Search results for: subdominant

Authors: Allan Kiptanui Kimisto, Geoffrey Odhiambo Ongondo, Anastasia Wairimu Muia, Cyrus Ndungu Kimani

Abstract:

The major challenge to proper sewage sludge treatment processes is the poor understanding of sludge microbiome diversities. This study applied the whole-genome. shotgun metagenomics technique to profile the microbial composition of sewage sludge in two active digestion lagoons at the Nyeri-Kangemi Wastewater Treatment Plant in Nyeri County, Kenya. Total microbial community DNA was extracted from samples using the available ZymoBIOMICS™ DNA Miniprep Kit and sequenced using Shotgun metagenomics. Samples were analyzed using MG-RAST software (Project ID: mgp100988), which allowed for comparing taxonomic diversity before β-diversities studies for Bacteria, Archaea and Eukaryotes. The study identified 57 phyla, 145 classes, 301 orders, 506 families, 963 genera, and 1980 species. Bacteria dominated the microbes and comprised 28 species, 51 classes, 110 orders, 243 families, 597 genera, and 1518 species. The Bacteroides(6.77%) were dominant, followed by Acinetobacter(1.44%) belonging to the Gammaproteobacteria and Acidororax (1.36%), Bacillus (1.24%) and Clostridium (1.02%) belonging to Betaproteobacteria. Archaea recorded 5 phyla, 13 classes, 19 orders, 29 families, 60 genera,and87 species, with the dominant genera being Methanospirillum (16.01%), methanosarcina (15.70%), and Methanoregula(14.80%) and Methanosaeta (8.74%), Methanosphaerula(5.48%) and Methanobrevibacter(5.03%) being the subdominant group. The eukaryotes were the least in abundance and comprised 24 phyla, 81 classes, 301 orders, 506 families, 963 genera, and 980 species. Arabidopsis (4.91%) and Caenorhabditis (4.81%) dominated the eukaryotes, while Dityostelium (3.63%) and Drosophila(2.08%) were the subdominant genera. All these microbes play distinct roles in the anaerobic treatment process of sewage sludge. The local sludge microbial composition and abundance variations may be due to age difference differences between the two digestion lagoons in operation at the plant and the different degradation rales played by the taxa. The information presented in this study can help in the genetic manipulation or formulation of optimal microbial ratios to improve their effectiveness in sewage sludge treatment. This study recommends further research on how the different taxa respond to environmental changes over time and space.

Keywords: shotgun metagenomics, sludge, bacteria, archaea, eukaryotes

Procedia PDF Downloads 66

Authors: Akmal E. Egamberdiev, Alim M. Nigmatullaev, Trobjon Kh. Makhkamov

Abstract:

The results of scientific research on the biomorphological features of Ajuga turkestanica (Regel) Brig., its role in plant communities, modern distribution areas, and raw material reserves are presented. Plant ontogeny is divided into 3 periods and 9 growth stages. Information on its seasonal and diurnal flowering and seed productivity is provided. As a result of the research, the participation of the studied species in plant communities, its place, the structure and floristic composition of communities were determined, and as a result, for the first time, the description of 11 new associations in 7 formations of Ajuga turkestanica, and a schematic map of the geolocation of formations and associations of plants in Uzbekistan is given. A. turkestanica (within the range) are divided into 3 categories and 21 massifs. Its current biological reserve is 93.5±35.3 tons, its usable reserve is 46.2±13.8 tons, and the reserve that can be prepared in 1 year is 28.4±5.42 tons.

Keywords: ontogeny, seed productivity, seasonal flowering, formation, association, dominant, subdominant, areal, biological reserve, operational reserve, annual reserve, GIS map

Procedia PDF Downloads 62

Authors: Laura A. Rodriguez-Villamizar, Alvaro Osornio-Vargas, Brian H. Rowe, Rhonda J. Rosychuk

Abstract:

Introduction/Objectives: The Census Metropolitan Area of Edmonton (CMAE) has important industrial emissions to the air from the Industrial Heartland Alberta (IHA) at the Northeast and the coal-fired power plants (CFPP) at the West. The objective of the study was to explore the presence of clusters of children asthma ED visits in the areas around the IHA and the CFPP. Methods: Retrospective data on children asthma ED visits was collected at the dissemination area (DA) level for children between 2 and 14 years of age, living in the CMAE between April 1, 2004, and March 31, 2010. We conducted a spatial analysis of disease clusters around putative sources with count (ecological) data using descriptive, hypothesis testing, and multivariable modeling analysis. Results: The mean crude rate of asthma ED visits was 9.3/1,000 children population per year during the study period. Circular spatial scan test for cases and events identified a cluster of children asthma ED visits in the DA where the CFPP are located in the Wabamum area. No clusters were identified around the IHA area. The multivariable models suggest that there is a significant decline in risk for children asthma ED visits as distance increases around the CFPP area this effect is modified at the SE direction with mean angle 125.58 degrees, where the risk increases with distance. In contrast, the regression models for IHA suggest that there is a significant increase in risk for children asthma ED visits as distance increases around the IHA area and this effect is modified at SW direction with mean angle 216.52 degrees, where the risk increases at shorter distances. Conclusions: Different methods for detecting clusters of disease consistently suggested the existence of a cluster of children asthma ED visits around the CFPP but not around the IHA within the CMAE. These results are probably explained by the direction of the air pollutants dispersion caused by the predominant and subdominant wind direction at each point. The use of different approaches to detect clusters of disease is valuable to have a better understanding of the presence, shape, direction and size of clusters of disease around pollution sources.

Keywords: air pollution, asthma, disease cluster, industry

Procedia PDF Downloads 254