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      Short-term restoration practices change the bacterial community in degraded soil from the Brazilian semiarid

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          Abstract

          Land degradation by deforestation adversely impacts soil properties, and long-term restoration practices have been reported to potentially reverse these effects, particularly on soil microorganisms. However, there is limited knowledge regarding the short-term effects of restoration on the soil bacterial community in semiarid areas. This study evaluates the bacterial community in soils experiencing degradation (due to slash-and-burn deforestation) and restoration (utilizing stone cordons and revegetation), in comparison to a native soil in the Brazilian semiarid region. Three areas were selected: (a) under degradation; (b) undergoing short-term restoration; and (c) a native area, and the bacterial community was assessed using 16S rRNA sequencing on soil samples collected during both dry and rainy seasons. The dry and rainy seasons exhibited distinct bacterial patterns, and native sites differed from degraded and restoration sites. Chloroflexi and Proteobacteria phyla exhibited higher prevalence in degraded and restoration sites, respectively, while Acidobacteria and Actinobacteria were more abundant in sites undergoing restoration compared to degraded sites. Microbial connections varied across sites and seasons, with an increase in nodes observed in the native site during the dry season, more edges and positive connections in the restoration site, and a higher occurrence of negative connections in the degradation site during the rainy season. Niche occupancy analysis revealed that degradation favored specialists over generalists, whereas restoration exhibited a higher prevalence of generalists compared to native sites. Specifically, degraded sites showed a higher abundance of specialists in contrast to restoration sites. This study reveals that land degradation impacts the soil bacterial community, leading to differences between native and degraded sites. Restoring the soil over a short period alters the status of the bacterial community in degraded soil, fostering an increase in generalist microbes that contribute to enhanced soil stability.

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          Most cited references42

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          Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

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            Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample.

            The ongoing revolution in high-throughput sequencing continues to democratize the ability of small groups of investigators to map the microbial component of the biosphere. In particular, the coevolution of new sequencing platforms and new software tools allows data acquisition and analysis on an unprecedented scale. Here we report the next stage in this coevolutionary arms race, using the Illumina GAIIx platform to sequence a diverse array of 25 environmental samples and three known "mock communities" at a depth averaging 3.1 million reads per sample. We demonstrate excellent consistency in taxonomic recovery and recapture diversity patterns that were previously reported on the basis of metaanalysis of many studies from the literature (notably, the saline/nonsaline split in environmental samples and the split between host-associated and free-living communities). We also demonstrate that 2,000 Illumina single-end reads are sufficient to recapture the same relationships among samples that we observe with the full dataset. The results thus open up the possibility of conducting large-scale studies analyzing thousands of samples simultaneously to survey microbial communities at an unprecedented spatial and temporal resolution.
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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
                asfaruaj@yahoo.com.br
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                21 March 2024
                21 March 2024
                2024
                : 14
                : 6845
                Affiliations
                [1 ]Soil Microbial Ecology Group, Federal University of Piauí, ( https://ror.org/00kwnx126) Teresina, PI Brazil
                [2 ]Federal University of Ceara, ( https://ror.org/03srtnf24) Fortaleza, CE Brazil
                [3 ]Plant Science Department, Federal University of Piauí, ( https://ror.org/00kwnx126) Teresina, PI Brazil
                [4 ]Center for Nuclear Energy in Agriculture, University of Sao Paulo, ( https://ror.org/036rp1748) Piracicaba, SP Brazil
                [5 ]Soil Quality Lab., Agricultural Science Center, Federal University of Piauí, ( https://ror.org/00kwnx126) Teresina, PI Brazil
                Article
                57690
                10.1038/s41598-024-57690-y
                10957980
                38514851
                7e0af293-9f25-48eb-8be4-9a565ad5c282
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 16 October 2023
                : 20 March 2024
                Categories
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                Custom metadata
                © Springer Nature Limited 2024

                Uncategorized
                land degradation,amplicon sequencing,semiarid soils,soil microbial ecology,environmental sciences,microbial ecology

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