Soil-Borne Microbiome: Linking Diversity to Function
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Soil microorganisms are sensitive to environment disturbances, and such alterations have consequences on microbial diversity and functions. Our hypothesis is that alpha diversity of microbial communities and functional diversity decrease from undisturbed to disturbed soils, with consequences for functional redundancy in the soil ecosystem. To test this hypothesis, we used soil DNA shotgun metagenomics approach to assess the soil microbiome in a chronosequence of land-use from a native tropical forest, followed by deforestation and cultivation of soybean croplands and pasture in different seasons. Agriculture and pasture soils were among the most diverse and presented higher functional redundancy, which is important to maintain the ecosystem functioning after the forest conversion. On the other hand, the ecosystem equilibrium in forest is maintained based on a lower alpha diversity but higher abundance of microorganisms. Our results indicate that land-use change alters the structure and composition of microbial communities; however, ecosystem functionality is overcome by different strategies based on the abundance and diversity of the communities.
KeywordsSoil microbiome Microbial ecology Soil function redundancy Tropical rainforest Land-use change Shotgun metagenomics
This study was supported by a grant from Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP 2010/20353-7, 2008/58114-3, 2011/51749-6), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES/Wageningen 1240/11-0), and Conselho Nacional de Desenvolvimento Científico (CNPq 485801/2011-6). Publication 5700 of the Netherlands Institute of Ecology (NIOO-KNAW).
Metagenome sequences available in MG-RAST server under the project “Amazon Soil Metagenome 2_Mendes” (Project ID 1519).
LWM and SMT contributed equally to this work. LWM, SMT, JAV, and EEK have substantial contributions to conception and design of the study and interpretation of data. LWM and AAN collected the samples and obtained the data. LWM, MH, and EEK conducted bioinformatics and statistical analyses. LWM and EEK wrote the paper. All authors discussed the results and commented on the manuscript.
Additional supporting information may be found in the online version of this article.
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