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      Tree rows in temperate agroforestry croplands alter the composition of soil bacterial communities

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      PLoS ONE
      Public Library of Science

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          Abstract

          Background

          Tree-based intercropping (agroforestry) has been advocated to reduce adverse environmental impacts of conventional arable cropping. Modern agroforestry systems in the temperate zone are alley-cropping systems that combine rows of fast-growing trees with rows of arable crops. Soil microbial communities in these systems have been investigated intensively; however, molecular studies with high taxonomical resolution are scarce.

          Methods

          Here, we assessed the effect of temperate agroforestry on the abundance, diversity and composition of soil bacterial communities at three paired poplar-based alley cropping and conventional monoculture cropland systems using real-time PCR and Illumina sequencing of bacterial 16S rRNA genes. Two of the three systems grew summer barley ( Hordeum vulgare); one system grew maize ( Zea mays) in the sampling year. To capture the spatial heterogeneity induced by the tree rows, soil samples in the agroforestry systems were collected along transects spanning from the centre of the tree rows to the centre of the agroforestry crop rows.

          Results

          Tree rows of temperate agroforestry systems increased the abundance of soil bacteria while their alpha diversity remained largely unaffected. The composition of the bacterial communities in tree rows differed from those in arable land (crop rows of the agroforestry systems and conventional monoculture croplands). Several bacterial groups in soil showed strong association with either tree rows or arable land, revealing that the introduction of trees into arable land through agroforestry is accompanied by the introduction of a tree row-associated microbiome.

          Conclusion

          The presence of tree row-associated bacteria in agroforestry increases the overall microbial diversity of the system. We speculate that the increase in biodiversity is accompanied by functional diversification. Differences in plant-derived nutrients (root exudates and tree litter) and management practices (fertilization and tillage) likely account for the differences between bacterial communities of tree rows and arable land in agroforestry systems.

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          Most cited references69

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          NIH Image to ImageJ: 25 years of image analysis

          For the past twenty five years the NIH family of imaging software, NIH Image and ImageJ have been pioneers as open tools for scientific image analysis. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
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            DADA2: High resolution sample inference from Illumina amplicon data

            We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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              The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

              SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – original draft
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                10 February 2021
                2021
                : 16
                : 2
                : e0246919
                Affiliations
                [001]Molecular Phytopathology and Mycotoxin Research, Faculty of Agricultural Sciences, University of Goettingen, Goettingen, Germany
                Centro de Edafologia y Biologia Aplicada del Segura, SPAIN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0003-1107-7540
                https://orcid.org/0000-0002-6532-5856
                Article
                PONE-D-20-31114
                10.1371/journal.pone.0246919
                7875383
                33566862
                fd926cf7-d7c5-454e-bac6-0e7135280eac
                © 2021 Beule, Karlovsky

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 3 October 2020
                : 29 January 2021
                Page count
                Figures: 6, Tables: 1, Pages: 20
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100002347, Bundesministerium für Bildung und Forschung;
                Award ID: 031A562A
                Funded by: funder-id http://dx.doi.org/10.13039/501100002347, Bundesministerium für Bildung und Forschung;
                Award ID: 031B0510A
                Funded by: Open Access Publication Funds of the Göttingen University
                Award Recipient :
                This study was financed by the German Federal Ministry of Education and Research (BMBF), in the framework of the Bonares-SIGNAL project (funding codes: 031A562A and 031B0510A). We acknowledge support by the Open Access Publication Funds of the Göttingen University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Agriculture
                Agricultural Soil Science
                Earth Sciences
                Soil Science
                Agricultural Soil Science
                Biology and Life Sciences
                Agriculture
                Agroecology
                Agroforests
                Biology and Life Sciences
                Ecology
                Agroecology
                Agroforests
                Ecology and Environmental Sciences
                Ecology
                Agroecology
                Agroforests
                Biology and Life Sciences
                Agriculture
                Forestry
                Agroforests
                Biology and Life Sciences
                Organisms
                Bacteria
                Biology and Life Sciences
                Agriculture
                Crop Science
                Crops
                Biology and Life Sciences
                Agriculture
                Agricultural Methods
                Monoculture Cropping
                Biology and Life Sciences
                Organisms
                Eukaryota
                Plants
                Trees
                Research and Analysis Methods
                Electrophoretic Techniques
                Gel Electrophoresis
                Biology and life sciences
                Genetics
                DNA
                DNA libraries
                Biology and life sciences
                Biochemistry
                Nucleic acids
                DNA
                DNA libraries
                Custom metadata
                Sequencing data have been deposited at NCBI’s Sequence Read Achieve (BioProject PRJNA667193).

                Uncategorized
                Uncategorized

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