scholarly journals Molecular ecological network analyses

2012 ◽  
Vol 13 (1) ◽  
pp. 113 ◽  
Author(s):  
Ye Deng ◽  
Yi-Huei Jiang ◽  
Yunfeng Yang ◽  
Zhili He ◽  
Feng Luo ◽  
...  
2021 ◽  
Vol 188 ◽  
pp. 116540
Author(s):  
Tao Ya ◽  
Shuai Du ◽  
Zhenyang Li ◽  
Shidi Liu ◽  
Minghan Zhu ◽  
...  

Author(s):  
Xiaoxiao Li ◽  
Qi Zhang ◽  
Jing Ma ◽  
Yongjun Yang ◽  
Yifei Wang ◽  
...  

Irrigation has been applied on a large scale for the improvement of grain yield per hectare and production stability. However, the dryland-to-paddy conversion affects the ecological environment of areas of long-term dry farming, especially soil microorganisms. Little attention has been paid to the changes in microbial communities and the interactions between their populations in this process. Therefore, in this paper, the compositions and diversity of soil bacterial and fungal communities were explored through a combination of high-throughput sequencing technology and molecular ecological network methods using bacterial 16S rRNA and fungal ITS. The results showed that: (1) both the abundance and diversity of soil bacteria and fungi decreased in a short time, and the abundance of Actinobacteria, Firmicutes and Olpidiomycota varied greatly. (2) Compared to dry land, the modular structure of interaction networks and interspecific relationships of bacterial and fungal communities in paddy soil were simpler, and the network became more unstable. A cooperative relationship dominated in the molecular ecological network of bacteria, while a competitive relationship was dominant in the network of fungi. Actinobacteria and Firmicutes were the dominant bacterial species in dry land and paddy field, respectively. Ascomycota was dominant in the fungal communities of both dry land and paddy field. (3) The change in soil environmental factors, such as pH, electrical conductivity (EC), organic matter (OM) and available potassium (AK), directly affected the soil microbial community structure, showing a significant correlation (p < 0.05). These environmental factors also influenced the dominant microbial species. Microorganisms are the most important link in the carbon and nitrogen cycles of soil, and a large-scale dryland-to-paddy conversion may reduce the ecological stability of regional soil.


2021 ◽  
Author(s):  
Samantha J Gleich ◽  
Jacob A Cram ◽  
Jake L Weissman ◽  
David A Caron

Ecological network analyses are used to identify potential biotic interactions between microorganisms from species abundance data. These analyses are often carried out using time-series data; however, time-series networks have unique statistical challenges. Time-dependent species abundance data can lead to species co-occurrence patterns that are not a result of direct, biotic associations and may therefore result in inaccurate network predictions. Here, we describe a generalize additive model (GAM)-based data transformation that removes time-series signals from species abundance data prior to running network analyses. Validation of the transformation was carried out by generating mock, time-series datasets, with an underlying covariance structure, running network analyses on these datasets with and without our GAM transformation, and comparing the network outputs to the known covariance structure of the simulated data. The results revealed that seasonal abundance patterns substantially decreased the accuracy of the inferred networks. Additionally, the GAM transformation increased the F1 score of inferred ecological networks on average and improved the ability of network inference methods to capture important features of network structure. This study underscores the importance of considering temporal features when carrying out network analyses and describes a simple, effective tool that can be used to improve results.


Sign in / Sign up

Export Citation Format

Share Document