We evaluated the bacterial and archaeal community dynamics and assembly in soils under forest, grassland and no-till cropping, using a high-throughput shotgun metagenomics approach. No significant alterations in alpha diversity were observed among different land uses, but beta diversity in grassland was lower than that observed in forest and no-till soils. Grassland communities showed assembly that predominantly followed the neutral model, i.e. high homogenizing selection with moderate dispersion, leading to biotic homogenization. Both no-till and forest soil communities were found to have assembly that predominantly followed a niche model, i.e. low rates of dispersal and weak homogenizing selection, resulting in maintenance of higher beta diversity relative to grasslands, indicating niche specialization or variable selection. Taken together, our results indicate that the patterns of assembly and their governing processes are dependent on the land use employed after deforestation, with consequences for taxa turnover and microbial functional potential.
Although the forest-to-agriculture conversion leads to a loss of diversity, the soybean rhizosphere selects a specific microbial community in order to keep important functions in a long-term cropping in Amazon soils.
Microbes constitute about a third of the Earth's biomass and are composed by an enormous genetic diversity. In a majority of environments the microbial communities play crucial roles for the ecosystem functioning, where a drastic biodiversity alteration or loss could lead to negative effects on the environment and sustainability. A central goal in microbiome studies is to elucidate the relation between microbial diversity to functions. A better understanding of the relation diversity-function would increase the ability to manipulate that diversity to improve plant and animal health and also setting conservation priorities. The recent advances in genomic methodologies in microbial ecology have provide means to assess highly complex communities in detail, making possible the link between diversity and the functions performed by the microbes. In this work we first explore some advances in bioinformatics tools to connect the microbial community biodiversity to their potential metabolism and after present some examples of how this information can be useful for a better understanding of the microbial role in the environment.
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