Studies on the restoration succession of PFU microbial communities in a pilot-scale microcosm

In order to imitate the restoration succession process of natural water ecosystem, a laboratory microcosm system of constant-flow-restoration was designed and established. A eutrophycation lake, Lake Donghu, was selected as the subject investigated. Six sampling stations were set on the lake, among which the water of station IV was natural clean water, and others were polluted with different degrees. Polyurethane foam unit microbial communities, which had colonized in the stations for a month, were collected from these stations and placed in their respective microcosms, using clean water of station IV to gradually replace the water of these microcosms. In this process, the healthy community in clean water continuously replaced the damaged communities in polluted water, the restoration succession of the damaged communities was characterized by weekly determination of several functional and structural community parameters, including species number (S), diversity index (DI), community pollution value (CPV), heterotrophy index (HI), and similarity coefficient. Cluster analysis based on similarity coefficient was used to compare the succession discrepancies of these microbial communities from different stations. The ecological succession of microbial communities during restoration was investigated by the variable patterns of these parameters, and based on which, the restoration standards of these polluted stations were suggested in an ecological sense. That was, while being restored, the water of station 0 (supereutrophycation) should be substituted with natural clean water by 95%; station I (eutrophycation), more than 90%; station II (eutrophycation), more than 85%; station III (eutrophycation), about 85%; station V (mesoetitrophycation), less than 50%. The effects of the structural and functional parameters in monitoring and assessing ecological restoration are analyzed and compared. (C) 2007 Elsevier Ltd. All rights reserved.

Development of the microbial communities in Lake Donghu in relation to water quality

There is increasing recognition that protozoa is very useful in monitoring and evaluating water ecological healthy and quality. In order to study the relationship between structure and function of protozoan communities and water qualities, six sampling stations were set on Lake Donghu, a hypereutrophic subtropical Chinese lake. Microbial communities and protists sampling from the six stations was conducted by PFU (Polyurethane foam unit) method. Species number (S), diversity index (DI), percentage of phytomastigophra, community pollution value (CPV), community similarity and heterophy index (HI) were mensurated. The measured indicators of water quality included total phosphorus (TP), dissolved oxygen (DO), Chemical oxygen demand (COD), NH4 (+), NO2 (-) and NO3-. Every month water samples from stations I, II, III, IV were chemically analyzed for a whole year, Among the chemically analyzed stations, station I was the most heavily polluted, station II was the next, stations III and IV had similar pollution degrees. The variable tendencies of COD, TP, NH3, NO2-, NO3-, and DO during the year was approximately coincident among the six stations. Analysis from the community parameters showed that the pollution of station 0 was much more serious than others, and station V was the most slight. Of the community parameters, CPV and HI were sensitive in reflecting the variables of the water quality. Community similarity index was also sensitive in dividing water qualities and the water quality status of different stations could be correctly classified by the cluster analysis. DI could reflect the tendency of water quality gradient, species number and percentage of Phytomastigophora was not obvious in indicating the water quality gradient.

Grids with multiple batch systems for performance enhancement of multi-component and parameter sweep parallel applications

In this work, we evaluate the benefits of using Grids with multiple batch systems to improve the performance of multi-component and parameter sweep parallel applications by reduction in queue waiting times. Using different job traces of different loads, job distributions and queue waiting times corresponding to three different queuing policies(FCFS, conservative and EASY backfilling), we conducted a large number of experiments using simulators of two important classes of applications. The first simulator models Community Climate System Model (CCSM), a prominent multi-component application and the second simulator models parameter sweep applications. We compare the performance of the applications when executed on multiple batch systems and on a single batch system for different system and application configurations. We show that there are a large number of configurations for which application execution using multiple batch systems can give improved performance over execution on a single system.

Cape Verde coastal ecosystem: a study of community structure, trophic interactions and exploitation pattern

Tese de dout., Ciências e Tecnologia das Pescas, Faculdade de Ciências do Mar e do Ambiente, Universidade do Algarve, 2005

Supporting dynamic parameter sweep applications in workflows: lessons learnt from the CancerGrid project

A vast majority of scientific grid applications are either parameter sweep applications or a significant subpart of these applications belong to class of parameter sweep activities. The paper describes a new graphical workflow language in which any node of the DAG-based workflow can be a parameter sweep node and the execution of these nodes are transparently executed either in service grids or in desktop grids depending on the computational complexity of the workflow node. The new concept is supported by the CancerGrid portal that has been established for a chemist community.

Prevalence and risk factors of radiographic vertebral fracture in Brazilian community-dwelling elderly

The prevalence and risk factors of radiographic vertebral fracture were determined among Brazilian community-dwelling elderly. Vertebral fractures were a common condition in this elderly population, and lower hip bone mineral density was a significant risk factor for vertebral fractures in both genders. The aim of the study was to estimate the prevalence of radiographic vertebral fracture and investigate factors associated with this condition in Brazilian community-dwelling elderly. This cross-sectional study included 943 elderly subjects (561 women and 382 men) living in So Paulo, Brazil. Thoracic and lumbar spine radiographs were obtained, and vertebral fractures were evaluated using Genant`s semiquantitative method. Bone mineral density (BMD) was measured by dual X-ray absorptiometry, and bone biochemical markers were also evaluated. Female and male subjects were analyzed independently, and each gender was divided into two groups based on whether vertebral fractures were present. The prevalence of vertebral fracture was 27.5% (95% CI 23.8-31.1) in women and 31.8% in men (95% CI 27.1-36.5) (P = 0.116). Cox regression analyses using variables that were significant in the univariate analysis showed that age (prevalence ratio = 1.03, 95% CI 1.01-1.06; p = 0.019) and total femur BMD (PR = 0.27, 95% CI 0.08-0.98; p = 0.048) were independent factors in predicting vertebral fracture for the female group. In the male group, Cox regression analyses demonstrated that femoral neck BMD (PR = 0.26, 95% CI 0.07-0.98; p = 0.046) was an independent parameter in predicting vertebral fractures. Our results suggest that radiographic vertebral fractures are common in Brazilian community-dwelling elderly and that a low hip BMD was an important risk factor for this condition in both genders. Age was also significantly correlated with the presence of vertebral fractures in women.

Shading effects on community composition and food web structure of a deforested pasture stream: Evidences from a field experiment in Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Variability in light absorption and scattering of phytoplankton in Patagonian waters: Role of community size structure and pigment composition

Intense phytoplankton blooms were observed along the Patagonian shelf-break with satellite ocean color data, but few in situ optical observations were made in that region. We examine the variability of phytoplankton absorption and particulate scattering coefficients during such blooms on the basis of field data. The chlorophyll-a concentration, [Chla], ranged from 0.1 to 22.3 mg m−3 in surface waters. The size fractionation of [Chla] showed that 80% of samples were dominated by nanophytoplankton (N-group) and 20% by microphytoplankton (M-group). Chlorophyll-specific phytoplankton absorption coefficients at 440 and 676 nm, a*ph(440) and a*ph(676), and particulate scattering coefficient at 660 nm, b*p(660), ranged from 0.018 to 0.173, 0.009 to 0.046, and 0.031 to 2.37 m2 (mg Chla)−1, respectively. Both a*ph(440) and a*ph(676) were statistically higher for the N-group than M-group and also considerably higher than expected from global trends as a function of [Chla]. This result suggests that size of phytoplankton cells in Patagonian waters tends to be smaller than in other regions at similar [Chla]. The phytoplankton cell size parameter, Sf, derived from phytoplankton absorption spectra, proved to be useful for interpreting the variability in the data around the general inverse dependence of a*ph(440), a*ph(676), and b*p(660) on [Chla]. Sf also showed a pattern along the increasing trend of a*ph(440) and a*ph(676) as a function of the ratios of some accessory pigments to [Chla]. Our results suggest that the variability in phytoplankton absorption and scattering coefficients in Patagonian waters is caused primarily by changes in the dominant phytoplankton cell size accompanied by covariation in the concentrations of accessory pigments.

MODULARITY BASED FUZZY COMMUNITY DETECTION IN SOCIAL NETWORKS

Fuzzy community detection is to identify fuzzy communities in a network, which are groups of vertices in the network such that the membership of a vertex in one community is in [0,1] and that the sum of memberships of vertices in all communities equals to 1. Fuzzy communities are pervasive in social networks, but only a few works have been done for fuzzy community detection. Recently, a one-step forward extension of Newman’s Modularity, the most popular quality function for disjoint community detection, results into the Generalized Modularity (GM) that demonstrates good performance in finding well-known fuzzy communities. Thus, GMis chosen as the quality function in our research. We first propose a generalized fuzzy t-norm modularity to investigate the effect of different fuzzy intersection operators on fuzzy community detection, since the introduction of a fuzzy intersection operation is made feasible by GM. The experimental results show that the Yager operator with a proper parameter value performs better than the product operator in revealing community structure. Then, we focus on how to find optimal fuzzy communities in a network by directly maximizing GM, which we call it Fuzzy Modularity Maximization (FMM) problem. The effort on FMM problem results into the major contribution of this thesis, an efficient and effective GM-based fuzzy community detection method that could automatically discover a fuzzy partition of a network when it is appropriate, which is much better than fuzzy partitions found by existing fuzzy community detection methods, and a crisp partition of a network when appropriate, which is competitive with partitions resulted from the best disjoint community detections up to now. We address FMM problem by iteratively solving a sub-problem called One-Step Modularity Maximization (OSMM). We present two approaches for solving this iterative procedure: a tree-based global optimizer called Find Best Leaf Node (FBLN) and a heuristic-based local optimizer. The OSMM problem is based on a simplified quadratic knapsack problem that can be solved in linear time; thus, a solution of OSMM can be found in linear time. Since the OSMM algorithm is called within FBLN recursively and the structure of the search tree is non-deterministic, we can see that the FMM/FBLN algorithm runs in a time complexity of at least O (n2). So, we also propose several highly efficient and very effective heuristic algorithms namely FMM/H algorithms. We compared our proposed FMM/H algorithms with two state-of-the-art community detection methods, modified MULTICUT Spectral Fuzzy c-Means (MSFCM) and Genetic Algorithm with a Local Search strategy (GALS), on 10 real-world data sets. The experimental results suggest that the H2 variant of FMM/H is the best performing version. The H2 algorithm is very competitive with GALS in producing maximum modularity partitions and performs much better than MSFCM. On all the 10 data sets, H2 is also 2-3 orders of magnitude faster than GALS. Furthermore, by adopting a simply modified version of the H2 algorithm as a mutation operator, we designed a genetic algorithm for fuzzy community detection, namely GAFCD, where elite selection and early termination are applied. The crossover operator is designed to make GAFCD converge fast and to enhance GAFCD’s ability of jumping out of local minimums. Experimental results on all the data sets show that GAFCD uncovers better community structure than GALS.

Model parameter

Interannual environmental variability in Peru is dominated by the El Niño Southern Oscillation (ENSO). The most dramatic changes are associated with the warm El Niño (EN) phase (opposite the cold La Niña phase), which disrupts the normal coastal upwelling and affects the dynamics of many coastal marine and terrestrial resources. This study presents a trophic model for Sechura Bay, located at the northern extension of the Peruvian upwelling system, where ENSO-induced environmental variability is most extreme. Using an initial steady-state model for the year 1996, we explore the dynamics of the ecosystem through the year 2003 (including the strong EN of 1997/98 and the weaker EN of 2002/03). Based on support from literature, we force biomass of several non-trophically-mediated 'drivers' (e.g. Scallops, Benthic detritivores, Octopus, and Littoral fish) to observe whether the fit between historical and simulated changes (by the trophic model) is improved. The results indicate that the Sechura Bay Ecosystem is a relatively inefficient system from a community energetics point of view, likely due to the periodic perturbations of ENSO. A combination of high system productivity and low trophic level target species of invertebrates (i.e. scallops) and fish (i.e. anchoveta) results in high catches and an efficient fishery. The importance of environmental drivers is suggested, given the relatively small improvements in the fit of the simulation with the addition of trophic drivers on remaining functional groups' dynamics. An additional multivariate regression model is presented for the scallop Argopecten purpuratus, which demonstrates a significant correlation between both spawning stock size and riverine discharge-mediated mortality on catch levels. These results are discussed in the context of the appropriateness of trophodynamic modeling in relatively open systems, and how management strategies may be focused given the highly environmentally influenced marine resources of the region.

Community Structurein Soil Porous System.

Soil is well recognized as a highly complex system. The interaction and coupled physical, chemical, and biological processes and phenomena occurring in the soil environment at different spatial and temporal scales are the main reasons for such complexity. There is a need for appropriate methodologies to characterize soil porous systems with an interdisciplinary character. Four different real soil samples, presenting different textures, have been modeled as heterogeneous complex networks, applying a model known as the heterogeneous preferential attachment. An analytical study of the degree distributions in the soil model shows a multiscaling behavior in the connectivity degrees, leaving an empirically testable signature of heterogeneity in the topology of soil pore networks. We also show that the power-law scaling in the degree distribution is a robust trait of the soil model. Last, the detection of spatial pore communities, as densely connected groups with only sparser connections between them, has been studied for the first time in these soil networks. Our results show that the presence of these communities depends on the parameter values used to construct the network. These findings could contribute to understanding the mechanisms of the diffusion phenomena in soils, such as gas and water diffusion, development and dynamics of microorganisms, among others.

The influence of substrate kinetics on the microbial community structure in granular anaerobic biomass

The development of a strong, active granular sludge bed is necessary for optimal operation of upflow anaerobic sludge blanket reactors. The microbial and mechanical structure of the granules may have a strong influence on desirable properties such as growth rate, settling velocity and shear strength. Theories have been proposed for granule microbial structure based on the relative kinetics of substrate degradation, but contradict some observations from both modelling and microscopic studies. In this paper, the structures of four granule types were examined from full-scale UASB reactors, treating wastewater from a cannery, a slaughterhouse, and two breweries. Microbial structure was determined using fluorescence in situ hybridisation probing with 16S rRNA-directed oligonucleotide probes, and superficial structure and microbial density (volume occupied by cells and microbial debris) assessed using scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The granules were also modelled using a distributed parameter biofilm model, with a previously published biochemical model structure, biofilm modelling approach, and model parameters. The model results reflected the trophic structures observed, indicating that the structures were possibly determined by kinetics. Of particular interest were results from simulations of the protein grown granules, which were predicted to have slow growth rates, low microbial density, and no trophic layers, the last two of which were reflected by microscopic observations. The primary cause of this structure, as assessed by modelling, was the particulate nature of the wastewater, and the slow rate of particulate hydrolysis, rather than the presence of proteins in the wastewater. Because solids hydrolysis was rate limiting, soluble substrate concentrations were very low (below Monod half saturation concentration), which caused low growth rates. (C) 2003 Elsevier Ltd. All rights reserved.