Events of soil contamination by heavy metals are mostly related to human activities that release these metals into the environment as emissions or effluents. Among the industrial activities related to heavy metal pollution, cement production plants are considered one of the most common sources. In this work we applied the High-throughput sequencing approach called 16 S rDNA metabarcoding to perform the taxonomic characterization of the prokaryotic communities of the soil surrounding three cement plants as well as two areas outside the influence of the cement plants that represented agricultural production environments free of heavy metal contamination (control areas). We applied the environmental genomics approaches known as "structural community metrics" (α- and β-diversity metrics) and "functional community metrics" (PICRUSt2 approach) to verify whether or not the effects of heavy metal contamination in the study area generated impacts on soil bacterial communities. We found that the impact related to the elevation of heavy metal concentration due to the operation of cement plants in the surrounding soil can be considered smooth according to globally recognized indices such as Igeo. However, we identified that both the taxonomic and functional structures of the communities surrounding cement plants were different from those found in the control areas. We consider that our findings contribute significantly to the general understanding of the effects of heavy metals on the soil ecosystem by showing that light contamination can disturb the dynamics of ecosystem services provided by soil, specifically those associated with microbial metabolism.
Keywords: Contamination; Environmental genomics; Heavy metals; Metabarcoding; Soil.
© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.