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      Influence of Soil and Water Conservation Measures on Soil Microbial Communities in a Citrus Orchard of Southeast China

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          Abstract

          Soil microbes play a crucial role in ecosystem function. Here, the effects of soil and water conservation measures on soil microbial community structures, biodiversity, and co-occurrence networks are investigated and compared. We sampled soils at three different depths (0–10 cm, 10–20 cm and 20–40 cm) in a citrus orchard that uses long-term soil and water conservation measures, which includes Bermuda grass strip intercropping (BS), Bermuda grass full coverage (BF), Radish–soybean crop rotation strip intercropping (RS) and clear tillage orchards (CT). Results demonstrated that BS and BF yields a significant increase in bacterial richness and diversity of fungal in soils, while BF contains more beneficial microbial taxa, especially those with degrading and nutrient cycling capabilities. Microbial community structures differed significantly among the applied measures. In addition, co-occurrence networks under BS, BF and RS were more complex and robust than that of CT, and the stability of the network in BF was the highest. Microbial interactive stability and potential interactions in bacterial networks were stronger than those of fungi. The distribution of dominant phyla showed that Chloroflexi and Ascomycota dominated the different soil and water conservation measures. Proteobacteria and Ascomycota are revealed to be keystone species in bacterial networks and fungal networks, respectively, while Proteobacteria was the keystone species in microbial networks. Though the relative abundance of Chloroflexi turned out to have increased among the four measures, the relative abundance for Proteobacteria, Acidobacteria and Actinobacteria all decreased along the soil profile, with Acidobacteria under BS to be an exception. Soils under BS and BF had higher total nitrogen, microbial biomass carbon and organic carbon than CT and RS. Organic carbon(C) and total nitrogen(N) in soil were the major drivers of these bacterial community patterns, while there was no significant correlation between them and fungi. Overall, BF increases soil nutrients and microbial diversity, and also promotes ecological stability and interrelations among microbial taxa that collectively improve soil quality in the citrus orchard studied. Therefore, we recommended BF to be an ideal application for citrus orchards of southeast China.

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          Most cited references55

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          Molecular ecological network analyses

          Background Understanding the interaction among different species within a community and their responses to environmental changes is a central goal in ecology. However, defining the network structure in a microbial community is very challenging due to their extremely high diversity and as-yet uncultivated status. Although recent advance of metagenomic technologies, such as high throughout sequencing and functional gene arrays, provide revolutionary tools for analyzing microbial community structure, it is still difficult to examine network interactions in a microbial community based on high-throughput metagenomics data. Results Here, we describe a novel mathematical and bioinformatics framework to construct ecological association networks named molecular ecological networks (MENs) through Random Matrix Theory (RMT)-based methods. Compared to other network construction methods, this approach is remarkable in that the network is automatically defined and robust to noise, thus providing excellent solutions to several common issues associated with high-throughput metagenomics data. We applied it to determine the network structure of microbial communities subjected to long-term experimental warming based on pyrosequencing data of 16 S rRNA genes. We showed that the constructed MENs under both warming and unwarming conditions exhibited topological features of scale free, small world and modularity, which were consistent with previously described molecular ecological networks. Eigengene analysis indicated that the eigengenes represented the module profiles relatively well. In consistency with many other studies, several major environmental traits including temperature and soil pH were found to be important in determining network interactions in the microbial communities examined. To facilitate its application by the scientific community, all these methods and statistical tools have been integrated into a comprehensive Molecular Ecological Network Analysis Pipeline (MENAP), which is open-accessible now (http://ieg2.ou.edu/MENA). Conclusions The RMT-based molecular ecological network analysis provides powerful tools to elucidate network interactions in microbial communities and their responses to environmental changes, which are fundamentally important for research in microbial ecology and environmental microbiology.
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            The ecology of the microbiome: Networks, competition, and stability.

            The human gut harbors a large and complex community of beneficial microbes that remain stable over long periods. This stability is considered critical for good health but is poorly understood. Here we develop a body of ecological theory to help us understand microbiome stability. Although cooperating networks of microbes can be efficient, we find that they are often unstable. Counterintuitively, this finding indicates that hosts can benefit from microbial competition when this competition dampens cooperative networks and increases stability. More generally, stability is promoted by limiting positive feedbacks and weakening ecological interactions. We have analyzed host mechanisms for maintaining stability-including immune suppression, spatial structuring, and feeding of community members-and support our key predictions with recent data.
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              Using network analysis to explore co-occurrence patterns in soil microbial communities.

              Exploring large environmental datasets generated by high-throughput DNA sequencing technologies requires new analytical approaches to move beyond the basic inventory descriptions of the composition and diversity of natural microbial communities. In order to investigate potential interactions between microbial taxa, network analysis of significant taxon co-occurrence patterns may help to decipher the structure of complex microbial communities across spatial or temporal gradients. Here, we calculated associations between microbial taxa and applied network analysis approaches to a 16S rRNA gene barcoded pyrosequencing dataset containing >160 000 bacterial and archaeal sequences from 151 soil samples from a broad range of ecosystem types. We described the topology of the resulting network and defined operational taxonomic unit categories based on abundance and occupancy (that is, habitat generalists and habitat specialists). Co-occurrence patterns were readily revealed, including general non-random association, common life history strategies at broad taxonomic levels and unexpected relationships between community members. Overall, we demonstrated the potential of exploring inter-taxa correlations to gain a more integrated understanding of microbial community structure and the ecological rules guiding community assembly.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Microorganisms
                Microorganisms
                microorganisms
                Microorganisms
                MDPI
                2076-2607
                04 February 2021
                February 2021
                : 9
                : 2
                : 319
                Affiliations
                [1 ]School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China; wbb15279839084@ 123456163.com (B.W.); atdevlin@ 123456jxnu.edu.cn (A.T.D.); shuwang0717@ 123456jxnu.edu.cn (W.S.); zhangh2013@ 123456jxnu.edu.cn (H.Z.); dingmingjun1128@ 123456163.com (M.D.)
                [2 ]Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China
                [3 ]Jiangxi Institute of Soil and Water Conservation, Nanchang 330029, China; xss19811213@ 123456163.com
                Author notes
                Article
                microorganisms-09-00319
                10.3390/microorganisms9020319
                7913868
                33557135
                f214befc-26dc-4c3e-8a0f-d072e65144fe
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 09 January 2021
                : 01 February 2021
                Categories
                Article

                soil and water conservation measures,high-throughput sequencing,soil bacterial–fungal,community and network,diversity

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