Impacts of invasive plant species on soil biodiversity: a case study of dog-strangling vine (Vincetoxicum rossicum) in a Canadian National Park

Soil microbial diversity is expected to be altered by the establishment of invasive plant species, such as dog-strangling vine (DSV) [Vincetoxicum rossicum (Apocynaceae)]. However, in urban ecosystems where DSV invasion is high, there is little research evaluating the impacts of DSV and other anthropogenic disturbances on microbial diversity. Our study was based in Rouge National Urban Park, Canada, where we used terminal restriction fragment length polymorphism data to evaluate (i) if DSV has a detectable impact on soil bacterial community composition and (ii) if these impacts occur independently of other anthropogenic change or soil characteristics. Variation in soil bacterial communities was greatly reduced in DSV-invaded sites vs. less-invaded sites. The degree of DSV invasion independently explained 23.8% of variation in bacterial community composition: a value similar to the explanatory power of proximity to roadways (which explained 22.6% of the variation in community composition), and considerably greater than soil parameters (pH, moisture, carbon, and nitrogen concentrations) which explained only between 6.0% and 10.0% of variation in bacterial community composition. Our findings indicate that DSV influences soil bacterial community composition independent of other anthropogenic disturbances and soil parameters, with potential impacts on multiple facets of plant–soil interactions and plant invasion dynamics.

Download Full-text

Molecular Characterization of Bacterial Community Composition in the Rhizosphere of Invasive Plant Species Amur Honeysuckle (<i>Lonicera maackii</i>) in an Urban Wetland Forest

Advances in Microbiology ◽

10.4236/aim.2021.119035 ◽

2021 ◽

Vol 11 (09) ◽

pp. 469-487

Author(s):

Azeem Ahmad ◽

Samina Akbar

Keyword(s):

Bacterial Community ◽

Molecular Characterization ◽

Community Composition ◽

Plant Species ◽

Invasive Plant ◽

Bacterial Community Composition ◽

Lonicera Maackii ◽

Invasive Plant Species ◽

Urban Wetland

Download Full-text

Molecular Study of Indigenous Bacterial Community Composition on Exposure to Soil Arsenic Concentration Gradient

Polish Journal of Microbiology ◽

10.5604/01.3001.0010.7838 ◽

2017 ◽

Vol 66 (2) ◽

pp. 209-221 ◽

Cited By ~ 1

Author(s):

Semanti Basu ◽

Tanima Paul ◽

Priya Yadav ◽

Abhijit Debnath ◽

Keka Sarkar

Keyword(s):

Cluster Analysis ◽

Community Structure ◽

Bacterial Community ◽

16S Rdna ◽

Community Composition ◽

Bacterial Community Composition ◽

Arsenic Concentration ◽

Soil Parameters ◽

Arsenic Content ◽

Soil Bacterial

Community structure of bacteria present in arsenic contaminated agricultural soil was studied with qPCR (quantitative PCR) and DGGE (Denaturing Gradient Gel Electrophoresis) as an indicator of extreme stresses. Copy number of six common bacterial taxa (Acidobacteria, Actinobacteria, α, β and γ-Proteobacteria, Firmicutes) was calculated using group specific primers of 16S rDNA. It revealed that soil contaminated with low concentration of arsenic was dominated by both Actinobacteria and Proteobacteria but a shift towards Proteobacteria was observed with increasing arsenic concentration, and number of Actinobacteria eventually decreases. PCA (Principle Component Analysis) plot of bacterial community composition indicated a distinct resemblance among high arsenic content samples, while low arsenic content samples remained separated from others. Cluster analysis of soil parameters identifies three clusters, each of them was related to the arsenic content. Further, cluster analysis of 16S rDNA based DGGE fingerprint markedly distributed the soil bacterial populations into low (<10 ppm) and high (>10 ppm) arsenic content subgroups. Following analysis of diversity indices shows significant variation in bacterial community structure. MDS (Multi Dimensional Scaling) plot revealed distinction in the distribution of each sample denoting variation in bacterial diversity. Phylogenetic sequence analysis of fragments excised from DGGE gel revealed the presence of γ-Proteobacteria group across the study sites. Collectively, our experiments indicated that gradient of arsenic contamination affected the shape of the soil bacterial population by significant structural shift.

Download Full-text

Artificial neural network analysis of microbial diversity in the central and southern Adriatic Sea

Scientific Reports ◽

10.1038/s41598-021-90863-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Danijela Šantić ◽

Kasia Piwosz ◽

Frano Matić ◽

Ana Vrdoljak Tomaš ◽

Jasna Arapov ◽

...

Keyword(s):

Neural Network ◽

Network Analysis ◽

Bacterial Community ◽

Microbial Diversity ◽

Community Composition ◽

Adriatic Sea ◽

Bacterial Community Composition ◽

Environmental Data ◽

Large Contribution ◽

Neural Network Analysis

AbstractBacteria are an active and diverse component of pelagic communities. The identification of main factors governing microbial diversity and spatial distribution requires advanced mathematical analyses. Here, the bacterial community composition was analysed, along with a depth profile, in the open Adriatic Sea using amplicon sequencing of bacterial 16S rRNA and the Neural gas algorithm. The performed analysis classified the sample into four best matching units representing heterogenic patterns of the bacterial community composition. The observed parameters were more differentiated by depth than by area, with temperature and identified salinity as important environmental variables. The highest diversity was observed at the deep chlorophyll maximum, while bacterial abundance and production peaked in the upper layers. The most of the identified genera belonged to Proteobacteria, with uncultured AEGEAN-169 and SAR116 lineages being dominant Alphaproteobacteria, and OM60 (NOR5) and SAR86 being dominant Gammaproteobacteria. Marine Synechococcus and Cyanobium-related species were predominant in the shallow layer, while Prochlorococcus MIT 9313 formed a higher portion below 50 m depth. Bacteroidota were represented mostly by uncultured lineages (NS4, NS5 and NS9 marine lineages). In contrast, Actinobacteriota were dominated by a candidatus genus Ca. Actinomarina. A large contribution of Nitrospinae was evident at the deepest investigated layer. Our results document that neural network analysis of environmental data may provide a novel insight into factors affecting picoplankton in the open sea environment.

Download Full-text

Soil Bacterial Community Diversity and Composition as Affected by Tillage Intensity Treatments in Corn-Soybean Production Systems

Microbiology Research ◽

10.3390/microbiolres12010012 ◽

2021 ◽

Vol 12 (1) ◽

pp. 157-172

Author(s):

Shankar G. Shanmugam ◽

Normie W. Buehring ◽

Jon D. Prevost ◽

William L. Kingery

Keyword(s):

Microbial Community ◽

Bacterial Community ◽

Community Composition ◽

Production System ◽

Soil Microbial Community ◽

Production Systems ◽

Bacterial Community Composition ◽

Soybean Production ◽

Soil Microbial ◽

Soil Bacterial

Our understanding on the effects of tillage intensity on the soil microbial community structure and composition in crop production systems are limited. This study evaluated the soil microbial community composition and diversity under different tillage management systems in an effort to identify management practices that effectively support sustainable agriculture. We report results from a three-year study to determine the effects on changes in soil microbial diversity and composition from four tillage intensity treatments and two residue management treatments in a corn-soybean production system using Illumina high-throughput sequencing of 16S rRNA genes. Soil samples were collected from tillage treatments at locations in the Southern Coastal Plain (Verona, Mississippi, USA) and Southern Mississippi River Alluvium (Stoneville, Mississippi, USA) for soil analysis and bacterial community characterization. Our results indicated that different tillage intensity treatments differentially changed the relative abundances of bacterial phyla. The Mantel test of correlations indicated that differences among bacterial community composition were significantly influenced by tillage regime (rM = 0.39, p ≤ 0.0001). Simpson’s reciprocal diversity index indicated greater bacterial diversity with reduction in tillage intensity for each year and study location. For both study sites, differences in tillage intensity had significant influence on the abundance of Proteobacteria. The shift in the soil bacterial community composition under different tillage systems was strongly correlated to changes in labile carbon pool in the system and how it affected the microbial metabolism. This study indicates that soil management through tillage intensity regime had a profound influence on diversity and composition of soil bacterial communities in a corn-soybean production system.

Download Full-text