scholarly journals Molecular ecological network analysis of the response of soil microbial communities to depth gradients in farmland soils

2020 ◽  
Vol 9 (3) ◽  
Author(s):  
Hang Yu ◽  
Dongmei Xue ◽  
Yidong Wang ◽  
Wei Zheng ◽  
Guilong Zhang ◽  
...  
Keyword(s):  
Network Analysis ◽  
Microbial Communities ◽  
Soil Microbial Communities ◽  
Ecological Network ◽  
Ecological Network Analysis ◽  
Soil Microbial ◽  
Farmland Soils ◽  
Depth Gradients ◽  
Molecular Ecological Network

scholarly journals The influence of e-waste recycling on the molecular ecological network of soil microbial communities in Pakistan and China

2017 ◽  
Vol 231 ◽  
pp. 173-181 ◽  
Author(s):  
Longfei Jiang ◽  
Zhineng Cheng ◽  
Dayi Zhang ◽  
Mengke Song ◽  
Yujie Wang ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Soil Microbial Communities ◽  
Waste Recycling ◽  
Ecological Network ◽  
Soil Microbial ◽  
Molecular Ecological Network

scholarly journals Comparison of soil microbial community between reseeding grassland and natural grassland in Songnen Meadow

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Ruifen Zhu ◽  
Jielin Liu ◽  
Jianli Wang ◽  
Weibo Han ◽  
Zhongbao Shen ◽  
...  
Keyword(s):  
Microbial Community ◽  
Network Analysis ◽  
Soil Microbial Community ◽  
Vegetation Restoration ◽  
Ecological Network ◽  
Soil Microbial Community Structure ◽  
Ecological Network Analysis ◽  
Soil Microbial ◽  
Natural Grassland ◽  
Molecular Ecological Network

Abstract Microorganisms have important ecological functions in ecosystems. Reseeding is considered as one of the main strategies for preventing grassland degradation in China. However, the response of soil microbial community and diversity to reseeding grassland (RG) and natural grassland (NG) remains unclear, especially in the Songnen Meadow. In this study, the soil microbial community compositions of two vegetation restoration types (RG vs NG) were analyzed using a high-throughput sequencing technique. A total of 23,142 microbial OTUs were detected, phylogenetically derived from 11 known bacterial phyla. Soil advantage categories included Proteobacteria, Acidobacteria, Actinobacteria, and Bacteroidetes, which together accounted for > 78% of the all phyla in vegetation restoration. The soil microbial diversity was higher in RG than in NG. Two types of vegetation restoration had significantly different characteristics of soil microbial community (P < 0.001). Based on a molecular ecological network analysis, we found that the network in RG had a longer average path distance and modularity than in NG network, making it more resilient to environment changes. Meanwhile, the results of the canonical correspondence analysis and molecular ecological network analysis showed that soil pH (6.34 ± 0.35 in RG and 7.26 ± 0.28 in NG) was the main factor affecting soil microbial community structure, followed by soil moisture (SM) in the Songnen meadow, China. Besides, soil microbial community characteristics can vary significantly in different vegetation restoration. Thus, we suggested that it was necessary and reasonable for this area to popularize reseeding grassland in the future.

scholarly journals From Diversity to Complexity: Microbial Networks in Soils

2021 ◽  
Author(s):  
Ksenia Guseva ◽  
Sean Darcy ◽  
Eva Simon ◽  
Lauren V. Alteio ◽  
Alicia Montesinos-Navarro ◽  
...  
Keyword(s):  
Network Analysis ◽  
Microbial Communities ◽  
Microbial Ecology ◽  
Soil Microbial Communities ◽  
Small Scale ◽  
Soil Microbial Ecology ◽  
Test Dataset ◽  
Soil Microbial ◽  
Network Properties ◽  
Plant Animal Interactions

Network analysis has been used for many years in ecological research to analyze organismal associations, for example in food webs, plant-plant or plant-animal interactions. Although network analysis is widely applied in microbial ecology, only recently has it entered the realms of soil microbial ecology, shown by a rapid rise in studies applying co-occurrence analysis to soil microbial communities. While this application offers great potential for deeper insights into the ecological structure of soil microbial ecosystems, it also brings new challenges related to the specific characteristics of soil datasets and the type of ecological questions that can be addressed. In this Perspectives Paper we assess the challenges of applying network analysis to soil microbial ecology due to the small-scale heterogeneity of the soil environment and the nature of soil microbial datasets. We review the different approaches of network construction that are commonly applied to soil microbial datasets and discuss their features and limitations. Using a test dataset of microbial communities from two depths of a forest soil, we demonstrate how different experimental designs and network constructing algorithms affect the structure of the resulting networks, and how this in turn may influence ecological conclusions. We will also reveal how assumptions of the construction method, methods of preparing the dataset, an definitions of thresholds affect the network structure. Finally, we discuss the particular questions in soil microbial ecology that can be approached by analyzing and interpreting specific network properties. Targeting these network properties in a meaningful way will allow applying this technique not in merely descriptive, but in hypothesis-driven research.

scholarly journals Using network analysis to explore co-occurrence patterns in soil microbial communities

2011 ◽  
Vol 6 (2) ◽  
pp. 343-351 ◽  
Author(s):  
Albert Barberán ◽  
Scott T Bates ◽  
Emilio O Casamayor ◽  
Noah Fierer
Keyword(s):  
Network Analysis ◽  
Microbial Communities ◽  
Soil Microbial Communities ◽  
Soil Microbial ◽  
Occurrence Patterns
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