symptom dynamics for assessment intervals shorter than 3 months over durations of several years. Online self-reported data was validated against the gold standard Parkinson's Disease Data and Organizing Center (PD-DOC) database, containing clinical symptom data at intervals greater than 3 months. The data were compared visually using quantile-quantile plots, and numerically using the Kolmogorov-Smirnov test. By using a simple piecewise linear trend estimation algorithm, the PLM data was smoothed to separate random fluctuations from continuous symptom dynamics. Subtracting the trends from the original data revealed random fluctuations in symptom severity. The average magnitude of

Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time-to-event in presence of censoring and competing risks.

PubMed

Blanche, Paul; Proust-Lima, Cécile; Loubère, Lucie; Berr, Claudine; Dartigues, Jean-François; Jacqmin-Gadda, Hélène

2015-03-01

Thanks to the growing interest in personalized medicine, joint modeling of longitudinal marker and time-to-event data has recently started to be used to derive dynamic individual risk predictions. Individual predictions are called dynamic because they are updated when information on the subject's health profile grows with time. We focus in this work on statistical methods for quantifying and comparing dynamic predictive accuracy of this kind of prognostic models, accounting for right censoring and possibly competing events. Dynamic area under the ROC curve (AUC) and Brier Score (BS) are used to quantify predictive accuracy. Nonparametric inverse probability of censoring weighting is used to estimate dynamic curves of AUC and BS as functions of the time at which predictions are made. Asymptotic results are established and both pointwise confidence intervals and simultaneous confidence bands are derived. Tests are also proposed to compare the dynamic prediction accuracy curves of two prognostic models. The finite sample behavior of the inference procedures is assessed via simulations. We apply the proposed methodology to compare various prediction models using repeated measures of two psychometric tests to predict dementia in the elderly, accounting for the competing risk of death. Models are estimated on the French Paquid cohort and predictive accuracies are evaluated and compared on the French Three-City cohort. © 2014, The International Biometric Society.

Market dynamics of community pharmacies in Minnesota, U.S. from 1992 through 2012.

PubMed

Schommer, Jon C; Yusuf, Akeem A; Hadsall, Ronald S

2014-01-01

An understanding of community pharmacy market dynamics is important for monitoring access points for pharmacist services. The purpose of this study was to describe (1) changes in pharmacy mix (independent versus chain) between 1992 and 2002 and between 2002 and 2012 for 87 counties in Minnesota (state in U.S.) and (2) the number (and proportion) of community pharmacies in Minnesota for the years 1992, 2002, and 2012 using a new categorization method developed specifically for this study. Data included licensure records for 1992, 2002, and 2012 from the State of Minnesota Board of Pharmacy and county level demographics for 1990, 2000 and 2010 from the US Census Bureau. Descriptive statistics were used to summarize findings over time and to describe associations between study variables. The ratio of independent pharmacies to chain pharmacies changed from approximately 2:1 in 1992 to 1:2 in 2012. The primary market factors associated with changes in the number of community pharmacies per county were (1) the metropolitan designation of the county and (2) whether the population density (persons/square mile) was increasing or decreasing. The face of community pharmacy in Minnesota changed between 1992 and 2012. By 2012, pharmacies were located in traditional retail pharmacies, mass merchandiser outlets, supermarkets, and clinics/medical centers. Furthermore, specialty pharmacies grew in proportion to meet patient needs. Between 1992 and 2012, the market dynamics of community pharmacies in Minnesota was characterized by vigorous market entry and exit. In light of recent health reform that is exhibiting characteristics such as continuity-of-care models, performance-based payment, technology advances, and the care of patients becoming more "ambulatory" (versus in-patient), we suggest that the market dynamics of community pharmacies will continue to exhibit vigorous market entry and exit in this new environment. It is proposed that the community pharmacy categories developed

The Community Surface Dynamics Modeling System: Experiences on Building a Collaborative Modeling Platform

NASA Astrophysics Data System (ADS)

Overeem, I.; Hutton, E.; Kettner, A.; Peckham, S. D.; Syvitski, J. P.

2012-12-01

The Community Surface Dynamics Modeling System - CSDMS- develops a software platform with shared and coupled modules for modeling earth surface processes as a community resource. The framework allows prediction of water, sediment and nutrient transport through the landscape and seacape. The underlying paradigm is that the Earth surface we live on is a dynamic system; topography changes with seasons, with landslides and earthquakes, with erosion and deposition. The Earth Surface changes due to storms and floods, and important boundaries, like the coast, are ever-moving features. CSDMS sets out to make better predictions of these changes. Earth surface process modeling bridges the terrestrial, coastal and marine domains and requires understanding of the system over a range of time scales, which inherently needs interdisciplinarity. Members of CSDMS (~830 in July 2012) are largely from academic institutions (˜75%), followed by federal agencies (˜17%), and oil and gas companies (˜5%). Members and governmental bodies meet once annually and rely additionally on web-based information for communication. As an organization that relies on volunteer participation, CSDMS faces challenges to scientific collaboration. Encouraging volunteerism among its members to provide and adapt metadata and model code to be sufficiently standardized for coupling is crucial to building an integrated community modeling system. We here present CSDMS strategies aimed at providing the appropriate technical tools and cyberinfrastructure to support a variety of user types, ranging from advanced to novice modelers. Application of these advances in science is key, both into the educational realm and for managers and decision-makers. We discuss some of the implemented ideas to further organizational transparency and user engagement in small-scale governance, such as advanced trackers and voting systems for model development prioritization through the CSDMS wiki. We analyzed data on community

Community Collectivism: A social dynamic approach to conceptualizing culture.

PubMed

Akkuş, Birol; Postmes, Tom; Stroebe, Katherine

2017-01-01

Culture shapes individuals, but the measurement of cultural differences has proven a challenge. Traditional measures of cultural values focus on individual perceptions. We suggest that values are established and maintained within social communities of proximate others, such as the family and its social environment. Within such communities, values serve to maintain collective harmony whilst preserving individual agency. From a social-dynamic analysis of communities, we infer that community values of loyalty regulate individual commitment, values of honor regulate norm compliance, and values of group hierarchy maintain a division of labor. In addition, communities may regulate the ways in which individuals have independent agency. A new scale to measure these values was validated in four studies (N = 398, 112, 465 and 111) among Dutch (religious and non-religious), Turkish-Dutch, Surinamese and Turkish groups. Values and practices were measured at the level of the individual ('What do you value?') and at the level of the perceived community ('What does your community value?'). Results show that, unlike individual-level measures of individualism/collectivism, this scale has excellent reliability, differentiates between cultural groups, and has predictive validity for future (voting) behavior. This approach provides a new way of conceptualizing culture, a new measure of collectivism and new insights into the role of proximate others in shaping culture.

Low latitude ionospheric TEC responses to dynamical complexity quantifiers during transient events over Nigeria

NASA Astrophysics Data System (ADS)

Ogunsua, Babalola

2018-04-01

In this study, the values of chaoticity and dynamical complexity parameters for some selected storm periods in the year 2011 and 2012 have been computed. This was done using detrended TEC data sets measured from Birnin-Kebbi, Torro and Enugu global positioning system (GPS) receiver stations in Nigeria. It was observed that the significance of difference (SD) values were mostly greater than 1.96 but surprisingly lower than 1.96 in September 29, 2011. The values of the computed SD were also found to be reduced in most cases just after the geomagnetic storm with immediate recovery a day after the main phase of the storm while the values of Lyapunov exponent and Tsallis entropy remains reduced due to the influence of geomagnetic storms. It was also observed that the value of Lyapunov exponent and Tsallis entropy reveals similar variation pattern during storm period in most cases. Also recorded surprisingly were lower values of these dynamical quantifiers during the solar flare event of August 8th and 9th of the year 2011. The possible mechanisms responsible for these observations were further discussed in this work. However, our observations show that the ionospheric effects of some other possible transient events other than geomagnetic storms can also be revealed by the variation of chaoticity and dynamical complexity.

Characterization of bacterial community dynamics in a full-scale drinking water treatment plant.

PubMed

Li, Cuiping; Ling, Fangqiong; Zhang, Minglu; Liu, Wen-Tso; Li, Yuxian; Liu, Wenjun

2017-01-01

Understanding the spatial and temporal dynamics of microbial communities in drinking water systems is vital to securing the microbial safety of drinking water. The objective of this study was to comprehensively characterize the dynamics of microbial biomass and bacterial communities at each step of a full-scale drinking water treatment plant in Beijing, China. Both bulk water and biofilm samples on granular activated carbon (GAC) were collected over 9months. The proportion of cultivable cells decreased during the treatment processes, and this proportion was higher in warm season than cool season, suggesting that treatment processes and water temperature probably had considerable impact on the R2A cultivability of total bacteria. 16s rRNA gene based 454 pyrosequencing analysis of the bacterial community revealed that Proteobacteria predominated in all samples. The GAC biofilm harbored a distinct population with a much higher relative abundance of Acidobacteria than water samples. Principle coordinate analysis and one-way analysis of similarity indicated that the dynamics of the microbial communities in bulk water and biofilm samples were better explained by the treatment processes rather than by sampling time, and distinctive changes of the microbial communities in water occurred after GAC filtration. Furthermore, 20 distinct OTUs contributing most to the dissimilarity among samples of different sampling locations and 6 persistent OTUs present in the entire treatment process flow were identified. Overall, our findings demonstrate the significant effects that treatment processes have on the microbial biomass and community fluctuation and provide implications for further targeted investigation on particular bacteria populations. Copyright © 2016. Published by Elsevier B.V.

Visualising uncertainty: interpreting quantified geoscientific inversion outputs for a diverse user community.

NASA Astrophysics Data System (ADS)

Reading, A. M.; Morse, P. E.; Staal, T.

2017-12-01

Geoscientific inversion outputs, such as seismic tomography contour images, are finding increasing use amongst scientific user communities that have limited knowledge of the impact of output parameter uncertainty on subsequent interpretations made from such images. We make use of a newly written computer application which enables seismic tomography images to be displayed in a performant 3D graphics environment. This facilitates the mapping of colour scales to the human visual sensorium for the interactive interpretation of contoured inversion results incorporating parameter uncertainty. Two case examples of seismic tomography inversions or contoured compilations are compared from the southern hemisphere continents of Australia and Antarctica. The Australian example is based on the AuSREM contoured seismic wavespeed model while the Antarctic example is a valuable but less well constrained result. Through adjusting the multiple colour gradients, layer separations, opacity, illumination, shadowing and background effects, we can optimise the insights obtained from the 3D structure in the inversion compilation or result. Importantly, we can also limit the display to show information in a way that is mapped to the uncertainty in the 3D result. Through this practical application, we demonstrate that the uncertainty in the result can be handled through a well-posed mapping of the parameter values to displayed colours in the knowledge of what is perceived visually by a typical human. We found that this approach maximises the chance of a useful tectonic interpretation by a diverse scientific user community. In general, we develop the idea that quantified inversion uncertainty can be used to tailor the way that the output is presented to the analyst for scientific interpretation.

Bacterial Community Composition and Dynamics Spanning Five Years in Freshwater Bog Lakes

DOE PAGES

Linz, Alexandra M.; Crary, Benjamin C.; Shade, Ashley; ...

2017-06-28

Bacteria play a key role in freshwater biogeochemical cycling, but long-term trends in freshwater bacterial community composition and dynamics are not yet well characterized. We used a multiyear time series of 16S rRNA gene amplicon sequencing data from eight bog lakes to census the freshwater bacterial community and observe annual and seasonal trends in abundance. The sites that we studied encompassed a range of water column mixing frequencies, which we hypothesized would be associated with trends in alpha and beta diversity. Each lake and layer contained a distinct bacterial community, with distinct levels of richness and indicator taxa that likelymore » reflected the environmental conditions of each lake type sampled, including Actinobacteria in polymictic lakes (i.e., lakes with multiple mixing events per year), Methylophilales in dimictic lakes (lakes with two mixing events per year, usually in spring and fall), and “CandidatusOmnitrophica” in meromictic lakes (lakes with no recorded mixing events). The community present during each year at each site was also surprisingly unique. Despite unexpected interannual variability in community composition, we detected a core community of taxa found in all lakes and layers, including Actinobacteria tribe acI-B2 and Betaprotobacteria lineage PnecC. Although trends in abundance did not repeat annually, each freshwater lineage within the communities had a consistent lifestyle, defined by persistence, abundance, and variability. The results of our analysis emphasize the importance of long-term multisite observations, as analyzing only a single year of data or one lake would not have allowed us to describe the dynamics and composition of these freshwater bacterial communities to the extent presented here. Lakes are excellent systems for investigating bacterial community dynamics because they have clear boundaries and strong environmental gradients. The results of our research demonstrate that bacterial community

Bacterial Community Composition and Dynamics Spanning Five Years in Freshwater Bog Lakes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Linz, Alexandra M.; Crary, Benjamin C.; Shade, Ashley

Bacteria play a key role in freshwater biogeochemical cycling, but long-term trends in freshwater bacterial community composition and dynamics are not yet well characterized. We used a multiyear time series of 16S rRNA gene amplicon sequencing data from eight bog lakes to census the freshwater bacterial community and observe annual and seasonal trends in abundance. The sites that we studied encompassed a range of water column mixing frequencies, which we hypothesized would be associated with trends in alpha and beta diversity. Each lake and layer contained a distinct bacterial community, with distinct levels of richness and indicator taxa that likelymore » reflected the environmental conditions of each lake type sampled, including Actinobacteria in polymictic lakes (i.e., lakes with multiple mixing events per year), Methylophilales in dimictic lakes (lakes with two mixing events per year, usually in spring and fall), and “CandidatusOmnitrophica” in meromictic lakes (lakes with no recorded mixing events). The community present during each year at each site was also surprisingly unique. Despite unexpected interannual variability in community composition, we detected a core community of taxa found in all lakes and layers, including Actinobacteria tribe acI-B2 and Betaprotobacteria lineage PnecC. Although trends in abundance did not repeat annually, each freshwater lineage within the communities had a consistent lifestyle, defined by persistence, abundance, and variability. The results of our analysis emphasize the importance of long-term multisite observations, as analyzing only a single year of data or one lake would not have allowed us to describe the dynamics and composition of these freshwater bacterial communities to the extent presented here. Lakes are excellent systems for investigating bacterial community dynamics because they have clear boundaries and strong environmental gradients. The results of our research demonstrate that bacterial community

Effects of ENSO and Temporal Rainfall Variation on the Dynamics of Successional Communities in Old-Field Succession of a Tropical Dry Forest

PubMed Central

Maza-Villalobos, Susana; Poorter, Lourens; Martínez-Ramos, Miguel

2013-01-01

The effects of temporal variation of rainfall on secondary succession of tropical dry ecosystems are poorly understood. We studied effects of inter-seasonal and inter-year rainfall variation on the dynamics of regenerative successional communities of a tropical dry forest in Mexico. We emphasized the effects caused by the severe El Niño Southern Oscillation (ENSO) occurred in 2005. We established permanent plots in sites representing a chronosequence of Pasture (abandoned pastures, 0–1 years fallow age), Early (3–5), Intermediate (8–12), and Old-Growth Forest categories (n = 3 per category). In total, 8210 shrubs and trees 10 to 100-cm height were identified, measured, and monitored over four years. Rates of plant recruitment, growth and mortality, and gain and loss of species were quantified per season (dry vs. rainy), year, and successional category, considering whole communities and separating seedlings from sprouts and shrubs from trees. Community rates changed with rainfall variation without almost any effect of successional stage. Mortality and species loss rates peaked during the ENSO year and the following year; however, after two rainy years mortality peaked in the rainy season. Such changes could result from the severe drought in the ENSO year, and of the outbreak of biotic agents during the following rainy years. Growth, recruitment and species gain rates were higher in the rainy season but they were significantly reduced after the ENSO year. Seedlings exhibited higher recruitment and mortality rate than sprouts, and shrubs showed higher recruitment than trees. ENSO strongly impacted both the dynamics and trajectory of succession, creating transient fluctuations in the abundance and species richness of the communities. Overall, there was a net decline in plant and species density in most successional stages along the years. Therefore, strong drought events have critical consequences for regeneration dynamics, delaying the successional process

a New Dynamic Community Model for Social Networks

NASA Astrophysics Data System (ADS)

Lu, Zhe-Ming; Wu, Zhen; Guo, Shi-Ze; Chen, Zhe; Song, Guang-Hua

2014-09-01

In this paper, based on the phenomenon that individuals join into and jump from the organizations in the society, we propose a dynamic community model to construct social networks. Two parameters are adopted in our model, one is the communication rate Pa that denotes the connection strength in the organization and the other is the turnover rate Pb, that stands for the frequency of jumping among the organizations. Based on simulations, we analyze not only the degree distribution, the clustering coefficient, the average distance and the network diameter but also the group distribution which is closely related to their community structure. Moreover, we discover that the networks generated by the proposed model possess the small-world property and can well reproduce the networks of social contacts.

A 15 Year Ecological Comparison for the Market Dynamics of Minnesota Community Pharmacies from 2002 to 2017.

PubMed

Olson, Anthony W; Schommer, Jon C; Hadsall, Ronald S

2018-06-02

Background: Understanding the factors that influence the market entry, exit, and stability of community pharmacies (i.e., market dynamics) is important for stakeholders ranging from patients to health policymakers and small business owners to large corporate institutions. Objective: The study's first objective was to describe the market dynamics of community pharmacies for Minnesota counties in 2002, 2007, 2012, and 2017 by associating county (a) population density and (b) metropolitan designation with the change in the number of 'All community pharmacies,' 'Chain community pharmacies', and 'Independent community pharmacies'. The study's second objective was to describe the number and proportion of community pharmacies for Minnesota counties in 2002, 2007, 2012, and 2017 by (1) 'Business Organization Structure' and (2) 'Pharmacy Type.' Methods: County-level data were obtained from the Minnesota Board of Pharmacy, US Census Bureau, and Minnesota State Demographic Center for 2002, 2007, 2012, and 2017. Findings were summarized and the associations between study variables described using descriptive statistics. Results: The ratio of 'Independent community pharmacies' to 'Chain community pharmacies' was about 1:1 (466:530) in 2002, 1:2 (352:718) in 2007, 1:2 (387:707) in 2012, and 1:3 (256:807) in 2017. There was not a consistent relationship that carried through the 15 year analysis between county population density and metropolitan designation and the market dynamic patterns of community pharmacies. The types of pharmacy in Minnesota changed significantly over the study with increases in state, regional, and national chains and declines in single entity and small chain independents. There were also notable declines in mass merchandiser community pharmacies and increases in clinic and medical center community pharmacies. Discussion: The findings suggest that different or additional factors beyond traditional market dynamic predictors of population density and

COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters.

PubMed

Links, Jonathan M; Schwartz, Brian S; Lin, Sen; Kanarek, Norma; Mitrani-Reiser, Judith; Sell, Tara Kirk; Watson, Crystal R; Ward, Doug; Slemp, Cathy; Burhans, Robert; Gill, Kimberly; Igusa, Tak; Zhao, Xilei; Aguirre, Benigno; Trainor, Joseph; Nigg, Joanne; Inglesby, Thomas; Carbone, Eric; Kendra, James M

2018-02-01

Policy-makers and practitioners have a need to assess community resilience in disasters. Prior efforts conflated resilience with community functioning, combined resistance and recovery (the components of resilience), and relied on a static model for what is inherently a dynamic process. We sought to develop linked conceptual and computational models of community functioning and resilience after a disaster. We developed a system dynamics computational model that predicts community functioning after a disaster. The computational model outputted the time course of community functioning before, during, and after a disaster, which was used to calculate resistance, recovery, and resilience for all US counties. The conceptual model explicitly separated resilience from community functioning and identified all key components for each, which were translated into a system dynamics computational model with connections and feedbacks. The components were represented by publicly available measures at the county level. Baseline community functioning, resistance, recovery, and resilience evidenced a range of values and geographic clustering, consistent with hypotheses based on the disaster literature. The work is transparent, motivates ongoing refinements, and identifies areas for improved measurements. After validation, such a model can be used to identify effective investments to enhance community resilience. (Disaster Med Public Health Preparedness. 2018;12:127-137).

Epiphytic lichen community dynamics in deciduous forests around a phosphorus fertiliser factory in Central Lithuania.

PubMed

Motiejūnaite, Jurga

2007-03-01

The detailed dynamics of epiphytic lichen communities were observed while studying permanent quadrats in the zone of influence of a phosphorus fertiliser factory in central Lithuania. The most significant changes were induced by several factors: changes in macroenvironment (increase of illumination), bark scaling, succession processes, individual growth characteristics of the community members, and influence of fungal infection and invertebrate grazing. None of these changes could be directly linked with air pollution. These observations have shown that in conditions of more or less stable pollution, epiphytic community dynamics should be evaluated with care, the best indicators of the characteristics of the communities being species richness and presence/absence and abundance of indicator (nitrophilous or acidophilous) species.

Imaging the Population Dynamics of Bacterial Communities in the Zebrafish Gut

NASA Astrophysics Data System (ADS)

Jemielita, Matthew; Taormina, Michael; Burns, Adam; Zac Stephens, W.; Hampton, Jennifer; Guillemin, Karen; Parthasarathy, Raghuveer

2013-03-01

The vertebrate gut is home to a diverse microbial ecosystem whose composition has a strong influence on the development and health of the host organism. While researchers are increasingly able to identify the constituent members of the microbiome, very little is known about the spatial and temporal dynamics of commensal microbial communities, including the mechanisms by which communities nucleate, grow, and interact. We address these issues using a model organism: the larval zebrafish (Danio rerio) prepared microbe-free and inoculated with controlled compositions of fluorophore-expressing bacteria. Live imaging with light sheet fluorescence microscopy enables visualization of individual bacterial cells as well as growing colonies over the entire volume of the gut over periods up to 24 hours. We analyze the structure and dynamics of imaged bacterial communities, uncovering correlations between population size, growth rates, and the timing of inoculations that suggest the existence of active changes in the host environment induced by early bacterial exposure. Our data provide the first visualizations of gut microbiota development over an extended period of time in a vertebrate.

Community Collectivism: A social dynamic approach to conceptualizing culture

PubMed Central

Postmes, Tom; Stroebe, Katherine

2017-01-01

Culture shapes individuals, but the measurement of cultural differences has proven a challenge. Traditional measures of cultural values focus on individual perceptions. We suggest that values are established and maintained within social communities of proximate others, such as the family and its social environment. Within such communities, values serve to maintain collective harmony whilst preserving individual agency. From a social-dynamic analysis of communities, we infer that community values of loyalty regulate individual commitment, values of honor regulate norm compliance, and values of group hierarchy maintain a division of labor. In addition, communities may regulate the ways in which individuals have independent agency. A new scale to measure these values was validated in four studies (N = 398, 112, 465 and 111) among Dutch (religious and non-religious), Turkish-Dutch, Surinamese and Turkish groups. Values and practices were measured at the level of the individual (‘What do you value?’) and at the level of the perceived community (‘What does your community value?’). Results show that, unlike individual-level measures of individualism/collectivism, this scale has excellent reliability, differentiates between cultural groups, and has predictive validity for future (voting) behavior. This approach provides a new way of conceptualizing culture, a new measure of collectivism and new insights into the role of proximate others in shaping culture. PMID:28957447

CAM-SE: A scalable spectral element dynamical core for the Community Atmosphere Model.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dennis, John; Edwards, Jim; Evans, Kate J

2012-01-01

The Community Atmosphere Model (CAM) version 5 includes a spectral element dynamical core option from NCAR's High-Order Method Modeling Environment. It is a continuous Galerkin spectral finite element method designed for fully unstructured quadrilateral meshes. The current configurations in CAM are based on the cubed-sphere grid. The main motivation for including a spectral element dynamical core is to improve the scalability of CAM by allowing quasi-uniform grids for the sphere that do not require polar filters. In addition, the approach provides other state-of-the-art capabilities such as improved conservation properties. Spectral elements are used for the horizontal discretization, while most othermore » aspects of the dynamical core are a hybrid of well tested techniques from CAM's finite volume and global spectral dynamical core options. Here we first give a overview of the spectral element dynamical core as used in CAM. We then give scalability and performance results from CAM running with three different dynamical core options within the Community Earth System Model, using a pre-industrial time-slice configuration. We focus on high resolution simulations of 1/4 degree, 1/8 degree, and T340 spectral truncation.« less

Quantifying the impacts of land surface schemes and dynamic vegetation on the model dependency of projected changes in surface energy and water budgets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Miao; Wang, Guiling; Chen, Haishan

Assessing and quantifying the uncertainties in projected future changes of energy and water budgets over land surface are important steps toward improving our confidence in climate change projections. In our study, the contribution of land surface models to the inter-GCM variation of projected future changes in land surface energy and water fluxes are assessed based on output from 19 global climate models (GCMs) and offline Community Land Model version 4 (CLM4) simulations driven by meteorological forcing from the 19 GCMs. Similar offline simulations using CLM4 with its dynamic vegetation submodel are also conducted to investigate how dynamic vegetation feedback, amore » process that is being added to more earth system models, may amplify or moderate the intermodel variations of projected future changes. Projected changes are quantified as the difference between the 2081–2100 period from the Representative Concentration Pathway 8.5 (RCP8.5) future experiment and the 1981–2000 period from the historical simulation. Under RCP8.5, projected changes in surface water and heat fluxes show a high degree of model dependency across the globe. Although precipitation is very likely to increase in the high latitudes of the Northern Hemisphere, a high degree of model-related uncertainty exists for evapotranspiration, soil water content, and surface runoff, suggesting discrepancy among land surface models (LSMs) in simulating the surface hydrological processes and snow-related processes. Large model-related uncertainties for the surface water budget also exist in the Tropics including southeastern South America and Central Africa. Moreover, these uncertainties would be reduced in the hypothetical scenario of a single near-perfect land surface model being used across all GCMs, suggesting the potential to reduce uncertainties through the use of more consistent approaches toward land surface model development. Under such a scenario, the most significant reduction is likely to

Quantifying the impacts of land surface schemes and dynamic vegetation on the model dependency of projected changes in surface energy and water budgets

DOE PAGES

Yu, Miao; Wang, Guiling; Chen, Haishan

2016-03-01

Assessing and quantifying the uncertainties in projected future changes of energy and water budgets over land surface are important steps toward improving our confidence in climate change projections. In our study, the contribution of land surface models to the inter-GCM variation of projected future changes in land surface energy and water fluxes are assessed based on output from 19 global climate models (GCMs) and offline Community Land Model version 4 (CLM4) simulations driven by meteorological forcing from the 19 GCMs. Similar offline simulations using CLM4 with its dynamic vegetation submodel are also conducted to investigate how dynamic vegetation feedback, amore » process that is being added to more earth system models, may amplify or moderate the intermodel variations of projected future changes. Projected changes are quantified as the difference between the 2081–2100 period from the Representative Concentration Pathway 8.5 (RCP8.5) future experiment and the 1981–2000 period from the historical simulation. Under RCP8.5, projected changes in surface water and heat fluxes show a high degree of model dependency across the globe. Although precipitation is very likely to increase in the high latitudes of the Northern Hemisphere, a high degree of model-related uncertainty exists for evapotranspiration, soil water content, and surface runoff, suggesting discrepancy among land surface models (LSMs) in simulating the surface hydrological processes and snow-related processes. Large model-related uncertainties for the surface water budget also exist in the Tropics including southeastern South America and Central Africa. Moreover, these uncertainties would be reduced in the hypothetical scenario of a single near-perfect land surface model being used across all GCMs, suggesting the potential to reduce uncertainties through the use of more consistent approaches toward land surface model development. Under such a scenario, the most significant reduction is likely to

Critical Zone Co-dynamics: Quantifying Interactions between Subsurface, Land Surface, and Vegetation Properties Using UAV and Geophysical Approaches

NASA Astrophysics Data System (ADS)

Dafflon, B.; Leger, E.; Peterson, J.; Falco, N.; Wainwright, H. M.; Wu, Y.; Tran, A. P.; Brodie, E.; Williams, K. H.; Versteeg, R.; Hubbard, S. S.

2017-12-01

Improving understanding and modelling of terrestrial systems requires advances in measuring and quantifying interactions among subsurface, land surface and vegetation processes over relevant spatiotemporal scales. Such advances are important to quantify natural and managed ecosystem behaviors, as well as to predict how watershed systems respond to increasingly frequent hydrological perturbations, such as droughts, floods and early snowmelt. Our study focuses on the joint use of UAV-based multi-spectral aerial imaging, ground-based geophysical tomographic monitoring (incl., electrical and electromagnetic imaging) and point-scale sensing (soil moisture sensors and soil sampling) to quantify interactions between above and below ground compartments of the East River Watershed in the Upper Colorado River Basin. We evaluate linkages between physical properties (incl. soil composition, soil electrical conductivity, soil water content), metrics extracted from digital surface and terrain elevation models (incl., slope, wetness index) and vegetation properties (incl., greenness, plant type) in a 500 x 500 m hillslope-floodplain subsystem of the watershed. Data integration and analysis is supported by numerical approaches that simulate the control of soil and geomorphic characteristic on hydrological processes. Results provide an unprecedented window into critical zone interactions, revealing significant below- and above-ground co-dynamics. Baseline geophysical datasets provide lithological structure along the hillslope, which includes a surface soil horizon, underlain by a saprolite layer and the fractured Mancos shale. Time-lapse geophysical data show very different moisture dynamics in various compartments and locations during the winter and growing season. Integration with aerial imaging reveals a significant linkage between plant growth and the subsurface wetness, soil characteristics and the topographic gradient. The obtained information about the organization and

Quantifying the uncertainty in heritability.

PubMed

Furlotte, Nicholas A; Heckerman, David; Lippert, Christoph

2014-05-01

The use of mixed models to determine narrow-sense heritability and related quantities such as SNP heritability has received much recent attention. Less attention has been paid to the inherent variability in these estimates. One approach for quantifying variability in estimates of heritability is a frequentist approach, in which heritability is estimated using maximum likelihood and its variance is quantified through an asymptotic normal approximation. An alternative approach is to quantify the uncertainty in heritability through its Bayesian posterior distribution. In this paper, we develop the latter approach, make it computationally efficient and compare it to the frequentist approach. We show theoretically that, for a sufficiently large sample size and intermediate values of heritability, the two approaches provide similar results. Using the Atherosclerosis Risk in Communities cohort, we show empirically that the two approaches can give different results and that the variance/uncertainty can remain large.

Quantifying the uncertainty in heritability

PubMed Central

Furlotte, Nicholas A; Heckerman, David; Lippert, Christoph

2014-01-01

The use of mixed models to determine narrow-sense heritability and related quantities such as SNP heritability has received much recent attention. Less attention has been paid to the inherent variability in these estimates. One approach for quantifying variability in estimates of heritability is a frequentist approach, in which heritability is estimated using maximum likelihood and its variance is quantified through an asymptotic normal approximation. An alternative approach is to quantify the uncertainty in heritability through its Bayesian posterior distribution. In this paper, we develop the latter approach, make it computationally efficient and compare it to the frequentist approach. We show theoretically that, for a sufficiently large sample size and intermediate values of heritability, the two approaches provide similar results. Using the Atherosclerosis Risk in Communities cohort, we show empirically that the two approaches can give different results and that the variance/uncertainty can remain large. PMID:24670270

The effects of coastal development on sponge abundance, diversity, and community composition on Jamaican coral reefs.

PubMed

Stubler, Amber D; Duckworth, Alan R; Peterson, Bradley J

2015-07-15

Over the past decade, development along the northern coast of Jamaica has accelerated, resulting in elevated levels of sedimentation on adjacent reefs. To understand the effects of this development on sponge community dynamics, we conducted surveys at three locations with varying degrees of adjacent coastal development to quantify species richness, abundance and diversity at two depths (8-10 m and 15-18 m). Sediment accumulation rate, total suspended solids and other water quality parameters were also quantified. The sponge community at the location with the least coastal development and anthropogenic influence was often significantly different from the other two locations, and exhibited higher sponge abundance, richness, and diversity. Sponge community composition and size distribution were statistically different among locations. This study provides correlative evidence that coastal development affects aspects of sponge community ecology, although the precise mechanisms are still unclear. Copyright © 2015 Elsevier Ltd. All rights reserved.

Quantifying predictability variations in a low-order ocean-atmosphere model - A dynamical systems approach

NASA Technical Reports Server (NTRS)

Nese, Jon M.; Dutton, John A.

1993-01-01

The predictability of the weather and climatic states of a low-order moist general circulation model is quantified using a dynamic systems approach, and the effect of incorporating a simple oceanic circulation on predictability is evaluated. The predictability and the structure of the model attractors are compared using Liapunov exponents, local divergence rates, and the correlation and Liapunov dimensions. It was found that the activation of oceanic circulation increases the average error doubling time of the atmosphere and the coupled ocean-atmosphere system by 10 percent and decreases the variance of the largest local divergence rate by 20 percent. When an oceanic circulation develops, the average predictability of annually averaged states is improved by 25 percent and the variance of the largest local divergence rate decreases by 25 percent.

Synchrony in small mammal community dynamics across a forested landscape

Treesearch

Ryan B. Stephens; Daniel J. Hocking; Mariko Yamasaki; Rebecca J. Rowe

2016-01-01

Long- term studies at local scales indicate that fluctuations in abundance among trophically similar species are often temporally synchronized. Complementary studies on synchrony across larger spatial extents are less common, as are studies that investigate the subsequent impacts on community dynamics across the landscape. We investigate the impact of species...

Quantifying temporal trends in fisheries abundance using Bayesian dynamic linear models: A case study of riverine Smallmouth Bass populations

USGS Publications Warehouse

Schall, Megan K.; Blazer, Vicki S.; Lorantas, Robert M.; Smith, Geoffrey; Mullican, John E.; Keplinger, Brandon J.; Wagner, Tyler

2018-01-01

Detecting temporal changes in fish abundance is an essential component of fisheries management. Because of the need to understand short‐term and nonlinear changes in fish abundance, traditional linear models may not provide adequate information for management decisions. This study highlights the utility of Bayesian dynamic linear models (DLMs) as a tool for quantifying temporal dynamics in fish abundance. To achieve this goal, we quantified temporal trends of Smallmouth Bass Micropterus dolomieu catch per effort (CPE) from rivers in the mid‐Atlantic states, and we calculated annual probabilities of decline from the posterior distributions of annual rates of change in CPE. We were interested in annual declines because of recent concerns about fish health in portions of the study area. In general, periods of decline were greatest within the Susquehanna River basin, Pennsylvania. The declines in CPE began in the late 1990s—prior to observations of fish health problems—and began to stabilize toward the end of the time series (2011). In contrast, many of the other rivers investigated did not have the same magnitude or duration of decline in CPE. Bayesian DLMs provide information about annual changes in abundance that can inform management and are easily communicated with managers and stakeholders.

Quantifying a Total Non-Methane Hydrocarbon Signal using Low-Cost VOC Sensors in an Effort to Help Communities Learn More About their Air Quality

NASA Astrophysics Data System (ADS)

Collier, A. M.; Hannigan, M.; Piedrahita, R.; Casey, J. G.; Johnston, J.; Chiang, S.

2016-12-01

The growing accessibility of low-cost air quality monitoring technologies has led to their increased usage among community-based organizations, particularly for the monitoring of pollutants dangerous to human health (e.g., hazardous air pollutants or HAPS). However, often these low-cost sensors are `off-the-shelf' and are being utilized in a manner that differs from their intended purpose - necessitating high quality calibrations. For example, VOC sensors intended for the detection of high levels of a particular compound in an industrial setting may instead be used for ambient monitoring of a group of VOCs. Academic/community partnerships can be an ideal way to improve this type of sensor quantification while providing a community with not only the opportunity to use these technologies with additional support around data quality, but also the opportunity for education around the abilities and applications of low-cost sensors. In the spring of 2016, our lab at the University of Colorado, Boulder partnered with communities in Los Angeles and Kern County to deploy low-cost air quality monitors for the purpose of quantifying methane and non-methane hydrocarbon signals in an effort to learn more about potential impacts from local sources (e.g., nearby highways and oil & gas development). The monitoring platform was developed in our lab and is capable of logging multiple gas phase species as well as some environmental parameters. The monitors include two different metal oxide VOC sensors - each with slightly different sensing capabilities. Calibration was achieved using a pre- and post-deployment field normalization to reference monitoring equipment maintained by the South Coast Air Quality Management District. Monitors were then deployed at locations throughout the community. We will present results on our efforts to quantify a total non-methane hydrocarbon signal, observations from the field data, and recommendations for academic/community partnerships formed around

Quantifying hyporheic exchange dynamics in a highly regulated large river reach

NASA Astrophysics Data System (ADS)

Zhou, T.; Bao, J.; Huang, M.; Hou, Z.; Arntzen, E.; Mackley, R.; Harding, S.; Crump, A.; Xu, Y.; Song, X.; Chen, X.; Stegen, J.; Hammond, G. E.; Thorne, P. D.; Zachara, J. M.

2016-12-01

Hyporheic exchange is an important mechanism taking place in riverbanks and riverbed sediments, where the river water and shallow groundwater mix and interact with each other. The direction and magnitude of hyporheic flux that penetrates the river bed and residence time of river water in the hyporheic zone are critical for biogeochemical processes such as carbon and nitrogen cycling, and biodegradation of organic contaminants. Hyporheic flux can be quantified using many direct and indirect measurements as well as analytical and numerical modeling tools. However, in a relatively large river, these methods can be limited by the accessibility, spatial constraints, complexity of geomorphologic features and subsurface properties, and computational power. In rivers regulated by hydroelectric dams, quantifying hyporheic fluxes becomes more challenging due to frequent hydropeaking events created by dam operations. In this study, we developed and validated methods that combined field measurements and numerical modeling for estimating hyporheic fluxes across the river bed in a 7-km long reach of the highly regulated Columbia River. The reach has a minimum width of about 800 meters and variations in river stage within a day could be up to two meters due to the upstream dam operations. In shallow water along the shoreline, vertical thermal profiles measured by self-recording thermistors were combined with time series of hydraulic gradient derived from river stage and water level at in-land wells to estimate the hyporheic flux rate. For the deep section, a high resolution computational fluid dynamics (CFD) modeling framework was developed to characterize the spatial distribution of flux rates at the river bed and the residence time of hyporheic flow at different river flow conditions. Our modeling results show that the rates of hyporheic exchange and residence time are controlled by (1) hydrostatic pressure induced by river stage fluctuations, and (2) hydrodynamic drivers

The movement ecology and dynamics of plant communities in fragmented landscapes.

PubMed

Damschen, Ellen I; Brudvig, Lars A; Haddad, Nick M; Levey, Douglas J; Orrock, John L; Tewksbury, Joshua J

2008-12-09

A conceptual model of movement ecology has recently been advanced to explain all movement by considering the interaction of four elements: internal state, motion capacity, navigation capacities, and external factors. We modified this framework to generate predictions for species richness dynamics of fragmented plant communities and tested them in experimental landscapes across a 7-year time series. We found that two external factors, dispersal vectors and habitat features, affected species colonization and recolonization in habitat fragments and their effects varied and depended on motion capacity. Bird-dispersed species richness showed connectivity effects that reached an asymptote over time, but no edge effects, whereas wind-dispersed species richness showed steadily accumulating edge and connectivity effects, with no indication of an asymptote. Unassisted species also showed increasing differences caused by connectivity over time, whereas edges had no effect. Our limited use of proxies for movement ecology (e.g., dispersal mode as a proxy for motion capacity) resulted in moderate predictive power for communities and, in some cases, highlighted the importance of a more complete understanding of movement ecology for predicting how landscape conservation actions affect plant community dynamics.

The movement ecology and dynamics of plant communities in fragmented landscapes

DOE PAGES

Damschen, Ellen I.; Brudvig, Lars A.; Haddad, Nick M.; ...

2008-12-05

A conceptual model of movement ecology has recently been advanced to explain all movement by considering the interaction of four elements: internal state, motion capacity, navigation capacities,and external factors. We modified this framework togenerate predictions for species richness dynamics of fragmented plant communities and tested them in experimental landscapes across a 7-year time series. We found that two external factors, dispersal vectors and habitat features, affected species colonization and recolonization in habitat fragments and their effects varied and depended on motion capacity. Bird-dispersed species richness showed connectivity effects that reached an asymptote over time, but no edge effects, whereas wind-dispersedmore » species richness showed steadily accumulating edge and connectivity effects, with no indication of an asymptote. Unassisted species also showed increasing differences caused by connectivity over time,whereas edges had no effect. Our limited use of proxies for movement ecology (e.g., dispersal mode as a proxy for motion capacity) resulted in moderate predictive power for communities and, in some cases, highlighted the importance of a more complete understanding of movement ecology for predicting how landscape conservation actions affect plant community dynamics.« less

Relative importance of evolutionary dynamics depends on the composition of microbial predator-prey community.

PubMed

Friman, Ville-Petri; Dupont, Alessandra; Bass, David; Murrell, David J; Bell, Thomas

2016-06-01

Community dynamics are often studied in subsets of pairwise interactions. Scaling pairwise interactions back to the community level is, however, problematic because one given interaction might not reflect ecological and evolutionary outcomes of other functionally similar species interactions or capture the emergent eco-evolutionary dynamics arising only in more complex communities. Here we studied this experimentally by exposing Pseudomonas fluorescens SBW25 prey bacterium to four different protist predators (Tetrahymena pyriformis, Tetrahymena vorax, Chilomonas paramecium and Acanthamoeba polyphaga) in all possible single-predator, two-predator and four-predator communities for hundreds of prey generations covering both ecological and evolutionary timescales. We found that only T. pyriformis selected for prey defence in single-predator communities. Although T. pyriformis selection was constrained in the presence of the intraguild predator, T. vorax, T. pyriformis selection led to evolution of specialised prey defence strategies in the presence of C. paramecium or A. polyphaga. At the ecological level, adapted prey populations were phenotypically more diverse, less stable and less productive compared with non-adapted prey populations. These results suggest that predator community composition affects the relative importance of ecological and evolutionary processes and can crucially determine when rapid evolution has the potential to change ecological properties of microbial communities.

Relative importance of evolutionary dynamics depends on the composition of microbial predator–prey community

PubMed Central

Friman, Ville-Petri; Dupont, Alessandra; Bass, David; Murrell, David J; Bell, Thomas

2016-01-01

Community dynamics are often studied in subsets of pairwise interactions. Scaling pairwise interactions back to the community level is, however, problematic because one given interaction might not reflect ecological and evolutionary outcomes of other functionally similar species interactions or capture the emergent eco-evolutionary dynamics arising only in more complex communities. Here we studied this experimentally by exposing Pseudomonas fluorescens SBW25 prey bacterium to four different protist predators (Tetrahymena pyriformis, Tetrahymena vorax, Chilomonas paramecium and Acanthamoeba polyphaga) in all possible single-predator, two-predator and four-predator communities for hundreds of prey generations covering both ecological and evolutionary timescales. We found that only T. pyriformis selected for prey defence in single-predator communities. Although T. pyriformis selection was constrained in the presence of the intraguild predator, T. vorax, T. pyriformis selection led to evolution of specialised prey defence strategies in the presence of C. paramecium or A. polyphaga. At the ecological level, adapted prey populations were phenotypically more diverse, less stable and less productive compared with non-adapted prey populations. These results suggest that predator community composition affects the relative importance of ecological and evolutionary processes and can crucially determine when rapid evolution has the potential to change ecological properties of microbial communities. PMID:26684728

Microbial community dynamics and biogas production from manure fractions in sludge bed anaerobic digestion.

PubMed

Nordgård, A S R; Bergland, W H; Bakke, R; Vadstein, O; Østgaard, K; Bakke, I

2015-12-01

To elucidate how granular sludge inoculum and particle-rich organic loading affect the structure of the microbial communities and process performance in upflow anaerobic sludge bed (UASB) reactors. We investigated four reactors run on dairy manure filtrate and four on pig manure supernatant for three months achieving similar methane yields. The reactors fed with less particle rich pig manure stabilized faster and had highest capacity. Microbial community dynamics analysed by a PCR/denaturing gradient gel electrophoresis approach showed that influent was a major determinant for the composition of the reactor communities. Comparisons of pre- and non-adapted inoculum in the reactors run on pig manure supernatant showed that the community structure of the nonadapted inoculum adapted in approximately two months. Microbiota variance partitioning analysis revealed that running time, organic loading rate and inoculum together explained 26 and 31% of the variance in bacterial and archaeal communities respectively. The microbial communities of UASBs adapted to the reactor conditions in treatment of particle rich manure fractions, obtaining high capacity, especially on pig manure supernatant. These findings provide relevant insight into the microbial community dynamics in startup and operation of sludge bed reactors for methane production from slurry fractions, a major potential source of biogas. © 2015 The Society for Applied Microbiology.

Dynamic functional connectivity using state-based dynamic community structure: method and application to opioid analgesia.

PubMed

Robinson, Lucy F; Atlas, Lauren Y; Wager, Tor D

2015-03-01

We present a new method, State-based Dynamic Community Structure, that detects time-dependent community structure in networks of brain regions. Most analyses of functional connectivity assume that network behavior is static in time, or differs between task conditions with known timing. Our goal is to determine whether brain network topology remains stationary over time, or if changes in network organization occur at unknown time points. Changes in network organization may be related to shifts in neurological state, such as those associated with learning, drug uptake or experimental conditions. Using a hidden Markov stochastic blockmodel, we define a time-dependent community structure. We apply this approach to data from a functional magnetic resonance imaging experiment examining how contextual factors influence drug-induced analgesia. Results reveal that networks involved in pain, working memory, and emotion show distinct profiles of time-varying connectivity. Copyright © 2014 Elsevier Inc. All rights reserved.

Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000

USGS Publications Warehouse

Zhao, Shuqing; Liu, Shuguang; Yin, Runsheng; Li, Zhengpeng; Deng, Yulin; Tan, Kun; Deng, Xiangzheng; Rothstein, David; Qi, Jiaguo

2010-01-01

Quantifying the spatial and temporal dynamics of carbon stocks in terrestrial ecosystems and carbon fluxes between the terrestrial biosphere and the atmosphere is critical to our understanding of regional patterns of carbon budgets. Here we use the General Ensemble biogeochemical Modeling System to simulate the terrestrial ecosystem carbon dynamics in the Jinsha watershed of China’s upper Yangtze basin from 1975 to 2000, based on unique combinations of spatial and temporal dynamics of major driving forces, such as climate, soil properties, nitrogen deposition, and land use and land cover changes. Our analysis demonstrates that the Jinsha watershed ecosystems acted as a carbon sink during the period of 1975–2000, with an average rate of 0.36 Mg/ha/yr, primarily resulting from regional climate variation and local land use and land cover change. Vegetation biomass accumulation accounted for 90.6% of the sink, while soil organic carbon loss before 1992 led to a lower net gain of carbon in the watershed, and after that soils became a small sink. Ecosystem carbon sink/source patterns showed a high degree of spatial heterogeneity. Carbon sinks were associated with forest areas without disturbances, whereas carbon sources were primarily caused by stand-replacing disturbances. It is critical to adequately represent the detailed fast-changing dynamics of land use activities in regional biogeochemical models to determine the spatial and temporal evolution of regional carbon sink/source patterns.

Microbial community dynamics in the rhizosphere of a cadmium hyper-accumulator

NASA Astrophysics Data System (ADS)

Wood, J. L.; Zhang, C.; Mathews, E. R.; Tang, C.; Franks, A. E.

2016-11-01

Phytoextraction is influenced by the indigenous soil microbial communities during the remediation of heavy metal contaminated soils. Soil microbial communities can affect plant growth, metal availability and the performance of phytoextraction-assisting inocula. Understanding the basic ecology of indigenous soil communities associated with the phytoextraction process, including the interplay between selective pressures upon the communities, is an important step towards phytoextraction optimization. This study investigated the impact of cadmium (Cd), and the presence of a Cd-accumulating plant, Carpobrotus rossii (Haw.) Schwantes, on the structure of soil-bacterial and fungal communities using automated ribosomal intergenic spacer analysis (ARISA) and quantitative PCR (qPCR). Whilst Cd had no detectable influence upon fungal communities, bacterial communities underwent significant structural changes with no reduction in 16S rRNA copy number. The presence of C. rossii influenced the structure of all communities and increased ITS copy number. Suites of operational taxonomic units (OTUs) changed in abundance in response to either Cd or C. rossii, however we found little evidence to suggest that the two selective pressures were acting synergistically. The Cd-induced turnover in bacterial OTUs suggests that Cd alters competition dynamics within the community. Further work to understand how competition is altered could provide a deeper understanding of the microbiome-plant-environment and aid phytoextraction optimization.

Dynamic dual-tracer MRI-guided fluorescence tomography to quantify receptor density in vivo

PubMed Central

Davis, Scott C.; Samkoe, Kimberley S.; Tichauer, Kenneth M.; Sexton, Kristian J.; Gunn, Jason R.; Deharvengt, Sophie J.; Hasan, Tayyaba; Pogue, Brian W.

2013-01-01

The up-regulation of cell surface receptors has become a central focus in personalized cancer treatment; however, because of the complex nature of contrast agent pharmacokinetics in tumor tissue, methods to quantify receptor binding in vivo remain elusive. Here, we present a dual-tracer optical technique for noninvasive estimation of specific receptor binding in cancer. A multispectral MRI-coupled fluorescence molecular tomography system was used to image the uptake kinetics of two fluorescent tracers injected simultaneously, one tracer targeted to the receptor of interest and the other tracer a nontargeted reference. These dynamic tracer data were then fit to a dual-tracer compartmental model to estimate the density of receptors available for binding in the tissue. Applying this approach to mice with deep-seated gliomas that overexpress the EGF receptor produced an estimate of available receptor density of 2.3 ± 0.5 nM (n = 5), consistent with values estimated in comparative invasive imaging and ex vivo studies. PMID:23671066

Quantifying changes in spatial patterns of surface air temperature dynamics over several decades

NASA Astrophysics Data System (ADS)

Zappalà, Dario A.; Barreiro, Marcelo; Masoller, Cristina

2018-04-01

We study daily surface air temperature (SAT) reanalysis in a grid over the Earth's surface to identify and quantify changes in SAT dynamics during the period 1979-2016. By analysing the Hilbert amplitude and frequency we identify the regions where relative variations are most pronounced (larger than ±50 % for the amplitude and ±100 % for the frequency). Amplitude variations are interpreted as due to changes in precipitation or ice melting, while frequency variations are interpreted as due to a northward shift of the inter-tropical convergence zone (ITCZ) and to a widening of the rainfall band in the western Pacific Ocean. The ITCZ is the ascending branch of the Hadley cell, and thus by affecting the tropical atmospheric circulation, ITCZ migration has far-reaching climatic consequences. As the methodology proposed here can be applied to many other geophysical time series, our work will stimulate new research that will advance the understanding of climate change impacts.

Building a Community of Research Practice: Intragroup Team Social Dynamics in Interdisciplinary Mixed Methods

ERIC Educational Resources Information Center

Hemmings, Annette; Beckett, Gulbahar; Kennerly, Susan; Yap, Tracey

2013-01-01

This article explicates the intragroup social dynamics and work of a nursing and education research team as a community of research practice interested in organizational cultures and occupational subcultures. Dynamics were characterized by processes of socialization through reeducation and group social identity formation that enabled members to…

Sound Links: Exploring the Social, Cultural and Educational Dynamics of Musical Communities in Australia

ERIC Educational Resources Information Center

Bartleet, Brydie-Leigh

2009-01-01

"Sound Links" examines the dynamics of community music in Australia, and the models it represents for informal music learning and teaching. This involves researching a selection of vibrant musical communities across the country, exploring their potential for complementarity and synergy with music in schools. This article focuses on the…

Methane dynamics regulated by microbial community response to permafrost thaw.

PubMed

McCalley, Carmody K; Woodcroft, Ben J; Hodgkins, Suzanne B; Wehr, Richard A; Kim, Eun-Hae; Mondav, Rhiannon; Crill, Patrick M; Chanton, Jeffrey P; Rich, Virginia I; Tyson, Gene W; Saleska, Scott R

2014-10-23

Permafrost contains about 50% of the global soil carbon. It is thought that the thawing of permafrost can lead to a loss of soil carbon in the form of methane and carbon dioxide emissions. The magnitude of the resulting positive climate feedback of such greenhouse gas emissions is still unknown and may to a large extent depend on the poorly understood role of microbial community composition in regulating the metabolic processes that drive such ecosystem-scale greenhouse gas fluxes. Here we show that changes in vegetation and increasing methane emissions with permafrost thaw are associated with a switch from hydrogenotrophic to partly acetoclastic methanogenesis, resulting in a large shift in the δ(13)C signature (10-15‰) of emitted methane. We used a natural landscape gradient of permafrost thaw in northern Sweden as a model to investigate the role of microbial communities in regulating methane cycling, and to test whether a knowledge of community dynamics could improve predictions of carbon emissions under loss of permafrost. Abundance of the methanogen Candidatus 'Methanoflorens stordalenmirensis' is a key predictor of the shifts in methane isotopes, which in turn predicts the proportions of carbon emitted as methane and as carbon dioxide, an important factor for simulating the climate feedback associated with permafrost thaw in global models. By showing that the abundance of key microbial lineages can be used to predict atmospherically relevant patterns in methane isotopes and the proportion of carbon metabolized to methane during permafrost thaw, we establish a basis for scaling changing microbial communities to ecosystem isotope dynamics. Our findings indicate that microbial ecology may be important in ecosystem-scale responses to global change.

Quantifying Short-Term Dynamics of Parkinson’s Disease Using Self-Reported Symptom Data From an Internet Social Network

PubMed Central

Wicks, Paul; Vaughan, Timothy; Pentland, Alex

2013-01-01

Background Parkinson’s disease (PD) is an incurable neurological disease with approximately 0.3% prevalence. The hallmark symptom is gradual movement deterioration. Current scientific consensus about disease progression holds that symptoms will worsen smoothly over time unless treated. Accurate information about symptom dynamics is of critical importance to patients, caregivers, and the scientific community for the design of new treatments, clinical decision making, and individual disease management. Long-term studies characterize the typical time course of the disease as an early linear progression gradually reaching a plateau in later stages. However, symptom dynamics over durations of days to weeks remains unquantified. Currently, there is a scarcity of objective clinical information about symptom dynamics at intervals shorter than 3 months stretching over several years, but Internet-based patient self-report platforms may change this. Objective To assess the clinical value of online self-reported PD symptom data recorded by users of the health-focused Internet social research platform PatientsLikeMe (PLM), in which patients quantify their symptoms on a regular basis on a subset of the Unified Parkinson’s Disease Ratings Scale (UPDRS). By analyzing this data, we aim for a scientific window on the nature of symptom dynamics for assessment intervals shorter than 3 months over durations of several years. Methods Online self-reported data was validated against the gold standard Parkinson’s Disease Data and Organizing Center (PD-DOC) database, containing clinical symptom data at intervals greater than 3 months. The data were compared visually using quantile-quantile plots, and numerically using the Kolmogorov-Smirnov test. By using a simple piecewise linear trend estimation algorithm, the PLM data was smoothed to separate random fluctuations from continuous symptom dynamics. Subtracting the trends from the original data revealed random fluctuations in symptom

Evaluation of the effect of an additional fertilizer on the dynamics of microbial community and the decomposition of organic matter in soil

NASA Astrophysics Data System (ADS)

Fabiola, B.; Olivier, M.; Houdusse, F.; Fuentes, M.; Garcia, M. J. M.; Lévêque, J.; Yvin, J. C.; Maron, P. A.; Lemenager, D.

2012-04-01

Organic matter (OM) influences many of the soil functions and occupies a central position in the global carbon cycle. At the scale of the agro-ecosystem, primary productivity is dependent on the recycling of soil organic matter (SOM) by the action of decomposers (mainly bacteria and fungi), which mineralize organic compounds, releasing the nutrients needed for plant growth. At a global scale, the recycling of the SOM determines the carbon flux between soil and atmosphere, with major consequences in terms of environmental quality. In this context, the management of SOM stocks in agro-ecosystems is a major issue from which depend the maintenance of the productivity and sustainability of agricultural practices. The use of additional fertilizer appears to be a promising way to achieve such management. These products have been proven effectives in many field trials. However, their mode of action, particularly in terms of impact on soil microbial component, is still nearly unknown. In this context, this study aims to test the influence of an additional fertilizer on (i) soil microbial communities (total biomass, density of bacteria and fungi), and (ii) soil functioning in terms of dynamics of organic matter. It is based on experiments in soil microcosms which follow in parallel the kinetics of mineralization of different organic carbon compartments (endogenous compartment: soil organic matter; exogenous compartment: wheat residue provided) and the dynamics of microbial communities after the addition of wheat residues in soil. Two different soils were used to evaluate the influence of soil physicochemical characteristics on the effect induced by the addition in terms of fertilization. The first results show a significant effect of the input of additional fertilizer on the dynamics of soil organic matter. They also show that soil pH as well as the dose at which the additional fertilizer is applied are important for modulating the observed effect. Characterization of

Supportive-Expressive Dynamic Psychotherapy in the Community Mental Health System: A Pilot Effectiveness Trial for the Treatment of Depression

PubMed Central

Connolly Gibbons, Mary Beth; Thompson, Sarah M.; Scott, Kelli; Schauble, Lindsay A.; Mooney, Tessa; Thompson, Donald; Green, Patricia; MacArthur, Mary Jo; Crits-Christoph, Paul

2013-01-01

The goal of the current article is to present the results of a randomized pilot investigation of a brief dynamic psychotherapy compared with treatment-as-usual (TAU) in the treatment of moderate-to-severe depression in the community mental health system. Forty patients seeking services for moderate-to-severe depression in the community mental health system were randomized to 12 weeks of psychotherapy, with either a community therapist trained in brief dynamic psychotherapy or a TAU therapist. Results indicated that blind judges could discriminate the dynamic sessions from the TAU sessions on adherence to dynamic interventions. The results indicate moderate-to-large effect sizes in favor of the dynamic psychotherapy over the TAU therapy in the treatment of depression. The Behavior and Symptom Identification Scale-24 showed that 50% of patients treated with dynamic therapy moved into a normative range compared with only 29% of patients treated with TAU. PMID:22962971

Dynamics of phytoplankton community composition in the western Gulf of Maine

NASA Astrophysics Data System (ADS)

Moore, Timothy S.

This dissertation is founded on the importance of phytoplankton community composition to marine biogeochemistry and ecosystem processes and motivated by the need to understand their distributions on regional to global scales. The ultimate goal was to predict surface phytoplankton communities using satellite remote sensing by relating marine habitats--defined through a statistical description of environmental properties--to different phytoplankton communities. While phytoplankton community composition is governed by the interplay of abiotic and biotic interactions, the strategy adopted here was to focus on the physical abiotic factors. This allowed for the detection of habitats from ocean satellites based on abiotic factors that were linked to associated phytoplankton communities. The research entailed three studies that addressed different aspects of the main goal using a dataset collected in the western Gulf of Maine over a 3-year period. The first study evaluated a chemotaxonomic method that quantified phytoplankton composition from pigment data. This enabled the characterization of three phytoplankton communities, which were defined by the relative abundance of diatoms and flagellates. The second study examined the cycles of these communities along with environmental variables, and the results revealed that the three phytoplankton communities exhibited an affinity to different hydrographic regimes. The third study focused on the implementation of a classifier that predicted phytoplankton communities from environmental variables. Its ability to differentiate communities dominated by diatoms versus flagellates was shown to be high. However, the increase in data imprecision when using satellite data led to lowered performance and favored an approach that incorporated fuzzy logic. The fuzzy method is well suited to characterize the uncertainties in phytoplankton community prediction, and provides a measure of confidence on predicted communities. The final product of

Quantifying ubiquitin signaling.

PubMed

Ordureau, Alban; Münch, Christian; Harper, J Wade

2015-05-21

Ubiquitin (UB)-driven signaling systems permeate biology, and are often integrated with other types of post-translational modifications (PTMs), including phosphorylation. Flux through such pathways is dictated by the fractional stoichiometry of distinct modifications and protein assemblies as well as the spatial organization of pathway components. Yet, we rarely understand the dynamics and stoichiometry of rate-limiting intermediates along a reaction trajectory. Here, we review how quantitative proteomic tools and enrichment strategies are being used to quantify UB-dependent signaling systems, and to integrate UB signaling with regulatory phosphorylation events, illustrated with the PINK1/PARKIN pathway. A key feature of ubiquitylation is that the identity of UB chain linkage types can control downstream processes. We also describe how proteomic and enzymological tools can be used to identify and quantify UB chain synthesis and linkage preferences. The emergence of sophisticated quantitative proteomic approaches will set a new standard for elucidating biochemical mechanisms of UB-driven signaling systems. Copyright © 2015 Elsevier Inc. All rights reserved.

Quantifying Ubiquitin Signaling

PubMed Central

Ordureau, Alban; Münch, Christian; Harper, J. Wade

2015-01-01

Ubiquitin (UB)-driven signaling systems permeate biology, and are often integrated with other types of post-translational modifications (PTMs), most notably phosphorylation. Flux through such pathways is typically dictated by the fractional stoichiometry of distinct regulatory modifications and protein assemblies as well as the spatial organization of pathway components. Yet, we rarely understand the dynamics and stoichiometry of rate-limiting intermediates along a reaction trajectory. Here, we review how quantitative proteomic tools and enrichment strategies are being used to quantify UB-dependent signaling systems, and to integrate UB signaling with regulatory phosphorylation events. A key regulatory feature of ubiquitylation is that the identity of UB chain linkage types can control downstream processes. We also describe how proteomic and enzymological tools can be used to identify and quantify UB chain synthesis and linkage preferences. The emergence of sophisticated quantitative proteomic approaches will set a new standard for elucidating biochemical mechanisms of UB-driven signaling systems. PMID:26000850

Infaunal macrobenthic community dynamics in a manipulated hyperhaline ecosystem: a long-term study

PubMed Central

2013-01-01

Background Understanding the responses of ecological communities to human-induced perturbations is crucial for establishing conservation goals. Ecological communities are dynamic entities undergoing fluctuations due to their intrinsic characteristics as well as anthropogenic pressures varying over time. In this respect, long-term studies, based on large spatial and temporal datasets, may provide useful information in understanding patterns and processes influencing the communities’ structure. Theoretical evidence suggests that a role of biodiversity is acting as a compensatory buffer against environmental variability by decreasing the temporal variance in ecosystem functioning and by raising the level of community response to perturbations through the selection of better performing species. Therefore, the spatial and temporal changes in the specialization of the community components may be used as an effective tool to monitor the effects of natural and anthropogenic alterations of the environment in dynamic systems. We examined the temporal dynamics of macroinvertebrate community structure in the hyperhaline habitat of Tarquinia Saltworks (central Italy). We aimed at: (i) investigating the relationships between the level of community specialization and the alterations of the environment across fourteen years; (ii) comparing the ability of aggregate community parameters such as the average abundance vs. species specialization in describing patterns of community composition. Results We arranged the data in three sub-sets according to three periods, each characterized by different environmental conditions. The mean abundance of sampled macroinvertebrates showed a significant change (p < 0.01) only in the community inhabiting the saltwork basin closely connected to the sea, characterized by the highest environmental variation (i.e. the coefficient of variation, CV, of the aggregate environmental variability over the study period, CVrange = 0.010 - 0.2). Here

Understanding past, contemporary, and future dynamics of plants, populations, and communities using Sonoran Desert winter annuals.

PubMed

Huxman, Travis E; Kimball, Sarah; Angert, Amy L; Gremer, Jennifer R; Barron-Gafford, Greg A; Venable, D Lawrence

2013-07-01

Global change requires plant ecologists to predict future states of biological diversity to aid the management of natural communities, thus introducing a number of significant challenges. One major challenge is considering how the many interacting features of biological systems, including ecophysiological processes, plant life histories, and species interactions, relate to performance in the face of a changing environment. We have employed a functional trait approach to understand the individual, population, and community dynamics of a model system of Sonoran Desert winter annual plants. We have used a comprehensive approach that connects physiological ecology and comparative biology to population and community dynamics, while emphasizing both ecological and evolutionary processes. This approach has led to a fairly robust understanding of past and contemporary dynamics in response to changes in climate. In this community, there is striking variation in physiological and demographic responses to both precipitation and temperature that is described by a trade-off between water-use efficiency (WUE) and relative growth rate (RGR). This community-wide trade-off predicts both the demographic and life history variation that contribute to species coexistence. Our framework has provided a mechanistic explanation to the recent warming, drying, and climate variability that has driven a surprising shift in these communities: cold-adapted species with more buffered population dynamics have increased in relative abundance. These types of comprehensive approaches that acknowledge the hierarchical nature of biology may be especially useful in aiding prediction. The emerging, novel and nonstationary climate constrains our use of simplistic statistical representations of past plant behavior in predicting the future, without understanding the mechanistic basis of change.

Dynamics of Different Bacterial Communities Are Capable of Generating Sustainable Electricity from Microbial Fuel Cells with Organic Waste

PubMed Central

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

Dynamics of different bacterial communities are capable of generating sustainable electricity from microbial fuel cells with organic waste.

PubMed

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.

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.

Microbial community dynamics in the rhizosphere of a cadmium hyper-accumulator

PubMed Central

Wood, J. L.; Zhang, C.; Mathews, E. R.; Tang, C.; Franks, A. E.

2016-01-01

Phytoextraction is influenced by the indigenous soil microbial communities during the remediation of heavy metal contaminated soils. Soil microbial communities can affect plant growth, metal availability and the performance of phytoextraction-assisting inocula. Understanding the basic ecology of indigenous soil communities associated with the phytoextraction process, including the interplay between selective pressures upon the communities, is an important step towards phytoextraction optimization. This study investigated the impact of cadmium (Cd), and the presence of a Cd-accumulating plant, Carpobrotus rossii (Haw.) Schwantes, on the structure of soil-bacterial and fungal communities using automated ribosomal intergenic spacer analysis (ARISA) and quantitative PCR (qPCR). Whilst Cd had no detectable influence upon fungal communities, bacterial communities underwent significant structural changes with no reduction in 16S rRNA copy number. The presence of C. rossii influenced the structure of all communities and increased ITS copy number. Suites of operational taxonomic units (OTUs) changed in abundance in response to either Cd or C. rossii, however we found little evidence to suggest that the two selective pressures were acting synergistically. The Cd-induced turnover in bacterial OTUs suggests that Cd alters competition dynamics within the community. Further work to understand how competition is altered could provide a deeper understanding of the microbiome-plant-environment and aid phytoextraction optimization. PMID:27805014

Spatial and temporal dynamics of the microbial community in the Hanford unconfined aquifer

PubMed Central

Lin, Xueju; McKinley, James; Resch, Charles T; Kaluzny, Rachael; Lauber, Christian L; Fredrickson, James; Knight, Rob; Konopka, Allan

2012-01-01

Pyrosequencing analysis of 16S rRNA genes was used to study temporal dynamics of groundwater bacteria and archaea over 10 months within three well clusters separated by ∼30 m and located 250 m from the Columbia River on the Hanford Site, WA. Each cluster contained three wells screened at different depths ranging from 10 to 17 m that differed in hydraulic conductivities. Representative samples were selected for analyses of prokaryotic 16S and eukaryotic 18S rRNA gene copy numbers. Temporal changes in community composition occurred in all nine wells over the 10-month sampling period. However, there were particularly strong effects near the top of the water table when the seasonal rise in the Columbia River caused river water intrusion at the top of the aquifer. The occurrence and disappearance of some microbial assemblages (such as Actinobacteria ACK-M1) were correlated with river water intrusion. This seasonal impact on microbial community structure was greater in the shallow saturated zone than deeper zone in the aquifer. Spatial and temporal patterns for several 16S rRNA gene operational taxonomic units associated with particular physiological functions (for example, methane oxidizers and metal reducers) suggests dynamic changes in fluxes of electron donors and acceptors over an annual cycle. In addition, temporal dynamics in eukaryotic 18S rRNA gene copies and the dominance of protozoa in 18S clone libraries suggest that bacterial community dynamics could be affected not only by the physical and chemical environment but also by top-down biological control. PMID:22456444

Spatial and temporal dynamics of the microbial community in the Hanford unconfined aquifer.

PubMed

Lin, Xueju; McKinley, James; Resch, Charles T; Kaluzny, Rachael; Lauber, Christian L; Fredrickson, James; Knight, Rob; Konopka, Allan

2012-09-01

Pyrosequencing analysis of 16S rRNA genes was used to study temporal dynamics of groundwater bacteria and archaea over 10 months within three well clusters separated by ~30 m and located 250 m from the Columbia River on the Hanford Site, WA. Each cluster contained three wells screened at different depths ranging from 10 to 17 m that differed in hydraulic conductivities. Representative samples were selected for analyses of prokaryotic 16S and eukaryotic 18S rRNA gene copy numbers. Temporal changes in community composition occurred in all nine wells over the 10-month sampling period. However, there were particularly strong effects near the top of the water table when the seasonal rise in the Columbia River caused river water intrusion at the top of the aquifer. The occurrence and disappearance of some microbial assemblages (such as Actinobacteria ACK-M1) were correlated with river water intrusion. This seasonal impact on microbial community structure was greater in the shallow saturated zone than deeper zone in the aquifer. Spatial and temporal patterns for several 16S rRNA gene operational taxonomic units associated with particular physiological functions (for example, methane oxidizers and metal reducers) suggests dynamic changes in fluxes of electron donors and acceptors over an annual cycle. In addition, temporal dynamics in eukaryotic 18S rRNA gene copies and the dominance of protozoa in 18S clone libraries suggest that bacterial community dynamics could be affected not only by the physical and chemical environment but also by top-down biological control.

The interaction of cannibalism and omnivory: consequences for community dynamics.

PubMed

Rudolf, Volker H W

2007-11-01

Although cannibalism is ubiquitous in food webs and frequent in systems where a predator and its prey also share a common resource (intraguild predation, IGP), its impacts on species interactions and the dynamics and structure of communities are still poorly understood. In addition, the few existing studies on cannibalism have generally focused on cannibalism in the top-predator, ignoring that it is frequent at intermediate trophic levels. A set of structured models shows that cannibalism can completely alter the dynamics and structure of three-species IGP systems depending on the trophic position where cannibalism occurs. Contrary to the expectations of simple models, the IG predator can exploit the resources more efficiently when it is cannibalistic, enabling the predator to persist at lower resource densities than the IG prey. Cannibalism in the IG predator can also alter the effect of enrichment, preventing predator-mediated extinction of the IG prey at high productivities predicted by simple models. Cannibalism in the IG prey can reverse the effect of top-down cascades, leading to an increase in the resource with decreasing IG predator density. These predictions are consistent with current data. Overall, cannibalism promotes the coexistence of the IG predator and IG prey. These results indicate that including cannibalism in current models can overcome the discrepancy between theory and empirical data. Thus, we need to measure and account for cannibalistic interactions to reliably predict the structure and dynamics of communities.

Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000

USGS Publications Warehouse

Zhao, Shuqing; Liu, Shuguang; Yin, Runsheng; Li, Zhengpeng; Deng, Yulin; Tan, Kun; Deng, Xiangzheng; Rothstein, David; Qi, Jiaguo; Yin, Runsheng

2009-01-01

Quantifying the spatial and temporal dynamics of carbon stocks in terrestrial ecosystems and carbon fluxes between the terrestrial biosphere and the atmosphere is critical to our understanding of regional patterns of carbon storage and loss. Here we use the General Ensemble Biogeochemical Modeling System to simulate the terrestrial ecosystem carbon dynamics in the Jinsha watershed of China's upper Yangtze basin from 1975 to 2000, based on unique combinations of spatial and temporal dynamics of major driving forces, such as climate, soil properties, nitrogen deposition, and land use and land cover changes. Our analysis demonstrates that the Jinsha watershed ecosystems acted as a carbon sink during the period of 1975–2000, with an average rate of 0.36 Mg/ha/yr, primarily resulting from regional climate variation and local land use and land cover change. Vegetation biomass accumulation accounted for 90.6% of the sink, while soil organic carbon loss before 1992 led to lower net gain of carbon in the watershed, and after that soils became a small sink. Ecosystem carbon sinks/source pattern showed a high degree of spatial heterogeneity, Carbon sinks were associated with forest areas without disturbances, whereas carbon Sources were primarily caused by stand-replacing disturbances. This highlights the importance of land-use history in determining the regional carbon sinks/source pattern.

Restructuring of the Aquatic Bacterial Community by Hydric Dynamics Associated with Superstorm Sandy

PubMed Central

Ulrich, Nikea; Rosenberger, Abigail; Brislawn, Colin; Wright, Justin; Kessler, Collin; Toole, David; Solomon, Caroline; Strutt, Steven; McClure, Erin

2016-01-01

ABSTRACT Bacterial community composition and longitudinal fluctuations were monitored in a riverine system during and after Superstorm Sandy to better characterize inter- and intracommunity responses associated with the disturbance associated with a 100-year storm event. High-throughput sequencing of the 16S rRNA gene was used to assess microbial community structure within water samples from Muddy Creek Run, a second-order stream in Huntingdon, PA, at 12 different time points during the storm event (29 October to 3 November 2012) and under seasonally matched baseline conditions. High-throughput sequencing of the 16S rRNA gene was used to track changes in bacterial community structure and divergence during and after Superstorm Sandy. Bacterial community dynamics were correlated to measured physicochemical parameters and fecal indicator bacteria (FIB) concentrations. Bioinformatics analyses of 2.1 million 16S rRNA gene sequences revealed a significant increase in bacterial diversity in samples taken during peak discharge of the storm. Beta-diversity analyses revealed longitudinal shifts in the bacterial community structure. Successional changes were observed, in which Betaproteobacteria and Gammaproteobacteria decreased in 16S rRNA gene relative abundance, while the relative abundance of members of the Firmicutes increased. Furthermore, 16S rRNA gene sequences matching pathogenic bacteria, including strains of Legionella, Campylobacter, Arcobacter, and Helicobacter, as well as bacteria of fecal origin (e.g., Bacteroides), exhibited an increase in abundance after peak discharge of the storm. This study revealed a significant restructuring of in-stream bacterial community structure associated with hydric dynamics of a storm event. IMPORTANCE In order to better understand the microbial risks associated with freshwater environments during a storm event, a more comprehensive understanding of the variations in aquatic bacterial diversity is warranted. This study

Nematode grazing promotes bacterial community dynamics in soil at the aggregate level

PubMed Central

Jiang, Yuji; Liu, Manqiang; Zhang, Jiabao; Chen, Yan; Chen, Xiaoyun; Chen, Lijun; Li, Huixin; Zhang, Xue-Xian; Sun, Bo

2017-01-01

Nematode predation has important roles in determining bacterial community composition and dynamics, but the extent of the effects remains largely rudimentary, particularly in natural environment settings. Here, we investigated the complex microbial–microfaunal interactions in the rhizosphere of maize grown in red soils, which were derived from four long-term fertilization regimes. Root-free rhizosphere soil samples were separated into three aggregate fractions whereby the abundance and community composition were examined for nematode and total bacterial communities. A functional group of alkaline phosphomonoesterase (ALP) producing bacteria was included to test the hypothesis that nematode grazing may significantly affect specific bacteria-mediated ecological functions, that is, organic phosphate cycling in soil. Results of correlation analysis, structural equation modeling and interaction networks combined with laboratory microcosm experiments consistently indicated that bacterivorous nematodes enhanced bacterial diversity, and the abundance of bacterivores was positively correlated with bacterial biomass, including ALP-producing bacterial abundance. Significantly, such effects were more pronounced in large macroaggregates than in microaggregates. There was a positive correlation between the most dominant bacterivores Protorhabditis and the ALP-producing keystone 'species' Mesorhizobium. Taken together, these findings implicate important roles of nematodes in stimulating bacterial dynamics in a spatially dependent manner. PMID:28742069

Nematode grazing promotes bacterial community dynamics in soil at the aggregate level.

PubMed

Jiang, Yuji; Liu, Manqiang; Zhang, Jiabao; Chen, Yan; Chen, Xiaoyun; Chen, Lijun; Li, Huixin; Zhang, Xue-Xian; Sun, Bo

2017-12-01

Nematode predation has important roles in determining bacterial community composition and dynamics, but the extent of the effects remains largely rudimentary, particularly in natural environment settings. Here, we investigated the complex microbial-microfaunal interactions in the rhizosphere of maize grown in red soils, which were derived from four long-term fertilization regimes. Root-free rhizosphere soil samples were separated into three aggregate fractions whereby the abundance and community composition were examined for nematode and total bacterial communities. A functional group of alkaline phosphomonoesterase (ALP) producing bacteria was included to test the hypothesis that nematode grazing may significantly affect specific bacteria-mediated ecological functions, that is, organic phosphate cycling in soil. Results of correlation analysis, structural equation modeling and interaction networks combined with laboratory microcosm experiments consistently indicated that bacterivorous nematodes enhanced bacterial diversity, and the abundance of bacterivores was positively correlated with bacterial biomass, including ALP-producing bacterial abundance. Significantly, such effects were more pronounced in large macroaggregates than in microaggregates. There was a positive correlation between the most dominant bacterivores Protorhabditis and the ALP-producing keystone 'species' Mesorhizobium. Taken together, these findings implicate important roles of nematodes in stimulating bacterial dynamics in a spatially dependent manner.

Plant community dynamics and restoring Louisiana's wetland ecosystems

NASA Astrophysics Data System (ADS)

Duke-Sylvester, S. M.; Visser, J.

2017-12-01

We have developed a computational model of plant community dynamics. Our model is designed to evaluate the effects of management actions on the structure and health of Louisiana's coastal wetland plant communities. A number of projects have been initiated or proposed to preserve and restore this ecosystem while still allowing the area to support Louisiana's economy. These projects involve both modification of the flow of freshwater as well as restoring natural wetlands. Evaluating the long term effects of these projects is complex and involves numerous moving pieces operating over an extensive and diverse landscape. The situation is further complicated by in sea level rise and climate change associated with global warming. The vegetation model is part of a larger set of linked models that include hydrology and soil morphology. Using hydrological conditions projected by the linked hydrology models, we are able to evaluate the effects of anthropogenic and climatic changes on Louisiana's wetland plant communities. Unique features of our model include replacing the division of wetlands into coarse groups defined by salinity conditions with species level responses to environmental conditions and extending the spatial scale of modeling to encompass the entirety of Louisiana's Gulf coast. Model results showing the potential impact of alternative management and climate change scenarios are presented.

Soil fungi colony growth and community dynamics

NASA Astrophysics Data System (ADS)

Falconer, Ruth E.; Kravchenko, Alexandra; Otten, Wilfred

2010-05-01

Fungi are a major player in soil functioning, they contribute to soil structure formation and shaping of plant communities through their role in nutrient cycling, pathogenesis and symbiosis. Theoretical approaches which have emerged over the years and improved considerably our understanding of above ground plant communities are still lacking below ground. A theoretical framework is needed, such that links soil physics, fungal biology and mathematical biology in order to understand fungal community dynamics and diversity in undisturbed soils. Such a framework is essential if we are to understand how environmental change or soil manipulation impacts biodiversity. Different land use and management practices significantly affect soil environmental characteristics crucial for fungal communities by contributing different quantities and qualities of biomass inputs, generating different levels of soil disturbance, influencing soil temperature and moisture regimes, and affecting structure and geometry of soil pore space. Differences in pore structures generated by long-term differences in land use and management are reflected in notable changes in soil physical and hydraulic properties, including soil porosity, hydraulic conductivity and water retention (Brye and Pirani, 2005). Changes in numbers, shapes, and distributions of soil macropores have been often observed (e.g., Pachepsky et al., 1996; Giménez et al., 1997; Udawatta et al., 2008). However, specific implications of these differences in pore structure and geometries for ability of pathogenic as well as non-pathogenic fungi to colonize soil have not yet been addressed. Recent advances in computed tomography and microscopy facilitate detailed examination of the inner pore structures of undisturbed soil samples as well as visualization of fungal mycelia. Such tools together with modelling generate a new level of understanding of the mechanisms governing fungal behaviour at microscopic scales, and for the first time

Quantifying uncertainties in precipitation measurement

NASA Astrophysics Data System (ADS)

Chen, H. Z. D.

2017-12-01

The scientific community have a long history of utilizing precipitation data for climate model design. However, precipitation record and its model contains more uncertainty than its temperature counterpart. Literature research have shown precipitation measurements to be highly influenced by its surrounding environment, and weather stations are traditionally situated in open areas and subject to various limitations. As a result, this restriction limits the ability of the scientific community to fully close the loop on the water cycle. Horizontal redistribution have been shown to be a major factor influencing precipitation measurements. Efforts have been placed on reducing its effect on the monitoring apparatus. However, the amount of factors contributing to this uncertainty is numerous and difficult to fully capture. As a result, noise factor remains high in precipitation data. This study aims to quantify all uncertainties in precipitation data by factoring out horizontal redistribution by measuring them directly. Horizontal contribution of precipitation will be quantified by measuring precipitation at different heights, with one directly shadowing the other. The above collection represents traditional precipitation data, whereas the bottom measurements sums up the overall error term at given location. Measurements will be recorded and correlated with nearest available wind measurements to quantify its impact on traditional precipitation record. Collections at different locations will also be compared to see whether this phenomenon is location specific or if a general trend can be derived. We aim to demonstrate a new way to isolate the noise component in traditional precipitation data via empirical measurements. By doing so, improve the overall quality of historic precipitation record. As a result, provide a more accurate information for the design and calibration of large scale climate modeling.

Quantifying suspended sediment dynamics in mega deltas using remote sensing data: A case study of the Mekong floodplains

NASA Astrophysics Data System (ADS)

Dang, Thanh Duc; Cochrane, Thomas A.; Arias, Mauricio E.

2018-06-01

Temporal and spatial concentrations of suspended sediment in floodplains are difficult to quantify because in situ measurements can be logistically complex, time consuming and costly. In this research, satellite imagery with long temporal and large spatial coverage (Landsat TM/ETM+) was used to complement in situ suspended sediment measurements to reflect sediment dynamics in a large (70,000 km2) floodplain. Instead of using a single spectral band from Landsat, a Principal Component Analysis was applied to obtain uncorrelated reflectance values for five bands of Landsat TM/ETM+. Significant correlations between the scores of the 1st principal component and the values of continuously gauged suspended sediment concentration, shown via high coefficients of determination of sediment rating curves (R2 ranging from 0.66 to 0.92), permit the application of satellite images to quantify spatial and temporal sediment variation in the Mekong floodplains. Estimated suspended sediment maps show that hydraulic regimes at Chaktomuk (Cambodia), where the Mekong, Bassac, and Tonle Sap rivers diverge, determine the amount of seasonal sediment supplies to the Mekong Delta. The development of flood prevention systems to allow for three rice crops a year in the Vietnam Mekong Delta significantly reduces localized flooding, but also prevents sediment (source of nutrients) from entering fields. A direct consequence of this is the need to apply more artificial fertilizers to boost agricultural productivity, which may trigger environmental problems. Overall, remote sensing is shown to be an effective tool to understand temporal and spatial sediment dynamics in large floodplains.

A family of interaction-adjusted indices of community similarity.

PubMed

Schmidt, Thomas Sebastian Benedikt; Matias Rodrigues, João Frederico; von Mering, Christian

2017-03-01

Interactions between taxa are essential drivers of ecological community structure and dynamics, but they are not taken into account by traditional indices of β diversity. In this study, we propose a novel family of indices that quantify community similarity in the context of taxa interaction networks. Using publicly available datasets, we assessed the performance of two specific indices that are Taxa INteraction-Adjusted (TINA, based on taxa co-occurrence networks), and Phylogenetic INteraction-Adjusted (PINA, based on phylogenetic similarities). TINA and PINA outperformed traditional indices when partitioning human-associated microbial communities according to habitat, even for extremely downsampled datasets, and when organising ocean micro-eukaryotic plankton diversity according to geographical and physicochemical gradients. We argue that interaction-adjusted indices capture novel aspects of diversity outside the scope of traditional approaches, highlighting the biological significance of ecological association networks in the interpretation of community similarity.

A family of interaction-adjusted indices of community similarity

PubMed Central

Schmidt, Thomas Sebastian Benedikt; Matias Rodrigues, João Frederico; von Mering, Christian

2017-01-01

Interactions between taxa are essential drivers of ecological community structure and dynamics, but they are not taken into account by traditional indices of β diversity. In this study, we propose a novel family of indices that quantify community similarity in the context of taxa interaction networks. Using publicly available datasets, we assessed the performance of two specific indices that are Taxa INteraction-Adjusted (TINA, based on taxa co-occurrence networks), and Phylogenetic INteraction-Adjusted (PINA, based on phylogenetic similarities). TINA and PINA outperformed traditional indices when partitioning human-associated microbial communities according to habitat, even for extremely downsampled datasets, and when organising ocean micro-eukaryotic plankton diversity according to geographical and physicochemical gradients. We argue that interaction-adjusted indices capture novel aspects of diversity outside the scope of traditional approaches, highlighting the biological significance of ecological association networks in the interpretation of community similarity. PMID:27935587

Quantified Facial Soft-tissue Strain in Animation Measured by Real-time Dynamic 3-Dimensional Imaging.

PubMed

Hsu, Vivian M; Wes, Ari M; Tahiri, Youssef; Cornman-Homonoff, Joshua; Percec, Ivona

2014-09-01

The aim of this study is to evaluate and quantify dynamic soft-tissue strain in the human face using real-time 3-dimensional imaging technology. Thirteen subjects (8 women, 5 men) between the ages of 18 and 70 were imaged using a dual-camera system and 3-dimensional optical analysis (ARAMIS, Trilion Quality Systems, Pa.). Each subject was imaged at rest and with the following facial expressions: (1) smile, (2) laughter, (3) surprise, (4) anger, (5) grimace, and (6) pursed lips. The facial strains defining stretch and compression were computed for each subject and compared. The areas of greatest strain were localized to the midface and lower face for all expressions. Subjects over the age of 40 had a statistically significant increase in stretch in the perioral region while lip pursing compared with subjects under the age of 40 (58.4% vs 33.8%, P = 0.015). When specific components of lip pursing were analyzed, there was a significantly greater degree of stretch in the nasolabial fold region in subjects over 40 compared with those under 40 (61.6% vs 32.9%, P = 0.007). Furthermore, we observed a greater degree of asymmetry of strain in the nasolabial fold region in the older age group (18.4% vs 5.4%, P = 0.03). This pilot study illustrates that the face can be objectively and quantitatively evaluated using dynamic major strain analysis. The technology of 3-dimensional optical imaging can be used to advance our understanding of facial soft-tissue dynamics and the effects of animation on facial strain over time.

Spatial-Temporal Survey and Occupancy-Abundance Modeling To Predict Bacterial Community Dynamics in the Drinking Water Microbiome

PubMed Central

Pinto, Ameet J.; Schroeder, Joanna; Lunn, Mary; Sloan, William

2014-01-01

ABSTRACT Bacterial communities migrate continuously from the drinking water treatment plant through the drinking water distribution system and into our built environment. Understanding bacterial dynamics in the distribution system is critical to ensuring that safe drinking water is being supplied to customers. We present a 15-month survey of bacterial community dynamics in the drinking water system of Ann Arbor, MI. By sampling the water leaving the treatment plant and at nine points in the distribution system, we show that the bacterial community spatial dynamics of distance decay and dispersivity conform to the layout of the drinking water distribution system. However, the patterns in spatial dynamics were weaker than those for the temporal trends, which exhibited seasonal cycling correlating with temperature and source water use patterns and also demonstrated reproducibility on an annual time scale. The temporal trends were driven by two seasonal bacterial clusters consisting of multiple taxa with different networks of association within the larger drinking water bacterial community. Finally, we show that the Ann Arbor data set robustly conforms to previously described interspecific occupancy abundance models that link the relative abundance of a taxon to the frequency of its detection. Relying on these insights, we propose a predictive framework for microbial management in drinking water systems. Further, we recommend that long-term microbial observatories that collect high-resolution, spatially distributed, multiyear time series of community composition and environmental variables be established to enable the development and testing of the predictive framework. PMID:24865557

Climate events synchronize the dynamics of a resident vertebrate community in the high Arctic.

PubMed

Hansen, Brage B; Grøtan, Vidar; Aanes, Ronny; Sæther, Bernt-Erik; Stien, Audun; Fuglei, Eva; Ims, Rolf A; Yoccoz, Nigel G; Pedersen, Ashild Ø

2013-01-18

Recently accumulated evidence has documented a climate impact on the demography and dynamics of single species, yet the impact at the community level is poorly understood. Here, we show that in Svalbard in the high Arctic, extreme weather events synchronize population fluctuations across an entire community of resident vertebrate herbivores and cause lagged correlations with the secondary consumer, the arctic fox. This synchronization is mainly driven by heavy rain on snow that encapsulates the vegetation in ice and blocks winter forage availability for herbivores. Thus, indirect and bottom-up climate forcing drives the population dynamics across all overwintering vertebrates. Icing is predicted to become more frequent in the circumpolar Arctic and may therefore strongly affect terrestrial ecosystem characteristics.

Community Microgrid Scheduling Considering Network Operational Constraints and Building Thermal Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Guodong; Ollis, Thomas B.; Xiao, Bailu

Here, this paper proposes a Mixed Integer Conic Programming (MICP) model for community microgrids considering the network operational constraints and building thermal dynamics. The proposed optimization model optimizes not only the operating cost, including fuel cost, purchasing cost, battery degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation from the set point, but also several performance indices, including voltage deviation, network power loss and power factor at the Point of Common Coupling (PCC). In particular, the detailed thermal dynamic model of buildings is integrated into the distribution optimal power flow (D-OPF)more » model for the optimal operation of community microgrids. The heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show the effectiveness of the proposed model and significant saving in electricity cost could be achieved with network operational constraints satisfied.« less

Community Microgrid Scheduling Considering Network Operational Constraints and Building Thermal Dynamics

DOE PAGES

Liu, Guodong; Ollis, Thomas B.; Xiao, Bailu; ...

2017-10-10

Here, this paper proposes a Mixed Integer Conic Programming (MICP) model for community microgrids considering the network operational constraints and building thermal dynamics. The proposed optimization model optimizes not only the operating cost, including fuel cost, purchasing cost, battery degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation from the set point, but also several performance indices, including voltage deviation, network power loss and power factor at the Point of Common Coupling (PCC). In particular, the detailed thermal dynamic model of buildings is integrated into the distribution optimal power flow (D-OPF)more » model for the optimal operation of community microgrids. The heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show the effectiveness of the proposed model and significant saving in electricity cost could be achieved with network operational constraints satisfied.« less

Stability in a changing world - palm community dynamics in the hyperdiverse western Amazon over 17 years.

PubMed

Olivares, Ingrid; Svenning, Jens-Christian; van Bodegom, Peter M; Valencia, Renato; Balslev, Henrik

2017-03-01

Are the hyperdiverse local forests of the western Amazon undergoing changes linked to global and local drivers such as climate change, or successional dynamics? We analyzed local climatic records to assess potential climatic changes in Yasuní National Park, Ecuador, and compared two censuses (1995, 2012) of a palm community to assess changes in community structure and composition. Over 17 years, the structure and composition of this palm community remained remarkably stable. Soil humidity was significantly lower and canopy conditions were significantly more open in 2012 compared to 1995, but local climatic records showed that no significant changes in precipitation, temperature or river level have occurred during the last decade. Thus, we found no evidence of recent directional shifts in climate or the palm community in Yasuní. The absence of changes in local climate and plant community dynamics in Yasuní contrasts with recent findings from eastern Amazon, where environmental change is driving significant changes in ecosystem dynamics. Our findings suggest that until now, local forests in the northwest Amazon may have escaped pressure from climate change. The stability of this rich palm community embedded in the hyperdiverse Yasuní National Park underlines its uniqueness as a sanctuary for the protection of Amazonian diversity from global change impacts. © 2016 John Wiley & Sons Ltd.

Practical technique to quantify small, dense low-density lipoprotein cholesterol using dynamic light scattering

NASA Astrophysics Data System (ADS)

Trirongjitmoah, Suchin; Iinaga, Kazuya; Sakurai, Toshihiro; Chiba, Hitoshi; Sriyudthsak, Mana; Shimizu, Koichi

2016-04-01

Quantification of small, dense low-density lipoprotein (sdLDL) cholesterol is clinically significant. We propose a practical technique to estimate the amount of sdLDL cholesterol using dynamic light scattering (DLS). An analytical solution in a closed form has newly been obtained to estimate the weight fraction of one species of scatterers in the DLS measurement of two species of scatterers. Using this solution, we can quantify the sdLDL cholesterol amount from the amounts of the low-density lipoprotein cholesterol and the high-density lipoprotein (HDL) cholesterol, which are commonly obtained through clinical tests. The accuracy of the proposed technique was confirmed experimentally using latex spheres with known size distributions. The applicability of the proposed technique was examined using samples of human blood serum. The possibility of estimating the sdLDL amount using the HDL data was demonstrated. These results suggest that the quantitative estimation of sdLDL amounts using DLS is feasible for point-of-care testing in clinical practice.

Quantifying Proportional Variability

PubMed Central

Heath, Joel P.; Borowski, Peter

2013-01-01

Real quantities can undergo such a wide variety of dynamics that the mean is often a meaningless reference point for measuring variability. Despite their widespread application, techniques like the Coefficient of Variation are not truly proportional and exhibit pathological properties. The non-parametric measure Proportional Variability (PV) [1] resolves these issues and provides a robust way to summarize and compare variation in quantities exhibiting diverse dynamical behaviour. Instead of being based on deviation from an average value, variation is simply quantified by comparing the numbers to each other, requiring no assumptions about central tendency or underlying statistical distributions. While PV has been introduced before and has already been applied in various contexts to population dynamics, here we present a deeper analysis of this new measure, derive analytical expressions for the PV of several general distributions and present new comparisons with the Coefficient of Variation, demonstrating cases in which PV is the more favorable measure. We show that PV provides an easily interpretable approach for measuring and comparing variation that can be generally applied throughout the sciences, from contexts ranging from stock market stability to climate variation. PMID:24386334

The Dynamic Community of Interest and Its Realization in ZODIAC

DTIC Science & Technology

2009-10-01

the ZODIAC project. ZODIAC is a network architecture that puts security first and foremost, with security broken down into confidentiality, integrity...hosts, a unified solution for MANETs will work for hosts or routers as well. DYNAMIC COMMUNITIES OF INTEREST The basis of the ZODIAC design is a new dis...narrow scope of each DCoI limits attack propagation, and supports confidentiality ABSTRACT The ZODIAC project has been exploring a security first

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.

Quantifying geomorphic controls on riparian forest dynamics using a linked physical-biological model: implications for river corridor conservation

NASA Astrophysics Data System (ADS)

Stella, J. C.; Harper, E. B.; Fremier, A. K.; Hayden, M. K.; Battles, J. J.

2009-12-01

In high-order alluvial river systems, physical factors of flooding and channel migration are particularly important drivers of riparian forest dynamics because they regulate habitat creation, resource fluxes of water, nutrients and light that are critical for growth, and mortality from fluvial disturbance. Predicting vegetation composition and dynamics at individual sites in this setting is challenging, both because of the stochastic nature of the flood regime and the spatial variability of flood events. Ecological models that correlate environmental factors with species’ occurrence and abundance (e.g., ’niche models’) often work well in infrequently-disturbed upland habitats, but are less useful in river corridors and other dynamic zones where environmental conditions fluctuate greatly and selection pressures on disturbance-adapted organisms are complex. In an effort to help conserve critical riparian forest habitat along the middle Sacramento River, CA, we are taking a mechanistic approach to quantify linkages between fluvial and biotic processes for Fremont cottonwood (Populus fremontii), a keystone pioneer tree in dryland rivers ecosystems of the U.S. Southwest. To predict the corridor-wide population effects of projected changes to the disturbance regime from flow regulation, climate change, and landscape modifications, we have coupled a physical model of channel meandering with a patch-based population model that incorporates the climatic, hydrologic, and topographic factors critical for tree recruitment and survival. We employed these linked simulations to study the relative influence of the two most critical habitat types--point bars and abandoned channels--in sustaining the corridor-wide cottonwood population over a 175-year period. The physical model uses discharge data and channel planform to predict the spatial distribution of new habitat patches; the population model runs on top of this physical template to track tree colonization and survival on

Dynamics of barite growth in porous media quantified by in situ synchrotron X-ray tomography

NASA Astrophysics Data System (ADS)

Godinho, jose; Gerke, kirill

2016-04-01

Current models used to formulate mineral sequestration strategies of dissolved contaminants in the bedrock often neglect the effect of confinement and the variation of reactive surface area with time. In this work, in situ synchrotron X-ray micro-tomography is used to quantify barite growth rates in a micro-porous structure as a function of time during 13.5 hours with a resolution of 1 μm. Additionally, the 3D porous network at different time frames are used to simulate the flow velocities and calculate the permeability evolution during the experiment. The kinetics of barite growth under porous confinement is compared with the kinetics of barite growth on free surfaces in the same fluid composition. Results are discussed in terms of surface area normalization and the evolution of flow velocities as crystals fill the porous structure. During the initial hours the growth rate measured in porous media is similar to the growth rate on free surfaces. However, as the thinner flow paths clog the growth rate progressively decreases, which is correlated to a decrease of local flow velocity. The largest pores remain open, enabling growth to continue throughout the structure. Quantifying the dynamics of mineral precipitation kinetics in situ in 4D, has revealed the importance of using a time dependent reactive surface area and accounting for the local properties of the porous network, when formulating predictive models of mineral precipitation in porous media.

[Dynamics of parasite communities in an age series of Arctic Cisco Coregonus migratorius (Georgi, 1775)].

PubMed

Dugarov, Zh N; Pronin, N M

2013-01-01

Parasite communities of Arctic cisco from Chivyrkui Bay of Lake Baikal have been analyzed at levels of a host individual (infracommunity), a individual age group of a host-(assemblages of infracommunities), and a host population (component community). Significant positive correlations of parameters of species richness (number of parasite species, Margalef and Menhinick indices) with the age of Arctic cisco were recorded only at the level of parasite inffacommunities. The absence of linear positive correlations between the parameters of species richness and the age of Arctic cisco at the level of assemblages of parasite infracommunities were revealed for the first time for fish of Lake Baikal. The peculiarity of the dynamics of parasite communities of. Arctic cisco is determined by specific features of the host physiology and ecology, primarily by the age dynamics of the feeding spectrum.

Effects of ecological interactions and environmental conditions on community dynamics in an estuarine ecosystem

NASA Astrophysics Data System (ADS)

Liu, H.; Minello, T.; Sutton, G.

2016-02-01

Coastal marine ecosystems are both productive and vulnerable to human and natural stressors. Examining the relative importance of fishing, environmental variability, and habitat alteration on ecosystem dynamics is challenging. Intensive harvest and habitat loss have resulted in widespread concerns related to declines in fisheries production, but causal mechanisms are rarely clear. In this study, we modeled trophic dynamics in Galveston Bay, Texas, using fishery-independent catch data for blue crab, shrimp, red drum, Atlantic croaker and spotted seatrout along with habitat information collected by the Texas Parks and Wildlife Department during 1984 - 2014. We developed a multispecies state-space model to examine ecological interactions and partition the relative effects of trophic interactions and environmental conditions on the community dynamics. Preliminary results showed the importance of salinity, density-dependence, and trophic interactions. We are continuing to explore these results from a perspective of fish community compensatory responses to exploitation, reflecting both direct and indirect effects of harvesting under the influence of climate variability.

Classifying and quantifying basins of attraction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sprott, J. C.; Xiong, Anda

2015-08-15

A scheme is proposed to classify the basins for attractors of dynamical systems in arbitrary dimensions. There are four basic classes depending on their size and extent, and each class can be further quantified to facilitate comparisons. The calculation uses a Monte Carlo method and is applied to numerous common dissipative chaotic maps and flows in various dimensions.

Quantifying the Contribution of Entire Free-Living Nematode Communities to Carbon Mineralization under Contrasting C and N Availability

PubMed Central

Gebremikael, Mesfin Tsegaye; Steel, Hanne; Bert, Wim; Maenhout, Peter; Sleutel, Steven; De Neve, Stefaan

2015-01-01

To understand the roles of nematodes in organic matter (OM) decomposition, experimental setups should include the entire nematode community, the native soil microflora, and their food sources. Yet, published studies are often based on either simplified experimental setups, using only a few selected species of nematode and their respective prey, despite the multitude of species present in natural soil, or on indirect estimation of the mineralization process using O2 consumption and the fresh weight of nematodes. We set up a six-month incubation experiment to quantify the contribution of the entire free living nematode community to carbon (C) mineralization under realistic conditions. The following treatments were compared with and without grass-clover amendment: defaunated soil reinoculated with the entire free living nematode communities (+Nem) and defaunated soil that was not reinoculated (-Nem). We also included untreated fresh soil as a control (CTR). Nematode abundances and diversity in +Nem was comparable to the CTR showing the success of the reinoculation. No significant differences in C mineralization were found between +Nem and -Nem treatments of the amended and unamended samples at the end of incubation. Other related parameters such as microbial biomass C and enzymatic activities did not show significant differences between +Nem and -Nem treatments in both amended and unamended samples. These findings show that the collective contribution of the entire nematode community to C mineralization is small. Previous reports in literature based on simplified experimental setups and indirect estimations are contrasting with the findings of the current study and further investigations are needed to elucidate the extent and the mechanisms of nematode involvement in C mineralization. PMID:26393517

Optimal Sizing of Energy Storage for Community Microgrids Considering Building Thermal Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Guodong; Li, Zhi; Starke, Michael R.

This paper proposes an optimization model for the optimal sizing of energy storage in community microgrids considering the building thermal dynamics and customer comfort preference. The proposed model minimizes the annualized cost of the community microgrid, including energy storage investment, purchased energy cost, demand charge, energy storage degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation. The decision variables are the power and energy capacity of invested energy storage. In particular, we assume the heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently by the microgrid central controller while maintainingmore » the indoor temperature in the comfort range set by customers. For this purpose, the detailed thermal dynamic characteristics of buildings have been integrated into the optimization model. Numerical simulation shows significant cost reduction by the proposed model. The impacts of various costs on the optimal solution are investigated by sensitivity analysis.« less

Challenges in microbial ecology: building predictive understanding of community function and dynamics

PubMed Central

Widder, Stefanie; Allen, Rosalind J; Pfeiffer, Thomas; Curtis, Thomas P; Wiuf, Carsten; Sloan, William T; Cordero, Otto X; Brown, Sam P; Momeni, Babak; Shou, Wenying; Kettle, Helen; Flint, Harry J; Haas, Andreas F; Laroche, Béatrice; Kreft, Jan-Ulrich; Rainey, Paul B; Freilich, Shiri; Schuster, Stefan; Milferstedt, Kim; van der Meer, Jan R; Groβkopf, Tobias; Huisman, Jef; Free, Andrew; Picioreanu, Cristian; Quince, Christopher; Klapper, Isaac; Labarthe, Simon; Smets, Barth F; Wang, Harris; Soyer, Orkun S

2016-01-01

The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development with mathematical model building. We discuss specific examples where model–experiment integration has already resulted in important insights into MC function and structure. We also highlight key research questions that still demand better integration of experiments and models. We argue that such integration is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved. PMID:27022995

Evolution of vulnerability of communities facing repeated hazards

PubMed Central

Guikema, Seth D.; Zhu, Laiyin; Igusa, Takeru

2017-01-01

The decisions that individuals make when recovering from and adapting to repeated hazards affect a region’s vulnerability in future hazards. As such, community vulnerability is not a static property but rather a dynamic property dependent on behavioral responses to repeated hazards and damage. This paper is the first of its kind to build a framework that addresses the complex interactions between repeated hazards, regional damage, mitigation decisions, and community vulnerability. The framework enables researchers and regional planners to visualize and quantify how a community could evolve over time in response to repeated hazards under various behavioral scenarios. An illustrative example using parcel-level data from Anne Arundel County, Maryland—a county that experiences fairly frequent hurricanes—is presented to illustrate the methodology and to demonstrate how the interplay between individual choices and regional vulnerability is affected by the region’s hurricane experience. PMID:28953893

[Dynamics of bacterial community during the bloom caused by Skeletonema costatum and Akashiwo sanguinea in Xiamen sea area].

PubMed

Li, Yi; Yang, Caiyun; Li, Dong; Tian, Yun; Zheng, Tianling

2012-10-04

To investigate the dynamics of bacterial community in Xiamen sea during the bloom mainly caused by Skeletonema costatum and Akashiwo sanguine in August 2011. Bacterial community structures of samples from two bloom sites and one non-bloom site were evaluated by PCR-DGGE (Denaturing gradient gel electrophoresis, DGGE). The genetic diversity of bacterial community was analyzed based on the DGGE fingerprint. The correlation between bacterial community and environmental parameters was studied by Canoco. The bacterial community was largely related to pH and N/P during the start-up stage of the bloom; while in the demise stage, it was mostly correlated to salinity and temperature. According to the results of sequence analysis of DGGE dominant bands, Gammaproteobacteria accounted for 47.7% during the bloom and Pseudoalteromonas, Pseudomonas, Alteromonas, Hydrogenophaga, Actibacter and Oleibacter were dominant genus in bacterial community. The Shannon-Weaver diversity index showed that the diversity of bacterial community in bloom site increased firstly and then decreased during this bloom. Hydrogenophaga was dominant in the start-up stage of bloom, while Pseudomonas and Pseudoalteromonas were dominant in the demise stage of bloom. The diversity of attached bacteria and free-living bacteria in bloom sites reached maximum in the same day (the concentration of algae was high) , both of them changed greatly during the bloom while the environment factors which correlated with the two communities were different. It is the first report about dynamics of bacterial community during the bloom caused by several algae together. This work is helpful to understand the dynamics of bacterial community during the bloom, and provides a theoretical basis for bloom's control in the future.

Structural stability of nonlinear population dynamics.

PubMed

Cenci, Simone; Saavedra, Serguei

2018-01-01

In population dynamics, the concept of structural stability has been used to quantify the tolerance of a system to environmental perturbations. Yet, measuring the structural stability of nonlinear dynamical systems remains a challenging task. Focusing on the classic Lotka-Volterra dynamics, because of the linearity of the functional response, it has been possible to measure the conditions compatible with a structurally stable system. However, the functional response of biological communities is not always well approximated by deterministic linear functions. Thus, it is unclear the extent to which this linear approach can be generalized to other population dynamics models. Here, we show that the same approach used to investigate the classic Lotka-Volterra dynamics, which is called the structural approach, can be applied to a much larger class of nonlinear models. This class covers a large number of nonlinear functional responses that have been intensively investigated both theoretically and experimentally. We also investigate the applicability of the structural approach to stochastic dynamical systems and we provide a measure of structural stability for finite populations. Overall, we show that the structural approach can provide reliable and tractable information about the qualitative behavior of many nonlinear dynamical systems.

Structural stability of nonlinear population dynamics

NASA Astrophysics Data System (ADS)

Cenci, Simone; Saavedra, Serguei

2018-01-01

In population dynamics, the concept of structural stability has been used to quantify the tolerance of a system to environmental perturbations. Yet, measuring the structural stability of nonlinear dynamical systems remains a challenging task. Focusing on the classic Lotka-Volterra dynamics, because of the linearity of the functional response, it has been possible to measure the conditions compatible with a structurally stable system. However, the functional response of biological communities is not always well approximated by deterministic linear functions. Thus, it is unclear the extent to which this linear approach can be generalized to other population dynamics models. Here, we show that the same approach used to investigate the classic Lotka-Volterra dynamics, which is called the structural approach, can be applied to a much larger class of nonlinear models. This class covers a large number of nonlinear functional responses that have been intensively investigated both theoretically and experimentally. We also investigate the applicability of the structural approach to stochastic dynamical systems and we provide a measure of structural stability for finite populations. Overall, we show that the structural approach can provide reliable and tractable information about the qualitative behavior of many nonlinear dynamical systems.

Quantified Facial Soft-tissue Strain in Animation Measured by Real-time Dynamic 3-Dimensional Imaging

PubMed Central

Hsu, Vivian M.; Wes, Ari M.; Tahiri, Youssef; Cornman-Homonoff, Joshua

2014-01-01

Background: The aim of this study is to evaluate and quantify dynamic soft-tissue strain in the human face using real-time 3-dimensional imaging technology. Methods: Thirteen subjects (8 women, 5 men) between the ages of 18 and 70 were imaged using a dual-camera system and 3-dimensional optical analysis (ARAMIS, Trilion Quality Systems, Pa.). Each subject was imaged at rest and with the following facial expressions: (1) smile, (2) laughter, (3) surprise, (4) anger, (5) grimace, and (6) pursed lips. The facial strains defining stretch and compression were computed for each subject and compared. Results: The areas of greatest strain were localized to the midface and lower face for all expressions. Subjects over the age of 40 had a statistically significant increase in stretch in the perioral region while lip pursing compared with subjects under the age of 40 (58.4% vs 33.8%, P = 0.015). When specific components of lip pursing were analyzed, there was a significantly greater degree of stretch in the nasolabial fold region in subjects over 40 compared with those under 40 (61.6% vs 32.9%, P = 0.007). Furthermore, we observed a greater degree of asymmetry of strain in the nasolabial fold region in the older age group (18.4% vs 5.4%, P = 0.03). Conclusions: This pilot study illustrates that the face can be objectively and quantitatively evaluated using dynamic major strain analysis. The technology of 3-dimensional optical imaging can be used to advance our understanding of facial soft-tissue dynamics and the effects of animation on facial strain over time. PMID:25426394

Profiling of dynamic changes in the microbial community during the soy sauce fermentation process.

PubMed

Wei, Quanzeng; Wang, Hongbin; Chen, Zhixin; Lv, Zhijia; Xie, Yufeng; Lu, Fuping

2013-10-01

Soy sauce is a traditional condiment manufactured by natural inoculation and mixed culture fermentation. As is well known, it is the microbial community that plays an important role in the formation of its flavors. However, to date, its dynamic changes during the long period of fermentation process are still unclear, intensively constraining the improvement and control of the soy sauce quality. In this work, we revealed the dynamic changes of the microbial community by combining a cultured dependent method and a cultured independent method of polymerase chain reaction (PCR)-denaturing gradient gel electrophoresis. Results indicated that the two methods verified and complemented each other in profiling microbial community, and that significant dynamics of the microbial community existed during the fermentation process, especially the strong inhibition of the growth of most of the microbes when entering into the mash stage from the koji stage. In the analysis of bacterial community, Staphylococcus and Bacillus were found to be the dominant bacteria and detected in the whole fermentation process. Kurthia and Klebsiella began to appear in the koji stage and then fade away in the early stage of the mash fermentation. In the analysis of fungal community, Aspergillus sojae and Zygosaccharomyces rouxii were found to be the dominant fungi in the koji and mash fermentation, respectively. It was clearly shown that when A. sojae decreased and disappeared in the middle stage of the mash fermentation, Z. rouxii appeared and increased at the meantime. Aspergillus parasiticus, Trichosporon ovoides and Trichosporon asahii also appeared in the koji and the early period of the mash fermentation and disappeared thereafter. Similar to Z. rouxii, Millerozyma farinosa and Peronospora farinosa were also found spontaneously which appeared in the mid-late period of the mash fermentation. The principal component analysis suggested that the microbial community underwent significant changes in

Post-fire reconstructions of fire intensity from fire severity data: quantifying the role of spatial variability of fire intensity on forest dynamics

NASA Astrophysics Data System (ADS)

Baker, Patrick; Oborne, Lisa

2015-04-01

Large, high-intensity fires have direct and long-lasting effects on forest ecosystems and present a serious threat to human life and property. However, even within the most catastrophic fires there is important variability in local-scale intensity that has important ramifications for forest mortality and regeneration. Quantifying this variability is difficult due to the rarity of catastrophic fire events, the extreme conditions at the time of the fires, and their large spatial extent. Instead fire severity is typically measured or estimated from observed patterns of vegetation mortality; however, differences in species- and size-specific responses to fires often makes fire severity a poor proxy for fire intensity. We developed a statistical method using simple, plot-based measurements of individual tree mortality to simultaneously estimate plot-level fire intensity and species-specific mortality patterns as a function of tree size. We applied our approach to an area of forest burned in the catastrophic Black Saturday fires that occurred near Melbourne, Australia, in February 2009. Despite being the most devastating fire in the past 70 years and our plots being located in the area that experienced some of the most intense fires in the 350,000 ha fire complex, we found that the estimated fire intensity was highly variable at multiple spatial scales. All eight tree species in our study differed in their susceptibility to fire-induced mortality, particularly among the largest size classes. We also found that seedling height and species richness of the post-fire seedling communities were both positively correlated with fire intensity. Spatial variability in disturbance intensity has important, but poorly understood, consequences for the short- and long-term dynamics of forests in the wake of catastrophic wildfires. Our study provides a tool to estimate fire intensity after a fire has passed, allowing new opportunities for linking spatial variability in fire intensity to

Use of Mobile Device Data To Better Estimate Dynamic Population Size for Wastewater-Based Epidemiology.

PubMed

Thomas, Kevin V; Amador, Arturo; Baz-Lomba, Jose Antonio; Reid, Malcolm

2017-10-03

Wastewater-based epidemiology is an established approach for quantifying community drug use and has recently been applied to estimate population exposure to contaminants such as pesticides and phthalate plasticizers. A major source of uncertainty in the population weighted biomarker loads generated is related to estimating the number of people present in a sewer catchment at the time of sample collection. Here, the population quantified from mobile device-based population activity patterns was used to provide dynamic population normalized loads of illicit drugs and pharmaceuticals during a known period of high net fluctuation in the catchment population. Mobile device-based population activity patterns have for the first time quantified the high degree of intraday, week, and month variability within a specific sewer catchment. Dynamic population normalization showed that per capita pharmaceutical use remained unchanged during the period when static normalization would have indicated an average reduction of up to 31%. Per capita illicit drug use increased significantly during the monitoring period, an observation that was only possible to measure using dynamic population normalization. The study quantitatively confirms previous assessments that population estimates can account for uncertainties of up to 55% in static normalized data. Mobile device-based population activity patterns allow for dynamic normalization that yields much improved temporal and spatial trend analysis.

Local community detection as pattern restoration by attractor dynamics of recurrent neural networks.

PubMed

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.

Dynamics of bacterial and fungal communities associated with eggshells during incubation

PubMed Central

Grizard, Stéphanie; Dini-Andreote, Francisco; Tieleman, B Irene; Salles, Joana F

2014-01-01

Microorganisms are closely associated with eggs and may play a determinant role in embryo survival. Yet, the majority of studies focusing on this association relied on culture-based methodology, eventually leading to a skewed assessment of microbial communities. By targeting the 16S rRNA gene and internal transcribed spacer (ITS) region, we, respectively, described bacterial and fungal communities on eggshells of the homing pigeon Columba livia. We explored their structure, abundance, and composition. Firstly, we showed that sampling technique affected the outcome of the results. While broadly used, the egg swabbing procedure led to a lower DNA extraction efficiency and provided different profiles of bacterial communities than those based on crushed eggshell pieces. Secondly, we observed shifts in bacterial and fungal communities during incubation. At late incubation, bacterial communities showed a reduction in diversity, while their abundance increased, possibly due to the competitive advantage of some species. When compared to their bacterial counterparts, fungal communities also decreased in diversity at late incubation. In that case, however, the decline was associated with a diminution of their overall abundance. Conclusively, our results showed that although incubation might inhibit microbial growth when compared to unincubated eggs, we observed the selective growth of specific bacterial species during incubation. Moreover, we showed that fungi are a substantial component of the microbial communities associated with eggshells and require further investigations in avian ecology. Identifying the functional roles of these microorganisms is likely to provide news insights into the evolutionary strategies that control embryo survival. We aimed to describe the dynamics of bacterial and fungal communities on homing pigeon eggshell surfaces. We investigated these communities at early and late incubation stages. PMID:24772289

Effects of Lipid Composition on Bilayer Membranes Quantified by All-Atom Molecular Dynamics.

PubMed

Ding, Wei; Palaiokostas, Michail; Wang, Wen; Orsi, Mario

2015-12-10

Biological bilayer membranes typically contain varying amounts of lamellar and nonlamellar lipids. Lamellar lipids, such as dioleoylphosphatidylcholine (DOPC), are defined by their tendency to form the lamellar phase, ubiquitous in biology. Nonlamellar lipids, such as dioleoylphosphatidylethanolamine (DOPE), prefer instead to form nonlamellar phases, which are mostly nonbiological. However, nonlamellar lipids mix with lamellar lipids in biomembrane structures that remain overall lamellar. Importantly, changes in the lamellar vs nonlamellar lipid composition are believed to affect membrane function and modulate membrane proteins. In this work, we employ atomistic molecular dynamics simulations to quantify how a range of bilayer properties are altered by variations in the lamellar vs nonlamellar lipid composition. Specifically, we simulate five DOPC/DOPE bilayers at mixing ratios of 1/0, 3/1, 1/1, 1/3, and 0/1. We examine properties including lipid area and bilayer thickness, as well as the transmembrane profiles of electron density, lateral pressure, electric field, and dipole potential. While the bilayer structure is only marginally altered by lipid composition changes, dramatic effects are observed for the lateral pressure, electric field, and dipole potential profiles. Possible implications for membrane function are discussed.

Functional enzyme-based modeling approach for dynamic simulation of denitrification process in hyporheic zone sediments: Genetically structured microbial community model

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.

The Dynamics of an Online Community of Practice Involving Teachers and Researchers

ERIC Educational Resources Information Center

Marques, Margarida Morais; Loureiro, Maria João; Marques, Luís

2016-01-01

In the literature, communities of practice (CoPs) are recognised as having potential to promote teachers' professional development. However, the study of the dynamics of CoPs with teachers and researchers, and their impact on teachers' professional development, is still scarce. Contributing to fill this gap, this paper presents a single case study…

Dynamic simulation of crime perpetration and reporting to examine community intervention strategies.

PubMed

Yonas, Michael A; Burke, Jessica G; Brown, Shawn T; Borrebach, Jeffrey D; Garland, Richard; Burke, Donald S; Grefenstette, John J

2013-10-01

To develop a conceptual computational agent-based model (ABM) to explore community-wide versus spatially focused crime reporting interventions to reduce community crime perpetrated by youth. Agents within the model represent individual residents and interact on a two-dimensional grid representing an abstract nonempirically grounded community setting. Juvenile agents are assigned initial random probabilities of perpetrating a crime and adults are assigned random probabilities of witnessing and reporting crimes. The agents' behavioral probabilities modify depending on the individual's experience with criminal behavior and punishment, and exposure to community crime interventions. Cost-effectiveness analyses assessed the impact of activating different percentages of adults to increase reporting and reduce community crime activity. Community-wide interventions were compared with spatially focused interventions, in which activated adults were focused in areas of highest crime prevalence. The ABM suggests that both community-wide and spatially focused interventions can be effective in reducing overall offenses, but their relative effectiveness may depend on the intensity and cost of the interventions. Although spatially focused intervention yielded localized reductions in crimes, such interventions were shown to move crime to nearby communities. Community-wide interventions can achieve larger reductions in overall community crime offenses than spatially focused interventions, as long as sufficient resources are available. The ABM demonstrates that community-wide and spatially focused crime strategies produce unique intervention dynamics influencing juvenile crime behaviors through the decisions and actions of community adults. It shows how such models might be used to investigate community-supported crime intervention programs by integrating community input and expertise and provides a simulated setting for assessing dimensions of cost comparison and intervention effect

A System Dynamics Approach to Understanding Cost and Revenue Interactions in the Community College Financial System.

ERIC Educational Resources Information Center

Howard, James E.

After identifying the components of a community college financial system as enrollment, costs, revenues and tuition, this paper addresses the need for a system dynamics analysis of a California community college district. This systems approach would assess the possible effects of alternative policies on the characteristic behavior modes of the…

Nutrient gradients in a granular activated carbon biofilter drives bacterial community organization and dynamics.

PubMed

Boon, Nico; Pycke, Benny F G; Marzorati, Massimo; Hammes, Frederik

2011-12-01

The quality of drinking water is ensured by hygienic barriers and filtration steps, such as ozonation and granular activated carbon (GAC) filtration. Apart from adsorption, GAC filtration involves microbial processes that remove biodegradable organic carbon from the ozonated ground or surface water and ensures biological stability of the treated water. In this study, microbial community dynamics in were monitored during the start-up and maturation of an undisturbed pilot-scale GAC filter at 4 depths (10, 45, 80 and 115 cm) over a period of 6 months. New ecological tools, based on 16S rRNA gene-DGGE, were correlated to filter performance and microbial activity and showed that the microbial gradients developing in the filter was of importance. At 10 cm from the top, receiving the freshly ozonated water with the highest concentration of nutrients, the microbial community dynamics were minimal and the species richness remained low. However, the GAC samples at 80-115 cm showed a 2-3 times higher species richness than the 10-45 cm samples. The highest biomass densities were observed at 45-80 cm, which corresponded with maximum removal of dissolved and assimilable organic carbon. Furthermore, the start-up period was clearly distinguishable using the Lorenz analysis, as after 80 days, the microbial community shifted to an apparent steady-state condition with increased evenness. This study showed that GAC biofilter performance is not necessarily correlated to biomass concentration, but rather that an elevated functionality can be the result of increased microbial community richness, evenness and dynamics. Copyright © 2011 Elsevier Ltd. All rights reserved.

Quantifying heterogeneity of lesion uptake in dynamic contrast enhanced MRI for breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Karahaliou, A.; Vassiou, K.; Skiadopoulos, S.; Kanavou, T.; Yiakoumelos, A.; Costaridou, L.

2009-07-01

The current study investigates whether texture features extracted from lesion kinetics feature maps can be used for breast cancer diagnosis. Fifty five women with 57 breast lesions (27 benign, 30 malignant) were subjected to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) on 1.5T system. A linear-slope model was fitted pixel-wise to a representative lesion slice time series and fitted parameters were used to create three kinetic maps (wash out, time to peak enhancement and peak enhancement). 28 grey level co-occurrence matrices features were extracted from each lesion kinetic map. The ability of texture features per map in discriminating malignant from benign lesions was investigated using a Probabilistic Neural Network classifier. Additional classification was performed by combining classification outputs of most discriminating feature subsets from the three maps, via majority voting. The combined scheme outperformed classification based on individual maps achieving area under Receiver Operating Characteristics curve 0.960±0.029. Results suggest that heterogeneity of breast lesion kinetics, as quantified by texture analysis, may contribute to computer assisted tissue characterization in DCE-MRI.

Temporal Microbial Community Dynamics in Microbial Electrolysis Cells – Influence of Acetate and Propionate Concentration

PubMed Central

Hari, Ananda Rao; Venkidusamy, Krishnaveni; Katuri, Krishna P.; Bagchi, Samik; Saikaly, Pascal E.

2017-01-01

Microbial electrolysis cells (MECs) are widely considered as a next generation wastewater treatment system. However, fundamental insight on the temporal dynamics of microbial communities associated with MEC performance under different organic types with varied loading concentrations is still unknown, nevertheless this knowledge is essential for optimizing this technology for real-scale applications. Here, the temporal dynamics of anodic microbial communities associated with MEC performance was examined at low (0.5 g COD/L) and high (4 g COD/L) concentrations of acetate or propionate, which are important intermediates of fermentation of municipal wastewaters and sludge. The results showed that acetate-fed reactors exhibited higher performance in terms of maximum current density (I: 4.25 ± 0.23 A/m2), coulombic efficiency (CE: 95 ± 8%), and substrate degradation rate (98.8 ± 1.2%) than propionate-fed reactors (I: 2.7 ± 0.28 A/m2; CE: 68 ± 9.5%; substrate degradation rate: 84 ± 13%) irrespective of the concentrations tested. Despite of the repeated sampling of the anodic biofilm over time, the high-concentration reactors demonstrated lower and stable performance in terms of current density (I: 1.1 ± 0.14 to 4.2 ± 0.21 A/m2), coulombic efficiency (CE: 44 ± 4.1 to 103 ± 7.2%) and substrate degradation rate (64.9 ± 6.3 to 99.7 ± 0.5%), while the low-concentration reactors produced higher and dynamic performance (I: 1.1 ± 0.12 to 4.6 ± 0.1 A/m2; CE: 52 ± 2.5 to 105 ± 2.7%; substrate degradation rate: 87.2 ± 0.2 to 99.9 ± 0.06%) with the different substrates tested. Correlating reactor’s performance with temporal dynamics of microbial communities showed that relatively similar anodic microbial community composition but with varying relative abundances was observed in all the reactors despite differences in the substrate and concentrations tested. Particularly, Geobacter was the predominant bacteria on the anode biofilm of all MECs over time suggesting

A trait based dynamic energy budget approach to explore emergent microalgal community structure

NASA Astrophysics Data System (ADS)

Cheng, Y.; Bouskill, N.; Karaoz, U.; Geng, H.; Lane, T.; Pett-Ridge, J.; Mayali, X.; Brodie, E.

2015-12-01

Microalgae play important roles in the global carbon budget. Phytoplankton, including microalgae, are responsible for around 50% of global primary production, and also hold promise as a viable renewable biofuel source. Research has been underway for decades to realize the full potential of algal biofuels at the commercial scale, however, uni-algal ponds are typically threatened by collapse due to microalgal grazing and parasite invasions. Recently, it has been proposed that functionally diverse microalgal-bacterial communities can achieve high biomass and/or lipid yields, and are more stable (less susceptible to invasion) than a monoculture. Similar positive diversity-productivity relationships have been observed in a wide range of ecosystem studies, but the purposeful maintenance of a diverse microbiome is less common in managed systems. In our work, a trait based dynamic energy budget model was developed to explore emergent microalgal community structure under various environmental (e.g. light, temperature, nutrient availability) conditions. The complex algal community can be reduced into functional groups (guilds). Each guild (algae or bacteria) is characterized by distinct physiological traits (e.g. nutrient requirement, growth rate, substrate affinity, lipid production) constrained by biochemical trade-offs. These trait values are derived from literature and information encoded in genomic data. Metabolism of the algae and the bacterial species (symbiotic or non-symbiotic) are described within a dynamic energy budget framework. The model offers a mechanistic framework to predict the optimal microalgal community assemblage towards high productivity and resistance to invasion under prevailing environmental conditions.

Dynamics of bacterial community succession in a salt marsh chronosequence: evidences for temporal niche partitioning.

PubMed

Dini-Andreote, Francisco; de Cássia Pereira e Silva, Michele; Triadó-Margarit, Xavier; Casamayor, Emilio O; van Elsas, Jan Dirk; Salles, Joana Falcão

2014-10-01

The mechanisms underlying community assembly and promoting temporal succession are often overlooked in microbial ecology. Here, we studied an undisturbed salt marsh chronosequence, spanning over a century of ecosystem development, to understand bacterial succession in soil. We used 16S rRNA gene-based quantitative PCR to determine bacterial abundance and multitag 454 pyrosequencing for community composition and diversity analyses. Despite 10-fold lower 16S rRNA gene abundances, the initial stages of soil development held higher phylogenetic diversities than the soil at late succession. Temporal variations in phylogenetic β-diversity were greater at initial stages of soil development, possibly as a result of the great dynamism imposed by the daily influence of the tide, promoting high immigration rates. Allogenic succession of bacterial communities was mostly driven by shifts in the soil physical structure, as well as variations in pH and salinity, which collectively explained 84.5% of the variation concerning community assemblage. The community assembly data for each successional stage were integrated into a network co-occurrence analysis, revealing higher complexity at initial stages, coinciding with great dynamism in turnover and environmental variability. Contrary to a spatial niche-based perspective of bacterial community assembly, we suggest temporal niche partitioning as the dominant mechanism of assembly (promoting more phylotype co-occurrence) in the initial stages of succession, where continuous environmental change results in the existence of multiple niches over short periods of time.

Dynamics of bacterial community succession in a salt marsh chronosequence: evidences for temporal niche partitioning

PubMed Central

Dini-Andreote, Francisco; de Cássia Pereira e Silva, Michele; Triadó-Margarit, Xavier; Casamayor, Emilio O; van Elsas, Jan Dirk; Salles, Joana Falcão

2014-01-01

The mechanisms underlying community assembly and promoting temporal succession are often overlooked in microbial ecology. Here, we studied an undisturbed salt marsh chronosequence, spanning over a century of ecosystem development, to understand bacterial succession in soil. We used 16S rRNA gene-based quantitative PCR to determine bacterial abundance and multitag 454 pyrosequencing for community composition and diversity analyses. Despite 10-fold lower 16S rRNA gene abundances, the initial stages of soil development held higher phylogenetic diversities than the soil at late succession. Temporal variations in phylogenetic β-diversity were greater at initial stages of soil development, possibly as a result of the great dynamism imposed by the daily influence of the tide, promoting high immigration rates. Allogenic succession of bacterial communities was mostly driven by shifts in the soil physical structure, as well as variations in pH and salinity, which collectively explained 84.5% of the variation concerning community assemblage. The community assembly data for each successional stage were integrated into a network co-occurrence analysis, revealing higher complexity at initial stages, coinciding with great dynamism in turnover and environmental variability. Contrary to a spatial niche-based perspective of bacterial community assembly, we suggest temporal niche partitioning as the dominant mechanism of assembly (promoting more phylotype co-occurrence) in the initial stages of succession, where continuous environmental change results in the existence of multiple niches over short periods of time. PMID:24739625

Quantifying microstructural dynamics and electrochemical activity of graphite and silicon-graphite lithium ion battery anodes

NASA Astrophysics Data System (ADS)

Pietsch, Patrick; Westhoff, Daniel; Feinauer, Julian; Eller, Jens; Marone, Federica; Stampanoni, Marco; Schmidt, Volker; Wood, Vanessa

2016-09-01

Despite numerous studies presenting advances in tomographic imaging and analysis of lithium ion batteries, graphite-based anodes have received little attention. Weak X-ray attenuation of graphite and, as a result, poor contrast between graphite and the other carbon-based components in an electrode pore space renders data analysis challenging. Here we demonstrate operando tomography of weakly attenuating electrodes during electrochemical (de)lithiation. We use propagation-based phase contrast tomography to facilitate the differentiation between weakly attenuating materials and apply digital volume correlation to capture the dynamics of the electrodes during operation. After validating that we can quantify the local electrochemical activity and microstructural changes throughout graphite electrodes, we apply our technique to graphite-silicon composite electrodes. We show that microstructural changes that occur during (de)lithiation of a pure graphite electrode are of the same order of magnitude as spatial inhomogeneities within it, while strain in composite electrodes is locally pronounced and introduces significant microstructural changes.

Quantifying and tuning entanglement for quantum systems

NASA Astrophysics Data System (ADS)

Xu, Qing

A 2D Ising model with transverse field on a triangular lattice is studied using exact diagonalization. The quantum entanglement of the system is quantified by the entanglement of formation. The ground state property of the system is studied and the quantified entanglement is shown to be closely related to the ground state wavefunction while the singularity in the entanglement as a function of the transverse field is a reasonable indicator of the quantum phase transition. In order to tune the entanglement, one can either include an impurity in the otherwise homogeneous system whose strength is tunable, or one can vary the external transverse field as a tuner. The latter kind of tuning involves complicated dynamical properties of the system. From the study of the dynamics on a comparatively smaller system, we provide ways to tune the entanglement without triggering any decoherence. The finite temperature effect is also discussed. Besides showing above physical results, the realization of the trace-minimization method in our system is provided; the scalability of such method to larger systems is argued.

Dynamic robustness of knowledge collaboration network of open source product development community

NASA Astrophysics Data System (ADS)

Zhou, Hong-Li; Zhang, Xiao-Dong

2018-01-01

As an emergent innovative design style, open source product development communities are characterized by a self-organizing, mass collaborative, networked structure. The robustness of the community is critical to its performance. Using the complex network modeling method, the knowledge collaboration network of the community is formulated, and the robustness of the network is systematically and dynamically studied. The characteristics of the network along the development period determine that its robustness should be studied from three time stages: the start-up, development and mature stages of the network. Five kinds of user-loss pattern are designed, to assess the network's robustness under different situations in each of these three time stages. Two indexes - the largest connected component and the network efficiency - are used to evaluate the robustness of the community. The proposed approach is applied in an existing open source car design community. The results indicate that the knowledge collaboration networks show different levels of robustness in different stages and different user loss patterns. Such analysis can be applied to provide protection strategies for the key users involved in knowledge dissemination and knowledge contribution at different stages of the network, thereby promoting the sustainable and stable development of the open source community.

Predation and resource fluctuations drive eco-evolutionary dynamics of a bacterial community

NASA Astrophysics Data System (ADS)

Hiltunen, Teppo; Friman, Ville-Petri; Kaitala, Veijo; Mappes, Johanna; Laakso, Jouni

2012-01-01

Predation and temporal resource availability are among the most important factors determining prey community dynamics and composition. Both factors have been shown to affect prey diversity, but less is known about their interactive effects, especially in rapidly evolving prey communities. In a laboratory microcosm experiment, we manipulated the presence of the predatory protozoan Tetrahymena thermophila and the temporal patterns in the availability of resources for a bacterial prey community. We found that both predation and temporal fluctuations in prey resources resulted in a more even prey community, and these factors also interacted so that the effect of predation was only seen in a fluctuating environment. One possible explanation for this finding could be differences in prey species grazing resistance and resource use abilities, which likely had the greatest effect on prey community structure in fluctuating environments with periodical resource limitation. We also found that prey communities evolved to be more grazing-resistant during the experiment, and that this effect was due to a clear increase in the grazing resistance of the bacterium Serratia marcescens. Our results demonstrate that temporal variability in prey resources and predation can promote more even prey species proportions by allowing the existence of both defensive and competitive prey life-history strategies.

Dynamics of western juniper woodland expansion into sagebrush communities in central Oregon

Treesearch

Mary M. Rowland; Lowell H. Suring; Robin J. Tausch; Susan Greer; Michael J. Wisdom

2011-01-01

Western juniper (Juniperus occidentalis) woodlands in Oregon have expanded four-fold from 600,000 ha in 1930 to > 2.6 million ha, often resulting in the reduction and fragmentation of sagebrush (Artemisia spp.) communities. We documented dynamics of western juniper across the John Day Ecological Province in central Oregon by recording size class and growth form at...

Dynamics of bacterial communities before and after distribution in a full-scale drinking water network.

PubMed

El-Chakhtoura, Joline; Prest, Emmanuelle; Saikaly, Pascal; van Loosdrecht, Mark; Hammes, Frederik; Vrouwenvelder, Hans

2015-05-01

Understanding the biological stability of drinking water distribution systems is imperative in the framework of process control and risk management. The objective of this research was to examine the dynamics of the bacterial community during drinking water distribution at high temporal resolution. Water samples (156 in total) were collected over short time-scales (minutes/hours/days) from the outlet of a treatment plant and a location in its corresponding distribution network. The drinking water is treated by biofiltration and disinfectant residuals are absent during distribution. The community was analyzed by 16S rRNA gene pyrosequencing and flow cytometry as well as conventional, culture-based methods. Despite a random dramatic event (detected with pyrosequencing and flow cytometry but not with plate counts), the bacterial community profile at the two locations did not vary significantly over time. A diverse core microbiome was shared between the two locations (58-65% of the taxa and 86-91% of the sequences) and found to be dependent on the treatment strategy. The bacterial community structure changed during distribution, with greater richness detected in the network and phyla such as Acidobacteria and Gemmatimonadetes becoming abundant. The rare taxa displayed the highest dynamicity, causing the major change during water distribution. This change did not have hygienic implications and is contingent on the sensitivity of the applied methods. The concept of biological stability therefore needs to be revised. Biostability is generally desired in drinking water guidelines but may be difficult to achieve in large-scale complex distribution systems that are inherently dynamic. Copyright © 2015 Elsevier Ltd. All rights reserved.

Building community research capacity: process evaluation of community training and education in a community-based participatory research program serving a predominantly Puerto Rican community.

PubMed

Tumiel-Berhalter, Laurene M; McLaughlin-Diaz, Victoria; Vena, John; Crespo, Carlos J

2007-01-01

Education and training build community research capacity and have impact on improvements of health outcomes. This manuscript describes the training and educational approaches to building research capacity that were utilized in a community-based participatory research program serving a Puerto Rican population and identifies barriers and strategies for overcoming them. A process evaluation identified a multitiered approach to training and education that was critical to reaching the broad community. This approach included four major categories providing a continuum of education and training opportunities: networking, methods training, on-the-job experience, and community education. Participation in these opportunities supported the development of a registry, the implementation of a survey, and two published manuscripts. Barriers included the lack of a formal evaluation of the education and training components, language challenges that limited involvement of ethnic groups other than Puerto Ricans, and potential biases associated with the familiarity of the data collector and the participant. The CBPR process facilitated relationship development between the university and the community and incorporated the richness of the community experience into research design. Strategies for improvement include incorporating evaluation into every training and educational opportunity and developing measures to quantify research capacity at the individual and community levels. Evaluating training and education in the community allows researchers to quantify the impact of CBPR on building community research capacity.

Temporal dynamics of the arthropod community in pear orchards intercropped with aromatic plants.

PubMed

Beizhou, Song; Jie, Zhang; Jinghui, Hu; Hongying, Wu; Yun, Kong; Yuncong, Yao

2011-09-01

Increasing attention has been paid to enhancing biological control through habitat management in agricultural systems for enhanced pest management. Pest management benefits can be realised by intercropping, which can increase natural enemy abundance and, in turn, reduce pest abundance. In this study, the composition and temporal dynamics of arthropod communities in pear orchards when intercropped with aromatic plants were investigated, and the effectiveness and applicability of aromatic plants as intercrops for enhancing insect control were assessed. When compared with natural grasses or clean tillage, intercropping significantly reduced pest abundance and increased the ratio of natural enemies to pests. Intercropping also shortened the occurrence duration and depressed the incidence peak in annual dynamics curves of the pest subcommunity and the arthropod community, mainly because of the repellent effects of aromatic plants. Equally important, intercropping significantly reduced the numbers of major pests, such as Psylla chinensis, Aphis citricola and Pseudococcus comstocki, while their incidence period was delayed to varying degrees, and the numbers of their dominant natural enemies (Coccinella septempunctata, Phytoseiulus persimilis and Chrysoperla sinica) increased. Intercropping with aromatic plants led to a considerable improvement in arthropod pest management by enhancing the activity of the beneficial arthropod community within the pear orchard ecosystem. Copyright © 2011 Society of Chemical Industry.

Interpreting beta-diversity components over time to conserve metacommunities in highly dynamic ecosystems.

PubMed

Ruhí, Albert; Datry, Thibault; Sabo, John L

2017-12-01

The concept of metacommunity (i.e., a set of local communities linked by dispersal) has gained great popularity among community ecologists. However, metacommunity research mostly addresses questions on spatial patterns of biodiversity at the regional scale, whereas conservation planning requires quantifying temporal variation in those metacommunities and the contributions that individual (local) sites make to regional dynamics. We propose that recent advances in diversity-partitioning methods may allow for a better understanding of metacommunity dynamics and the identification of keystone sites. We used time series of the 2 components of beta diversity (richness and replacement) and the contributions of local sites to these components to examine which sites controlled source-sink dynamics in a highly dynamic model system (an intermittent river). The relative importance of the richness and replacement components of beta diversity fluctuated over time, and sample aggregation led to underestimation of beta diversity by up to 35%. Our literature review revealed that research on intermittent rivers would benefit greatly from examination of beta-diversity components over time. Adequately appraising spatiotemporal variability in community composition and identifying sites that are pivotal for maintaining biodiversity at the landscape scale are key needs for conservation prioritization and planning. Thus, our framework may be used to guide conservation actions in highly dynamic ecosystems when time-series data describing biodiversity across sites connected by dispersal are available. © 2017 Society for Conservation Biology.

A dynamic microbial community with high functional redundancy inhabits the cold, oxic subseafloor aquifer

NASA Astrophysics Data System (ADS)

Tully, B. J.; Wheat, C. G.; Glazer, B. T.; Huber, J. A.

2017-12-01

The rock-hosted subseafloor crustal aquifer harbors a reservoir of microbial life that may influence global marine biogeochemical cycles. Here we utilized genomic reconstruction of crustal fluid samples from North Pond, located on the flanks of the Mid-Atlantic Ridge, a site with cold, oxic subseafloor fluid circulation within the upper basement. Twenty-one samples were collected during a two-year period at three different depths and two locations with the basaltic aquifer to examine potential microbial metabolism and community dynamics. We observed minor changes in the geochemical signatures over the two years, yet a dynamic microbial community was present in the crustal fluids that underwent large shifts in the dominant taxonomic groups. An analysis of 195 metagenome-assembled genomes (MAGs) were generated from the dataset and revealed a connection between litho- and autotrophic processes, linking carbon fixation to the oxidation of sulfide, sulfur, thiosulfate, hydrogen, and ferrous iron in a diverse group of microorganisms. Despite oxic conditions, analysis of the MAGs indicated that members of the microbial community were poised to exploit hypoxic or anoxic conditions through the use of microaerobic cytochromes and alternative electron acceptors. Temporal and spatial trends from the MAGs revealed a high degree of functional redundancy that did not correlate with the shifting microbial community membership, suggesting functional stability in mediating subseafloor biogeochemical cycles.

Empirical phylogenies and species abundance distributions are consistent with preequilibrium dynamics of neutral community models with gene flow.

PubMed

Bonnet-Lebrun, Anne-Sophie; Manica, Andrea; Eriksson, Anders; Rodrigues, Ana S L

2017-05-01

Community characteristics reflect past ecological and evolutionary dynamics. Here, we investigate whether it is possible to obtain realistically shaped modeled communities-that is with phylogenetic trees and species abundance distributions shaped similarly to typical empirical bird and mammal communities-from neutral community models. To test the effect of gene flow, we contrasted two spatially explicit individual-based neutral models: one with protracted speciation, delayed by gene flow, and one with point mutation speciation, unaffected by gene flow. The former produced more realistic communities (shape of phylogenetic tree and species-abundance distribution), consistent with gene flow being a key process in macro-evolutionary dynamics. Earlier models struggled to capture the empirically observed branching tempo in phylogenetic trees, as measured by the gamma statistic. We show that the low gamma values typical of empirical trees can be obtained in models with protracted speciation, in preequilibrium communities developing from an initially abundant and widespread species. This was even more so in communities sampled incompletely, particularly if the unknown species are the youngest. Overall, our results demonstrate that the characteristics of empirical communities that we have studied can, to a large extent, be explained through a purely neutral model under preequilibrium conditions. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Fungal networks shape dynamics of bacterial dispersal and community assembly in cheese rind microbiomes.

PubMed

Zhang, Yuanchen; Kastman, Erik K; Guasto, Jeffrey S; Wolfe, Benjamin E

2018-01-23

Most studies of bacterial motility have examined small-scale (micrometer-centimeter) cell dispersal in monocultures. However, bacteria live in multispecies communities, where interactions with other microbes may inhibit or facilitate dispersal. Here, we demonstrate that motile bacteria in cheese rind microbiomes use physical networks created by filamentous fungi for dispersal, and that these interactions can shape microbial community structure. Serratia proteamaculans and other motile cheese rind bacteria disperse on fungal networks by swimming in the liquid layers formed on fungal hyphae. RNA-sequencing, transposon mutagenesis, and comparative genomics identify potential genetic mechanisms, including flagella-mediated motility, that control bacterial dispersal on hyphae. By manipulating fungal networks in experimental communities, we demonstrate that fungal-mediated bacterial dispersal can shift cheese rind microbiome composition by promoting the growth of motile over non-motile community members. Our single-cell to whole-community systems approach highlights the interactive dynamics of bacterial motility in multispecies microbiomes.

Species abundance distribution and population dynamics in a two-community model of neutral ecology

NASA Astrophysics Data System (ADS)

Vallade, M.; Houchmandzadeh, B.

2006-11-01

Explicit formulas for the steady-state distribution of species in two interconnected communities of arbitrary sizes are derived in the framework of Hubbell’s neutral model of biodiversity. Migrations of seeds from both communities as well as mutations in both of them are taken into account. These results generalize those previously obtained for the “island-continent” model and they allow an analysis of the influence of the ratio of the sizes of the two communities on the dominance/diversity equilibrium. Exact expressions for species abundance distributions are deduced from a master equation for the joint probability distribution of species in the two communities. Moreover, an approximate self-consistent solution is derived. It corresponds to a generalization of previous results and it proves to be accurate over a broad range of parameters. The dynamical correlations between the abundances of a species in both communities are also discussed.

Functional and taxonomic dynamics of an electricity-consuming methane-producing microbial community.

PubMed

Bretschger, Orianna; Carpenter, Kayla; Phan, Tony; Suzuki, Shino; Ishii, Shun'ichi; Grossi-Soyster, Elysse; Flynn, Michael; Hogan, John

2015-11-01

The functional and taxonomic microbial dynamics of duplicate electricity-consuming methanogenic communities were observed over a 6 months period to characterize the reproducibility, stability and recovery of electromethanogenic consortia. The highest rate of methanogenesis was 0.72 mg-CH4/L/day, which occurred during the third month of enrichment when multiple methanogenic phylotypes and associated Desulfovibrionaceae phylotypes were present in the electrode-associated microbial community. Results also suggest that electromethanogenic microbial communities are very sensitive to electron donor-limiting open-circuit conditions. A 45 min exposure to open-circuit conditions induced an 87% drop in volumetric methane production rates. Methanogenic performance recovered after 4 months to a maximum value of 0.30 mg-CH4/L/day under set potential operation (-700 mV vs Ag/AgCl); however, current consumption and biomass production was variable over time. Long-term functional and taxonomic analyses from experimental replicates provide new knowledge toward understanding how to enrich electromethanogenic communities and operate bioelectrochemical systems for stable and reproducible performance. Copyright © 2015 Elsevier Ltd. All rights reserved.

Environmental factors influencing the structural dynamics of soil microbial communities during assisted phytostabilization of acid-generating mine tailings: a mesocosm experiment.

PubMed

Valentín-Vargas, Alexis; Root, Robert A; Neilson, Julia W; Chorover, Jon; Maier, Raina M

2014-12-01

Compost-assisted phytostabilization has recently emerged as a robust alternative for reclamation of metalliferous mine tailings. Previous studies suggest that root-associated microbes may be important for facilitating plant establishment on the tailings, yet little is known about the long-term dynamics of microbial communities during reclamation. A mechanistic understanding of microbial community dynamics in tailings ecosystems undergoing remediation is critical because these dynamics profoundly influence both the biogeochemical weathering of tailings and the sustainability of a plant cover. Here we monitor the dynamics of soil microbial communities (i.e. bacteria, fungi, archaea) during a 12-month mesocosm study that included 4 treatments: 2 unplanted controls (unamended and compost-amended tailings) and 2 compost-amended seeded tailings treatments. Bacterial, fungal and archaeal communities responded distinctively to the revegetation process and concurrent changes in environmental conditions and pore water chemistry. Compost addition significantly increased microbial diversity and had an immediate and relatively long-lasting buffering-effect on pH, allowing plants to germinate and thrive during the early stages of the experiment. However, the compost buffering capacity diminished after six months and acidification took over as the major factor affecting plant survival and microbial community structure. Immediate changes in bacterial communities were observed following plant establishment, whereas fungal communities showed a delayed response that apparently correlated with the pH decline. Fluctuations in cobalt pore water concentrations, in particular, had a significant effect on the structure of all three microbial groups, which may be linked to the role of cobalt in metal detoxification pathways. The present study represents, to our knowledge, the first documentation of the dynamics of the three major microbial groups during revegetation of compost

Environmental Factors Influencing the Structural Dynamics of Soil Microbial Communities During Assisted Phytostabilization of Acid-Generating Mine Tailings: a Mesocosm Experiment

PubMed Central

Valentín-Vargas, Alexis; Root, Robert A.; Neilson, Julia W; Chorover, Jon; Maier, Raina M.

2014-01-01

Compost-assisted phytostabilization has recently emerged as a robust alternative for reclamation of metalliferous mine tailings. Previous studies suggest that root-associated microbes may be important for facilitating plant establishment on the tailings, yet little is known about the long-term dynamics of microbial communities during reclamation. A mechanistic understanding of microbial community dynamics in tailings ecosystems undergoing remediation is critical because these dynamics profoundly influence both the biogeochemical weathering of tailings and the sustainability of a plant cover. Here we monitor the dynamics of soil microbial communities (i.e. bacteria, fungi, archaea) during a 12-month mesocosm study that included 4 treatments: 2 unplanted controls (unamended and compost-amended tailings) and 2 compost-amended seeded tailings treatments. Bacterial, fungal and archaeal communities responded distinctively to the revegetation process and concurrent changes in environmental conditions and pore water chemistry. Compost addition significantly increased microbial diversity and had an immediate and relatively long-lasting buffering-effect on pH, allowing plants to germinate and thrive during the early stages of the experiment. However, the compost buffering capacity diminished after six months and acidification took over as the major factor affecting plant survival and microbial community structure. Immediate changes in bacterial communities were observed following plant establishment, whereas fungal communities showed a delayed response that apparently correlated with the pH decline. Fluctuations in cobalt pore water concentrations, in particular, had a significant effect on the structure of all three microbial groups, which may be linked to the role of cobalt in metal detoxification pathways. The present study represents, to our knowledge, the first documentation of the dynamics of the three major microbial groups during revegetation of compost

Structural stability, microbial biomass and community composition of sediments affected by the hydric dynamics of an urban stormwater infiltration basin. Dynamics of physical and microbial characteristics of stormwater sediment.

PubMed

Badin, Anne Laure; Monier, Armelle; Volatier, Laurence; Geremia, Roberto A; Delolme, Cécile; Bedell, Jean-Philippe

2011-05-01

The sedimentary layer deposited at the surface of stormwater infiltration basins is highly organic and multicontaminated. It undergoes considerable moisture content fluctuations due to the drying and inundation cycles (called hydric dynamics) of these basins. Little is known about the microflora of the sediments and its dynamics; hence, the purpose of this study is to describe the physicochemical and biological characteristics of the sediments at different hydric statuses of the infiltration basin. Sediments were sampled at five time points following rain events and dry periods. They were characterized by physical (aggregation), chemical (nutrients and heavy metals), and biological (total, bacterial and fungal biomasses, and genotypic fingerprints of total bacterial and fungal communities) parameters. Data were processed using statistical analyses which indicated that heavy metal (1,841 μg/g dry weight (DW)) and organic matter (11%) remained stable through time. By contrast, aggregation, nutrient content (NH₄⁺, 53-717 μg/g DW), pH (6.9-7.4), and biological parameters were shown to vary with sediment water content and sediment biomass, and were higher consecutive to stormwater flows into the basin (up to 7 mg C/g DW) than during dry periods (0.6 mg C/g DW). Coinertia analysis revealed that the structure of the bacterial communities is driven by the hydric dynamics of the infiltration basin, although no such trend was found for fungal communities. Hydric dynamics more than rain events appear to be more relevant for explaining variations of aggregation, microbial biomass, and shift in the microbial community composition. We concluded that the hydric dynamics of stormwater infiltration basins greatly affects the structural stability of the sedimentary layer, the biomass of the microbial community living in it and its dynamics. The decrease in aggregation consecutive to rewetting probably enhances access to organic matter (OM), explaining the consecutive release

[Spatial and temporal dynamics of the weed community in the Zoysia matrella lawn].

PubMed

Liu, Jia-Qi; Li, You-Han; Zeng, Ying; Xie, Xin-Ming

2014-02-01

The heterogeneity of species composition is one of the main attributes in weed community dynamics. Based on species frequency and power law, this paper studied the variations of weed community species composition and spatial heterogeneity in a Zoysia matrella lawn in Guangzhou at different time. The results showed that there were 43 weed species belonging to 19 families in the Z. matrella lawn from 2007 to 2009, in which Gramineae, Compositae, Cyperaceae and Rubiaceae had a comparative advantage. Perennial weeds accounted for the largest proportion of weeds and increased gradually in the three years. Weed communities distributed in higher heterogeneity than in a random model. Dominant weeds varied with season and displayed regularity in the order of 'dicotyledon-monocotyledon-dicotyledon weeds' and 'perennial-annual-perennial weeds'. The spatial heterogeneity of weed community in Z. matrella lawn was higher in summer than in winter. The diversity and evenness of weed community were higher in summer and autumn than in winter and spring. The number of weed species with high heterogeneity in summer was higher than in the other seasons. The spatial heterogeneity and diversity of weed community had no significant change in the three years, while the evenness of weed community had the tendency to decline gradually.

Microbial community structure and dynamics during anaerobic digestion of various agricultural waste materials.

PubMed

Ziganshin, Ayrat M; Liebetrau, Jan; Pröter, Jürgen; Kleinsteuber, Sabine

2013-06-01

The influence of the feedstock type on the microbial communities involved in anaerobic digestion was investigated in laboratory-scale biogas reactors fed with different agricultural waste materials. Community composition and dynamics over 2 months of reactors' operation were investigated by amplicon sequencing and profiling terminal restriction fragment length polymorphisms of 16S rRNA genes. Major bacterial taxa belonged to the Clostridia and Bacteroidetes, whereas the archaeal community was dominated by methanogenic archaea of the orders Methanomicrobiales and Methanosarcinales. Correlation analysis revealed that the community composition was mainly influenced by the feedstock type with the exception of a temperature shift from 38 to 55 °C which caused the most pronounced community shifts. Bacterial communities involved in the anaerobic digestion of conventional substrates such as maize silage combined with cattle manure were relatively stable and similar to each other. In contrast, special waste materials such as chicken manure or Jatropha press cake were digested by very distinct and less diverse communities, indicating partial ammonia inhibition or the influence of other inhibiting factors. Anaerobic digestion of chicken manure relied on syntrophic acetate oxidation as the dominant acetate-consuming process due to the inhibition of aceticlastic methanogenesis. Jatropha as substrate led to the enrichment of fiber-degrading specialists belonging to the genera Actinomyces and Fibrobacter.

Immigrant community integration in world cities

PubMed Central

Lamanna, Fabio; Lenormand, Maxime; Salas-Olmedo, María Henar; Romanillos, Gustavo; Gonçalves, Bruno

2018-01-01

As a consequence of the accelerated globalization process, today major cities all over the world are characterized by an increasing multiculturalism. The integration of immigrant communities may be affected by social polarization and spatial segregation. How are these dynamics evolving over time? To what extent the different policies launched to tackle these problems are working? These are critical questions traditionally addressed by studies based on surveys and census data. Such sources are safe to avoid spurious biases, but the data collection becomes an intensive and rather expensive work. Here, we conduct a comprehensive study on immigrant integration in 53 world cities by introducing an innovative approach: an analysis of the spatio-temporal communication patterns of immigrant and local communities based on language detection in Twitter and on novel metrics of spatial integration. We quantify the Power of Integration of cities –their capacity to spatially integrate diverse cultures– and characterize the relations between different cultures when acting as hosts or immigrants. PMID:29538383

Extreme climatic events change the dynamics and invasibility of semi-arid annual plant communities.

PubMed

Jiménez, Milagros A; Jaksic, Fabian M; Armesto, Juan J; Gaxiola, Aurora; Meserve, Peter L; Kelt, Douglas A; Gutiérrez, Julio R

2011-12-01

Extreme climatic events represent disturbances that change the availability of resources. We studied their effects on annual plant assemblages in a semi-arid ecosystem in north-central Chile. We analysed 130 years of precipitation data using generalised extreme-value distribution to determine extreme events, and multivariate techniques to analyse 20 years of plant cover data of 34 native and 11 exotic species. Extreme drought resets the dynamics of the system and renders it susceptible to invasion. On the other hand, by favouring native annuals, moderately wet events change species composition and allow the community to be resilient to extreme drought. The probability of extreme drought has doubled over the last 50 years. Therefore, investigations on the interaction of climate change and biological invasions are relevant to determine the potential for future effects on the dynamics of semi-arid annual plant communities. 2011 Blackwell Publishing Ltd/CNRS.

Delineating ecological regions in marine systems: Integrating physical structure and community composition to inform spatial management in the eastern Bering Sea

NASA Astrophysics Data System (ADS)

Baker, Matthew R.; Hollowed, Anne B.

2014-11-01

Characterizing spatial structure and delineating meaningful spatial boundaries have useful applications to understanding regional dynamics in marine systems, and are integral to ecosystem approaches to fisheries management. Physical structure and drivers combine with biological responses and interactions to organize marine systems in unique ways at multiple scales. We apply multivariate statistical methods to define spatially coherent ecological units or ecoregions in the eastern Bering Sea. We also illustrate a practical approach to integrate data on species distribution, habitat structure and physical forcing mechanisms to distinguish areas with distinct biogeography as one means to define management units in large marine ecosystems. We use random forests to quantify the relative importance of habitat and environmental variables to the distribution of individual species, and to quantify shifts in multispecies assemblages or community composition along environmental gradients. Threshold shifts in community composition are used to identify regions with distinct physical and biological attributes, and to evaluate the relative importance of predictor variables to determining regional boundaries. Depth, bottom temperature and frontal boundaries were dominant factors delineating distinct biological communities in this system, with a latitudinal divide at approximately 60°N. Our results indicate that distinct climatic periods will shift habitat gradients and that dynamic physical variables such as temperature and stratification are important to understanding temporal stability of ecoregion boundaries. We note distinct distribution patterns among functional guilds and also evidence for resource partitioning among individual species within each guild. By integrating physical and biological data to determine spatial patterns in community composition, we partition ecosystems along ecologically significant gradients. This may provide a basis for defining spatial management

Relative Importance of Biotic and Abiotic Forces on the Composition and Dynamics of a Soft-Sediment Intertidal Community

PubMed Central

Barbeau, Myriam A.

2016-01-01

Top-down, bottom-up, middle-out and abiotic factors are usually viewed as main forces structuring biological communities, although assessment of their relative importance, in a single study, is rarely done. We quantified, using multivariate methods, associations between abiotic and biotic (top-down, bottom-up and middle-out) variables and infaunal population/community variation on intertidal mudflats in the Bay of Fundy, Canada, over two years. Our analysis indicated that spatial structural factors like site and plot accounted for most of the community and population variation. Although we observed a significant relationship between the community/populations and the biotic and abiotic variables, most were of minor importance relative to the structural factors. We suggest that community and population structure were relatively uncoupled from the structuring influences of biotic and abiotic factors in this system because of high concentrations of resources that sustain high densities of infauna and limit exploitative competition. Furthermore, we hypothesize that the infaunal community primarily reflects stochastic spatial events, namely a “first come, first served” process. PMID:26790098

Seasonal dynamics of bacterioplankton community in a large, shallow, highly dynamic freshwater lake.

PubMed

Kong, Zhaoyu; Kou, Wenbo; Ma, Yantian; Yu, Haotian; Ge, Gang; Wu, Lan

2018-05-23

The spatio-temporal shifts of bacterioplankton community can mirror their transition of functional traits in aquatic ecosystem. However, our understanding of spatio-temporal variation of bacterioplankton community composition structure (BCCs) within large, shallow and highly dynamic freshwater lake is still elusive. Here we examined the seasonal and spatial variability of BCCs in the Poyang Lake by 16S rRNA gene amplicon sequencing to explore how hydrological changes affect the BCCs. Principal coordinate analysis showed that the BCCs varied significantly among four sampling seasons, but not spatially. The seasonal changes of BCCs were mainly attributed to the differences between autumn and spring/winter. Higher alpha diversity indices were observed in autumn. Redundancy analysis indicated that the BCCs co-variated with water level, pH, temperature, total phosphorus, ammoniacal nitrogen, electrical conductivity, total nitrogen, and turbidity. Among them, water level was the key determinant separating autumn BCCs from the BCCs in other seasons. A significant lower relative abundance of Burkholderiales (betI and betVII) and a higher relative abundance of Actinomycetales (acI, acTH1 and acTH2) were found in autumn than in other seasons. Overall, our results suggest that water level changes associated with pH, temperature and nutrient status shaped the seasonal patterns of BCCs in the Poyang Lake.

Climate change in our backyards: the reshuffling of North America's winter bird communities.

PubMed

Princé, Karine; Zuckerberg, Benjamin

2015-02-01

Much of the recent changes in North American climate have occurred during the winter months, and as result, overwintering birds represent important sentinels of anthropogenic climate change. While there is mounting evidence that bird populations are responding to a warming climate (e.g., poleward shifts) questions remain as to whether these species-specific responses are resulting in community-wide changes. Here, we test the hypothesis that a changing winter climate should favor the formation of winter bird communities dominated by warm-adapted species. To do this, we quantified changes in community composition using a functional index--the Community Temperature Index (CTI)--which measures the balance between low- and high-temperature dwelling species in a community. Using data from Project FeederWatch, an international citizen science program, we quantified spatiotemporal changes in winter bird communities (n = 38 bird species) across eastern North America and tested the influence of changes in winter minimum temperature over a 22-year period. We implemented a jackknife analysis to identify those species most influential in driving changes at the community level and the population dynamics (e.g., extinction or colonization) responsible for these community changes. Since 1990, we found that the winter bird community structure has changed with communities increasingly composed of warm-adapted species. This reshuffling of winter bird communities was strongest in southerly latitudes and driven primarily by local increases in abundance and regional patterns of colonization by southerly birds. CTI tracked patterns of changing winter temperature at different temporal scales ranging from 1 to 35 years. We conclude that a shifting winter climate has provided an opportunity for smaller, southerly distributed species to colonize new regions and promote the formation of unique winter bird assemblages throughout eastern North America. © 2014 John Wiley & Sons Ltd.

Temporal Dynamics of the Microbial Community Composition with a Focus on Toxic Cyanobacteria and Toxin Presence during Harmful Algal Blooms in Two South German Lakes

PubMed Central

Scherer, Pia I.; Millard, Andrew D.; Miller, Andreas; Schoen, Renate; Raeder, Uta; Geist, Juergen; Zwirglmaier, Katrin

2017-01-01

Bacterioplankton plays an essential role in aquatic ecosystems, and cyanobacteria are an influential part of the microbiome in many water bodies. In freshwaters used for recreational activities or drinking water, toxic cyanobacteria cause concerns due to the risk of intoxication with cyanotoxins, such as microcystins. In this study, we aimed to unmask relationships between toxicity, cyanobacterial community composition, and environmental factors. At the same time, we assessed the correlation of a genetic marker with microcystin concentration and aimed to identify the main microcystin producer. We used Illumina MiSeq sequencing to study the bacterioplankton in two recreational lakes in South Germany. We quantified a microcystin biosynthesis gene (mcyB) using qPCR and linked this information with microcystin concentration to assess toxicity. Microcystin biosynthesis gene (mcyE)-clone libraries were used to determine the origin of microcystin biosynthesis genes. Bloom toxicity did not alter the bacterial community composition, which was highly dynamic at the lowest taxonomic level for some phyla such as Cyanobacteria. At the OTU level, we found distinctly different degrees of temporal variation between major bacteria phyla. Cyanobacteria and Bacteroidetes showed drastic temporal changes in their community compositions, while the composition of Actinobacteria remained rather stable in both lakes. The bacterial community composition of Alpha- and Beta-proteobacteria remained stable over time in Lake Klostersee, but it showed temporal variations in Lake Bergknappweiher. The presence of potential microcystin degraders and potential algicidal bacteria amongst prevalent Bacteroidetes and Alphaproteobacteria implied a role of those co-occurring heterotrophic bacteria in cyanobacterial bloom dynamics. Comparison of both lakes studied revealed a large shared microbiome, which was shaped toward the lake specific community composition by environmental factors. Microcystin

Astute, Assertive, and Alpha-1: Quantifying Empowerment in a Rare Genetic Community

ERIC Educational Resources Information Center

Finn, Symma

2008-01-01

We investigated empowerment in the Alpha-1 Antitrypsin Deficiency (Alpha-1) community, a rare, genetic disease network in the United States. The research was motivated by nine years of observations in the community. After observing what seemed to be a heightened amount of activism among Alpha-1 community members, I had hypothesized that this…

POPULATION DYNAMICS OF AMBIENT AND ALTERED EARTHWORM COMMUNITIES IN ROW-CROP AGROECOSYSTEMS IN OHIO, USA

EPA Science Inventory

Although earthworms are known to influence agroecosystem processes, there are relatively few long-term studies addressing population dynamics under cropping systems in which earthworm populations were intentionally altered. We assessed earthworm communities from fall 1994 to spr...

Dynamics in cyanobacterial communities from a relatively stable environment in an urbanised area (ambient springs in Central Poland).

PubMed

Nowicka-Krawczyk, Paulina; Żelazna-Wieczorek, Joanna

2017-02-01

Ambient springs are often cited as an example of an ecosystem with stable environmental conditions. A static biotope fosters the development of constant communities with a stable qualitative and relatively stable quantitative structure. Two years of studying cyanobacteria in different microhabitats of the rheocrenic and limnocrenic ambient springs located in urban areas showed that there is a high degree of cyanobacterial diversity and spatial and seasonal dynamics in communities. Spatial heterogeneity in relation to the type of spring and the type of microhabitat is reflected not only by a change in the quantitative structure (the number of species and their biomass), but also by a change in the composition of species. Seasonal changes depended on the type of spring and the type of microhabitat, where weather conditions influenced the communities by different degrees. Cyanobacterial communities of limnocrenes were more diverse in terms of composition and biomass, but they revealed a low seasonal dynamic in contrast to the communities of rheocrenes. The classification of springs based on their environmental conditions revealed that some springs were similar. The resemblance stemmed from the origin of human impact, which was reflected to a high degree in changes in the natural hydrochemical conditions of the springs. For the purpose of understanding which environmental factors had the greatest influence on cyanobacterial communities, a BIO-ENV procedure was performed. The procedure revealed that of most importance was a group of ions not related to the nature of the spring environment - NH 4 + , NO 2 - , NO 3 - , and PO 4 3- . The presence of these ions in groundwater was a result of direct and indirect human activity in the area of aquifers. The dynamics in communities in the studied springs were accelerated by human impact and weather conditions. Copyright © 2016 Elsevier B.V. All rights reserved.

Recent advances quantifying the large wood dynamics in river basins: New methods and remaining challenges

NASA Astrophysics Data System (ADS)

Ruiz-Villanueva, Virginia; Piégay, Hervé; Gurnell, Angela A.; Marston, Richard A.; Stoffel, Markus

2016-09-01

Large wood is an important physical component of woodland rivers and significantly influences river morphology. It is also a key component of stream ecosystems. However, large wood is also a source of risk for human activities as it may damage infrastructure, block river channels, and induce flooding. Therefore, the analysis and quantification of large wood and its mobility are crucial for understanding and managing wood in rivers. As the amount of large-wood-related studies by researchers, river managers, and stakeholders increases, documentation of commonly used and newly available techniques and their effectiveness has also become increasingly relevant as well. Important data and knowledge have been obtained from the application of very different approaches and have generated a significant body of valuable information representative of different environments. This review brings a comprehensive qualitative and quantitative summary of recent advances regarding the different processes involved in large wood dynamics in fluvial systems including wood budgeting and wood mechanics. First, some key definitions and concepts are introduced. Second, advances in quantifying large wood dynamics are reviewed; in particular, how measurements and modeling can be combined to integrate our understanding of how large wood moves through and is retained within river systems. Throughout, we present a quantitative and integrated meta-analysis compiled from different studies and geographical regions. Finally, we conclude by highlighting areas of particular research importance and their likely future trajectories, and we consider a particularly underresearched area so as to stress the future challenges for large wood research.

Atlantic Salmon (Salmo salar L.) Gastrointestinal Microbial Community Dynamics in Relation to Digesta Properties and Diet.

PubMed

Zarkasi, Kamarul Zaman; Taylor, Richard S; Abell, Guy C J; Tamplin, Mark L; Glencross, Brett D; Bowman, John P

2016-04-01

To better understand salmon GI tract microbial community dynamics in relation to diet, a feeding trial was performed utilising diets with different proportions of fish meal, protein, lipid and energy levels. Salmon gut dysfunction has been associated with the occurrence of casts, or an empty hind gut. A categorical scoring system describing expressed digesta consistency was evaluated in relation to GI tract community structure. Faster growing fish generally had lower faecal scores while the diet cohorts showed minor differences in faecal score though the overall lowest scores were observed with a low protein, low energy diet. The GI tract bacterial communities were highly dynamic over time with the low protein, low energy diet associated with the most divergent community structure. This included transiently increased abundance of anaerobic (Bacteroidia and Clostridia) during January and February, and facultatively anaerobic (lactic acid bacteria) taxa from February onwards. The digesta had enriched populations of these groups in relation to faecal cast samples. The majority of samples (60-86 %) across all diet cohorts were eventually dominated by the genus Aliivibrio. The results suggest that an interaction between time of sampling and diet is most strongly related to community structure. Digesta categorization revealed microbes involved with metabolism of diet components change progressively over time and could be a useful system to assess feeding responses.

Experiments in clustered neuronal networks: A paradigm for complex modular dynamics

NASA Astrophysics Data System (ADS)

Teller, Sara; Soriano, Jordi

2016-06-01

Uncovering the interplay activity-connectivity is one of the major challenges in neuroscience. To deepen in the understanding of how a neuronal circuit shapes network dynamics, neuronal cultures have emerged as remarkable systems given their accessibility and easy manipulation. An attractive configuration of these in vitro systems consists in an ensemble of interconnected clusters of neurons. Using calcium fluorescence imaging to monitor spontaneous activity in these clustered neuronal networks, we were able to draw functional maps and reveal their topological features. We also observed that these networks exhibit a hierarchical modular dynamics, in which clusters fire in small groups that shape characteristic communities in the network. The structure and stability of these communities is sensitive to chemical or physical action, and therefore their analysis may serve as a proxy for network health. Indeed, the combination of all these approaches is helping to develop models to quantify damage upon network degradation, with promising applications for the study of neurological disorders in vitro.

Markov Dynamics as a Zooming Lens for Multiscale Community Detection: Non Clique-Like Communities and the Field-of-View Limit

PubMed Central

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

Trait-mediated assembly processes predict successional changes in community diversity of tropical forests.

PubMed

Lasky, Jesse R; Uriarte, María; Boukili, Vanessa K; Chazdon, Robin L

2014-04-15

Interspecific differences in relative fitness can cause local dominance by a single species. However, stabilizing interspecific niche differences can promote local diversity. Understanding these mechanisms requires that we simultaneously quantify their effects on demography and link these effects to community dynamics. Successional forests are ideal systems for testing assembly theory because they exhibit rapid community assembly. Here, we leverage functional trait and long-term demographic data to build spatially explicit models of successional community dynamics of lowland rainforests in Costa Rica. First, we ask what the effects and relative importance of four trait-mediated community assembly processes are on tree survival, a major component of fitness. We model trait correlations with relative fitness differences that are both density-independent and -dependent in addition to trait correlations with stabilizing niche differences. Second, we ask how the relative importance of these trait-mediated processes relates to successional changes in functional diversity. Tree dynamics were more strongly influenced by trait-related interspecific variation in average survival than trait-related responses to neighbors, with wood specific gravity (WSG) positively correlated with greater survival. Our findings also suggest that competition was mediated by stabilizing niche differences associated with specific leaf area (SLA) and leaf dry matter content (LDMC). These drivers of individual-level survival were reflected in successional shifts to higher SLA and LDMC diversity but lower WSG diversity. Our study makes significant advances to identifying the links between individual tree performance, species functional traits, and mechanisms of tropical forest succession.

Quantifying the Influence of Dynamics Across Scales on Regional Climate Uncertainty in Western North America

NASA Astrophysics Data System (ADS)

Goldenson, Naomi L.

Uncertainties in climate projections at the regional scale are inevitably larger than those for global mean quantities. Here, focusing on western North American regional climate, several approaches are taken to quantifying uncertainties starting with the output of global climate model projections. Internal variance is found to be an important component of the projection uncertainty up and down the west coast. To quantify internal variance and other projection uncertainties in existing climate models, we evaluate different ensemble configurations. Using a statistical framework to simultaneously account for multiple sources of uncertainty, we find internal variability can be quantified consistently using a large ensemble or an ensemble of opportunity that includes small ensembles from multiple models and climate scenarios. The latter offers the advantage of also producing estimates of uncertainty due to model differences. We conclude that climate projection uncertainties are best assessed using small single-model ensembles from as many model-scenario pairings as computationally feasible. We then conduct a small single-model ensemble of simulations using the Model for Prediction Across Scales with physics from the Community Atmosphere Model Version 5 (MPAS-CAM5) and prescribed historical sea surface temperatures. In the global variable resolution domain, the finest resolution (at 30 km) is in our region of interest over western North America and upwind over the northeast Pacific. In the finer-scale region, extreme precipitation from atmospheric rivers (ARs) is connected to tendencies in seasonal snowpack in mountains of the Northwest United States and California. In most of the Cascade Mountains, winters with more AR days are associated with less snowpack, in contrast to the northern Rockies and California's Sierra Nevadas. In snowpack observations and reanalysis of the atmospheric circulation, we find similar relationships between frequency of AR events and winter

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice.

PubMed

Fernandez, Laura M J; Lecci, Sandro; Cardis, Romain; Vantomme, Gil; Béard, Elidie; Lüthi, Anita

2017-08-02

Three vigilance states dominate mammalian life: wakefulness, non-rapid eye movement (non-REM) sleep, and REM sleep. As more neural correlates of behavior are identified in freely moving animals, this three-fold subdivision becomes too simplistic. During wakefulness, ensembles of global and local cortical activities, together with peripheral parameters such as pupillary diameter and sympathovagal balance, define various degrees of arousal. It remains unclear the extent to which sleep also forms a continuum of brain states-within which the degree of resilience to sensory stimuli and arousability, and perhaps other sleep functions, vary gradually-and how peripheral physiological states co-vary. Research advancing the methods to monitor multiple parameters during sleep, as well as attributing to constellations of these functional attributes, is central to refining our understanding of sleep as a multifunctional process during which many beneficial effects must be executed. Identifying novel parameters characterizing sleep states will open opportunities for novel diagnostic avenues in sleep disorders. We present a procedure to describe dynamic variations of mouse non-REM sleep states via the combined monitoring and analysis of electroencephalogram (EEG)/electrocorticogram (ECoG), electromyogram (EMG), and electrocardiogram (ECG) signals using standard polysomnographic recording techniques. Using this approach, we found that mouse non-REM sleep is organized into cycles of coordinated neural and cardiac oscillations that generate successive 25-s intervals of high and low fragility to external stimuli. Therefore, central and autonomic nervous systems are coordinated to form behaviorally distinct sleep states during consolidated non-REM sleep. We present surgical manipulations for polysomnographic (i.e., EEG/EMG combined with ECG) monitoring to track these cycles in the freely sleeping mouse, the analysis to quantify their dynamics, and the acoustic stimulation protocols to

The dynamics of community and NGO partnership: primary health care experiences in rural Mali.

PubMed

Solomon, Yodit; Ballif-Spanvill, Bonnie; Ward, Carol; Fuhriman, Addie; Widdision-Jones, Kacey

2008-12-01

Utilizing ethnographic research methods, this case study examines the experiences of an NGO-sponsored health care program in rural Mali. The findings indicate that while, in principle, the organization operates from an alternative development base, it has been unable to decentralize the decision-making process and facilitate community dialogue and participation. Numerous problems resulted, including superficial forms of local participation, lack of community ownership, non-remuneration of health workers and midwives, inadequate training, and ultimately, limited program gains. The analyses highlight the complexity and dynamic nature of health program implementation in a developing context, and suggest several factors important to project success. These include drawing on diverse local perspectives, promoting broad-based participation, and providing culturally appropriate ways to include all community members, particularly women.

Community Identity and User Engagement in a Multi-Community Landscape.

PubMed

Zhang, Justine; Hamilton, William L; Danescu-Niculescu-Mizil, Cristian; Jurafsky, Dan; Leskovec, Jure

2017-05-01

A community's identity defines and shapes its internal dynamics. Our current understanding of this interplay is mostly limited to glimpses gathered from isolated studies of individual communities. In this work we provide a systematic exploration of the nature of this relation across a wide variety of online communities. To this end we introduce a quantitative, language-based typology reflecting two key aspects of a community's identity: how distinctive , and how temporally dynamic it is. By mapping almost 300 Reddit communities into the landscape induced by this typology, we reveal regularities in how patterns of user engagement vary with the characteristics of a community. Our results suggest that the way new and existing users engage with a community depends strongly and systematically on the nature of the collective identity it fosters, in ways that are highly consequential to community maintainers. For example, communities with distinctive and highly dynamic identities are more likely to retain their users. However, such niche communities also exhibit much larger acculturation gaps between existing users and newcomers, which potentially hinder the integration of the latter. More generally, our methodology reveals differences in how various social phenomena manifest across communities, and shows that structuring the multi-community landscape can lead to a better understanding of the systematic nature of this diversity.

Dynamic systems and the role of evaluation: The case of the Green Communities project.

PubMed

Anzoise, Valentina; Sardo, Stefania

2016-02-01

The crucial role evaluation can play in the co-development of project design and its implementation will be addressed through the analysis of a case study, the Green Communities (GC) project, funded by the Italian Ministry of Environment within the EU Interregional Operational Program (2007-2013) "Renewable Energy and Energy Efficiency". The project's broader goals included an attempt to trigger a change in Italian local development strategies, especially for mountain and inland areas, which would be tailored to the real needs of communities, and based on a sustainable exploitation and management of the territorial assets. The goal was not achieved, and this paper addresses the issues of how GC could have been more effective in fostering a vision of change, and which design adaptations and evaluation procedures would have allowed the project to better cope with the unexpected consequences and resistances it encountered. The conclusions drawn are that projects should be conceived, designed and carried out as dynamic systems, inclusive of a dynamic and engaged evaluation enabling the generation of feedbacks loops, iteratively interpreting the narratives and dynamics unfolding within the project, and actively monitoring the potential of various relationships among project participants for generating positive social change. Copyright © 2015 Elsevier Ltd. All rights reserved.

Use of real-time qPCR to quantify members of the unculturable heterotrophic bacterial community in a deep sea marine sponge, Vetulina sp.

PubMed

Cassler, M; Peterson, C L; Ledger, A; Pomponi, S A; Wright, A E; Winegar, R; McCarthy, P J; Lopez, J V

2008-04-01

In this report, real-time quantitative PCR (TaqMan qPCR) of the small subunit (SSU) 16S-like rRNA molecule, a universal phylogenetic marker, was used to quantify the relative abundance of individual bacterial members of a diverse, yet mostly unculturable, microbial community from a marine sponge. Molecular phylogenetic analyses of bacterial communities derived from Caribbean Lithistid sponges have shown a wide diversity of microbes that included at least six major subdivisions; however, very little overlap was observed between the culturable and unculturable microbial communities. Based on sequence data of three culture-independent Lithistid-derived representative bacteria, we designed probe/primer sets for TaqMan qPCR to quantitatively characterize selected microbial residents in a Lithistid sponge, Vetulina, metagenome. TaqMan assays included specificity testing, DNA limit of detection analysis, and quantification of specific microbial rRNA sequences such as Nitrospira-like microbes and Actinobacteria up to 172 million copies per microgram per Lithistid sponge metagenome. By contrast, qPCR amplification with probes designed for common previously cultured sponge-associated bacteria in the genera Rheinheimera and Marinomonas and a representative of the CFB group resulted in only minimal detection of the Rheiheimera in total DNA extracted from the sponge. These data verify that a large portion of the microbial community within Lithistid sponges may consist of currently unculturable microorganisms.

Dynamics of bloggers’ communities: Bipartite networks from empirical data and agent-based modeling

NASA Astrophysics Data System (ADS)

Mitrović, Marija; Tadić, Bosiljka

2012-11-01

We present an analysis of the empirical data and the agent-based modeling of the emotional behavior of users on the Web portals where the user interaction is mediated by posted comments, like Blogs and Diggs. We consider the dataset of discussion-driven popular Diggs, in which all comments are screened by machine-learning emotion detection in the text, to determine positive and negative valence (attractiveness and aversiveness) of each comment. By mapping the data onto a suitable bipartite network, we perform an analysis of the network topology and the related time-series of the emotional comments. The agent-based model is then introduced to simulate the dynamics and to capture the emergence of the emotional behaviors and communities. The agents are linked to posts on a bipartite network, whose structure evolves through their actions on the posts. The emotional states (arousal and valence) of each agent fluctuate in time, subject to the current contents of the posts to which the agent is exposed. By an agent’s action on a post its current emotions are transferred to the post. The model rules and the key parameters are inferred from the considered empirical data to ensure their realistic values and mutual consistency. The model assumes that the emotional arousal over posts drives the agent’s action. The simulations are preformed for the case of constant flux of agents and the results are analyzed in full analogy with the empirical data. The main conclusions are that the emotion-driven dynamics leads to long-range temporal correlations and emergent networks with community structure, that are comparable with the ones in the empirical system of popular posts. In view of pure emotion-driven agents actions, this type of comparisons provide a quantitative measure for the role of emotions in the dynamics on real blogs. Furthermore, the model reveals the underlying mechanisms which relate the post popularity with the emotion dynamics and the prevalence of negative

Biological soil crusts across disturbance–recovery scenarios: effect of grazing regime on community dynamics.

PubMed

Concostrina-Zubiri, L; Huber-Sannwald, E; Martínez, I; Flores Flores, J L; Reyes-Agüero, J A; Escude, A; Belnap, J

Grazing represents one of the most common disturbances in drylands worldwide, affecting both ecosystem structure and functioning. Despite the efforts to understand the nature and magnitude of grazing effects on ecosystem components and processes, contrasting results continue to arise. This is particularly remarkable for the biological soil crust (BSC) communities (i.e., cyanobacteria, lichens, and bryophytes), which play an important role in soil dynamics. Here we evaluated simultaneously the effect of grazing impact on BSC communities (resistance) and recovery after livestock exclusion (resilience) in a semiarid grassland of Central Mexico. In particular, we examined BSC species distribution, species richness, taxonomical group cover (i.e., cyanobacteria, lichen, bryophyte), and composition along a disturbance gradient with different grazing regimes (low, medium, high impact) and along a recovery gradient with differently aged livestock exclosures (short-, medium-, long-term exclusion). Differences in grazing impact and time of recovery from grazing both resulted in slight changes in species richness; however, there were pronounced shifts in species composition and group cover. We found we could distinguish four highly diverse and dynamic BSC species groups: (1) species with high resistance and resilience to grazing, (2) species with high resistance but low resilience, (3) species with low resistance but high resilience, and (4) species with low resistance and resilience. While disturbance resulted in a novel diversity configuration, which may profoundly affect ecosystem functioning, we observed that 10 years of disturbance removal did not lead to the ecosystem structure found after 27 years of recovery. These findings are an important contribution to our understanding of BCS dynamics from a species and community perspective placed in a land use change context.

Biological soil crusts across disturbance-recovery scenarios: effect of grazing regime on community dynamics

USGS Publications Warehouse

Concostrina-Zubiri, L.; Huber-Sannwald, E.; Martínez, I.; Flores Flores, J. L.; Reyes-Agüero, J. A.; Escudero, A.; Belnap, Jayne

2014-01-01

Grazing represents one of the most common disturbances in drylands worldwide, affecting both ecosystem structure and functioning. Despite the efforts to understand the nature and magnitude of grazing effects on ecosystem components and processes, contrasting results continue to arise. This is particularly remarkable for the biological soil crust (BSC) communities (i.e., cyanobacteria, lichens, and bryophytes), which play an important role in soil dynamics. Here we evaluated simultaneously the effect of grazing impact on BSC communities (resistance) and recovery after livestock exclusion (resilience) in a semiarid grassland of Central Mexico. In particular, we examined BSC species distribution, species richness, taxonomical group cover (i.e., cyanobacteria, lichen, bryophyte), and composition along a disturbance gradient with different grazing regimes (low, medium, high impact) and along a recovery gradient with differently aged livestock exclosures (short-, medium-, long-term exclusion). Differences in grazing impact and time of recovery from grazing both resulted in slight changes in species richness; however, there were pronounced shifts in species composition and group cover. We found we could distinguish four highly diverse and dynamic BSC species groups: (1) species with high resistance and resilience to grazing, (2) species with high resistance but low resilience, (3) species with low resistance but high resilience, and (4) species with low resistance and resilience. While disturbance resulted in a novel diversity configuration, which may profoundly affect ecosystem functioning, we observed that 10 years of disturbance removal did not lead to the ecosystem structure found after 27 years of recovery. These findings are an important contribution to our understanding of BCS dynamics from a species and community perspective placed in a land use change context.

Hillslope characterization: Identifying key controls on local-scale plant communities' distribution using remote sensing and subsurface data fusion.

NASA Astrophysics Data System (ADS)

Falco, N.; Wainwright, H. M.; Dafflon, B.; Leger, E.; Peterson, J.; Steltzer, H.; Wilmer, C.; Williams, K. H.; Hubbard, S. S.

2017-12-01

Mountainous watershed systems are characterized by extreme heterogeneity in hydrological and pedological properties that influence biotic activities, plant communities and their dynamics. To gain predictive understanding of how ecosystem and watershed system evolve under climate change, it is critical to capture such heterogeneity and to quantify the effect of key environmental variables such as topography, and soil properties. In this study, we exploit advanced geophysical and remote sensing techniques - coupled with machine learning - to better characterize and quantify the interactions between plant communities' distribution and subsurface properties. First, we have developed a remote sensing data fusion framework based on the random forest (RF) classification algorithm to estimate the spatial distribution of plant communities. The framework allows the integration of both plant spectral and structural information, which are derived from multispectral satellite images and airborne LiDAR data. We then use the RF method to evaluate the estimated plant community map, exploiting the subsurface properties (such as bedrock depth, soil moisture and other properties) and geomorphological parameters (such as slope, curvature) as predictors. Datasets include high-resolution geophysical data (electrical resistivity tomography) and LiDAR digital elevation maps. We demonstrate our approach on a mountain hillslope and meadow within the East River watershed in Colorado, which is considered to be a representative headwater catchment in the Upper Colorado Basin. The obtained results show the existence of co-evolution between above and below-ground processes; in particular, dominant shrub communities in wet and flat areas. We show that successful integration of remote sensing data with geophysical measurements allows identifying and quantifying the key environmental controls on plant communities' distribution, and provides insights into their potential changes in the future

Examining the patterns and dynamics of species abundance distributions in succession of forest communities by model selection.

PubMed

Yin, Zuo-Yun; Zeng, Lu; Luo, Shao-Ming; Chen, Ping; He, Xiao; Guo, Wei; Li, Bailian

2018-01-01

There are a few common species and many rare species in a biological community or a multi-species collection in given space and time. This hollow distribution curve is called species abundance distribution (SAD). Few studies have examined the patterns and dynamics of SADs during the succession of forest communities by model selection. This study explored whether the communities in different successional stages followed different SAD models and whether there existed a best SAD model to reveal their intrinsic quantitative features of structure and dynamics in succession. The abundance (the number of individuals) of each vascular plant was surveyed by quadrat sampling method from the tree, shrub and herb layers in two typical communities (i.e., the evergreen needle- and broad-leaved mixed forest and the monsoon evergreen broad-leaved forest) in southern subtropical Dinghushan Biosphere Reserve, South China. The sites of two forest communities in different successional stages are both 1 ha in area. We collected seven widely representative SAD models with obviously different function forms and transformed them into the same octave (log2) scale. These models are simultaneously confronted with eight datasets from four layers of two communities, and their goodness-of-fits to the data were evaluated by the chi-squared test, the adjusted coefficient of determination and the information criteria. The results indicated that: (1) the logCauchy model followed all the datasets and was the best among seven models; (2) the fitness of each model to the data was not directly related to the successional stage of forest community; (3) according to the SAD curves predicted by the best model (i.e., the logCauchy), the proportion of rare species decreased but that of common ones increased in the upper layers with succession, while the reverse was true in the lower layers; and (4) the difference of the SADs increased between the upper and the lower layers with succession. We concluded that

Examining the patterns and dynamics of species abundance distributions in succession of forest communities by model selection

PubMed Central

Luo, Shao-Ming; Chen, Ping; He, Xiao; Guo, Wei; Li, Bailian

2018-01-01

There are a few common species and many rare species in a biological community or a multi-species collection in given space and time. This hollow distribution curve is called species abundance distribution (SAD). Few studies have examined the patterns and dynamics of SADs during the succession of forest communities by model selection. This study explored whether the communities in different successional stages followed different SAD models and whether there existed a best SAD model to reveal their intrinsic quantitative features of structure and dynamics in succession. The abundance (the number of individuals) of each vascular plant was surveyed by quadrat sampling method from the tree, shrub and herb layers in two typical communities (i.e., the evergreen needle- and broad-leaved mixed forest and the monsoon evergreen broad-leaved forest) in southern subtropical Dinghushan Biosphere Reserve, South China. The sites of two forest communities in different successional stages are both 1 ha in area. We collected seven widely representative SAD models with obviously different function forms and transformed them into the same octave (log2) scale. These models are simultaneously confronted with eight datasets from four layers of two communities, and their goodness-of-fits to the data were evaluated by the chi-squared test, the adjusted coefficient of determination and the information criteria. The results indicated that: (1) the logCauchy model followed all the datasets and was the best among seven models; (2) the fitness of each model to the data was not directly related to the successional stage of forest community; (3) according to the SAD curves predicted by the best model (i.e., the logCauchy), the proportion of rare species decreased but that of common ones increased in the upper layers with succession, while the reverse was true in the lower layers; and (4) the difference of the SADs increased between the upper and the lower layers with succession. We concluded that

Effective time closures: quantifying the conservation benefits of input control for the Pacific chub mackerel fishery.

PubMed

Ichinokawa, Momoko; Okamura, Hiroshi; Watanabe, Chikako; Kawabata, Atsushi; Oozeki, Yoshioki

2015-09-01

Restricting human access to a specific wildlife species, community, or ecosystem, i.e., input control, is one of the most popular tools to control human impacts for natural resource management and wildlife conservation. However, quantitative evaluations of input control are generally difficult, because it is unclear how much human impacts can actually be reduced by the control. We present a model framework to quantify the effectiveness of input control using day closures to reduce actual fishing impact by considering the observed fishery dynamics. The model framework was applied to the management of the Pacific stock of the chub mackerel (Scomber japonicus) fishery, in which fishing was suspended for one day following any day when the total mackerel catch exceeded a threshold level. We evaluated the management measure according to the following steps: (1) we fitted the daily observed catch and fishing effort data to a generalized linear model (GLM) or generalized autoregressive state-space model (GASSM), (2) we conducted population dynamics simulations based on annual catches randomly generated from the parameters estimated in the first step, (3) we quantified the effectiveness of day closures by comparing the results of two simulation scenarios with and without day closures, and (4) we conducted additional simulations based on different sets of explanatory variables and statistical models (sensitivity analysis). In the first step, we found that the GASSM explained the observed data far better than the simple GLM. The model parameterized with the estimates from the GASSM demonstrated that the day closures implemented from 2004 to 2009 would have decreased exploitation fractions by ~10% every year and increased the 2009 stock biomass by 37-46% (median), relative to the values without day closures. The sensitivity analysis revealed that the effectiveness of day closures was particularly influenced by autoregressive processes in the fishery data and by positive

Polar ecosystem dynamics: recovery of communities from organic enrichment in McMurdo Sound, Antarctica.

PubMed

Kim, Stacy; Hammerstom, Kamille K; Conlan, Kathleen E; Thurber, Andrew R

2010-12-01

Community structure and diversity are influenced by patterns of disturbance and input of food. In Antarctica, the marine ecosystem undergoes highly seasonal changes in availability of light and in primary production. Near research stations, organic input from human activities can disturb the regular productivity regime with a consistent input of sewage. McMurdo Sound has both high-productivity and low-productivity habitats, thereby providing an ideal test bed for community recovery dynamics under polar conditions. We used experimental manipulations of the subtidal communities to test the hypotheses that (1) benthic communities respond differently to disturbance from organic enrichment versus burial and (2) community response also varies in areas with different natural patterns of food supply. Both in low- and high-food habitats, the strongest community response was to organic enrichment and resulted in dominance of typical organic-enrichment specialists. In habitats with highly seasonal productivity, community response was predictable and recovery was rapid. In habitats with low productivity, community variability was high and caging treatments suggested that inconsistencies were due to patchy impacts by scavengers. In areas normally subject to regular organic enrichment, either from primary production or from further up the food web (defecation by marine mammals), recovery of benthic communities takes only years even in a polar system. However, a low-productivity regime is as common in near shore habitats around the continent; under these conditions, recovery of benthic communities from disturbance is likely to be much slower and follow a variable ecological trajectory.

Inferring Characteristics of Sensorimotor Behavior by Quantifying Dynamics of Animal Locomotion

NASA Astrophysics Data System (ADS)

Leung, KaWai

Locomotion is one of the most well-studied topics in animal behavioral studies. Many fundamental and clinical research make use of the locomotion of an animal model to explore various aspects in sensorimotor behavior. In the past, most of these studies focused on population average of a specific trait due to limitation of data collection and processing power. With recent advance in computer vision and statistical modeling techniques, it is now possible to track and analyze large amounts of behavioral data. In this thesis, I present two projects that aim to infer the characteristics of sensorimotor behavior by quantifying the dynamics of locomotion of nematode Caenorhabditis elegans and fruit fly Drosophila melanogaster, shedding light on statistical dependence between sensing and behavior. In the first project, I investigate the possibility of inferring noxious sensory information from the behavior of Caenorhabditis elegans. I develop a statistical model to infer the heat stimulus level perceived by individual animals from their stereotyped escape responses after stimulation by an IR laser. The model allows quantification of analgesic-like effects of chemical agents or genetic mutations in the worm. At the same time, the method is able to differentiate perturbations of locomotion behavior that are beyond affecting the sensory system. With this model I propose experimental designs that allows statistically significant identification of analgesic-like effects. In the second project, I investigate the relationship of energy budget and stability of locomotion in determining the walking speed distribution of Drosophila melanogaster during aging. The locomotion stability at different age groups is estimated from video recordings using Floquet theory. I calculate the power consumption of different locomotion speed using a biomechanics model. In conclusion, the power consumption, not stability, predicts the locomotion speed distribution at different ages.

Autumn leaf subsidies influence spring dynamics of freshwater plankton communities.

PubMed

Fey, Samuel B; Mertens, Andrew N; Cottingham, Kathryn L

2015-07-01

While ecologists primarily focus on the immediate impact of ecological subsidies, understanding the importance of ecological subsidies requires quantifying the long-term temporal dynamics of subsidies on recipient ecosystems. Deciduous leaf litter transferred from terrestrial to aquatic ecosystems exerts both immediate and lasting effects on stream food webs. Recently, deciduous leaf additions have also been shown to be important subsidies for planktonic food webs in ponds during autumn; however, the inter-seasonal effects of autumn leaf subsidies on planktonic food webs have not been studied. We hypothesized that autumn leaf drop will affect the spring dynamics of freshwater pond food webs by altering the availability of resources, water transparency, and the metabolic state of ponds. We created leaf-added and no-leaf-added field mesocosms in autumn 2012, allowed mesocosms to ice-over for the winter, and began sampling the physical, chemical, and biological properties of mesocosms immediately following ice-off in spring 2013. At ice-off, leaf additions reduced dissolved oxygen, elevated total phosphorus concentrations and dissolved materials, and did not alter temperature or total nitrogen. These initial abiotic effects contributed to higher bacterial densities and lower chlorophyll concentrations, but by the end of spring, the abiotic environment, chlorophyll and bacterial densities converged. By contrast, zooplankton densities diverged between treatments during the spring, with leaf additions stimulating copepods but inhibiting cladocerans. We hypothesized that these differences between zooplankton orders resulted from resource shifts following leaf additions. These results suggest that leaf subsidies can alter both the short- and long-term dynamics of planktonic food webs, and highlight the importance of fully understanding how ecological subsidies are integrated into recipient food webs.

Seasonal species interactions minimize the impact of species turnover on the likelihood of community persistence.

PubMed

Saavedra, Serguei; Rohr, Rudolf P; Fortuna, Miguel A; Selva, Nuria; Bascompte, Jordi

2016-04-01

Many of the observed species interactions embedded in ecological communities are not permanent, but are characterized by temporal changes that are observed along with abiotic and biotic variations. While work has been done describing and quantifying these changes, little is known about their consequences for species coexistence. Here, we investigate the extent to which changes of species composition impact the likelihood of persistence of the predator-prey community in the highly seasonal Białowieza Primeval Forest (northeast Poland), and the extent to which seasonal changes of species interactions (predator diet) modulate the expected impact. This likelihood is estimated extending recent developments on the study of structural stability in ecological communities. We find that the observed species turnover strongly varies the likelihood of community persistence between summer and winter. Importantly, we demonstrate that the observed seasonal interaction changes minimize the variation in the likelihood of persistence associated with species turnover across the year. We find that these community dynamics can be explained as the coupling of individual species to their environment by minimizing both the variation in persistence conditions and the interaction changes between seasons. Our results provide a homeostatic explanation for seasonal species interactions and suggest that monitoring the association of interactions changes with the level of variation in community dynamics can provide a good indicator of the response of species to environmental pressures.

Quantifying the ice-albedo feedback through decoupling

NASA Astrophysics Data System (ADS)

Kravitz, B.; Rasch, P. J.

2017-12-01

The ice-albedo feedback involves numerous individual components, whereby warming induces sea ice melt, inducing reduced surface albedo, inducing increased surface shortwave absorption, causing further warming. Here we attempt to quantify the sea ice albedo feedback using an analogue of the "partial radiative perturbation" method, but where the governing mechanisms are directly decoupled in a climate model. As an example, we can isolate the insulating effects of sea ice on surface energy and moisture fluxes by allowing sea ice thickness to change but fixing Arctic surface albedo, or vice versa. Here we present results from such idealized simulations using the Community Earth System Model in which individual components are successively fixed, effectively decoupling the ice-albedo feedback loop. We isolate the different components of this feedback, including temperature change, sea ice extent/thickness, and air-sea exchange of heat and moisture. We explore the interactions between these different components, as well as the strengths of the total feedback in the decoupled feedback loop, to quantify contributions from individual pieces. We also quantify the non-additivity of the effects of the components as a means of investigating the dominant sources of nonlinearity in the ice-albedo feedback.

Preliminary evaluation of the effect of a dynamic preferential runway system upon community noise disturbance

NASA Technical Reports Server (NTRS)

Patterson, H. P.; Edmiston, R. P.; Connor, W. K.

1972-01-01

A dynamic preferential runway system (DPRS) was developed for John F. Kennedy International Airport for the purpose of controlling short term noise exposure in the neighboring communities. The DPRS is a computer-aided procedure for optimum selection of runways from the standpoint of noise and is based upon a community disturbance model which takes into account flyover levels, size of exposed populations, time of day and week, and persistence of overflights. A preliminary evaluation of the DPRS is presented on the basis of social survey data and telephone complaint records, for the trial period of August and September, 1971. Comparative use is made of data taken in a previous survey of the same community areas in 1969.

Quantifying Grassland-to-Woodland Transitions and the Implications for Carbon and Nitrogen Dynamics in the Southwest United States

NASA Technical Reports Server (NTRS)

Wessman, Carol A.; Archer, Steven R.; Asner, Gregory P.; Bateson, C. Ann

2004-01-01

Replacement of grasslands and savannas by shrublands and woodlands has been widely reported in tropical, temperate and high-latitude rangelands worldwide (Archer 1994). These changes in vegetation structure may reflect historical shifts in climate and land use; and are likely to influence biodiversity, productivity, above- and below ground carbon and nitrogen sequestration and biophysical aspects of land surface-atmosphere interactions. The goal of our proposed research is to investigate how changes in the relative abundance of herbaceous and woody vegetation affect carbon and nitrogen dynamics across heterogeneous savannas and shrub/woodlands. By linking actual land-cover composition (derived through spectral mixture analysis of AVIRIS, TM, and AVHRR imagery) with a process-based ecosystem model, we will generate explicit predictions of the C and N storage in plants and soils resulting from changes in vegetation structure. Our specific objectives will be to (1) continue development and test applications of spectral mixture analysis across grassland-to-woodland transitions; (2) quantify temporal changes in plant and soil C and N storage and turnover for remote sensing and process model parameterization and verification; and (3) couple landscape fraction maps to an ecosystem simulation model to observe biogeochemical dynamics under changing landscape structure and climatological forcings.

Consistent nutrient storage and supply mediated by diverse fish communities in coral reef ecosystems.

PubMed

Allgeier, Jacob E; Layman, Craig A; Mumby, Peter J; Rosemond, Amy D

2014-08-01

Corals thrive in low nutrient environments and the conservation of these globally imperiled ecosystems is largely dependent on mitigating the effects of anthropogenic nutrient enrichment. However, to better understand the implications of anthropogenic nutrients requires a heightened understanding of baseline nutrient dynamics within these ecosystems. Here, we provide a novel perspective on coral reef nutrient dynamics by examining the role of fish communities in the supply and storage of nitrogen (N) and phosphorus (P). We quantified fish-mediated nutrient storage and supply for 144 species and modeled these data onto 172 fish communities (71 729 individual fish), in four types of coral reefs, as well as seagrass and mangrove ecosystems, throughout the Northern Antilles. Fish communities supplied and stored large quantities of nutrients, with rates varying among ecosystem types. The size structure and diversity of the fish communities best predicted N and P supply and storage and N : P supply, suggesting that alterations to fish communities (e.g., overfishing) will have important implications for nutrient dynamics in these systems. The stoichiometric ratio (N : P) for storage in fish mass (~8 : 1) and supply (~20 : 1) was notably consistent across the four coral reef types (but not seagrass or mangrove ecosystems). Published nutrient enrichment studies on corals show that deviations from this N : P supply ratio may be associated with poor coral fitness, providing qualitative support for the hypothesis that corals and their symbionts may be adapted to specific ratios of nutrient supply. Consumer nutrient stoichiometry provides a baseline from which to better understand nutrient dynamics in coral reef and other coastal ecosystems, information that is greatly needed if we are to implement more effective measures to ensure the future health of the world's oceans. © 2014 John Wiley & Sons Ltd.

Quantifying hypoxia in human cancers using static PET imaging.

PubMed

Taylor, Edward; Yeung, Ivan; Keller, Harald; Wouters, Bradley G; Milosevic, Michael; Hedley, David W; Jaffray, David A

2016-11-21

Compared to FDG, the signal of 18 F-labelled hypoxia-sensitive tracers in tumours is low. This means that in addition to the presence of hypoxic cells, transport properties contribute significantly to the uptake signal in static PET images. This sensitivity to transport must be minimized in order for static PET to provide a reliable standard for hypoxia quantification. A dynamic compartmental model based on a reaction-diffusion formalism was developed to interpret tracer pharmacokinetics and applied to static images of FAZA in twenty patients with pancreatic cancer. We use our model to identify tumour properties-well-perfused without substantial necrosis or partitioning-for which static PET images can reliably quantify hypoxia. Normalizing the measured activity in a tumour voxel by the value in blood leads to a reduction in the sensitivity to variations in 'inter-corporal' transport properties-blood volume and clearance rate-as well as imaging study protocols. Normalization thus enhances the correlation between static PET images and the FAZA binding rate K 3 , a quantity which quantifies hypoxia in a biologically significant way. The ratio of FAZA uptake in spinal muscle and blood can vary substantially across patients due to long muscle equilibration times. Normalized static PET images of hypoxia-sensitive tracers can reliably quantify hypoxia for homogeneously well-perfused tumours with minimal tissue partitioning. The ideal normalizing reference tissue is blood, either drawn from the patient before PET scanning or imaged using PET. If blood is not available, uniform, homogeneously well-perfused muscle can be used. For tumours that are not homogeneously well-perfused or for which partitioning is significant, only an analysis of dynamic PET scans can reliably quantify hypoxia.

Quantifying hypoxia in human cancers using static PET imaging

NASA Astrophysics Data System (ADS)

Taylor, Edward; Yeung, Ivan; Keller, Harald; Wouters, Bradley G.; Milosevic, Michael; Hedley, David W.; Jaffray, David A.

2016-11-01

Compared to FDG, the signal of 18F-labelled hypoxia-sensitive tracers in tumours is low. This means that in addition to the presence of hypoxic cells, transport properties contribute significantly to the uptake signal in static PET images. This sensitivity to transport must be minimized in order for static PET to provide a reliable standard for hypoxia quantification. A dynamic compartmental model based on a reaction-diffusion formalism was developed to interpret tracer pharmacokinetics and applied to static images of FAZA in twenty patients with pancreatic cancer. We use our model to identify tumour properties—well-perfused without substantial necrosis or partitioning—for which static PET images can reliably quantify hypoxia. Normalizing the measured activity in a tumour voxel by the value in blood leads to a reduction in the sensitivity to variations in ‘inter-corporal’ transport properties—blood volume and clearance rate—as well as imaging study protocols. Normalization thus enhances the correlation between static PET images and the FAZA binding rate K 3, a quantity which quantifies hypoxia in a biologically significant way. The ratio of FAZA uptake in spinal muscle and blood can vary substantially across patients due to long muscle equilibration times. Normalized static PET images of hypoxia-sensitive tracers can reliably quantify hypoxia for homogeneously well-perfused tumours with minimal tissue partitioning. The ideal normalizing reference tissue is blood, either drawn from the patient before PET scanning or imaged using PET. If blood is not available, uniform, homogeneously well-perfused muscle can be used. For tumours that are not homogeneously well-perfused or for which partitioning is significant, only an analysis of dynamic PET scans can reliably quantify hypoxia.

Quantifying the Incoming Jet Past Heart Valve Prostheses Using Vortex Formation Dynamics

NASA Astrophysics Data System (ADS)

Pierrakos, Olga

2005-11-01

Heart valve (HV) replacement prostheses are associated with hemodynamic compromises compared to their native counterparts. Traditionally, HV performance and hemodynamics have been quantified using effective orifice size and pressure gradients. However, quality and direction of flow are also important aspects of HV function and relate to HV design, implantation technique, and orientation. The flow past any HV is governed by the generation of shear layers followed by the formation and shedding of organized flow structures in the form of vortex rings (VR). For the first time, vortex formation (VF) in the LV is quantified. Vortex energy measurements allow for calculation of the critical formation number (FN), which is the time at which the VR reaches its maximum strength. Inefficiencies in HV function result in critical FN decrease. This study uses the concept of FN to compare mitral HV prostheses in an in-vitro model (a silicone LV model housed in a piston-driven heart simulator) using Time-resolved Digital Particle Image Velocimetry. Two HVs were studied: a porcine HV and bileaflet MHV, which was tested in an anatomic and non-anatomic orientation. The results suggest that HV orientation and design affect the critical FN. We propose that the critical FN, which is contingent on the HV design, orientation, and physical flow characteristics, serve as a parameter to quantify the incoming jet and the efficiency of the HV.

Monitoring the dynamics of an invasive emergent macrophyte community using operational remote sensing data

USGS Publications Warehouse

Albright, Thomas P.; Ode, D.J.

2011-01-01

Potamogeton crispus L. (curly pondweed) is a cosmopolitan aquatic macrophyte considered invasive in North America and elsewhere. Its range is expanding and, on individual water bodies, its coverage can be dynamic both within and among years. In this study, we evaluate the use of free and low-cost satellite remote sensing data to monitor a problematic emergent macrophyte community dominated by P. crispus. Between 2000 and 2006, we acquired eight satellite images of 24,000-ha Lake Sharpe, South Dakota (USA). During one of the dates for which satellite imagery was acquired, we sampled the lake for P. crispus and other emergent macrophytes using GPS and photography for documentation. We used cluster analysis to assist in classification of the satellite imagery and independently validated results using the field data. Resulting estimates of emergent macrophyte coverage ranged from less than 20 ha in 2002 to 245 ha in 2004. Accuracy assessment indicated 82% of image pixels were correctly classified, with errors being primarily due to failure to identify emergent macrophytes. These results emphasize the dynamic nature of P. crispus-dominated macrophyte communities and show how they can be effectively monitored over large areas using low-cost remote sensing imagery. While results may vary in other systems depending on water quality and local flora, such an approach could be applied elsewhere and for a variety of macrophyte communities.

B-Vitamin Competition: Intracellular and Dissolved B-Vitamins Provide Insight into Marine Microbial Community Dynamics

NASA Astrophysics Data System (ADS)

Suffridge, C.; Gomez-Consarnau, L.; Qu, P.; Tenenbaum, N.; Fu, F.; Hutchins, D. A.; Sanudo-Wilhelmy, S. A.

2016-02-01

The availability of B-vitamins has the ability to directly affect the dynamics of the marine microbial community. Here we show, for the first time, the connection between dissolved and intracellular B-vitamins in a marine environmental community. Two incubation experiments were conducted at a long-term study site (SPOT) in the San Pedro Basin off the coast of Los Angeles, CA. Experiments were conducted in oligotrophic, preupwelling conditions. Due to the 2015 El Niño event, the seasonal upwelling at SPOT did not occur, creating unusually nutrient depleted conditions. Vitamins B1, B7, and B12 were added in addition to macronutrients at concentrations similar to typical SPOT upwelling conditions. Intracellular and dissolved B-vitamin analyses were conducted to determine shifts in cellular B-vitamin requirements as a function of growth rate. We observed a significant bacterioplankton and phytoplankton growth responses with the addition of B-vitamins in a manner that appears to match the enzymatic requirements for these compounds (e.g. B1>B7>B12). Intracellular B-vitamin analysis of T0 samples support this observation, as all four forms of B12 were not detectable within cells, yet multiple forms of B1 and B7 were detected at or near levels previously reported. Treatments with B12 and macronutrients were observed to have the greatest growth rates. This finding, in addition to the apparent lack of intracellular B12 in the initial community, appears to indicate that the initial microbial community was limited by B12. The addition of each vitamin caused a distinct shift in the blooming microbial community. Our results demonstrate that B-vitamins strongly influence not only the growth rate, but also the species composition and species succession of the microbial community as a whole. Large-scale changes to upwelling regimes are predicted in the future ocean; our results indicate that B-vitamins will have a substantial role in controlling microbial community dynamics under

Expansion of Phragmites australis alters methane dynamics and methanogen, methanotroph, and sulfate reducing bacteria communities in tidal marsh in Korea

NASA Astrophysics Data System (ADS)

Kim, J.; Lee, J.; Kim, H.; Gauhar, M.; Kang, H.

2016-12-01

Plant invasion is known to change substantially methane dynamics in tidal marshes. However, the exact mechanisms related to methane dynamics change due to plant invasion have not been fully understood. In Suncheon Bay, South Korea, Phragmites australis has invaded the habitat of native species, Suaeda japonica, and becomes dominant vegetation in this area. We measured methane fluxes, soil biogeochemistry, and microbial communities from both vegetation sites throughout a growing season and conducted a chronosequence analysis in order to illustrate the effect of plant invasion on methane dynamics and microbial communities. For analyzing microbial communities, we collected 1m intact soil cores and conducted functional gene-targeted real-time qPCR, T-RFLP, and PLFA. P. australis invasion significantly increased methane emission in a summer season, accompanied by greater dissolved organic carbon and soil water content. Methanogen, methanotroph, and sulfate reducing bacterial communities were gradually changed along with the invasion periods. In particular, abundances ratio of mcrA/pmoA and mcrA/dsrA had a positive correlation with methane emission, which indicates that P. australis invasion reduces methane oxidation by methanotroph, and competitive inhibition between methanogen and sulfate reducing bacteria. In conclusion, P. australis invasion on S. japonica significantly increased methane emission in tidal marsh by altering the microbial communities in a way that C decomposition would be dominated by methanogenesis.

Perspective: Defining and quantifying the role of dynamics in enzyme catalysis

PubMed Central

Warshel, Arieh; Bora, Ram Prasad

2016-01-01

Enzymes control chemical reactions that are key to life processes, and allow them to take place on the time scale needed for synchronization between the relevant reaction cycles. In addition to general interest in their biological roles, these proteins present a fundamental scientific puzzle, since the origin of their tremendous catalytic power is still unclear. While many different hypotheses have been put forward to rationalize this, one of the proposals that has become particularly popular in recent years is the idea that dynamical effects contribute to catalysis. Here, we present a critical review of the dynamical idea, considering all reasonable definitions of what does and does not qualify as a dynamical effect. We demonstrate that no dynamical effect (according to these definitions) has ever been experimentally shown to contribute to catalysis. Furthermore, the existence of non-negligible dynamical contributions to catalysis is not supported by consistent theoretical studies. Our review is aimed, in part, at readers with a background in chemical physics and biophysics, and illustrates that despite a substantial body of experimental effort, there has not yet been any study that consistently established a connection between an enzyme’s conformational dynamics and a significant increase in the catalytic contribution of the chemical step. We also make the point that the dynamical proposal is not a semantic issue but a well-defined scientific hypothesis with well-defined conclusions. PMID:27179464

Perspective: Defining and quantifying the role of dynamics in enzyme catalysis.

PubMed

Warshel, Arieh; Bora, Ram Prasad

2016-05-14

Enzymes control chemical reactions that are key to life processes, and allow them to take place on the time scale needed for synchronization between the relevant reaction cycles. In addition to general interest in their biological roles, these proteins present a fundamental scientific puzzle, since the origin of their tremendous catalytic power is still unclear. While many different hypotheses have been put forward to rationalize this, one of the proposals that has become particularly popular in recent years is the idea that dynamical effects contribute to catalysis. Here, we present a critical review of the dynamical idea, considering all reasonable definitions of what does and does not qualify as a dynamical effect. We demonstrate that no dynamical effect (according to these definitions) has ever been experimentally shown to contribute to catalysis. Furthermore, the existence of non-negligible dynamical contributions to catalysis is not supported by consistent theoretical studies. Our review is aimed, in part, at readers with a background in chemical physics and biophysics, and illustrates that despite a substantial body of experimental effort, there has not yet been any study that consistently established a connection between an enzyme's conformational dynamics and a significant increase in the catalytic contribution of the chemical step. We also make the point that the dynamical proposal is not a semantic issue but a well-defined scientific hypothesis with well-defined conclusions.

Persistence, Seasonal Dynamics and Pathogenic Potential of Vibrio Communities from Pacific Oyster Hemolymph

PubMed Central

Wendling, Carolin C.; Batista, Frederico M.; Wegner, K. Mathias

2014-01-01

Bacteria of the genus Vibrio occur at a continuum from free-living to symbiotic life forms, including opportunists and pathogens, that can contribute to severe diseases, for instance summer mortality events of Pacific oysters Crassostrea gigas. While most studies focused on Vibrio isolated from moribund oysters during mortality outbreaks, investigations of the Vibrio community in healthy oysters are rare. Therefore, we characterized the persistence, diversity, seasonal dynamics, and pathogenicity of the Vibrio community isolated from healthy Pacific oysters. In a reciprocal transplant experiment we repeatedly sampled hemolymph from adult Pacific oysters to differentiate population from site-specific effects during six months of in situ incubation in the field. We characterized virulence phenotypes and genomic diversity based on multilocus sequence typing in a total of 70 Vibrio strains. Based on controlled infection experiments we could show that strains with the ability to colonize healthy adult oysters can also have the potential to induce high mortality rates on larvae. Diversity and abundance of Vibrio varied significantly over time with highest values during and after spawning season. Vibrio communities from transplanted and stationary oysters converged over time, indicating that communities were not population specific, but rather assemble from the surrounding environment forming communities, some of which can persist over longer periods. PMID:24728233

Synchrony, compensatory dynamics, and the functional trait basis of phenological diversity in a tropical dry forest tree community: effects of rainfall seasonality

NASA Astrophysics Data System (ADS)

Lasky, Jesse R.; Uriarte, María; Muscarella, Robert

2016-11-01

Interspecific variation in phenology is a key axis of functional diversity, potentially mediating how communities respond to climate change. The diverse drivers of phenology act across multiple temporal scales. For example, abiotic constraints favor synchronous reproduction (positive covariance among species), while biotic interactions can favor synchrony or compensatory dynamics (negative covariance). We used wavelet analyses to examine phenology of community flower and seed production for 45 tree species across multiple temporal scales in a tropical dry forest in Puerto Rico with marked rainfall seasonality. We asked three questions: (1) do species exhibit synchronous or compensatory temporal dynamics in reproduction, (2) do interspecific differences in phenology reflect variable responses to rainfall, and (3) is interspecific variation in phenology and response to a major drought associated with functional traits that mediate responses to moisture? Community-level flowering was synchronized at seasonal scales (˜5-6 mo) and at short scales (˜1 mo, following rainfall). However, seed rain exhibited significant compensatory dynamics at intraseasonal scales (˜3 mo), suggesting interspecific variation in temporal niches. Species with large leaves (associated with sensitivity to water deficit) peaked in reproduction synchronously with the peak of seasonal rainfall (˜5 mo scale). By contrast, species with high wood specific gravity (associated with drought resistance) tended to flower in drier periods. Flowering of tall species and those with large leaves was most tightly linked to intraseasonal (˜2 mo scale) rainfall fluctuations. Although the 2015 drought dramatically reduced community-wide reproduction, functional traits were not associated with the magnitude of species-specific declines. Our results suggest opposing drivers of synchronous versus compensatory dynamics at different temporal scales. Phenology associations with functional traits indicated that

Market dynamics immediately before and after financial shocks: Quantifying the Omori, productivity, and Bath laws

NASA Astrophysics Data System (ADS)

Petersen, Alexander M.; Wang, Fengzhong; Havlin, Shlomo; Stanley, H. Eugene

2010-09-01

We study the cascading dynamics immediately before and immediately after 219 market shocks. We define the time of a market shock Tc to be the time for which the market volatility V(Tc) has a peak that exceeds a predetermined threshold. The cascade of high volatility “aftershocks” triggered by the “main shock” is quantitatively similar to earthquakes and solar flares, which have been described by three empirical laws—the Omori law, the productivity law, and the Bath law. We analyze the most traded 531 stocks in U.S. markets during the 2 yr period of 2001-2002 at the 1 min time resolution. We find quantitative relations between the main shock magnitude M≡log10V(Tc) and the parameters quantifying the decay of volatility aftershocks as well as the volatility preshocks. We also find that stocks with larger trading activity react more strongly and more quickly to market shocks than stocks with smaller trading activity. Our findings characterize the typical volatility response conditional on M , both at the market and the individual stock scale. We argue that there is potential utility in these three statistical quantitative relations with applications in option pricing and volatility trading.

Quantifying time-of-flight-resolved optical field dynamics in turbid media with interferometric near-infrared spectroscopy (iNIRS) (Conference Presentation)

NASA Astrophysics Data System (ADS)

Borycki, Dawid; Kholiqov, Oybek; Zhou, Wenjun; Srinivasan, Vivek J.

2017-03-01

Sensing and imaging methods based on the dynamic scattering of coherent light, including laser speckle, laser Doppler, and diffuse correlation spectroscopy quantify scatterer motion using light intensity (speckle) fluctuations. The underlying optical field autocorrelation (OFA), rather than being measured directly, is typically inferred from the intensity autocorrelation (IA) through the Siegert relationship, by assuming that the scattered field obeys Gaussian statistics. In this work, we demonstrate interferometric near-infrared spectroscopy (iNIRS) for measurement of time-of-flight (TOF) resolved field and intensity autocorrelations in fluid tissue phantoms and in vivo. In phantoms, we find a breakdown of the Siegert relationship for short times-of-flight due to a contribution from static paths whose optical field does not decorrelate over experimental time scales, and demonstrate that eliminating such paths by polarization gating restores the validity of the Siegert relationship. Inspired by these results, we developed a method, called correlation gating, for separating the OFA into static and dynamic components. Correlation gating enables more precise quantification of tissue dynamics. To prove this, we show that iNIRS and correlation gating can be applied to measure cerebral hemodynamics of the nude mouse in vivo using dynamically scattered (ergodic) paths and not static (non-ergodic) paths, which may not be impacted by blood. More generally, correlation gating, in conjunction with TOF resolution, enables more precise separation of diffuse and non-diffusive contributions to OFA than is possible with TOF resolution alone. Finally, we show that direct measurements of OFA are statistically more efficient than indirect measurements based on IA.

Dynamics of arbuscular mycorrhizal fungal community structure and functioning along a nitrogen enrichment gradient in an alpine meadow ecosystem.

PubMed

Jiang, Shengjing; Liu, Yongjun; Luo, Jiajia; Qin, Mingsen; Johnson, Nancy Collins; Öpik, Maarja; Vasar, Martti; Chai, Yuxing; Zhou, Xiaolong; Mao, Lin; Du, Guozhen; An, Lizhe; Feng, Huyuan

2018-03-30

Nitrogen (N) availability is increasing dramatically in many ecosystems, but the influence of elevated N on the functioning of arbuscular mycorrhizal (AM) fungi in natural ecosystems is not well understood. We measured AM fungal community structure and mycorrhizal function simultaneously across an experimental N addition gradient in an alpine meadow that is limited by N but not by phosphorus (P). AM fungal communities at both whole-plant-community (mixed roots) and single-plant-species (Elymus nutans roots) scales were described using pyro-sequencing, and the mycorrhizal functioning was quantified using a mycorrhizal-suppression treatment in the field (whole-plant-community scale) and a glasshouse inoculation experiment (single-plant-species scale). Nitrogen enrichment progressively reduced AM fungal abundance, changed AM fungal community composition, and shifted mycorrhizal functioning towards parasitism at both whole-plant-community and E. nutans scales. N-induced shifts in AM fungal community composition were tightly linked to soil N availability and/or plant species richness, whereas the shifts in mycorrhizal function were associated with the communities of specific AM fungal lineages. The observed changes in both AM fungal community structure and functioning across an N enrichment gradient highlight that N enrichment of ecosystems that are not P-limited can induce parasitic mycorrhizal functioning and influence plant community structure and ecosystem sustainability. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

Children's interpretations of general quantifiers, specific quantifiers, and generics

PubMed Central

Gelman, Susan A.; Leslie, Sarah-Jane; Was, Alexandra M.; Koch, Christina M.

2014-01-01

Recently, several scholars have hypothesized that generics are a default mode of generalization, and thus that young children may at first treat quantifiers as if they were generic in meaning. To address this issue, the present experiment provides the first in-depth, controlled examination of the interpretation of generics compared to both general quantifiers ("all Xs", "some Xs") and specific quantifiers ("all of these Xs", "some of these Xs"). We provided children (3 and 5 years) and adults with explicit frequency information regarding properties of novel categories, to chart when "some", "all", and generics are deemed appropriate. The data reveal three main findings. First, even 3-year-olds distinguish generics from quantifiers. Second, when children make errors, they tend to be in the direction of treating quantifiers like generics. Third, children were more accurate when interpreting specific versus general quantifiers. We interpret these data as providing evidence for the position that generics are a default mode of generalization, especially when reasoning about kinds. PMID:25893205

Real-time PCR to quantify composition of arbuscular mycorrhizal fungal communities--marker design, verification, calibration and field validation.

PubMed

Thonar, C; Erb, A; Jansa, J

2012-03-01

Quantitative real-time PCR (qPCR) is slowly becoming established as a tool to quantify abundance of different arbuscular mycorrhizal fungal (AMF) taxa in roots and in soil. Here, we describe the development and field validation of qPCR markers (i.e. primers with associated hydrolysis probes), targeting taxon-specific motifs in the nuclear large ribosomal subunit RNA genes. Design of such markers is complicated by the multinuclear and multigenomic cellular organization of these fungi and the high DNA sequence diversity within the smallest biologically relevant units (i.e. single-spore isolates). These limitations are further compounded by inefficient biomass production of these fungi, resulting in limited availability of pure genomic DNA (gDNA) of well-defined isolates for cross-specificity testing of the markers. Here we demonstrate, using a number of AMF isolates, the possibility to establish stringent qPCR running conditions allowing quantification of phylogenetically disjunctive AMF taxa. Further, we show that these markers can more generally be used to quantify abundance (i.e. number of target gene copies or amount of gDNA) of what is usually considered the level of AMF species, regardless of the isolate identities. We also illustrate the range of variation within qPCR signal strength across different AMF taxa with respect to the detected number of gene copies per unit amount of gDNA. This information is paramount for interpretation of the qPCR analyses of field samples. Finally, the field validation of these markers confirmed their potential to assess composition of field AMF communities and monitor the changes owing to agricultural practices such as soil tillage. © 2011 Blackwell Publishing Ltd.

Quantifying evolutionary dynamics from variant-frequency time series

NASA Astrophysics Data System (ADS)

Khatri, Bhavin S.

2016-09-01

From Kimura’s neutral theory of protein evolution to Hubbell’s neutral theory of biodiversity, quantifying the relative importance of neutrality versus selection has long been a basic question in evolutionary biology and ecology. With deep sequencing technologies, this question is taking on a new form: given a time-series of the frequency of different variants in a population, what is the likelihood that the observation has arisen due to selection or neutrality? To tackle the 2-variant case, we exploit Fisher’s angular transformation, which despite being discovered by Ronald Fisher a century ago, has remained an intellectual curiosity. We show together with a heuristic approach it provides a simple solution for the transition probability density at short times, including drift, selection and mutation. Our results show under that under strong selection and sufficiently frequent sampling these evolutionary parameters can be accurately determined from simulation data and so they provide a theoretical basis for techniques to detect selection from variant or polymorphism frequency time-series.

Quantifying evolutionary dynamics from variant-frequency time series.

PubMed

Khatri, Bhavin S

2016-09-12

From Kimura's neutral theory of protein evolution to Hubbell's neutral theory of biodiversity, quantifying the relative importance of neutrality versus selection has long been a basic question in evolutionary biology and ecology. With deep sequencing technologies, this question is taking on a new form: given a time-series of the frequency of different variants in a population, what is the likelihood that the observation has arisen due to selection or neutrality? To tackle the 2-variant case, we exploit Fisher's angular transformation, which despite being discovered by Ronald Fisher a century ago, has remained an intellectual curiosity. We show together with a heuristic approach it provides a simple solution for the transition probability density at short times, including drift, selection and mutation. Our results show under that under strong selection and sufficiently frequent sampling these evolutionary parameters can be accurately determined from simulation data and so they provide a theoretical basis for techniques to detect selection from variant or polymorphism frequency time-series.

Genes, communities & invasive species: understanding the ecological and evolutionary dynamics of host-pathogen interactions.

PubMed

Burdon, J J; Thrall, P H; Ericson, L

2013-08-01

Reciprocal interactions between hosts and pathogens drive ecological, epidemiological and co-evolutionary trajectories, resulting in complex patterns of diversity at population, species and community levels. Recent results confirm the importance of negative frequency-dependent rather than 'arms-race' processes in the evolution of individual host-pathogen associations. At the community level, complex relationships between species abundance and diversity dampen or alter pathogen impacts. Invasive pathogens challenge these controls reflecting the earliest stages of evolutionary associations (akin to arms-race) where disease effects may be so great that they overwhelm the host's and community's ability to respond. Viewing these different stabilization/destabilization phases as a continuum provides a valuable perspective to assessment of the role of genetics and ecology in the dynamics of both natural and invasive host-pathogen associations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Dynamic Succession of Groundwater Sulfate-Reducing Communities during Prolonged Reduction of Uranium in a Contaminated Aquifer.

PubMed

Zhang, Ping; He, Zhili; Van Nostrand, Joy D; Qin, Yujia; Deng, Ye; Wu, Liyou; Tu, Qichao; Wang, Jianjun; Schadt, Christopher W; W Fields, Matthew; Hazen, Terry C; Arkin, Adam P; Stahl, David A; Zhou, Jizhong

2017-04-04

To further understand the diversity and dynamics of SRB in response to substrate amendment, we sequenced genes coding for the dissimilatory sulfite reductase (dsrA) in groundwater samples collected after an emulsified vegetable oil (EVO) amendment, which sustained U(VI)-reducing conditions for one year in a fast-flowing aquifer. EVO amendment significantly altered the composition of groundwater SRB communities. Sequences having no closely related-described species dominated (80%) the indigenous SRB communities in nonamended wells. After EVO amendment, Desulfococcus, Desulfobacterium, and Desulfovibrio, known for long-chain-fatty-acid, short-chain-fatty-acid and H 2 oxidation and U(VI) reduction, became dominant accounting for 7 ± 2%, 21 ± 8%, and 55 ± 8% of the SRB communities, respectively. Succession of these SRB at different bioactivity stages based on redox substrates/products (acetate, SO 4 -2 , U(VI), NO 3 - , Fe(II), and Mn(II)) was observed. Desulfovibrio and Desulfococcus dominated SRB communities at 4-31 days, whereas Desulfobacterium became dominant at 80-140 days. By the end of the experiment (day 269), the abundance of these SRB decreased but the overall diversity of groundwater SRB was still higher than non-EVO controls. Up to 62% of the SRB community changes could be explained by groundwater geochemical variables, including those redox substrates/products. A significant (P < 0.001) correlation was observed between groundwater U(VI) concentrations and Desulfovibrio abundance. Our results showed that the members of SRB and their dynamics were correlated significantly with slow EVO biodegradation, electron donor production and maintenance of U(VI)-reducing conditions in the aquifer.

Microbial community dynamics during fermentation of doenjang-meju, traditional Korean fermented soybean.

PubMed

Jung, Ji Young; Lee, Se Hee; Jeon, Che Ok

2014-08-18

Bacterial and fungal community dynamics, along with viable plate counts and water content, were investigated in the exterior and interior regions of doenjang-meju, traditional Korean fermented soybean, during its fermentation process. Measurement of viable cells showed that the meju molding equipment might be an important source of bacterial cells (mostly Bacillus) during doenjang-meju fermentation, whereas fungi might be mostly derived from the fermentation environment including incubation shelves, air, and rice straws. Community analysis using rRNA-targeted pyrosequencing revealed that Bacillus among bacteria and Mucor among fungi were predominant in both the exterior and interior regions of doenjang-meju during the early fermentation period. Bacteria such as Ignatzschineria, Myroides, Enterococcus, Corynebacterium, and Clostridium and fungi such as Geotrichum, Scopulariopsis, Monascus, Fusarium, and eventually Aspergillus were mainly detected as the fermentation progressed. Bacillus, an aerobic bacterial group, was predominant in the exterior regions during the entire fermentation period, while anaerobic, facultative anaerobic, and microaerobic bacteria including Enterococcus, Lactobacillus, Clostridium, Myroides, and Ignatzschineria were much more abundant in the interior regions. Principal component analysis (PCA) also indicated that the bacterial communities in the exterior and interior regions were clearly differentiated, suggesting that aeration might be an important factor in determining the bacterial communities during doenjang-meju fermentation. However, PCA showed that fungal communities were not separated in the exterior and interior regions and Pearson's correlation coefficients showed that the major fungal taxa had significantly positive (Mucor and Geotrichum) or negative (Aspergillus) correlations with the water content during doenjang-meju fermentation, indicating that water content might be a significant factor in determining the fungal

Relationships between and formation dynamics of the microbiota of consumers, producers, and the environment in an abalone aquatic system

PubMed Central

Zhao, Wang; Liu, Guang-Feng; Wang, Jiang-Yong

2017-01-01

An ecosystem is a community comprising living and nonliving components of the environment. Microbes are ubiquitous elements in each of these components. The dynamics of microbiota formation in an ecosystem is important to elucidate, because how the different components of a system exchange microbes, and how the microbes control ecological processes remain unresolved. In this study, an abalone, Haliotis diversicolor, seed-nursing pond was used as a model system. We first examined changes in bacterial communities during the seedling cultivation of this herbivorous juvenile aquatic invertebrate animal. Denaturing gradient gel electrophoresis (DGGE) and pyrosequencing were used to analyze bacterial community dynamics and spatio-temporal interactions of different system components: consumers (abalone), producers (algae or a substrate), and the environment (water). DGGE fingerprints revealed that the developmental stages of abalone influences bacterial communities of both the abalone and substrate. Although the communities in water fluctuated daily, they could be divided into two clusters that coincided with abalone stages, reflecting the transition from larva to juvenile at around day 21. Pyrosequencing showed that the microbiota in the abalone and substrate had more operational taxonomic units in common than that of either with water. The Bray-Curtis similarity index was used to quantify the formation dynamics of microbiota among the various components of the system. The bacterial communities in producers and consumers showed similar changes. These communities were unstable at the beginning and then slowly stabilized over time. The environmental bacterial community was more stable than the bacterial communities in consumers and producers, and may have been the basis for stability in the system. Our research provides insights into the dynamics of microbiota formation in various biotic elements of a system that will contribute to predictive systems modeling. PMID

Relationships between and formation dynamics of the microbiota of consumers, producers, and the environment in an abalone aquatic system.

PubMed

Jiang, Jing-Zhe; Zhao, Wang; Liu, Guang-Feng; Wang, Jiang-Yong

2017-01-01

An ecosystem is a community comprising living and nonliving components of the environment. Microbes are ubiquitous elements in each of these components. The dynamics of microbiota formation in an ecosystem is important to elucidate, because how the different components of a system exchange microbes, and how the microbes control ecological processes remain unresolved. In this study, an abalone, Haliotis diversicolor, seed-nursing pond was used as a model system. We first examined changes in bacterial communities during the seedling cultivation of this herbivorous juvenile aquatic invertebrate animal. Denaturing gradient gel electrophoresis (DGGE) and pyrosequencing were used to analyze bacterial community dynamics and spatio-temporal interactions of different system components: consumers (abalone), producers (algae or a substrate), and the environment (water). DGGE fingerprints revealed that the developmental stages of abalone influences bacterial communities of both the abalone and substrate. Although the communities in water fluctuated daily, they could be divided into two clusters that coincided with abalone stages, reflecting the transition from larva to juvenile at around day 21. Pyrosequencing showed that the microbiota in the abalone and substrate had more operational taxonomic units in common than that of either with water. The Bray-Curtis similarity index was used to quantify the formation dynamics of microbiota among the various components of the system. The bacterial communities in producers and consumers showed similar changes. These communities were unstable at the beginning and then slowly stabilized over time. The environmental bacterial community was more stable than the bacterial communities in consumers and producers, and may have been the basis for stability in the system. Our research provides insights into the dynamics of microbiota formation in various biotic elements of a system that will contribute to predictive systems modeling.

Quantifying Transmission of Clostridium difficile within and outside Healthcare Settings

PubMed Central

Olsen, Margaret A.; Dubberke, Erik R.; Galvani, Alison P.; Townsend, Jeffrey P.

2016-01-01

To quantify the effect of hospital and community-based transmission and control measures on Clostridium difficile infection (CDI), we constructed a transmission model within and between hospital, community, and long-term care-facility settings. By parameterizing the model from national databases and calibrating it to C. difficile prevalence and CDI incidence, we found that hospitalized patients with CDI transmit C. difficile at a rate 15 (95% CI 7.2–32) times that of asymptomatic patients. Long-term care facility residents transmit at a rate of 27% (95% CI 13%–51%) that of hospitalized patients, and persons in the community at a rate of 0.1% (95% CI 0.062%–0.2%) that of hospitalized patients. Despite lower transmission rates for asymptomatic carriers and community sources, these transmission routes have a substantial effect on hospital-onset CDI because of the larger reservoir of hospitalized carriers and persons in the community. Asymptomatic carriers and community sources should be accounted for when designing and evaluating control interventions. PMID:26982504

Advances in the Use of DNA Barcodes to Build a Community Phylogeny for Tropical Trees in a Puerto Rican Forest Dynamics Plot

Treesearch

W. John Kress; David L. Erickson; Nathan G. Swenson; Jill Thompson; Maria Uriarte; Jess K. Zimmerman; Jerome Chave

2010-01-01

BACKGROUND: Species number, functional traits, and phylogenetic history all contribute to characterizing the biological diversity in plant communities. The phylogenetic component of diversity has been particularly difficult to quantify in species-rich tropical tree assemblages. The compilation of previously published (and often incomplete) data on evolutionary...

SPRUCE S1 Bog Tree Basal Area and Understory Community Composition Assessed in the Southern and Northern Ends of the S1 Bog

DOE Data Explorer

Iversen, C. M. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A; Garrett, A. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A; Martin, A. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A; Turetsky, M. R. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A; Norby, R. J. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A; Childs, J. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A; Ontl, T. A. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A

2017-01-01

The composition and cover of woody and understory species, along with the timing of stem growth, were characterized near minirhizotron installations at the south and north ends of the S1 bog in order to understand the relationship between root dynamics and the surrounding plant communities. There are three data streams: (1) Woody species basal area -- the number, basal area, and distance from the center point of all trees within a 5-m radius of each minirhizotron pair, which were quantified in 2011, (2) Understory cover -- the understory vascular plant community composition and percent cover, which were surveyed in 1 m2 areas at four cardinal directions adjacent to each pair of minirhizotrons in June 2011, and (3) Stem growth -- the basal area increment (stem growth) of nearby trees, which was quantified using automated or manual dendrobands in 2011 and 2012, respectively.

Validation and Application of a PCR Primer Set to Quantify Fungal Communities in the Soil Environment by Real-Time Quantitative PCR

PubMed Central

Chemidlin Prévost-Bouré, Nicolas; Christen, Richard; Dequiedt, Samuel; Mougel, Christophe; Lelièvre, Mélanie; Jolivet, Claudy; Shahbazkia, Hamid Reza; Guillou, Laure; Arrouays, Dominique; Ranjard, Lionel

2011-01-01

Fungi constitute an important group in soil biological diversity and functioning. However, characterization and knowledge of fungal communities is hampered because few primer sets are available to quantify fungal abundance by real-time quantitative PCR (real-time Q-PCR). The aim in this study was to quantify fungal abundance in soils by incorporating, into a real-time Q-PCR using the SYBRGreen® method, a primer set already used to study the genetic structure of soil fungal communities. To satisfy the real-time Q-PCR requirements to enhance the accuracy and reproducibility of the detection technique, this study focused on the 18S rRNA gene conserved regions. These regions are little affected by length polymorphism and may provide sufficiently small targets, a crucial criterion for enhancing accuracy and reproducibility of the detection technique. An in silico analysis of 33 primer sets targeting the 18S rRNA gene was performed to select the primer set with the best potential for real-time Q-PCR: short amplicon length; good fungal specificity and coverage. The best consensus between specificity, coverage and amplicon length among the 33 sets tested was the primer set FR1 / FF390. This in silico analysis of the specificity of FR1 / FF390 also provided additional information to the previously published analysis on this primer set. The specificity of the primer set FR1 / FF390 for Fungi was validated in vitro by cloning - sequencing the amplicons obtained from a real time Q-PCR assay performed on five independent soil samples. This assay was also used to evaluate the sensitivity and reproducibility of the method. Finally, fungal abundance in samples from 24 soils with contrasting physico-chemical and environmental characteristics was examined and ranked to determine the importance of soil texture, organic carbon content, C∶N ratio and land use in determining fungal abundance in soils. PMID:21931659

Temporal dynamics of hot desert microbial communities reveal structural and functional responses to water input

PubMed Central

Armstrong, Alacia; Valverde, Angel; Ramond, Jean-Baptiste; Makhalanyane, Thulani P.; Jansson, Janet K.; Hopkins, David W.; Aspray, Thomas J.; Seely, Mary; Trindade, Marla I.; Cowan, Don A.

2016-01-01

The temporal dynamics of desert soil microbial communities are poorly understood. Given the implications for ecosystem functioning under a global change scenario, a better understanding of desert microbial community stability is crucial. Here, we sampled soils in the central Namib Desert on sixteen different occasions over a one-year period. Using Illumina-based amplicon sequencing of the 16S rRNA gene, we found that α-diversity (richness) was more variable at a given sampling date (spatial variability) than over the course of one year (temporal variability). Community composition remained essentially unchanged across the first 10 months, indicating that spatial sampling might be more important than temporal sampling when assessing β-diversity patterns in desert soils. However, a major shift in microbial community composition was found following a single precipitation event. This shift in composition was associated with a rapid increase in CO2 respiration and productivity, supporting the view that desert soil microbial communities respond rapidly to re-wetting and that this response may be the result of both taxon-specific selection and changes in the availability or accessibility of organic substrates. Recovery to quasi pre-disturbance community composition was achieved within one month after rainfall. PMID:27680878

Temporal dynamics of hot desert microbial communities reveal structural and functional responses to water input.

PubMed

Armstrong, Alacia; Valverde, Angel; Ramond, Jean-Baptiste; Makhalanyane, Thulani P; Jansson, Janet K; Hopkins, David W; Aspray, Thomas J; Seely, Mary; Trindade, Marla I; Cowan, Don A

2016-09-29

The temporal dynamics of desert soil microbial communities are poorly understood. Given the implications for ecosystem functioning under a global change scenario, a better understanding of desert microbial community stability is crucial. Here, we sampled soils in the central Namib Desert on sixteen different occasions over a one-year period. Using Illumina-based amplicon sequencing of the 16S rRNA gene, we found that α-diversity (richness) was more variable at a given sampling date (spatial variability) than over the course of one year (temporal variability). Community composition remained essentially unchanged across the first 10 months, indicating that spatial sampling might be more important than temporal sampling when assessing β-diversity patterns in desert soils. However, a major shift in microbial community composition was found following a single precipitation event. This shift in composition was associated with a rapid increase in CO 2 respiration and productivity, supporting the view that desert soil microbial communities respond rapidly to re-wetting and that this response may be the result of both taxon-specific selection and changes in the availability or accessibility of organic substrates. Recovery to quasi pre-disturbance community composition was achieved within one month after rainfall.

Habitat dynamics, marine reserve status, and the decline and recovery of coral reef fish communities.

PubMed

Williamson, David H; Ceccarelli, Daniela M; Evans, Richard D; Jones, Geoffrey P; Russ, Garry R

2014-02-01

Severe climatic disturbance events often have major impacts on coral reef communities, generating cycles of decline and recovery, and in some extreme cases, community-level phase shifts from coral-to algal-dominated states. Benthic habitat changes directly affect reef fish communities, with low coral cover usually associated with low fish diversity and abundance. No-take marine reserves (NTRs) are widely advocated for conserving biodiversity and enhancing the sustainability of exploited fish populations. Numerous studies have documented positive ecological and socio-economic benefits of NTRs; however, the ability of NTRs to ameliorate the effects of acute disturbances on coral reefs has seldom been investigated. Here, we test these factors by tracking the dynamics of benthic and fish communities, including the important fishery species, coral trout (Plectropomus spp.), over 8 years in both NTRs and fished areas in the Keppel Island group, Great Barrier Reef, Australia. Two major disturbances impacted the reefs during the monitoring period, a coral bleaching event in 2006 and a freshwater flood plume in 2011. Both disturbances generated significant declines in coral cover and habitat complexity, with subsequent declines in fish abundance and diversity, and pronounced shifts in fish assemblage structure. Coral trout density also declined in response to the loss of live coral, however, the approximately 2:1 density ratio between NTRs and fished zones was maintained over time. The only post-disturbance refuges for coral trout spawning stocks were within the NTRs that escaped the worst effects of the disturbances. Although NTRs had little discernible effect on the temporal dynamics of benthic or fish communities, it was evident that the post-disturbance refuges for coral trout spawning stocks within some NTRs may be critically important to regional-scale population persistence and recovery.

Habitat dynamics, marine reserve status, and the decline and recovery of coral reef fish communities

PubMed Central

Williamson, David H; Ceccarelli, Daniela M; Evans, Richard D; Jones, Geoffrey P; Russ, Garry R

2014-01-01

Severe climatic disturbance events often have major impacts on coral reef communities, generating cycles of decline and recovery, and in some extreme cases, community-level phase shifts from coral-to algal-dominated states. Benthic habitat changes directly affect reef fish communities, with low coral cover usually associated with low fish diversity and abundance. No-take marine reserves (NTRs) are widely advocated for conserving biodiversity and enhancing the sustainability of exploited fish populations. Numerous studies have documented positive ecological and socio-economic benefits of NTRs; however, the ability of NTRs to ameliorate the effects of acute disturbances on coral reefs has seldom been investigated. Here, we test these factors by tracking the dynamics of benthic and fish communities, including the important fishery species, coral trout (Plectropomus spp.), over 8 years in both NTRs and fished areas in the Keppel Island group, Great Barrier Reef, Australia. Two major disturbances impacted the reefs during the monitoring period, a coral bleaching event in 2006 and a freshwater flood plume in 2011. Both disturbances generated significant declines in coral cover and habitat complexity, with subsequent declines in fish abundance and diversity, and pronounced shifts in fish assemblage structure. Coral trout density also declined in response to the loss of live coral, however, the approximately 2:1 density ratio between NTRs and fished zones was maintained over time. The only post-disturbance refuges for coral trout spawning stocks were within the NTRs that escaped the worst effects of the disturbances. Although NTRs had little discernible effect on the temporal dynamics of benthic or fish communities, it was evident that the post-disturbance refuges for coral trout spawning stocks within some NTRs may be critically important to regional-scale population persistence and recovery. PMID:24634720

Dynamics of the microbial community during continuous methane fermentation in continuously stirred tank reactors.

PubMed

Tang, Yue-Qin; Shigematsu, Toru; Morimura, Shigeru; Kida, Kenji

2015-04-01

Methane fermentation is an attractive technology for the treatment of organic wastes and wastewaters. However, the process is difficult to control, and treatment rates and digestion efficiency require further optimization. Understanding the microbiology mechanisms of methane fermentation is of fundamental importance to improving this process. In this review, we summarize the dynamics of microbial communities in methane fermentation chemostats that are operated using completely stirred tank reactors (CSTRs). Each chemostat was supplied with one substrate as the sole carbon source. The substrates include acetate, propionate, butyrate, long-chain fatty acids, glycerol, protein, glucose, and starch. These carbon sources are general substrates and intermediates of methane fermentation. The factors that affect the structure of the microbial community are discussed. The carbon source, the final product, and the operation conditions appear to be the main factors that affect methane fermentation and determine the structure of the microbial community. Understanding the structure of the microbial community during methane fermentation will guide the design and operation of practical wastewater treatments. Copyright © 2014 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Microbial communities in methane seep sediments along US Atlantic Margin are structured by organic matter and seepage dynamics

NASA Astrophysics Data System (ADS)

Graw, M. F.; Pohlman, J.; Treude, T.; Ruppel, C. D.; Colwell, F. S.

2016-12-01

Methane seeps are dynamic environments on continental margins where subsurface methane reaches the ocean. Microbial communities play a critical role in carbon cycling within seep sediments via organic carbon degradation, methane production, and anaerobic oxidation of methane (AOM), which consumes 20-80% of methane in seep sediments. However, biogeochemical controls on microbial community structure at seeps on a margin-wide scale remain unclear. The passive US Atlantic Margin (USAM) has been identified as a region of active methane seepage. Passive margin seeps have traditionally been understudied relative to seeps on active margins. Passive margins exhibit large cross-margin variability in organic carbon deposition and are anticipated to have divergent seep dynamics from active margins. Thus, the USAM offers a unique opportunity to investigate controls on microbial communities in seep sediments. We undertook analysis of microbial communities inhabiting seep sediments at 6 biogeochemically distinct sites along the USAM. Microbiological samples were co-located with measurements of sediment geochemistry and AOM and sulfate reduction rates. Illumina sequencing of the 16S rRNA gene, using both universal (83 samples) and archaeal-specific (64 samples) primers, and the mcrA gene (18 samples) identified 44 bacterial phyla and 7 archaeal phyla. Seeps in canyons and on open slope, likely representing high and low organic content sediments, hosted distinct communities; the former was dominated by ammonia-oxidizing Marine Group I Thaumarchaeota and the latter by mixotrophic Hadesarchaeota. Seep stability also impacted microbial community structure, and in particular the establishment of an AOM community rather than a Bathyarchaeota-dominated community. These findings contribute to understanding how microbial communities are structured within methane seep sediments and pave the way for investigating broad differences in carbon cycling between seeps on passive and active margins.

Rare but active taxa contribute to community dynamics of benthic biofilms in glacier-fed streams.

PubMed

Wilhelm, Linda; Besemer, Katharina; Fasching, Christina; Urich, Tim; Singer, Gabriel A; Quince, Christopher; Battin, Tom J

2014-08-01

Glaciers harbour diverse microorganisms, which upon ice melt can be released downstream. In glacier-fed streams microorganisms can attach to stones or sediments to form benthic biofilms. We used 454-pyrosequencing to explore the bulk (16S rDNA) and putatively active (16S rRNA) microbial communities of stone and sediment biofilms across 26 glacier-fed streams. We found differences in community composition between bulk and active communities among streams and a stronger congruence between biofilm types. Relative abundances of rRNA and rDNA were positively correlated across different taxa and taxonomic levels, but at lower taxonomic levels, the higher abundance in either the active or the bulk communities became more apparent. Here, environmental variables played a minor role in structuring active communities. However, we found a large number of rare taxa with higher relative abundances in rRNA compared with rDNA. This suggests that rare taxa contribute disproportionately to microbial community dynamics in glacier-fed streams. Our findings propose that high community turnover, where taxa repeatedly enter and leave the 'seed bank', contributes to the maintenance of microbial biodiversity in harsh ecosystems with continuous environmental perturbations, such as glacier-fed streams. © 2014 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.

Bacterial community dynamics in a rumen fluid bioreactor during in-vitro cultivation.

PubMed

Zapletalová, Martina; Kašparovská, Jitka; Křížová, Ludmila; Kašparovský, Tomáš; Šerý, Omar; Lochman, Jan

2016-09-20

To study the various processes in the rumen the in vitro techniques are widely used to realize more controlled and reproducible conditions compared to in vivo experiments. Mostly, only the parameters like pH changes, volatile fatty acids content or metabolite production are monitored. In this study we examine the bacterial community dynamics of rumen fluid in course of ten day cultivation realize under standard conditions described in the literature. Whereas the pH values, total VFA content and A/P ratio in bioreactor were consistent with natural conditions in the rumen, the mean redox-potential values of -251 and -243mV were much more negative. For culture-independent assessment of bacterial community composition, the Illumina MiSeq results indicated that the community contained 292 bacterial genera. In course of ten days cultivation a significant changes in the microbial community were measured when Bacteroidetes to Firmicutes ratio changed from 3.2 to 1.2 and phyla Proteobacteria and Actinobacteria represented by genus Bifidobacterium and Olsenella significantly increased. The main responsible factor of these changes seems to be very low redox potential in bioreactor together with accumulation of simple carbohydrates in milieu as a result of limited excretion of fermented feed and absence of nutrient absorbing mechanisms. Copyright © 2016 Elsevier B.V. All rights reserved.

Dynamics of Marine Microbial Metabolism and Physiology at Station ALOHA

NASA Astrophysics Data System (ADS)

Casey, John R.

Marine microbial communities influence global biogeochemical cycles by coupling the transduction of free energy to the transformation of Earth's essential bio-elements: H, C, N, O, P, and S. The web of interactions between these processes is extraordinarily complex, though fundamental physical and thermodynamic principles should describe its dynamics. In this collection of 5 studies, aspects of the complexity of marine microbial metabolism and physiology were investigated as they interact with biogeochemical cycles and direct the flow of energy within the Station ALOHA surface layer microbial community. In Chapter 1, and at the broadest level of complexity discussed, a method to relate cell size to metabolic activity was developed to evaluate allometric power laws at fine scales within picoplankton populations. Although size was predictive of metabolic rates, within-population power laws deviated from the broader size spectrum, suggesting metabolic diversity as a key determinant of microbial activity. In Chapter 2, a set of guidelines was proposed by which organic substrates are selected and utilized by the heterotrophic community based on their nitrogen content, carbon content, and energy content. A hierarchical experimental design suggested that the heterotrophic microbial community prefers high nitrogen content but low energy density substrates, while carbon content was not important. In Chapter 3, a closer look at the light-dependent dynamics of growth on a single organic substrate, glycolate, suggested that growth yields were improved by photoheterotrophy. The remaining chapters were based on the development of a genome-scale metabolic network reconstruction of the cyanobacterium Prochlorococcus to probe its metabolic capabilities and quantify metabolic fluxes. Findings described in Chapter 4 pointed to evolution of the Prochlorococcus metabolic network to optimize growth at low phosphate concentrations. Finally, in Chapter 5 and at the finest scale of

Interspecies interactions are an integral determinant of microbial community dynamics

PubMed Central

Aziz, Fatma A. A.; Suzuki, Kenshi; Ohtaki, Akihiro; Sagegami, Keita; Hirai, Hidetaka; Seno, Jun; Mizuno, Naoko; Inuzuka, Yuma; Saito, Yasuhisa; Tashiro, Yosuke; Hiraishi, Akira; Futamata, Hiroyuki

2015-01-01

This study investigated the factors that determine the dynamics of bacterial communities in a complex system using multidisciplinary methods. Since natural and engineered microbial ecosystems are too complex to study, six types of synthetic microbial ecosystems (SMEs) were constructed under chemostat conditions with phenol as the sole carbon and energy source. Two to four phenol-degrading, phylogenetically and physiologically different bacterial strains were used in each SME. Phylogeny was based on the nucleotide sequence of 16S rRNA genes, while physiologic traits were based on kinetic and growth parameters on phenol. Two indices, J parameter and “interspecies interaction,” were compared to predict which strain would become dominant in an SME. The J parameter was calculated from kinetic and growth parameters. On the other hand, “interspecies interaction,” a new index proposed in this study, was evaluated by measuring the specific growth activity, which was determined on the basis of relative growth of a strain with or without the supernatant prepared from other bacterial cultures. Population densities of strains used in SMEs were enumerated by real-time quantitative PCR (qPCR) targeting the gene encoding the large subunit of phenol hydroxylase and were compared to predictions made from J parameter and interspecies interaction calculations. In 4 of 6 SEMs tested the final dominant strain shown by real-time qPCR analyses coincided with the strain predicted by both the J parameter and the interspecies interaction. However, in SMEII-2 and SMEII-3 the final dominant Variovorax strains coincided with prediction of the interspecies interaction but not the J parameter. These results demonstrate that the effects of interspecies interactions within microbial communities contribute to determining the dynamics of the microbial ecosystem. PMID:26539177

An immunological approach to quantifying the saprotrophic growth dynamics of Trichoderma species during antagonistic interactions with Rhizoctonia solani in a soil-less mix.

PubMed

Thornton, Christopher R

2004-04-01

Studies of the saprotrophic growth dynamics of Trichoderma species and their fungal hosts during antagonistic interactions are severely hampered by the absence of methods that allow the unambiguous identification and quantification of individual genera in complex environments such as soil or compost containing mixed populations of fungi. Furthermore, methods are required that allow discrimination between active hyphal growth and other components of fungal biomass such as quiescent spores that are produced in large numbers by Trichoderma species. This study details the use of monoclonal antibodies to quantify the saprotrophic growth dynamics of the soil-borne plant pathogen Rhizoctonia solani and biological control strains of Trichoderma asperellum and Trichoderma harzianum during antagonistic interactions in peat-based microcosms. Quantification was based on the immunological detection of constitutive, extracellular antigens that are secreted from the growing tip of Rhizoctonia and Trichoderma mycelium and, in the case of Trichoderma harzianum, from quiescent phialoconidia also. The Trichoderma-specific monoclonal antibody (MF2) binds to a protein epitope of the enzyme glucoamylase, which was shown by immunofluorescence and immunogold electron gold microscopy studies of Trichoderma virens in vitro to be produced at the origin of germ tube emergence in phialoconidia and from the growing tip of germ tubes. In addition, a non-destructive immunoblotting technique showed that the enzyme was secreted during active growth of Trichoderma asperellum mycelium in peat. The Rhizoctonia solani-specific monoclonal antibody (EH2) similarly binds to a protein epitope of a glycoprotein that is secreted during active mycelial growth. Extracts derived from lyophilized mycelium were used as a quantifiable and repeatable source of antigens for construction of calibration curves. These curves were used to convert the absorbance values obtained in ELISA tests of peat extracts to biomass

Quantifying non-ergodic dynamics of force-free granular gases.

PubMed

Bodrova, Anna; Chechkin, Aleksei V; Cherstvy, Andrey G; Metzler, Ralf

2015-09-14

Brownian motion is ergodic in the Boltzmann-Khinchin sense that long time averages of physical observables such as the mean squared displacement provide the same information as the corresponding ensemble average, even at out-of-equilibrium conditions. This property is the fundamental prerequisite for single particle tracking and its analysis in simple liquids. We study analytically and by event-driven molecular dynamics simulations the dynamics of force-free cooling granular gases and reveal a violation of ergodicity in this Boltzmann-Khinchin sense as well as distinct ageing of the system. Such granular gases comprise materials such as dilute gases of stones, sand, various types of powders, or large molecules, and their mixtures are ubiquitous in Nature and technology, in particular in Space. We treat-depending on the physical-chemical properties of the inter-particle interaction upon their pair collisions-both a constant and a velocity-dependent (viscoelastic) restitution coefficient ε. Moreover we compare the granular gas dynamics with an effective single particle stochastic model based on an underdamped Langevin equation with time dependent diffusivity. We find that both models share the same behaviour of the ensemble mean squared displacement (MSD) and the velocity correlations in the limit of weak dissipation. Qualitatively, the reported non-ergodic behaviour is generic for granular gases with any realistic dependence of ε on the impact velocity of particles.

Seasonal dynamics of ant community structure in the Moroccan Argan Forest.

PubMed

El Keroumi, Abderrahim; Naamani, Khalid; Soummane, Hassna; Dahbi, Abdallah

2012-01-01

In this study we describe the structure and composition of ant communities in the endemic Moroccan Argan forest, using pitfall traps sampling technique throughout the four seasons between May 2006 and February 2007. The study focused on two distinct climatic habitats within the Essaouira Argan forest, a semi-continental site at Lahssinate, and a coastal site at Boutazarte. Thirteen different ant species were identified, belonging to seven genera. Monomorium subopacum Smith and Tapinoma simrothi Krausse-Heldrungen (Hymenoptera: Formicidae) were the most abundant and behaviorally dominant ant species in the arganeraie. In addition, more specimens were captured in the semi-continental site than in the coastal area. However, no significant difference was observed in species richness, evenness, or diversity between both sites. Composition and community structure showed clear seasonal dynamics. The number of species, their abundance, their diversity, and their evenness per Argan tree were significantly dissimilar among seasons. The richness (except between summer and autumn), and the abundance and the evenness of ant species among communities, showed a significant difference between the dry period (summer and spring) and the rainy period (winter and autumn). Higher abundance and richness values occurred in the dry period of the year. Ant species dominance and seasonal climatic variations in the arganeraie might be among the main factors affecting the composition, structure, and foraging activity of ant communities. This study, together with recent findings on ant predation behavior below Argan trees, highlights the promising use of dominant ant species as potential agents of Mediterranean fruit fly bio-control in the Argan forest and surrounding ecosystems.

In-Well Sediment Incubators to Evaluate Microbial Community Stability and Dynamics following Bioimmobilization of Uranium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baldwin, Brett R.; Peacock, Aaron D.; Gan, M.

2009-09-23

An in-situ incubation device (ISI) was developed in order to investigate the stability and dynamics of sediment associated microbial communities to prevailing subsurface oxidizing or reducing conditions. Here we describe the use of these devices at the Old Rifle Uranium Mill Tailings Remedial Action (UMTRA) site. During the 7 month deployment oxidized Rifle aquifer background sediments (RABS) were deployed in previously biostimulated wells under iron reducing conditions, cell densities of known iron reducing bacteria including Geobacteraceae increased significantly showing the microbial community response to local subsurface conditions. PLFA profiles of RABS following in situ deployment were strikingly similar to thosemore » of adjacent sediment cores suggesting ISI results could be extrapolated to the native material of the test plots. Results for ISI deployed reduced sediments showed only slight changes in community composition and pointed toward the ability of the ISIs to monitor microbial community stability and response to subsurface conditions.« less

Loschmidt echo as a robust decoherence quantifier for many-body systems

NASA Astrophysics Data System (ADS)

Zangara, Pablo R.; Dente, Axel D.; Levstein, Patricia R.; Pastawski, Horacio M.

2012-07-01

We employ the Loschmidt echo, i.e., the signal recovered after the reversal of an evolution, to identify and quantify the processes contributing to decoherence. This procedure, which has been extensively used in single-particle physics, is employed here in a spin ladder. The isolated chains have 1/2 spins with XY interaction and their excitations would sustain a one-body-like propagation. One of them constitutes the controlled system S whose reversible dynamics is degraded by the weak coupling with the uncontrolled second chain, i.e., the environment E. The perturbative SE coupling is swept through arbitrary combinations of XY and Ising-like interactions, that contain the standard Heisenberg and dipolar ones. Different time regimes are identified for the Loschmidt echo dynamics in this perturbative configuration. In particular, the exponential decay scales as a Fermi golden rule, where the contributions of the different SE terms are individually evaluated and analyzed. Comparisons with previous analytical and numerical evaluations of decoherence based on the attenuation of specific interferences show that the Loschmidt echo is an advantageous decoherence quantifier at any time, regardless of the S internal dynamics.

Signatures of ecological processes in microbial community time series.

PubMed

Faust, Karoline; Bauchinger, Franziska; Laroche, Béatrice; de Buyl, Sophie; Lahti, Leo; Washburne, Alex D; Gonze, Didier; Widder, Stefanie

2018-06-28

Growth rates, interactions between community members, stochasticity, and immigration are important drivers of microbial community dynamics. In sequencing data analysis, such as network construction and community model parameterization, we make implicit assumptions about the nature of these drivers and thereby restrict model outcome. Despite apparent risk of methodological bias, the validity of the assumptions is rarely tested, as comprehensive procedures are lacking. Here, we propose a classification scheme to determine the processes that gave rise to the observed time series and to enable better model selection. We implemented a three-step classification scheme in R that first determines whether dependence between successive time steps (temporal structure) is present in the time series and then assesses with a recently developed neutrality test whether interactions between species are required for the dynamics. If the first and second tests confirm the presence of temporal structure and interactions, then parameters for interaction models are estimated. To quantify the importance of temporal structure, we compute the noise-type profile of the community, which ranges from black in case of strong dependency to white in the absence of any dependency. We applied this scheme to simulated time series generated with the Dirichlet-multinomial (DM) distribution, Hubbell's neutral model, the generalized Lotka-Volterra model and its discrete variant (the Ricker model), and a self-organized instability model, as well as to human stool microbiota time series. The noise-type profiles for all but DM data clearly indicated distinctive structures. The neutrality test correctly classified all but DM and neutral time series as non-neutral. The procedure reliably identified time series for which interaction inference was suitable. Both tests were required, as we demonstrated that all structured time series, including those generated with the neutral model, achieved a moderate to high

Seasonal dynamics in the community structure and trophic structure of testate amoebae inhabiting the Sanjiang peatlands, Northeast China.

PubMed

Song, Lihong; Li, Hongkai; Wang, Kehong; Yan, Xiumin; Wu, Donghui

2018-04-01

Peatlands cover 3% of the earth's land surface but contain 30% of the world's soil carbon pool. Microbial communities constitute a crucial detrital food web for nutrient and carbon cycling in peatlands. Heterotrophic protozoans are considered top predators in the microbial food web; however, they are not yet well understood. In this study, we investigated seasonal dynamics in the community and the trophic structure of testate amoebae in four peatlands. Testate amoebae density and biomass in August were significantly higher than those in May and October. The highest density, 6.7 × 10 4 individual g -1 dry moss, was recorded in August 2014. The highest biomass, 7.7 × 10 2  μg C g -1 dry moss, was recorded in August 2013. Redundancy analyses showed that water-table depth was the most important factor, explaining over one third of the variance in fauna communities in all sampled seasons. High trophic position taxa dominated testate amoebae communities. The Shannon diversity index and community size structure index declined from August to October in 2013 and from May to October in 2014. These seasonal patterns of testate amoebae indicated the seasonal variations of the peatlands' microbial food web and are possibly related to the seasonal carbon dynamics in Northeast Chinese peatlands. Copyright © 2018 Elsevier GmbH. All rights reserved.

Dynamic Succession of Groundwater Sulfate-Reducing Communities during Prolonged Reduction of Uranium in a Contaminated Aquifer

DOE PAGES

Zhang, Ping; He, Zhili; Van Nostrand, Joy D.; ...

2017-03-16

To further understand the diversity and dynamics of SRB in response to substrate amendment, we sequenced genes coding for the dissimilatory sulfite reductase (dsrA) in groundwater samples collected after an emulsified vegetable oil (EVO) amendment, which sustained U(VI)-reducing conditions for one year in a fast-flowing aquifer. EVO amendment significantly altered the composition of groundwater SRB communities. Sequences having no closely related-described species dominated (80%) the indigenous SRB communities in nonamended wells. After EVO amendment, Desulfococcus, Desulfobacterium, and Desulfovibrio, known for long-chain-fatty-acid, short-chain-fatty-acid and H 2 oxidation and U(VI) reduction, became dominant accounting for 7 ± 2%, 21 ± 8%, andmore » 55 ± 8% of the SRB communities, respectively. Succession of these SRB at different bioactivity stages based on redox substrates/products (acetate, SO 4 –2, U(VI), NO 3 –, Fe(II), and Mn(II)) was observed. Desulfovibrio and Desulfococcus dominated SRB communities at 4–31 days, whereas Desulfobacterium became dominant at 80–140 days. By the end of the experiment (day 269), the abundance of these SRB decreased but the overall diversity of groundwater SRB was still higher than non-EVO controls. Up to 62% of the SRB community changes could be explained by groundwater geochemical variables, including those redox substrates/products. A significant ( P < 0.001) correlation was observed between groundwater U(VI) concentrations and Desulfovibrio abundance. Lastly, our results showed that the members of SRB and their dynamics were correlated significantly with slow EVO biodegradation, electron donor production and maintenance of U(VI)-reducing conditions in the aquifer.« less

Dynamic Succession of Groundwater Sulfate-Reducing Communities during Prolonged Reduction of Uranium in a Contaminated Aquifer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Ping; He, Zhili; Van Nostrand, Joy D.

To further understand the diversity and dynamics of SRB in response to substrate amendment, we sequenced genes coding for the dissimilatory sulfite reductase (dsrA) in groundwater samples collected after an emulsified vegetable oil (EVO) amendment, which sustained U(VI)-reducing conditions for one year in a fast-flowing aquifer. EVO amendment significantly altered the composition of groundwater SRB communities. Sequences having no closely related-described species dominated (80%) the indigenous SRB communities in nonamended wells. After EVO amendment, Desulfococcus, Desulfobacterium, and Desulfovibrio, known for long-chain-fatty-acid, short-chain-fatty-acid and H 2 oxidation and U(VI) reduction, became dominant accounting for 7 ± 2%, 21 ± 8%, andmore » 55 ± 8% of the SRB communities, respectively. Succession of these SRB at different bioactivity stages based on redox substrates/products (acetate, SO 4 –2, U(VI), NO 3 –, Fe(II), and Mn(II)) was observed. Desulfovibrio and Desulfococcus dominated SRB communities at 4–31 days, whereas Desulfobacterium became dominant at 80–140 days. By the end of the experiment (day 269), the abundance of these SRB decreased but the overall diversity of groundwater SRB was still higher than non-EVO controls. Up to 62% of the SRB community changes could be explained by groundwater geochemical variables, including those redox substrates/products. A significant ( P < 0.001) correlation was observed between groundwater U(VI) concentrations and Desulfovibrio abundance. Lastly, our results showed that the members of SRB and their dynamics were correlated significantly with slow EVO biodegradation, electron donor production and maintenance of U(VI)-reducing conditions in the aquifer.« less

Dynamic Succession of Groundwater Sulfate-Reducing Communities during Prolonged Reduction of Uranium in a Contaminated Aquifer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Ping; He, Zhili; Van Nostrand, Joy D.

To further understand the diversity and dynamics of SRB in response to substrate amendment, we sequenced in this paper genes coding for the dissimilatory sulfite reductase (dsrA) in groundwater samples collected after an emulsified vegetable oil (EVO) amendment, which sustained U(VI)-reducing conditions for one year in a fast-flowing aquifer. EVO amendment significantly altered the composition of groundwater SRB communities. Sequences having no closely related-described species dominated (80%) the indigenous SRB communities in nonamended wells. After EVO amendment, Desulfococcus, Desulfobacterium, and Desulfovibrio, known for long-chain-fatty-acid, short-chain-fatty-acid and H 2 oxidation and U(VI) reduction, became dominant accounting for 7 ± 2%, 21more » ± 8%, and 55 ± 8% of the SRB communities, respectively. Succession of these SRB at different bioactivity stages based on redox substrates/products (acetate, SO 4 –2, U(VI), NO 3 –, Fe(II), and Mn(II)) was observed. Desulfovibrio and Desulfococcus dominated SRB communities at 4–31 days, whereas Desulfobacterium became dominant at 80–140 days. By the end of the experiment (day 269), the abundance of these SRB decreased but the overall diversity of groundwater SRB was still higher than non-EVO controls. Up to 62% of the SRB community changes could be explained by groundwater geochemical variables, including those redox substrates/products. A significant (P < 0.001) correlation was observed between groundwater U(VI) concentrations and Desulfovibrio abundance. Finally, our results showed that the members of SRB and their dynamics were correlated significantly with slow EVO biodegradation, electron donor production and maintenance of U(VI)-reducing conditions in the aquifer.« less

Host-Specificity and Dynamics in Bacterial Communities Associated with Bloom-Forming Freshwater Phytoplankton

PubMed Central

Bagatini, Inessa Lacativa; Eiler, Alexander; Bertilsson, Stefan; Klaveness, Dag; Tessarolli, Letícia Piton; Vieira, Armando Augusto Henriques

2014-01-01

Many freshwater phytoplankton species have the potential to form transient nuisance blooms that affect water quality and other aquatic biota. Heterotrophic bacteria can influence such blooms via nutrient regeneration but also via antagonism and other biotic interactions. We studied the composition of bacterial communities associated with three bloom-forming freshwater phytoplankton species, the diatom Aulacoseira granulata and the cyanobacteria Microcystis aeruginosa and Cylindrospermopsis raciborskii. Experimental cultures incubated with and without lake bacteria were sampled in three different growth phases and bacterial community composition was assessed by 454-Pyrosequencing of 16S rRNA gene amplicons. Betaproteobacteria were dominant in all cultures inoculated with lake bacteria, but decreased during the experiment. In contrast, Alphaproteobacteria, which made up the second most abundant class of bacteria, increased overall during the course of the experiment. Other bacterial classes responded in contrasting ways to the experimental incubations causing significantly different bacterial communities to develop in response to host phytoplankton species, growth phase and between attached and free-living fractions. Differences in bacterial community composition between cyanobacteria and diatom cultures were greater than between the two cyanobacteria. Despite the significance, major differences between phytoplankton cultures were in the proportion of the OTUs rather than in the absence or presence of specific taxa. Different phytoplankton species favoring different bacterial communities may have important consequences for the fate of organic matter in systems where these bloom forming species occur. The dynamics and development of transient blooms may also be affected as bacterial communities seem to influence phytoplankton species growth in contrasting ways. PMID:24465807

Quantifying Ciliary Dynamics during Assembly Reveals Step-wise Waveform Maturation in Airway Cells.

PubMed

Oltean, Alina; Schaffer, Andrew J; Bayly, Philip V; Brody, Steven L

2018-05-31

Motile cilia are essential for clearance of particulates and pathogens from airways. For effective transport, ciliary motor proteins and axonemal structures interact to generate the rhythmic, propulsive bending, but the mechanisms that produce a dynamic waveform remain incompletely understood. Biomechanical measures of human cilia motion and their relationships to cilia assembly are needed to illuminate the biophysics of normal cilia function, and to quantify dysfunction in ciliopathies. To these ends, we analyzed cilia motion from high-speed video microscopy of ciliated cells sampled from human lung airways compared to primary-culture cells that undergo ciliogenesis in vitro. Quantitative assessment of waveform parameters showed variations in waveform shape between individual cilia; however, general trends in waveform parameters emerged, associated with progression of cilia length and stage of differentiation. When cilia emerged from cultured cells, beat frequency was initially elevated, then fell and remained stable as cilia lengthened. In contrast, the average bending amplitude and the ability to generate force gradually increased and eventually approached values observed in ex vivo samples. Dynein arm motor proteins DNAH5, DNAH9, DNAH11, and DNAH6 were localized within specific regions of the axoneme in the ex vivo cells; however distinct stages of in vitro waveform development identified by biomechanical features were associated with the progressive movement of dyneins to the appropriate proximal or distal sections of the cilium. These observations suggest that the step-wise variation in waveform development during ciliogenesis is dependent on cilia length and potentially outer dynein arm assembly.

87Sr/86Sr as a quantitative geochemical proxy for 14C reservoir age in dynamic, brackish waters: assessing applicability and quantifying uncertainties.

NASA Astrophysics Data System (ADS)

Lougheed, Bryan; van der Lubbe, Jeroen; Davies, Gareth

2016-04-01

Accurate geochronologies are crucial for reconstructing the sensitivity of brackish and estuarine environments to rapidly changing past external impacts. A common geochronological method used for such studies is radiocarbon (14C) dating, but its application in brackish environments is severely limited by an inability to quantify spatiotemporal variations in 14C reservoir age, or R(t), due to dynamic interplay between river runoff and marine water. Additionally, old carbon effects and species-specific behavioural processes also influence 14C ages. Using the world's largest brackish water body (the estuarine Baltic Sea) as a test-bed, combined with a comprehensive approach that objectively excludes both old carbon and species-specific effects, we demonstrate that it is possible to use 87Sr/86Sr ratios to quantify R(t) in ubiquitous mollusc shell material, leading to almost one order of magnitude increase in Baltic Sea 14C geochronological precision over the current state-of-the-art. We propose that this novel proxy method can be developed for other brackish water bodies worldwide, thereby improving geochronological control in these climate sensitive, near-coastal environments.

The role of reproductive plant traits and biotic interactions in the dynamics of semi-arid plant communities.

PubMed

Pueyo, Y; Kéfi, S; Díaz-Sierra, R; Alados, C L; Rietkerk, M

2010-12-01

The dynamics of semi-arid plant communities are determined by the interplay between competition and facilitation among plants. The sign and strength of these biotic interactions depend on plant traits. However, the relationships between plant traits and biotic interactions, and the consequences for plant communities are still poorly understood. Our objective here was to investigate, with a modelling approach, the role of plant reproductive traits on biotic interactions, and the consequences for processes such as plant succession and invasion. The dynamics of two plant types were modelled with a spatially-explicit integrodifferential model: (1) a plant with seed dispersal (colonizer of bare soil) and (2) a plant with local vegetative propagation (local competitor). Both plant types were involved in facilitation due to a local positive feedback between vegetation biomass and soil water availability, which promoted establishment and growth. Plants in the system also competed for limited water. The efficiency in water acquisition (dependent on reproductive and growth plant traits) determined which plant type dominated the community at the steady state. Facilitative interactions between plant types also played an important role in the community dynamics, promoting establishment in the driest conditions and recovery from low biomass. Plants with vegetative propagation took advantage of the ability of seed dispersers to establish on bare soil from a low initial biomass. Seed dispersers were good invaders, maintained high biomass at intermediate and high rainfall and showed a high ability in taking profit from the positive feedback originated by plants with vegetative propagation under the driest conditions. However, seed dispersers lost competitiveness with an increasing investment in fecundity. All together, our results showed that reproductive plant traits can affect the balance between facilitative and competitive interactions. Understanding this effect of plant traits

Entropy of dynamical social networks

NASA Astrophysics Data System (ADS)

Zhao, Kun; Karsai, Marton; Bianconi, Ginestra

2012-02-01

Dynamical social networks are evolving rapidly and are highly adaptive. Characterizing the information encoded in social networks is essential to gain insight into the structure, evolution, adaptability and dynamics. Recently entropy measures have been used to quantify the information in email correspondence, static networks and mobility patterns. Nevertheless, we still lack methods to quantify the information encoded in time-varying dynamical social networks. In this talk we present a model to quantify the entropy of dynamical social networks and use this model to analyze the data of phone-call communication. We show evidence that the entropy of the phone-call interaction network changes according to circadian rhythms. Moreover we show that social networks are extremely adaptive and are modified by the use of technologies such as mobile phone communication. Indeed the statistics of duration of phone-call is described by a Weibull distribution and is significantly different from the distribution of duration of face-to-face interactions in a conference. Finally we investigate how much the entropy of dynamical social networks changes in realistic models of phone-call or face-to face interactions characterizing in this way different type human social behavior.

Evolutionary history of Daphnia drives divergence in grazing selectivity and alters temporal community dynamics of producers.

PubMed

Park, John S; Post, David M

2018-01-01

Consumers with different seasonal life histories encounter different communities of producers during specific seasonal phases. If consumers evolve to prefer the producers that they encounter, then consumers may reciprocally influence the temporal composition of producer communities. Here, we study the keystone consumer Daphnia ambigua, whose seasonal life history has diverged due to intraspecific predator divergence across lakes of New England. We ask whether grazing preferences of Daphnia have diverged also and test whether any grazing differences influence temporal composition patterns of producers. We reared clonal populations of Daphnia from natural populations representing the two diverged life history types for multiple generations. We conducted short-term (24 hr) and long-term (27 days) grazing experiments in equal polycultures consisting of three diatom and two green algae species, treated with no consumer, Daphnia from lakes with anadromous alewife, or from lakes with landlocked alewife. After 24 hr, life history and grazing preference divergence in Daphnia ambigua drove significant differences in producer composition. However, those differences disappeared at the end of the 27-day experiment. Our results illustrate that, despite potentially more complex long-term dynamics, a multitrophic cascade of evolutionary divergence from a predator can influence temporal community dynamics at the producer level.

Remote Sensing for Hydrology: Surface Water Dynamics from Three Decades of Landsat Data

NASA Astrophysics Data System (ADS)

Tulbure, M. G.; Broich, M.; Kingsford, R.; Lucas, R.; Keith, D.

2014-12-01

Surface water is a vital resource affected by changes in climate and anthropogenic factors. Knowledge of surface water dynamics provides critical information for flood and drought management. Here we focused on the on the entire Murray-Darling Basin (MDB) of Australia, a large semi-arid region with scarce water resources, high hydroclimatic variability and competing water demands, impacted by climate change, altered flow regimes and land use changes. The MDB is also an area where substantial investment in environmental water allocation of large volumes of environmental flow was made. We used Landsat TM and ETM+ time series to synoptically map the dynamic of surface water extent with an internally consistent algorithm (Tulbure and Broich, 2013) over decades (1986-2011). We used a subset of Landsat path/rows for image training in both wet and dry years. Results show high interannual variability in number and size of flooded areas, with flooded areas during the Millennium Drought (until 2009) being substantially smaller than during the excessive 2010-2011 La Nina flooding. Flooding frequency in 2006, a very dry year was lower than in 2010, the La Nina year when extensive floods occurred. More developed areas of the basin showed different inter-annual patterns from natural areas of the basin. At Barmah-Millewa, the largest river red gum forest in the world, we also mapped flooded forest and tracked changes in NDVI. Higher NDVI values were found in areas more frequently flooded. Knowledge of the spatial and temporal dynamics of flooding and the response of riparian vegetation communities to flooding is important for management of floodplain wetlands and vegetation communities and for investigating effectiveness of environmental flows and flow regimes in the MDB. Existing maps of inundated areas are linked with river flow to quantify the relationship between river flow and inundated area in the MDB. Historic flood inundation extent mapped via remote sensing can be used

Long-term community dynamics of small landbirds with and without exposure to extensive disturbance from military training activities.

PubMed

Rivers, James W; Gipson, Philip S; Althoff, Donald P; Pontius, Jeffrey S

2010-02-01

Military training activities are known to impact individual species, yet our understanding of how such activities influence animal communities is limited. In this study, we used long-term data in a case study approach to examine the extent to which the local small landbird community differed between a site in northeast Kansas that experienced intensive disturbance from military training activities (Ft. Riley Military Installation) and a similar, nearby site that experienced minimal human disturbance (Konza Prairie Biological Station). In addition, we characterized how the regional pool of potential colonizers influenced local community dynamics using Breeding Bird Survey data. From 1991 to 2001, most species of small terrestrial landbirds (73%) recorded during breeding surveys were found at both sites and the mean annual richness at Ft. Riley (39.0 +/- 2.86 [SD]) was very similar to that of Konza Prairie (39.4 +/- 2.01). Richness was maintained at relatively constant levels despite compositional changes because colonizations compensated local extinctions at both sites. These dynamics were driven primarily by woodland species that exhibited stochastic losses and gains and were present at a low local and regional abundance. Our results suggest that military training activities may mimic natural disturbances for some species in this area because the small landbird community did not differ markedly between sites with and sites without extensive human disturbance. Although our results suggest that military training is not associated with large changes in the avian community, additional studies are needed to determine if this pattern is found in other ecological communities.

Seasonal Dynamics of the Airborne Bacterial Community and Selected Viruses in a Children's Daycare Center.

PubMed

Prussin, Aaron J; Vikram, Amit; Bibby, Kyle J; Marr, Linsey C

2016-01-01

Children's daycare centers appear to be hubs of respiratory infectious disease transmission, yet there is only limited information about the airborne microbial communities that are present in daycare centers. We have investigated the microbial community of the air in a daycare center, including seasonal dynamics in the bacterial community and the presence of specific viral pathogens. We collected filters from the heating, ventilation, and air conditioning (HVAC) system of a daycare center every two weeks over the course of a year. Amplifying and sequencing the 16S rRNA gene revealed that the air was dominated by Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes that are commonly associated with the human skin flora. Clear seasonal differences in the microbial community were not evident; however, the community structure differed when the daycare center was closed and unoccupied for a 13-day period. These results suggest that human occupancy, rather than the environment, is the major driver in shaping the microbial community structure in the air of the daycare center. Using PCR for targeted viruses, we detected a seasonal pattern in the presence of respiratory syncytial virus that included the period of typical occurrence of the disease related to the virus; however, we did not detect the presence of adenovirus or rotavirus at any time.

Seasonally dynamic fungal communities in the Quercus macrocarpa phyllosphere differ between urban and nonurban environments.

PubMed

Jumpponen, A; Jones, K L

2010-04-01

*The fungal richness, diversity and community composition in the Quercus macrocarpa phyllosphere were compared across a growing season in trees located in six stands within and outside a small urban center using 454-sequencing and DNA tagging. The approaches did not differentiate between endophytic and epiphytic fungal communities. *Fungi accumulated in the phyllosphere rapidly and communities were temporally dynamic, with more than a third of the analyzed operational taxonomic units (OTUs) and half of the BLAST-inferred genera showing distinct seasonal patterns. The seasonal patterns could be explained by fungal life cycles or environmental tolerances. *The communities were hyperdiverse and differed between the urban and nonurban stands, albeit not consistently across the growing season. Foliar macronutrients (nitrogen (N), potassium (K) and sulfur (S)), micronutrients (boron (B), manganese (Mn) and selenium (Se)) and trace elements (cadmium (Cd), lead (Pb) and zinc (Zn)) were enriched in the urban trees, probably as a result of anthropogenic activities. Because of correlations with the experimental layout, these chemical elements should not be considered as community drivers without further empirical studies. *We suggest that a combination of mechanisms leads to differences between urban and nonurban communities. Among those are stand isolation and size, nutrient and pollutant accumulation plus stand management, including fertilization and litter removal.

Temporal dynamics of hot desert microbial communities reveal structural and functional responses to water input

DOE Office of Scientific and Technical Information (OSTI.GOV)

Armstrong, Alacia; Valverde, Angel; Ramond, Jean-Baptiste

The temporal dynamics of desert soil microbial communities are poorly understood. Given the implications for ecosystem functioning under a global change scenario, a better understanding of desert microbial community stability is crucial. Here, we sampled soils in the central Namib Desert on sixteen different occasions over a one-year period. Using Illumina-based amplicon sequencing of the 16S rRNA gene, we found that α-diversity (richness) was more variable at a given sampling date (spatial variability) than over the course of one year (temporal variability). Community composition remained essentially unchanged across the first 10 months, indicating that spatial sampling might be more importantmore » than temporal sampling when assessing β-diversity patterns in desert soils. However, a major shift in microbial community composition was found following a single precipitation event. This shift in composition was associated with a rapid increase in CO2 respiration and productivity, supporting the view that desert soil microbial communities respond rapidly to re-wetting and that this response may be the result of both taxon-specific selection and changes in the availability or accessibility of organic substrates. Recovery to quasi pre-disturbance community composition was achieved within one month after rainfall.« less

Community dynamics drive punctuated engraftment of the fecal microbiome following transplantation using freeze-dried, encapsulated fecal microbiota.

PubMed

Staley, Christopher; Vaughn, Byron P; Graiziger, Carolyn T; Singroy, Stephanie; Hamilton, Matthew J; Yao, Dan; Chen, Chi; Khoruts, Alexander; Sadowsky, Michael J

2017-05-04

Fecal microbiota transplantation (FMT) is a highly effective treatment of recurrent and recalcitrant Clostridium difficile infection (rCDI). In a recent study oral-delivery of encapsulated, freeze-dried donor material, resulted in comparable rates of cure to colonoscopic approaches. Here we characterize shifts in the fecal bacterial community structure of patients treated for rCDI using encapsulated donor material. Prior to FMT, patient fecal samples showed declines in diversity and abundance of Firmicutes and Bacteroidetes, with concurrent increases in members of the Proteobacteria, specifically Enterobacteriaceae. Moreover, patients who experienced recurrence of CDI within the 2-month clinical follow-up had greater abundances of Enterobacteriaceae and did not show resolution of dysbioses. Despite resolution of rCDI following oral-administration of encapsulated fecal microbiota, community composition was slow to return to a normal donor-like assemblage. Post-FMT taxa within the Firmicutes showed rapid increases in relative abundance and did not vary significantly over time. Conversely, Bacteroidetes taxa only showed significant increases in abundance after one month post-FMT, corresponding to significant increases in the community attributable to the donors. Changes in the associations among dominant OTUs were observed at days, weeks, and months post-FMT, suggesting shifts in community dynamics may be related to the timing of increases in abundance of specific taxa. Administration of encapsulated, freeze-dried, fecal microbiota to rCDI patients resulted in restoration of bacterial diversity and resolution of dysbiosis. However, shifts in the fecal microbiome were incremental rather than immediate, and may be driven by changes in community dynamics reflecting changes in the host environment.

Quantifying the impact of the Three Gorges Dam on the thermal dynamics of the Yangtze River

NASA Astrophysics Data System (ADS)

Cai, Huayang; Piccolroaz, Sebastiano; Huang, Jingzheng; Liu, Zhiyong; Liu, Feng; Toffolon, Marco

2018-05-01

This study examines the impact of the world’s largest dam, the Three Gorges Dam (TGD), on the thermal dynamics of the Yangtze River (China). The analysis uses long-term observations of river water temperature (RWT) in four stations and reconstructs the RWT that would have occurred in absence of the TGD. Relative to pre-TGD conditions, RWT consistently warmed in the region due to air temperature (AT) increase. In addition, the analysis demonstrates that the TGD significantly affected RWT in the downstream reach. At the closest downstream station (Yichang) to the TGD, the annual cycle of RWT experienced a damped response to AT and a marked seasonal alteration: warming during all seasons except for spring and early summer which were characterized by cooling. Both effects were a direct consequence of the larger thermal inertia of the massive water volume stored in the TGD reservoir, causing the downstream reach to be more thermally resilient. The approach used here to quantify the separate contributions of climate and human interventions on RWT can be used to set scientific guidelines for river management and conservation planning strategies.

Differential Variance Analysis: a direct method to quantify and visualize dynamic heterogeneities

NASA Astrophysics Data System (ADS)

Pastore, Raffaele; Pesce, Giuseppe; Caggioni, Marco

2017-03-01

Many amorphous materials show spatially heterogenous dynamics, as different regions of the same system relax at different rates. Such a signature, known as Dynamic Heterogeneity, has been crucial to understand the nature of the jamming transition in simple model systems and is currently considered very promising to characterize more complex fluids of industrial and biological relevance. Unfortunately, measurements of dynamic heterogeneities typically require sophisticated experimental set-ups and are performed by few specialized groups. It is now possible to quantitatively characterize the relaxation process and the emergence of dynamic heterogeneities using a straightforward method, here validated on video microscopy data of hard-sphere colloidal glasses. We call this method Differential Variance Analysis (DVA), since it focuses on the variance of the differential frames, obtained subtracting images at different time-lags. Moreover, direct visualization of dynamic heterogeneities naturally appears in the differential frames, when the time-lag is set to the one corresponding to the maximum dynamic susceptibility. This approach opens the way to effectively characterize and tailor a wide variety of soft materials, from complex formulated products to biological tissues.

The Choice of PCR Primers Has Great Impact on Assessments of Bacterial Community Diversity and Dynamics in a Wastewater Treatment Plant

PubMed Central

Fredriksson, Nils Johan; Hermansson, Malte; Wilén, Britt-Marie

2013-01-01

Assessments of bacterial community diversity and dynamics are fundamental for the understanding of microbial ecology as well as biotechnological applications. We show that the choice of PCR primers has great impact on the results of analyses of diversity and dynamics using gene libraries and DNA fingerprinting. Two universal primer pairs targeting the 16S rRNA gene, 27F&1492R and 63F&M1387R, were compared and evaluated by analyzing the bacterial community in the activated sludge of a large-scale wastewater treatment plant. The two primer pairs targeted distinct parts of the bacterial community, none encompassing the other, both with similar richness. Had only one primer pair been used, very different conclusions had been drawn regarding dominant phylogenetic and putative functional groups. With 27F&1492R, Betaproteobacteria would have been determined to be the dominating taxa while 63F&M1387R would have described Alphaproteobacteria as the most common taxa. Microscopy and fluorescence in situ hybridization analysis showed that both Alphaproteobacteria and Betaproteobacteria were abundant in the activated sludge, confirming that the two primer pairs target two different fractions of the bacterial community. Furthermore, terminal restriction fragment polymorphism analyses of a series of four activated sludge samples showed that the two primer pairs would have resulted in different conclusions about community stability and the factors contributing to changes in community composition. In conclusion, different PCR primer pairs, although considered universal, target different ranges of bacteria and will thus show the diversity and dynamics of different fractions of the bacterial community in the analyzed sample. We also show that while a database search can serve as an indicator of how universal a primer pair is, an experimental assessment is necessary to evaluate the suitability for a specific environmental sample. PMID:24098498

Long-term spatial and temporal microbial community dynamics in a large-scale drinking water distribution system with multiple disinfectant regimes.

PubMed

Potgieter, Sarah; Pinto, Ameet; Sigudu, Makhosazana; du Preez, Hein; Ncube, Esper; Venter, Stephanus

2018-08-01

Long-term spatial-temporal investigations of microbial dynamics in full-scale drinking water distribution systems are scarce. These investigations can reveal the process, infrastructure, and environmental factors that influence the microbial community, offering opportunities to re-think microbial management in drinking water systems. Often, these insights are missed or are unreliable in short-term studies, which are impacted by stochastic variabilities inherent to large full-scale systems. In this two-year study, we investigated the spatial and temporal dynamics of the microbial community in a large, full scale South African drinking water distribution system that uses three successive disinfection strategies (i.e. chlorination, chloramination and hypochlorination). Monthly bulk water samples were collected from the outlet of the treatment plant and from 17 points in the distribution system spanning nearly 150 km and the bacterial community composition was characterised by Illumina MiSeq sequencing of the V4 hypervariable region of the 16S rRNA gene. Like previous studies, Alpha- and Betaproteobacteria dominated the drinking water bacterial communities, with an increase in Betaproteobacteria post-chloramination. In contrast with previous reports, the observed richness, diversity, and evenness of the bacterial communities were higher in the winter months as opposed to the summer months in this study. In addition to temperature effects, the seasonal variations were also likely to be influenced by changes in average water age in the distribution system and corresponding changes in disinfectant residual concentrations. Spatial dynamics of the bacterial communities indicated distance decay, with bacterial communities becoming increasingly dissimilar with increasing distance between sampling locations. These spatial effects dampened the temporal changes in the bulk water community and were the dominant factor when considering the entire distribution system. However

The dynamics of meaningful social interactions and the emergence of collective knowledge.

PubMed

Dankulov, Marija Mitrović; Melnik, Roderick; Tadić, Bosiljka

2015-07-15

Collective knowledge as a social value may arise in cooperation among actors whose individual expertise is limited. The process of knowledge creation requires meaningful, logically coordinated interactions, which represents a challenging problem to physics and social dynamics modeling. By combining two-scale dynamics model with empirical data analysis from a well-known Questions &Answers system Mathematics, we show that this process occurs as a collective phenomenon in an enlarged network (of actors and their artifacts) where the cognitive recognition interactions are properly encoded. The emergent behavior is quantified by the information divergence and innovation advancing of knowledge over time and the signatures of self-organization and knowledge sharing communities. These measures elucidate the impact of each cognitive element and the individual actor's expertise in the collective dynamics. The results are relevant to stochastic processes involving smart components and to collaborative social endeavors, for instance, crowdsourcing scientific knowledge production with online games.

A dynamic modelling approach for estimating critical loads of nitrogen based on plant community changes under a changing climate.

PubMed

Belyazid, Salim; Kurz, Dani; Braun, Sabine; Sverdrup, Harald; Rihm, Beat; Hettelingh, Jean-Paul

2011-03-01

A dynamic model of forest ecosystems was used to investigate the effects of climate change, atmospheric deposition and harvest intensity on 48 forest sites in Sweden (n = 16) and Switzerland (n = 32). The model was used to investigate the feasibility of deriving critical loads for nitrogen (N) deposition based on changes in plant community composition. The simulations show that climate and atmospheric deposition have comparably important effects on N mobilization in the soil, as climate triggers the release of organically bound nitrogen stored in the soil during the elevated deposition period. Climate has the most important effect on plant community composition, underlining the fact that this cannot be ignored in future simulations of vegetation dynamics. Harvest intensity has comparatively little effect on the plant community in the long term, while it may be detrimental in the short term following cutting. This study shows: that critical loads of N deposition can be estimated using the plant community as an indicator; that future climatic changes must be taken into account; and that the definition of the reference deposition is critical for the outcome of this estimate. Copyright © 2010 Elsevier Ltd. All rights reserved.

Microbial Community Dynamics in Soil Depth Profiles Over 120,000 Years of Ecosystem Development

PubMed Central

Turner, Stephanie; Mikutta, Robert; Meyer-Stüve, Sandra; Guggenberger, Georg; Schaarschmidt, Frank; Lazar, Cassandre S.; Dohrmann, Reiner; Schippers, Axel

2017-01-01

Along a long-term ecosystem development gradient, soil nutrient contents and mineralogical properties change, therefore probably altering soil microbial communities. However, knowledge about the dynamics of soil microbial communities during long-term ecosystem development including progressive and retrogressive stages is limited, especially in mineral soils. Therefore, microbial abundances (quantitative PCR) and community composition (pyrosequencing) as well as their controlling soil properties were investigated in soil depth profiles along the 120,000 years old Franz Josef chronosequence (New Zealand). Additionally, in a microcosm incubation experiment the effects of particular soil properties, i.e., soil age, soil organic matter fraction (mineral-associated vs. particulate), O2 status, and carbon and phosphorus additions, on microbial abundances (quantitative PCR) and community patterns (T-RFLP) were analyzed. The archaeal to bacterial abundance ratio not only increased with soil depth but also with soil age along the chronosequence, coinciding with mineralogical changes and increasing phosphorus limitation. Results of the incubation experiment indicated that archaeal abundances were less impacted by the tested soil parameters compared to Bacteria suggesting that Archaea may better cope with mineral-induced substrate restrictions in subsoils and older soils. Instead, archaeal communities showed a soil age-related compositional shift with the Bathyarchaeota, that were frequently detected in nutrient-poor, low-energy environments, being dominant at the oldest site. However, bacterial communities remained stable with ongoing soil development. In contrast to the abundances, the archaeal compositional shift was associated with the mineralogical gradient. Our study revealed, that archaeal and bacterial communities in whole soil profiles are differently affected by long-term soil development with archaeal communities probably being better adapted to subsoil conditions

Quantifying non-Markovianity of continuous-variable Gaussian dynamical maps

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vasile, Ruggero; Maniscalco, Sabrina; Paris, Matteo G. A.

2011-11-15

We introduce a non-Markovianity measure for continuous-variable open quantum systems based on the idea put forward in H.-P. Breuer et al.[Phys. Rev. Lett. 103, 210401 (2009);], that is, by quantifying the flow of information from the environment back to the open system. Instead of the trace distance we use here the fidelity to assess distinguishability of quantum states. We employ our measure to evaluate non-Markovianity of two paradigmatic Gaussian channels: the purely damping channel and the quantum Brownian motion channel with Ohmic environment. We consider different classes of Gaussian states and look for pairs of states maximizing the backflow ofmore » information. For coherent states we find simple analytical solutions, whereas for squeezed states we provide both exact numerical and approximate analytical solutions in the weak coupling limit.« less

Quantifying carbon stores and decomposition in dead wood: A review

Treesearch

Matthew B. Russell; Shawn Fraver; Tuomas Aakala; Jeffrey H. Gove; Christopher W. Woodall; Anthony W. D’Amato; Mark J. Ducey

2015-01-01

The amount and dynamics of forest dead wood (both standing and downed) has been quantified by a variety of approaches throughout the forest science and ecology literature. Differences in the sampling and quantification of dead wood can lead to differences in our understanding of forests and their role in the sequestration and emissions of CO2, as...

From theory to experimental design-Quantifying a trait-based theory of predator-prey dynamics.

PubMed

Laubmeier, A N; Wootton, Kate; Banks, J E; Bommarco, Riccardo; Curtsdotter, Alva; Jonsson, Tomas; Roslin, Tomas; Banks, H T

2018-01-01

Successfully applying theoretical models to natural communities and predicting ecosystem behavior under changing conditions is the backbone of predictive ecology. However, the experiments required to test these models are dictated by practical constraints, and models are often opportunistically validated against data for which they were never intended. Alternatively, we can inform and improve experimental design by an in-depth pre-experimental analysis of the model, generating experiments better targeted at testing the validity of a theory. Here, we describe this process for a specific experiment. Starting from food web ecological theory, we formulate a model and design an experiment to optimally test the validity of the theory, supplementing traditional design considerations with model analysis. The experiment itself will be run and described in a separate paper. The theory we test is that trophic population dynamics are dictated by species traits, and we study this in a community of terrestrial arthropods. We depart from the Allometric Trophic Network (ATN) model and hypothesize that including habitat use, in addition to body mass, is necessary to better model trophic interactions. We therefore formulate new terms which account for micro-habitat use as well as intra- and interspecific interference in the ATN model. We design an experiment and an effective sampling regime to test this model and the underlying assumptions about the traits dominating trophic interactions. We arrive at a detailed sampling protocol to maximize information content in the empirical data obtained from the experiment and, relying on theoretical analysis of the proposed model, explore potential shortcomings of our design. Consequently, since this is a "pre-experimental" exercise aimed at improving the links between hypothesis formulation, model construction, experimental design and data collection, we hasten to publish our findings before analyzing data from the actual experiment, thus

Simulations of Long-Term Community Dynamics in Coral Reefs - How Perturbations Shape Trajectories

PubMed Central

Kubicek, Andreas; Muhando, Christopher; Reuter, Hauke

2012-01-01

Tropical coral reefs feature extraordinary biodiversity and high productivity rates in oligotrophic waters. Due to increasing frequencies of perturbations – anthropogenic and natural – many reefs are under threat. Such perturbations often have devastating effects on these unique ecosystems and especially if they occur simultaneously and amplify each other's impact, they might trigger a phase shift and create irreversible conditions. We developed a generic, spatially explicit, individual-based model in which competition drives the dynamics of a virtual benthic reef community – comprised of scleractinian corals and algae – under different environmental settings. Higher system properties, like population dynamics or community composition arise through self-organization as emergent properties. The model was parameterized for a typical coral reef site at Zanzibar, Tanzania and features coral bleaching and physical disturbance regimes as major sources of perturbations. Our results show that various types and modes (intensities and frequencies) of perturbations create diverse outcomes and that the switch from high diversity to single species dominance can be evoked by small changes in a key parameter. Here we extend the understanding of coral reef resilience and the identification of key processes, drivers and respective thresholds, responsible for changes in local situations. One future goal is to provide a tool which may aid decision making processes in management of coral reefs. PMID:23209397

The impact of 850,000 years of climate changes on the structure and dynamics of mammal food webs.

PubMed

Nenzén, Hedvig K; Montoya, Daniel; Varela, Sara

2014-01-01

Most evidence of climate change impacts on food webs comes from modern studies and little is known about how ancient food webs have responded to climate changes in the past. Here, we integrate fossil evidence from 71 fossil sites, body-size relationships and actualism to reconstruct food webs for six large mammal communities that inhabited the Iberian Peninsula at different times during the Quaternary. We quantify the long-term dynamics of these food webs and study how their structure changed across the Quaternary, a period for which fossil data and climate changes are well known. Extinction, immigration and turnover rates were correlated with climate changes in the last 850 kyr. Yet, we find differences in the dynamics and structural properties of Pleistocene versus Holocene mammal communities that are not associated with glacial-interglacial cycles. Although all Quaternary mammal food webs were highly nested and robust to secondary extinctions, general food web properties changed in the Holocene. These results highlight the ability of communities to re-organize with the arrival of phylogenetically similar species without major structural changes, and the impact of climate change and super-generalist species (humans) on Iberian Holocene mammal communities.

The Impact of 850,000 Years of Climate Changes on the Structure and Dynamics of Mammal Food Webs

PubMed Central

Nenzén, Hedvig K.; Montoya, Daniel; Varela, Sara

2014-01-01

Most evidence of climate change impacts on food webs comes from modern studies and little is known about how ancient food webs have responded to climate changes in the past. Here, we integrate fossil evidence from 71 fossil sites, body-size relationships and actualism to reconstruct food webs for six large mammal communities that inhabited the Iberian Peninsula at different times during the Quaternary. We quantify the long-term dynamics of these food webs and study how their structure changed across the Quaternary, a period for which fossil data and climate changes are well known. Extinction, immigration and turnover rates were correlated with climate changes in the last 850 kyr. Yet, we find differences in the dynamics and structural properties of Pleistocene versus Holocene mammal communities that are not associated with glacial-interglacial cycles. Although all Quaternary mammal food webs were highly nested and robust to secondary extinctions, general food web properties changed in the Holocene. These results highlight the ability of communities to re-organize with the arrival of phylogenetically similar species without major structural changes, and the impact of climate change and super-generalist species (humans) on Iberian Holocene mammal communities. PMID:25207754

Dynamic Succession of Groundwater Functional Microbial Communities in Response to Emulsified Vegetable Oil Amendment during Sustained In Situ U(VI) Reduction.

PubMed

Zhang, Ping; Wu, Wei-Min; Van Nostrand, Joy D; Deng, Ye; He, Zhili; Gihring, Thomas; Zhang, Gengxin; Schadt, Chris W; Watson, David; Jardine, Phil; Criddle, Craig S; Brooks, Scott; Marsh, Terence L; Tiedje, James M; Arkin, Adam P; Zhou, Jizhong

2015-06-15

A pilot-scale field experiment demonstrated that a one-time amendment of emulsified vegetable oil (EVO) reduced groundwater U(VI) concentrations for 1 year in a fast-flowing aquifer. However, little is known about how EVO amendment stimulates the functional gene composition, structure, and dynamics of groundwater microbial communities toward prolonged U(VI) reduction. In this study, we hypothesized that EVO amendment would shift the functional gene composition and structure of groundwater microbial communities and stimulate key functional genes/groups involved in EVO biodegradation and reduction of electron acceptors in the aquifer. To test these hypotheses, groundwater microbial communities after EVO amendment were analyzed using a comprehensive functional gene microarray. Our results showed that EVO amendment stimulated sequential shifts in the functional composition and structure of groundwater microbial communities. Particularly, the relative abundance of key functional genes/groups involved in EVO biodegradation and the reduction of NO3 (-), Mn(IV), Fe(III), U(VI), and SO4 (2-) significantly increased, especially during the active U(VI) reduction period. The relative abundance for some of these key functional genes/groups remained elevated over 9 months. Montel tests suggested that the dynamics in the abundance, composition, and structure of these key functional genes/groups were significantly correlated with groundwater concentrations of acetate, NO3 (-), Mn(II), Fe(II), U(VI), and SO4 (2-). Our results suggest that EVO amendment stimulated dynamic succession of key functional microbial communities. This study improves our understanding of the composition, structure, and function changes needed for groundwater microbial communities to sustain a long-term U(VI) reduction. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Dynamic Succession of Groundwater Functional Microbial Communities in Response to Emulsified Vegetable Oil Amendment during Sustained In Situ U(VI) Reduction

PubMed Central

Zhang, Ping; Wu, Wei-Min; Van Nostrand, Joy D.; Deng, Ye; He, Zhili; Gihring, Thomas; Zhang, Gengxin; Schadt, Chris W.; Watson, David; Jardine, Phil; Criddle, Craig S.; Brooks, Scott; Marsh, Terence L.; Tiedje, James M.; Arkin, Adam P.

2015-01-01

A pilot-scale field experiment demonstrated that a one-time amendment of emulsified vegetable oil (EVO) reduced groundwater U(VI) concentrations for 1 year in a fast-flowing aquifer. However, little is known about how EVO amendment stimulates the functional gene composition, structure, and dynamics of groundwater microbial communities toward prolonged U(VI) reduction. In this study, we hypothesized that EVO amendment would shift the functional gene composition and structure of groundwater microbial communities and stimulate key functional genes/groups involved in EVO biodegradation and reduction of electron acceptors in the aquifer. To test these hypotheses, groundwater microbial communities after EVO amendment were analyzed using a comprehensive functional gene microarray. Our results showed that EVO amendment stimulated sequential shifts in the functional composition and structure of groundwater microbial communities. Particularly, the relative abundance of key functional genes/groups involved in EVO biodegradation and the reduction of NO3−, Mn(IV), Fe(III), U(VI), and SO42− significantly increased, especially during the active U(VI) reduction period. The relative abundance for some of these key functional genes/groups remained elevated over 9 months. Montel tests suggested that the dynamics in the abundance, composition, and structure of these key functional genes/groups were significantly correlated with groundwater concentrations of acetate, NO3−, Mn(II), Fe(II), U(VI), and SO42−. Our results suggest that EVO amendment stimulated dynamic succession of key functional microbial communities. This study improves our understanding of the composition, structure, and function changes needed for groundwater microbial communities to sustain a long-term U(VI) reduction. PMID:25862231

Dynamic Succession of Groundwater Functional Microbial Communities in Response to Emulsified Vegetable Oil Amendment during Sustained In Situ U(VI) Reduction

DOE PAGES

Zhang, Ping; Wu, Wei-Min; Van Nostrand, Joy D.; ...

2015-04-10

A pilot-scale field experiment demonstrated that a one-time amendment of emulsified vegetable oil (EVO) reduced groundwater U(VI) concentrations for 1 year in a fast-flowing aquifer. However, little is known about how EVO amendment stimulates the functional gene composition, structure, and dynamics of groundwater microbial communities toward prolonged U(VI) reduction. In this paper, we hypothesized that EVO amendment would shift the functional gene composition and structure of groundwater microbial communities and stimulate key functional genes/groups involved in EVO biodegradation and reduction of electron acceptors in the aquifer. To test these hypotheses, groundwater microbial communities after EVO amendment were analyzed using amore » comprehensive functional gene microarray. Our results showed that EVO amendment stimulated sequential shifts in the functional composition and structure of groundwater microbial communities. Particularly, the relative abundance of key functional genes/groups involved in EVO biodegradation and the reduction of NO 3 -, Mn(IV), Fe(III), U(VI), and SO 4 2- significantly increased, especially during the active U(VI) reduction period. The relative abundance for some of these key functional genes/groups remained elevated over 9 months. Montel tests suggested that the dynamics in the abundance, composition, and structure of these key functional genes/groups were significantly correlated with groundwater concentrations of acetate, NO 3 -, Mn(II), Fe(II), U(VI), and SO 4 2-. Our results suggest that EVO amendment stimulated dynamic succession of key functional microbial communities. Finally, this study improves our understanding of the composition, structure, and function changes needed for groundwater microbial communities to sustain a long-term U(VI) reduction.« less

Dynamic Succession of Groundwater Functional Microbial Communities in Response to Emulsified Vegetable Oil Amendment during Sustained In Situ U(VI) Reduction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Ping; Wu, Wei-Min; Van Nostrand, Joy D.

A pilot-scale field experiment demonstrated that a one-time amendment of emulsified vegetable oil (EVO) reduced groundwater U(VI) concentrations for 1 year in a fast-flowing aquifer. However, little is known about how EVO amendment stimulates the functional gene composition, structure, and dynamics of groundwater microbial communities toward prolonged U(VI) reduction. In this paper, we hypothesized that EVO amendment would shift the functional gene composition and structure of groundwater microbial communities and stimulate key functional genes/groups involved in EVO biodegradation and reduction of electron acceptors in the aquifer. To test these hypotheses, groundwater microbial communities after EVO amendment were analyzed using amore » comprehensive functional gene microarray. Our results showed that EVO amendment stimulated sequential shifts in the functional composition and structure of groundwater microbial communities. Particularly, the relative abundance of key functional genes/groups involved in EVO biodegradation and the reduction of NO 3 -, Mn(IV), Fe(III), U(VI), and SO 4 2- significantly increased, especially during the active U(VI) reduction period. The relative abundance for some of these key functional genes/groups remained elevated over 9 months. Montel tests suggested that the dynamics in the abundance, composition, and structure of these key functional genes/groups were significantly correlated with groundwater concentrations of acetate, NO 3 -, Mn(II), Fe(II), U(VI), and SO 4 2-. Our results suggest that EVO amendment stimulated dynamic succession of key functional microbial communities. Finally, this study improves our understanding of the composition, structure, and function changes needed for groundwater microbial communities to sustain a long-term U(VI) reduction.« less

Microbial community dynamics in anaerobic bioreactors and algal tanks treating piggery wastewater.

PubMed

Patil, Sayali S; Kumar, Martin S; Ball, Andrew S

2010-06-01

Integrated biosystem is becoming a major aspect of wastewater management practice. Microbial communities in piggery wastewater sampled from anaerobic (thermophilic and mesophilic) and aerobic digesters (algal tanks) during waste remediation were analyzed by culture-independent techniques based on polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE). The use of Muyzer's 314F-GC, 518R bacterial primers, and archaeal A934F, 1309R primers followed by partial 16s rDNA sequence analysis of the main bands from DGGE revealed the presence of unknown and as yet uncultured microorganisms but also showed functional and ecologically significant denitrifying, acetogenic bacteria along with autotrophic, hydrogenotrophic, and acetoclastic methanogen archaea. Thermophilic digesters were dominated by gamma-Proteobacteria, Methanothermobacter sp., while mesophilic digesters showed dominance by Firmicutes, uncultured bacteria, Methanosarcina, and Methanoculleus genera. Under aerobic conditions within algal tanks, pH rose from 7.17 to 9.32, with a significant decrease in total ammonia nitrogen, chemical oxygen demand, and soluble phosphorus levels. PCR-DGGE proved a useful tool for investigating the dynamics of microbial community in the bio-processing of piggery wastewater. Knowledge of the microbial communities involved in digestion of piggery wastewater will allow optimization of integrated biosystem by removing the main pollutants like inorganic ammonium-nitrogen, phosphorus, and pathogens from intensive farming system.

Sourdough microbial community dynamics: An analysis during French organic bread-making processes.

PubMed

Lhomme, Emilie; Urien, Charlotte; Legrand, Judith; Dousset, Xavier; Onno, Bernard; Sicard, Delphine

2016-02-01

Natural sourdoughs are commonly used in bread-making processes, especially for organic bread. Despite its role in bread flavor and dough rise, the stability of the sourdough microbial community during and between bread-making processes is debated. We investigated the dynamics of lactic acid bacteria (LAB) and yeast communities in traditional organic sourdoughs of five French bakeries during the bread-making process and several months apart using classical and molecular microbiology techniques. Sourdoughs were sampled at four steps of the bread-making process with repetition. The analysis of microbial density over 68 sourdough/dough samples revealed that both LAB and yeast counts changed along the bread-making process and between bread-making runs. The species composition was less variable. A total of six LAB and nine yeast species was identified from 520 and 1675 isolates, respectively. The dominant LAB species was Lactobacillus sanfranciscensis, found for all bakeries and each bread-making run. The dominant yeast species changed only once between bread-making processes but differed between bakeries. They mostly belonged to the Kazachstania clade. Overall, this study highlights the change of population density within the bread-making process and between bread-making runs and the relative stability of the sourdough species community during bread-making process. Copyright © 2014 Elsevier Ltd. All rights reserved.

Bacterial community dynamics in aerated cow manure slurry at different aeration intensities.

PubMed

Hanajima, D; Fukumoto, Y; Yasuda, T; Suzuki, K; Maeda, K; Morioka, R

2011-12-01

This study aimed to characterize microbial community dynamics in aerated cow manure slurry at different aeration intensities. Batch aerobic treatments were set up in 5-l jar fermentor, each containing 3 l of manure slurry; the slurries were subjected to low, medium and high (50, 150 and 250 ml min(-1), respectively) aeration for 9 days. Microbial community composition was determined using terminal restriction fragment length polymorphism and a clone library targeting 16S rRNA genes. High and medium aeration accelerated organic carbon degradation in parallel with the degree of aeration intensity; however, 90% of the initial total organic carbon was retained during low-aeration treatment. During the active stages of organic carbon decomposition, clones belonging to the class Bacilli accumulated. Moreover, Bacilli accumulation occurred earlier under high aeration than under medium aeration. Organic matter degradation was mainly governed by a common microbial assemblage consisting of many lineages belonging to the class Bacilli. The timing of community development differed depending on aeration intensity. This study reports on changes in several environmentally important parameters and the principal microbial assemblage during the pollution-reducing phase of cattle manure aeration treatment. © 2011 The Authors. Journal of Applied Microbiology © 2011 The Society for Applied Microbiology.

Quantification of brain macrostates using dynamical nonstationarity of physiological time series.

PubMed

Latchoumane, Charles-Francois Vincent; Jeong, Jaeseung

2011-04-01

The brain shows complex, nonstationarity temporal dynamics, with abrupt micro- and macrostate transitions during its information processing. Detecting and characterizing these transitions in dynamical states of the brain is a critical issue in the field of neuroscience and psychiatry. In the current study, a novel method is proposed to quantify brain macrostates (e.g., sleep stages or cognitive states) from shifts of dynamical microstates or dynamical nonstationarity. A ``dynamical microstate'' is a temporal unit of the information processing in the brain with fixed dynamical parameters and specific spatial distribution. In this proposed approach, a phase-space-based dynamical dissimilarity map (DDM) is used to detect transitions between dynamically stationary microstates in the time series, and Tsallis time-dependent entropy is applied to quantify dynamical patterns of transitions in the DDM. We demonstrate that the DDM successfully detects transitions between microstates of different temporal dynamics in the simulated physiological time series against high levels of noise. Based on the assumption of nonlinear, deterministic brain dynamics, we also demonstrate that dynamical nonstationarity analysis is useful to quantify brain macrostates (sleep stages I, II, III, IV, and rapid eye movement (REM) sleep) from sleep EEGs with an overall accuracy of 77%. We suggest that dynamical nonstationarity is a useful tool to quantify macroscopic mental states (statistical integration) of the brain using dynamical transitions at the microscopic scale in physiological data.

The community dynamics of major bioleaching microorganisms during chalcopyrite leaching under the effect of organics.

PubMed

Li, Qihou; Tian, Ye; Fu, Xian; Yin, Huaqun; Zhou, Zhijun; Liang, Yiting; Qiu, Guanzhou; Liu, Jie; Liu, Hongwei; Liang, Yili; Shen, Li; Cong, Jing; Liu, Xueduan

2011-08-01

To determine the effect of organics (yeast extract) on microbial community during chalcopyrite bioleaching at different temperature, real-time polymerase chain reaction (PCR) was employed to analyze community dynamics of major bacteria applied in bioleaching. The results showed that yeast extract exerted great impact on microbial community, and therefore influencing bioleaching rate. To be specific, yeast extract was adverse to this bioleaching process at 30°C due to decreased proportion of important chemolithotrophs such as Acidithiobacillus ferrooxidans and Acidithiobacillus thiooxidans. However, yeast extract could promote bioleaching rate at 40°C on account of the increased number and enhanced work of Ferroplasma thermophilum, a kind of facultative bacteria. Similarly, bioleaching rate was enhanced under the effect of yeast extract at 50°C owing to the work of Acidianus brierleyi. At 60°C, bioleaching rate was close to 100% and temperature was the dominant factor determining bioleaching rate. Interestingly, the existence of yeast extract greatly enhanced the relative competitiveness of Ferroplasma thermophilum in this complex bioleaching microbial community.

The process-related dynamics of microbial community during a simulated fermentation of Chinese strong-flavored liquor.

PubMed

Zhang, Yanyan; Zhu, Xiaoyu; Li, Xiangzhen; Tao, Yong; Jia, Jia; He, Xiaohong

2017-09-15

Famous Chinese strong-flavored liquor (CSFL) is brewed by microbial consortia in a special fermentation pit (FT). However, the fermentation process was not fully understood owing to the complicate community structure and metabolism. In this study, the process-related dynamics of microbial communities and main flavor compounds during the 70-day fermentation process were investigated in a simulated fermentation system. A three-phase model was proposed to characterize the process of the CSFL fermentation. (i) In the early fermentation period (1-23 days), glucose was produced from macromolecular carbohydrates (e.g., starch). The prokaryotic diversity decreased significantly. The Lactobacillaceae gradually predominated in the prokaryotic community. In contrast, the eukaryotic diversity rose remarkably in this stage. Thermoascus, Aspergillus, Rhizopus and unidentified Saccharomycetales were dominant eukaryotic members. (ii) In the middle fermentation period (23-48 days), glucose concentration decreased while lactate acid and ethanol increased significantly. Prokaryotic community was almost dominated by the Lactobacillus, while eukaryotic community was mainly comprised of Thermoascus, Emericella and Aspergillus. (iii) In the later fermentation period (48-70 days), the concentrations of ethyl esters, especially ethyl caproate, increased remarkably. The CSFL fermentation could undergo three stages: saccharification, glycolysis and esterification. Saccharomycetales, Monascus, and Rhizopus were positively correlated to glucose concentration (P < 0.05), highlighting their important roles in the starch saccharification. The Lactobacillaceae, Bacilli, Botryotinia, Aspergillus, unidentified Pleosporales and Capnodiales contributed to the glycolysis and esterification, because they were positively correlated to most organic acids and ethyl esters (P < 0.05). Additionally, four genera, including Emericella, Suillus, Mortierella and Botryotinia, that likely played key roles

The bias associated with amplicon sequencing does not affect the quantitative assessment of bacterial community dynamics.

PubMed

Ibarbalz, Federico M; Pérez, María Victoria; Figuerola, Eva L M; Erijman, Leonardo

2014-01-01

The performance of two sets of primers targeting variable regions of the 16S rRNA gene V1-V3 and V4 was compared in their ability to describe changes of bacterial diversity and temporal turnover in full-scale activated sludge. Duplicate sets of high-throughput amplicon sequencing data of the two 16S rRNA regions shared a collection of core taxa that were observed across a series of twelve monthly samples, although the relative abundance of each taxon was substantially different between regions. A case in point was the changes in the relative abundance of filamentous bacteria Thiothrix, which caused a large effect on diversity indices, but only in the V1-V3 data set. Yet the relative abundance of Thiothrix in the amplicon sequencing data from both regions correlated with the estimation of its abundance determined using fluorescence in situ hybridization. In nonmetric multidimensional analysis samples were distributed along the first ordination axis according to the sequenced region rather than according to sample identities. The dynamics of microbial communities indicated that V1-V3 and the V4 regions of the 16S rRNA gene yielded comparable patterns of: 1) the changes occurring within the communities along fixed time intervals, 2) the slow turnover of activated sludge communities and 3) the rate of species replacement calculated from the taxa-time relationships. The temperature was the only operational variable that showed significant correlation with the composition of bacterial communities over time for the sets of data obtained with both pairs of primers. In conclusion, we show that despite the bias introduced by amplicon sequencing, the variable regions V1-V3 and V4 can be confidently used for the quantitative assessment of bacterial community dynamics, and provide a proper qualitative account of general taxa in the community, especially when the data are obtained over a convenient time window rather than at a single time point.

The Bias Associated with Amplicon Sequencing Does Not Affect the Quantitative Assessment of Bacterial Community Dynamics

PubMed Central

Figuerola, Eva L. M.; Erijman, Leonardo

2014-01-01

The performance of two sets of primers targeting variable regions of the 16S rRNA gene V1–V3 and V4 was compared in their ability to describe changes of bacterial diversity and temporal turnover in full-scale activated sludge. Duplicate sets of high-throughput amplicon sequencing data of the two 16S rRNA regions shared a collection of core taxa that were observed across a series of twelve monthly samples, although the relative abundance of each taxon was substantially different between regions. A case in point was the changes in the relative abundance of filamentous bacteria Thiothrix, which caused a large effect on diversity indices, but only in the V1–V3 data set. Yet the relative abundance of Thiothrix in the amplicon sequencing data from both regions correlated with the estimation of its abundance determined using fluorescence in situ hybridization. In nonmetric multidimensional analysis samples were distributed along the first ordination axis according to the sequenced region rather than according to sample identities. The dynamics of microbial communities indicated that V1–V3 and the V4 regions of the 16S rRNA gene yielded comparable patterns of: 1) the changes occurring within the communities along fixed time intervals, 2) the slow turnover of activated sludge communities and 3) the rate of species replacement calculated from the taxa–time relationships. The temperature was the only operational variable that showed significant correlation with the composition of bacterial communities over time for the sets of data obtained with both pairs of primers. In conclusion, we show that despite the bias introduced by amplicon sequencing, the variable regions V1–V3 and V4 can be confidently used for the quantitative assessment of bacterial community dynamics, and provide a proper qualitative account of general taxa in the community, especially when the data are obtained over a convenient time window rather than at a single time point. PMID:24923665

[Soil respiration dynamics and its controlling factors of typical vegetation communities on meadow steppes in the western Songnen Plain].

PubMed

Wang, Ming; Liu, Xing-Tu; Li, Xiu-Jun; Zhang, Ji-Tao; Wang, Guo-Dong; Lu, Xin-Rui; Li, Xiao-Yu

2014-01-01

In order to accurately explore the soil respiration dynamics and its controlling factors of typical vegetation types in the western Songnen Plain, soil respiration rates of Chloris virgata, Puccinellia distans, Phragmites australis and Leymus chinensis communities were measured. The results showed that the diurnal curves of soil respiration rates of the four vegetation communities had simple peak values, which appeared at 11:00-15:00, and the valley values occurred at 21:00-1:00 or 3:00-5:00. The seasonal dynamic patterns of their soil respiration rates were similar, with the maximum (3.21-4.84 micromol CO2 x m(-2) x s(-1)) occurring in July and August and the minimum (0.46-1.51 micromol CO2 x m(-2) x s(-1)) in October. The soil respiration rates of the four vegetation communities had significant exponential correlations with ambient air temperature and soil temperature. Soil moisture, however, only played an important role in affecting the soil respiration rate of C. virgata community while air humidity near the soil surface was significantly correlated with the soil respiration rates of P. australis and L. chinensis communities. The soil salt contents seriously constrained the CO2 dioxide emission, and the soil pH, electrical conductivity (EC), exchangeable sodium percentage (ESP) could explain 87%-91% spatial variations of the soil respiration rate.

Quantifying Intracranial Aneurysm Wall Permeability for Risk Assessment Using Dynamic Contrast-Enhanced MRI: A Pilot Study.

PubMed

Vakil, P; Ansari, S A; Cantrell, C G; Eddleman, C S; Dehkordi, F H; Vranic, J; Hurley, M C; Batjer, H H; Bendok, B R; Carroll, T J

2015-05-01

Pathological changes in the intracranial aneurysm wall may lead to increases in its permeability; however the clinical significance of such changes has not been explored. The purpose of this pilot study was to quantify intracranial aneurysm wall permeability (K(trans), VL) to contrast agent as a measure of aneurysm rupture risk and compare these parameters against other established measures of rupture risk. We hypothesized K(trans) would be associated with intracranial aneurysm rupture risk as defined by various anatomic, imaging, and clinical risk factors. Twenty-seven unruptured intracranial aneurysms in 23 patients were imaged with dynamic contrast-enhanced MR imaging, and wall permeability parameters (K(trans), VL) were measured in regions adjacent to the aneurysm wall and along the paired control MCA by 2 blinded observers. K(trans) and VL were evaluated as markers of rupture risk by comparing them against established clinical (symptomatic lesions) and anatomic (size, location, morphology, multiplicity) risk metrics. Interobserver agreement was strong as shown in regression analysis (R(2) > 0.84) and intraclass correlation (intraclass correlation coefficient >0.92), indicating that the K(trans) can be reliably assessed clinically. All intracranial aneurysms had a pronounced increase in wall permeability compared with the paired healthy MCA (P < .001). Regression analysis demonstrated a significant trend toward an increased K(trans) with increasing aneurysm size (P < .001). Logistic regression showed that K(trans) also predicted risk in anatomic (P = .02) and combined anatomic/clinical (P = .03) groups independent of size. We report the first evidence of dynamic contrast-enhanced MR imaging-modeled contrast permeability in intracranial aneurysms. We found that contrast agent permeability across the aneurysm wall correlated significantly with both aneurysm size and size-independent anatomic risk factors. In addition, K(trans) was a significant and size

Aggregated filter-feeding consumers alter nutrient limitation: consequences for ecosystem and community dynamics.

PubMed

Atkinson, Carla L; Vaughn, Caryn C; Forshay, Kenneth J; Cooper, Joshua T

2013-06-01

Nutrient cycling is a key process linking organisms in ecosystems. This is especially apparent in stream environments in which nutrients are taken up readily and cycled through the system in a downstream trajectory. Ecological stoichiometry predicts that biogeochemical cycles of different elements are interdependent because the organisms that drive these cycles require fixed ratios of nutrients. There is growing recognition that animals play an important role in biogeochemical cycling across ecosystems. In particular, dense aggregations of consumers can create biogeochemical hotspots in aquatic ecosystems via nutrient translocation. We predicted that filter-feeding freshwater mussels, which occur as speciose, high-biomass aggregates, would create biogeochemical hotspots in streams by altering nutrient limitation and algal dynamics. In a field study, we manipulated nitrogen and phosphorus using nutrient-diffusing substrates in areas with high and low mussel abundance, recorded algal growth and community composition, and determined in situ mussel excretion stoichiometry at 18 sites in three rivers (Kiamichi, Little, and Mountain Fork Rivers, south-central United States). Our results indicate that mussels greatly influence ecosystem processes by modifying the nutrients that limit primary productivity. Sites without mussels were N-limited with -26% higher relative abundances of N-fixing blue-green algae, while sites with high mussel densities were co-limited (N and P) and dominated by diatoms. These results corroborated the results of our excretion experiments; our path analysis indicated that mussel excretion has a strong influence on stream water column N:P. Due to the high N:P of mussel excretion, strict N-limitation was alleviated, and the system switched to being co-limited by both N and P. This shows that translocation of nutrients by mussel aggregations is important to nutrient dynamics and algal species composition in these rivers. Our study highlights the

Food-web complexity, meta-community complexity and community stability.

PubMed

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.

Microbial Community Structures and Dynamics in the O3/BAC Drinking Water Treatment Process

PubMed Central

Tian, Jian; Lu, Jun; Zhang, Yu; Li, Jian-Cheng; Sun, Li-Chen; Hu, Zhang-Li

2014-01-01

Effectiveness of drinking water treatment, in particular pathogen control during the water treatment process, is always a major public health concern. In this investigation, the application of PCR-DGGE technology to the analysis of microbial community structures and dynamics in the drinking water treatment process revealed several dominant microbial populations including: α-Proteobacteria, β-Proteobacteria, γ-Proteobacteria, Bacteroidetes, Actinobacteria Firmicutes and Cyanobacteria. α-Proteobacteria and β-Proteobacteria were the dominant bacteria during the whole process. Bacteroidetes and Firmicutes were the dominant bacteria before and after treatment, respectively. Firmicutes showed season-dependent changes in population dynamics. Importantly, γ-Proteobacteria, which is a class of medically important bacteria, was well controlled by the O3/biological activated carbon (BAC) treatment, resulting in improved effluent water bio-safety. PMID:24937529

Dynamics and diversity of microbial community succession in traditional fermentation of Shanxi aged vinegar.

PubMed

Nie, Zhiqiang; Zheng, Yu; Du, Hongfu; Xie, Sankuan; Wang, Min

2015-05-01

The traditional fermentation of Shanxi aged vinegar (SAV), a well-known traditional Chinese vinegar, generally involves the preparation of starter daqu, starch saccharification, alcoholic fermentation (AF) and acetic acid fermentation (AAF). Dynamics and diversity of microbial community succession in daqu and other fermentation stages were investigated by denaturing gradient gel electrophoresis (DGGE). Results showed that eight bacterial genera and four fungal genera were found in daqu. However, Staphylococcus, Saccharopolyspora, Bacillus, Oceanobacillus, Enterobacter, Streptomyces, Eurotium, Monascus and Pichia in daqu were eradicated during AF. Four bacterial genera and three fungal genera were found in this stage. Weissella, Lactobacillus, Streptococcus, Saccharomyces, and Saccharomycopsis were the dominant microorganisms in the late stage of AF. During AAF, four bacterial genera and four fungal genera were found. Weissella, Streptococcus, Klebsiella, Escherichia, and Cladosporium gradually disappeared; the dominant microorganisms were Acetobacter, Lactobacillus, Saccharomycopsis, and Alternaria in the late stage of AAF. Alpha diversity metrics showed that fungal diversity in daqu was greater than that in AF and AAF. By contrast, bacterial diversity decreased from daqu to AF and increased in the first three days of AAF and then decreased. Hence, these results could help understand dynamics of microbial community succession in continuous fermentation of traditional Chinese vinegars. Copyright © 2014 Elsevier Ltd. All rights reserved.

Impacts of 3 years of elevated atmospheric CO2 on rhizosphere carbon flow and microbial community dynamics.

PubMed

Drigo, Barbara; Kowalchuk, George A; Knapp, Brigitte A; Pijl, Agata S; Boschker, Henricus T S; van Veen, Johannes A

2013-02-01

Carbon (C) uptake by terrestrial ecosystems represents an important option for partially mitigating anthropogenic CO2 emissions. Short-term atmospheric elevated CO2 exposure has been shown to create major shifts in C flow routes and diversity of the active soil-borne microbial community. Long-term increases in CO2 have been hypothesized to have subtle effects due to the potential adaptation of soil microorganism to the increased flow of organic C. Here, we studied the effects of prolonged elevated atmospheric CO2 exposure on microbial C flow and microbial communities in the rhizosphere. Carex arenaria (a nonmycorrhizal plant species) and Festuca rubra (a mycorrhizal plant species) were grown at defined atmospheric conditions differing in CO2 concentration (350 and 700 ppm) for 3 years. During this period, C flow was assessed repeatedly (after 6 months, 1, 2, and 3 years) by (13) C pulse-chase experiments, and label was tracked through the rhizosphere bacterial, general fungal, and arbuscular mycorrhizal fungal (AMF) communities. Fatty acid biomarker analyses and RNA-stable isotope probing (RNA-SIP), in combination with real-time PCR and PCR-DGGE, were used to examine microbial community dynamics and abundance. Throughout the experiment the influence of elevated CO2 was highly plant dependent, with the mycorrhizal plant exerting a greater influence on both bacterial and fungal communities. Biomarker data confirmed that rhizodeposited C was first processed by AMF and subsequently transferred to bacterial and fungal communities in the rhizosphere soil. Over the course of 3 years, elevated CO2 caused a continuous increase in the (13) C enrichment retained in AMF and an increasing delay in the transfer of C to the bacterial community. These results show that, not only do elevated atmospheric CO2 conditions induce changes in rhizosphere C flow and dynamics but also continue to develop over multiple seasons, thereby affecting terrestrial ecosystems C utilization processes

Dynamic communities in multichannel data: an application to the foreign exchange market during the 2007-2008 credit crisis.

PubMed

Fenn, Daniel J; Porter, Mason A; McDonald, Mark; Williams, Stacy; Johnson, Neil F; Jones, Nick S

2009-09-01

We study the cluster dynamics of multichannel (multivariate) time series by representing their correlations as time-dependent networks and investigating the evolution of network communities. We employ a node-centric approach that allows us to track the effects of the community evolution on the functional roles of individual nodes without having to track entire communities. As an example, we consider a foreign exchange market network in which each node represents an exchange rate and each edge represents a time-dependent correlation between the rates. We study the period 2005-2008, which includes the recent credit and liquidity crisis. Using community detection, we find that exchange rates that are strongly attached to their community are persistently grouped with the same set of rates, whereas exchange rates that are important for the transfer of information tend to be positioned on the edges of communities. Our analysis successfully uncovers major trading changes that occurred in the market during the credit crisis.

Dynamic communities in multichannel data: An application to the foreign exchange market during the 2007-2008 credit crisis

NASA Astrophysics Data System (ADS)

Fenn, Daniel J.; Porter, Mason A.; McDonald, Mark; Williams, Stacy; Johnson, Neil F.; Jones, Nick S.

2009-09-01

We study the cluster dynamics of multichannel (multivariate) time series by representing their correlations as time-dependent networks and investigating the evolution of network communities. We employ a node-centric approach that allows us to track the effects of the community evolution on the functional roles of individual nodes without having to track entire communities. As an example, we consider a foreign exchange market network in which each node represents an exchange rate and each edge represents a time-dependent correlation between the rates. We study the period 2005-2008, which includes the recent credit and liquidity crisis. Using community detection, we find that exchange rates that are strongly attached to their community are persistently grouped with the same set of rates, whereas exchange rates that are important for the transfer of information tend to be positioned on the edges of communities. Our analysis successfully uncovers major trading changes that occurred in the market during the credit crisis.

Microbial Community Structure and Dynamics of Dark Fire-Cured Tobacco Fermentation▿ †

PubMed Central

Di Giacomo, Michele; Paolino, Marianna; Silvestro, Daniele; Vigliotta, Giovanni; Imperi, Francesco; Visca, Paolo; Alifano, Pietro; Parente, Dino

2007-01-01

The Italian Toscano cigar production includes a fermentation step that starts when dark fire-cured tobacco leaves are moistened and mixed with ca. 20% prefermented tobacco to form a 500-kg bulk. The dynamics of the process, lasting ca. 18 days, has never been investigated in detail, and limited information is available on microbiota involved. Here we show that Toscano fermentation is invariably associated with the following: (i) an increase in temperature, pH, and total microbial population; (ii) a decrease in reducing sugars, citric and malic acids, and nitrate content; and (iii) an increase in oxalic acid, nitrite, and tobacco-specific nitrosamine content. The microbial community structure and dynamics were investigated by culture-based and culture-independent approaches, including denaturing gradient gel electrophoresis and single-strand conformational polymorphism. Results demonstrate that fermentation is assisted by a complex microbial community, changing in structure and composition during the process. During the early phase, the moderately acidic and mesophilic environment supports the rapid growth of a yeast population predominated by Debaryomyces hansenii. At this stage, Staphylococcaceae (Jeotgalicoccus and Staphylococcus) and Lactobacillales (Aerococcus, Lactobacillus, and Weissella) are the most commonly detected bacteria. When temperature and pH increase, endospore-forming low-G+C content gram-positive bacilli (Bacillus spp.) become evident. This leads to a further pH increase and promotes growth of moderately halotolerant and alkaliphilic Actinomycetales (Corynebacterium and Yania) during the late phase. To postulate a functional role for individual microbial species assisting the fermentation process, a preliminary physiological and biochemical characterization of representative isolates was performed. PMID:17142368

Quantifying an Integral Ecology Framework: A Case Study of the Riverina, Australia

NASA Astrophysics Data System (ADS)

Wheeler, Sarah A.; Haensch, Juliane; Edwards, Jane; Schirmer, Jackie; Zuo, Alec

2018-02-01

Communities in Australia's Murray-Darling Basin face the challenge of trying to achieve social, economic, and environmental sustainability; but experience entrenched conflict about the best way to achieve a sustainable future, especially for small rural communities. Integral ecology is a philosophical concept that seeks to address community, economic, social, and environmental sustainability simultaneously. Its inclusive processes are designed to reduce stakeholder conflict. However, to date the application of the integral ecology concept has been largely qualitative in nature. This study developed a quantitative integral ecology framework, and applied this framework to a case study of the Riverina, in the Murray-Darling Basin. Seventy-seven community-focused initiatives were assessed, ranked, and quantified. The majority of the community-focused ranked initiatives did not exhibit all aspects of integral ecology. Initiatives typically prioritized either (1) economic and community development or (2) environmental health; rarely both together. The integral ecology framework developed here enables recommendations on future community initiatives and may provide a pathway for community leaders and other policy-makers to more readily apply integral ecology objectives. Further research refining the framework's operationalization, application and implementation to a wider-scale may enhance communities' capacity to develop and grow sustainably.

Predicting community responses to perturbations in the face of imperfect knowledge and network complexity

USGS Publications Warehouse

Novak, Mark; Wootton, J. Timothy; Doak, Daniel F.; Emmerson, Mark; Estes, James A.; Tinker, M. Timothy

2011-01-01

How best to predict the effects of perturbations to ecological communities has been a long-standing goal for both applied and basic ecology. This quest has recently been revived by new empirical data, new analysis methods, and increased computing speed, with the promise that ecologically important insights may be obtainable from a limited knowledge of community interactions. We use empirically based and simulated networks of varying size and connectance to assess two limitations to predicting perturbation responses in multispecies communities: (1) the inaccuracy by which species interaction strengths are empirically quantified and (2) the indeterminacy of species responses due to indirect effects associated with network size and structure. We find that even modest levels of species richness and connectance (∼25 pairwise interactions) impose high requirements for interaction strength estimates because system indeterminacy rapidly overwhelms predictive insights. Nevertheless, even poorly estimated interaction strengths provide greater average predictive certainty than an approach that uses only the sign of each interaction. Our simulations provide guidance in dealing with the trade-offs involved in maximizing the utility of network approaches for predicting dynamics in multispecies communities.

Fixed and dynamic predictors of treatment process in therapeutic communities for substance abusers in Belgium.

PubMed

Goethals, Ilse; Vanderplasschen, Wouter; Vandevelde, Stijn; Broekaert, Eric

2012-10-11

Research on substance abuse treatment services in general reflects substantial attention to the notion of treatment process. Despite the growing popularity of process studies, only a few researchers have used instruments specifically tailored to measure the therapeutic community (TC) treatment process, and even fewer have investigated client attributes in relation to early TC treatment process experiences. The aim of the current study is to address this gap by exploring clients' early in-treatment experiences and to determine the predictors that are related to the treatment process, using a TC-specific multidimensional instrument. Data was gathered among 157 adults in five TCs in Flanders (Belgium). Descriptive statistics were used to explore clients' early in-treatment experiences and multiple linear regressions were conducted to determine the fixed and dynamic predictors of Community Environment and Personal Development and Change (two indicators of TC treatment process). Clients reveal a more positive first-month response to TC social processes than to personal-development processes that require self-reflection and insight. The variance in clients' ratings of Community Environment was primarily due to dynamic client factors, while the variance in clients' ratings of Personal Development and Change was only related to fixed client factors. Suitability for treatment was the strongest predictor of Community Environment ratings, whereas a judicial referral more strongly predicted Personal Development and Change scores. Special attention should be devoted to suitability for treatment as part of motivational assessment as this seems to be a very strong predictor of how clients react to the initiation stage of TC treatment. To help improve clients' (meta-)cognitive skills needed to achieve insight and self-reflection and perhaps speed up the process of recovery, the authors suggest the introduction of (meta-)cognitive training strategies in the pre-program and/or the

Virulence and biodegradation potential of dynamic microbial communities associated with decaying Cladophora in Great Lakes

USGS Publications Warehouse

Chun, Chan Lan; Peller, Julie R.; Shively, Dawn; Byappanahalli, Muruleedhara N.; Whitman, Richard L.; Staley, Christopher; Zhang, Qian; Ishii, Satoshi; Sadowsky, Michael J.

2017-01-01

Cladophora mats that accumulate and decompose along shorelines of the Great Lakes create potential threats to the health of humans and wildlife. The decaying algae create a low oxygen and redox potential environment favoring growth and persistence of anaerobic microbial populations, including Clostridium botulinum, the causal agent of botulism in humans, birds, and other wildlife. In addition to the diverse population of microbes, a dynamic chemical environment is generated, which involves production of numerous organic and inorganic substances, many of which are believed to be toxic to the sand and aquatic biotic communities. In this study, we used 16S-rDNA-based-amplicon sequencing and microfluidic-based quantitative PCR approaches to characterize the bacterial community structure and the abundances of human pathogens associated with Cladophora at different stages (up to 90 days) of algal decay in laboratory microcosms. Oxygen levels were largely depleted after a few hours of incubation. As Cladophora decayed, the algal microbial biodiversity decreased within 24 h, and the mat transitioned from an aerobic to anaerobic environment. There were increasing abundances of enteric and pathogenic bacteria during decomposition of Cladophora, including Acinetobacter, Enterobacter, Kluyvera, Cedecea, and others. In contrast, there were no or very few sequences (< 0.07%) assigned to such groups in fresh Cladophora samples. Principal coordinate analysis indicated that the bacterial community structure was dynamic and changed significantly with decay time. Knowledge of microbial communities and chemical composition of decaying algal mats is critical to our further understanding of the role that Cladophora plays in a beach ecosystem's structure and function, including the algal role in trophic interactions. Based on these findings, public and environmental health concerns should be considered when decaying Cladophora mats accumulate Great Lakes shorelines.

Virulence and biodegradation potential of dynamic microbial communities associated with decaying Cladophora in Great Lakes.

PubMed

Chun, Chan Lan; Peller, Julie R; Shively, Dawn; Byappanahalli, Muruleedhara N; Whitman, Richard L; Staley, Christopher; Zhang, Qian; Ishii, Satoshi; Sadowsky, Michael J

2017-01-01

Cladophora mats that accumulate and decompose along shorelines of the Great Lakes create potential threats to the health of humans and wildlife. The decaying algae create a low oxygen and redox potential environment favoring growth and persistence of anaerobic microbial populations, including Clostridium botulinum, the causal agent of botulism in humans, birds, and other wildlife. In addition to the diverse population of microbes, a dynamic chemical environment is generated, which involves production of numerous organic and inorganic substances, many of which are believed to be toxic to the sand and aquatic biotic communities. In this study, we used 16S-rDNA-based-amplicon sequencing and microfluidic-based quantitative PCR approaches to characterize the bacterial community structure and the abundances of human pathogens associated with Cladophora at different stages (up to 90days) of algal decay in laboratory microcosms. Oxygen levels were largely depleted after a few hours of incubation. As Cladophora decayed, the algal microbial biodiversity decreased within 24h, and the mat transitioned from an aerobic to anaerobic environment. There were increasing abundances of enteric and pathogenic bacteria during decomposition of Cladophora, including Acinetobacter, Enterobacter, Kluyvera, Cedecea, and others. In contrast, there were no or very few sequences (<0.07%) assigned to such groups in fresh Cladophora samples. Principal coordinate analysis indicated that the bacterial community structure was dynamic and changed significantly with decay time. Knowledge of microbial communities and chemical composition of decaying algal mats is critical to our further understanding of the role that Cladophora plays in a beach ecosystem's structure and function, including the algal role in trophic interactions. Based on these findings, public and environmental health concerns should be considered when decaying Cladophora mats accumulate Great Lakes shorelines. Copyright © 2016

Timing of transients: quantifying reaching times and transient behavior in complex systems

NASA Astrophysics Data System (ADS)

Kittel, Tim; Heitzig, Jobst; Webster, Kevin; Kurths, Jürgen

2017-08-01

In dynamical systems, one may ask how long it takes for a trajectory to reach the attractor, i.e. how long it spends in the transient phase. Although for a single trajectory the mathematically precise answer may be infinity, it still makes sense to compare different trajectories and quantify which of them approaches the attractor earlier. In this article, we categorize several problems of quantifying such transient times. To treat them, we propose two metrics, area under distance curve and regularized reaching time, that capture two complementary aspects of transient dynamics. The first, area under distance curve, is the distance of the trajectory to the attractor integrated over time. It measures which trajectories are ‘reluctant’, i.e. stay distant from the attractor for long, or ‘eager’ to approach it right away. Regularized reaching time, on the other hand, quantifies the additional time (positive or negative) that a trajectory starting at a chosen initial condition needs to approach the attractor as compared to some reference trajectory. A positive or negative value means that it approaches the attractor by this much ‘earlier’ or ‘later’ than the reference, respectively. We demonstrated their substantial potential for application with multiple paradigmatic examples uncovering new features.

The σ law of evolutionary dynamics in community-structured population.

PubMed

Tang, Changbing; Li, Xiang; Cao, Lang; Zhan, Jingyuan

2012-08-07

Evolutionary game dynamics in finite populations provide a new framework to understand the selection of traits with frequency-dependent fitness. Recently, a simple but fundamental law of evolutionary dynamics, which we call σ law, describes how to determine the selection between two competing strategies: in most evolutionary processes with two strategies, A and B, strategy A is favored over B in weak selection if and only if σR+S>T+σP. This relationship holds for a wide variety of structured populations with mutation rate and weak selection under certain assumptions. In this paper, we propose a model of games based on a community-structured population and revisit this law under the Moran process. By calculating the average payoffs of A and B individuals with the method of effective sojourn time, we find that σ features not only the structured population characteristics, but also the reaction rate between individuals. That is to say, an interaction between two individuals are not uniform, and we can take σ as a reaction rate between any two individuals with the same strategy. We verify this viewpoint by the modified replicator equation with non-uniform interaction rates in a simplified version of the prisoner's dilemma game (PDG). Copyright © 2012 Elsevier Ltd. All rights reserved.

Climate warming and agricultural stressors interact to determine stream macroinvertebrate community dynamics.

PubMed

Piggott, Jeremy J; Townsend, Colin R; Matthaei, Christoph D

2015-05-01

Global climate change is likely to modify the ecological consequences of currently acting stressors, but potentially important interactions between climate warming and land-use related stressors remain largely unknown. Agriculture affects streams and rivers worldwide, including via nutrient enrichment and increased fine sediment input. We manipulated nutrients (simulating agricultural run-off) and deposited fine sediment (simulating agricultural erosion) (two levels each) and water temperature (eight levels, 0-6°C above ambient) simultaneously in 128 streamside mesocosms to determine the individual and combined effects of the three stressors on macroinvertebrate community dynamics (community composition and body size structure of benthic, drift and insect emergence assemblages). All three stressors had pervasive individual effects, but in combination often produced additive or antagonistic outcomes. Changes in benthic community composition showed a complex interplay among habitat quality (with or without sediment), resource availability (with or without nutrient enrichment) and the behavioural/physiological tendency to drift or emerge as temperature rose. The presence of sediment and raised temperature both resulted in a community of smaller organisms. Deposited fine sediment strongly increased the propensity to drift. Stressor effects were most prominent in the benthic assemblage, frequently reflected by opposite patterns in individuals quitting the benthos (in terms of their propensity to drift or emerge). Of particular importance is that community measures of stream health routinely used around the world (taxon richness, EPT richness and diversity) all showed complex three-way interactions, with either a consistently stronger temperature response or a reversal of its direction when one or both agricultural stressors were also in operation. The negative effects of added fine sediment, which were often stronger at raised temperatures, suggest that streams already

Demographic drivers of functional composition dynamics.

PubMed

Muscarella, Robert; Lohbeck, Madelon; Martínez-Ramos, Miguel; Poorter, Lourens; Rodríguez-Velázquez, Jorge Enrique; van Breugel, Michiel; Bongers, Frans

2017-11-01

Mechanisms of community assembly and ecosystem function are often analyzed using community-weighted mean trait values (CWMs). We present a novel conceptual framework to quantify the contribution of demographic processes (i.e., growth, recruitment, and mortality) to temporal changes in CWMs. We used this framework to analyze mechanisms of secondary succession in wet tropical forests in Mexico. Seed size increased over time, reflecting a trade-off between colonization by small seeds early in succession, to establishment by large seeds later in succession. Specific leaf area (SLA) and leaf phosphorus content decreased over time, reflecting a trade-off between fast growth early in succession vs. high survival late in succession. On average, CWM shifts were driven mainly (70%) by growth of surviving trees that comprise the bulk of standing biomass, then mortality (25%), and weakly by recruitment (5%). Trait shifts of growing and recruiting trees mirrored the CWM trait shifts, and traits of dying trees did not change during succession, indicating that these traits are important for recruitment and growth, but not for mortality, during the first 30 yr of succession. Identifying the demographic drivers of functional composition change links population dynamics to community change, and enhances insights into mechanisms of succession. © 2017 by the Ecological Society of America.

Bacterial diversity differences along an epigenic cave stream reveal evidence of community dynamics, succession, and stability.

PubMed

Brannen-Donnelly, Kathleen; Engel, Annette S

2015-01-01

Unchanging physicochemical conditions and nutrient sources over long periods of time in cave and karst subsurface habitats, particularly aquifers, can support stable ecosystems, termed autochthonous microbial endokarst communities (AMEC). AMEC existence is unknown for other karst settings, such as epigenic cave streams. Conceptually, AMEC should not form in streams due to faster turnover rates and seasonal disturbances that have the capacity to transport large quantities of water and sediment and to change allochthonous nutrient and organic matter sources. Our goal was to investigate whether AMEC could form and persist in hydrologically active, epigenic cave streams. We analyzed bacterial diversity from cave water, sediments, and artificial substrates (Bio-Traps®) placed in the cave at upstream and downstream locations. Distinct communities existed for the water, sediments, and Bio-Trap® samplers. Throughout the study period, a subset of community members persisted in the water, regardless of hydrological disturbances. Stable habitat conditions based on flow regimes resulted in more than one contemporaneous, stable community throughout the epigenic cave stream. However, evidence for AMEC was insufficient for the cave water or sediments. Community succession, specifically as predictable exogenous heterotrophic microbial community succession, was evident from decreases in community richness from the Bio-Traps®, a peak in Bio-Trap® community biomass, and from changes in the composition of Bio-Trap® communities. The planktonic community was compositionally similar to Bio-Trap® initial colonizers, but the downstream Bio-Trap® community became more similar to the sediment community at the same location. These results can help in understanding the diversity of planktonic and attached microbial communities from karst, as well as microbial community dynamics, stability, and succession during disturbance or contamination responses over time.

A novel method for quantifying arm motion similarity.

PubMed

Zhi Li; Hauser, Kris; Roldan, Jay Ryan; Milutinovic, Dejan; Rosen, Jacob

2015-08-01

This paper proposes a novel task-independent method for quantifying arm motion similarity that can be applied to any kinematic/dynamic variable of interest. Given two arm motions for the same task, not necessarily with the same completion time, it plots the time-normalized curves against one another and generates four real-valued features. To validate these features we apply them to quantify the relationship between healthy and paretic arm motions of chronic stroke patients. Studying both unimanual and bimanual arm motions of eight chronic stroke patients, we find that inter-arm coupling that tends to synchronize the motions of both arms in bimanual motions, has a stronger effect at task-relevant joints than at task-irrelevant joints. It also revealed that the paretic arm suppresses the shoulder flexion of the non-paretic arm, while the latter encourages the shoulder rotation of the former.

Quantifiers more or less quantify online: ERP evidence for partial incremental interpretation

PubMed Central

Urbach, Thomas P.; Kutas, Marta

2010-01-01

Event-related brain potentials were recorded during RSVP reading to test the hypothesis that quantifier expressions are incrementally interpreted fully and immediately. In sentences tapping general knowledge (Farmers grow crops/worms as their primary source of income), Experiment 1 found larger N400s for atypical (worms) than typical objects (crops). Experiment 2 crossed object typicality with non-logical subject-noun phrase quantifiers (most, few). Off-line plausibility ratings exhibited the crossover interaction predicted by full quantifier interpretation: Most farmers grow crops and Few farmers grow worms were rated more plausible than Most farmers grow worms and Few farmers grow crops. Object N400s, although modulated in the expected direction, did not reverse. Experiment 3 replicated these findings with adverbial quantifiers (Farmers often/rarely grow crops/worms). Interpretation of quantifier expressions thus is neither fully immediate nor fully delayed. Furthermore, object atypicality was associated with a frontal slow positivity in few-type/rarely quantifier contexts, suggesting systematic processing differences among quantifier types. PMID:20640044

Community Dynamics of Carrion Flies and their Parasitoids in Experimental Carcasses in Central Argentina

PubMed Central

Horenstein, Moira Battán; Salvo, Adriana

2012-01-01

Insects are the predominant group regarding both species richness and abundance that develop on carrion. Among them, the most important decomposers using carrion as a source of food for their development are the immature stages of the dipteran families Calliphoridae, Muscidae, and Sarcophagidae. The large numbers of their larvae in carcasses are attacked by a rich community of parasitoids, including species of Braconidae, Ichneumonidae, and Pteromalidae (Hymenoptera: Parasitica). The objective of this study was describing the temporal composition and dynamics of a parasitoid community in relation to their dipterans hosts in carrion in terms of number of species and specific composition, irrespective of the particular interactions between species in both trophic levels. Additionally, seasonality of the climate in the region was investigated as a factor structuring the studied communities. The experiments were undertaken in the south of Cordoba, Argentina during 2004 in a rural area. Two traps per season were placed separately approximately 300 m from each other in the study site. Each trap contained a domestic pig (Sus scrofa) of approximately 8 kg as bait. Samples were taken daily during the first four weeks and then every two or three days over the following weeks until the end of the experiment. The dipteran community was represented by 15 species in 6 families of the Calyptratae Diptera whereas parasitoids belonged to six families of the parasitic Apocrita Hymenoptera. Climatic seasonality was an important factor in determining the number of occurring species in the carcasses and community composition. The highest number of species was observed in the spring for both communities. PMID:22963038

Complexity and Dynamics of the Winemaking Bacterial Communities in Berries, Musts, and Wines from Apulian Grape Cultivars through Time and Space

PubMed Central

Marzano, Marinella; Fosso, Bruno; Manzari, Caterina; Grieco, Francesco; Intranuovo, Marianna; Cozzi, Giuseppe; Mulè, Giuseppina; Scioscia, Gaetano; Valiente, Gabriel; Tullo, Apollonia; Sbisà, Elisabetta; Pesole, Graziano; Santamaria, Monica

2016-01-01

Currently, there is very little information available regarding the microbiome associated with the wine production chain. Here, we used an amplicon sequencing approach based on high-throughput sequencing (HTS) to obtain a comprehensive assessment of the bacterial community associated with the production of three Apulian red wines, from grape to final product. The relationships among grape variety, the microbial community, and fermentation was investigated. Moreover, the winery microbiota was evaluated compared to the autochthonous species in vineyards that persist until the end of the winemaking process. The analysis highlighted the remarkable dynamics within the microbial communities during fermentation. A common microbial core shared among the examined wine varieties was observed, and the unique taxonomic signature of each wine appellation was revealed. New species belonging to the genus Halomonas were also reported. This study demonstrates the potential of this metagenomic approach, supported by optimized protocols, for identifying the biodiversity of the wine supply chain. The developed experimental pipeline offers new prospects for other research fields in which a comprehensive view of microbial community complexity and dynamics is desirable. PMID:27299312

Modeling household and community transmission of Ebola virus disease: Epidemic growth, spatial dynamics and insights for epidemic control

PubMed Central

Kiskowski, Maria; Chowell, Gerardo

2016-01-01

The mechanisms behind the sub-exponential growth dynamics of the West Africa Ebola virus disease epidemic could be related to improved control of the epidemic and the result of reduced disease transmission in spatially constrained contact structures. An individual-based, stochastic network model is used to model immediate and delayed epidemic control in the context of social contact networks and investigate the extent to which the relative role of these factors may be determined during an outbreak. We find that in general, epidemics quickly establish a dynamic equilibrium of infections in the form of a wave of fixed size and speed traveling through the contact network. Both greater epidemic control and limited community mixing decrease the size of an infectious wave. However, for a fixed wave size, epidemic control (in contrast with limited community mixing) results in lower community saturation and a wave that moves more quickly through the contact network. We also found that the level of epidemic control has a disproportionately greater reductive effect on larger waves, so that a small wave requires nearly as much epidemic control as a larger wave to end an epidemic. PMID:26399855

Modeling household and community transmission of Ebola virus disease: Epidemic growth, spatial dynamics and insights for epidemic control.