Microbial Indicators Show the Rehabilitation Flow of Soil Microbiota After the Brumadinho Dam Collapse

Iron ore extraction can lead to significant environmental degradation, particularly due to the generation of tailings during the beneficiation process. This issue was highlighted by the B1 dam collapse in Brumadinho, Brazil, in 2019. Therefore, the study and monitoring of affected areas is essential to assess soil quality throughout the rehabilitation process, whether through natural recovery or active rehabilitation practices. Microbial indicators can serve as valuable tools to track the recovery of these areas, given their high sensitivity and rapid response to environmental changes. The aim of this study was to evaluate soil microbial indicators, such as enzyme activity, microbial biomass carbon, microbial basal respiration and microbial diversity, and to select microbial approaches for monitoring the area affected by mining tailings in Brumadinho. The results indicated that the reference area initially outperformed the affected area on all evaluated bioindicators, highlighting environmental stress in the affected zone. Over the course of the study, the two areas began to show greater similarity, suggesting a natural recovery of the soil together with the return of natural vegetation. Indicators such as microbial carbon biomass went from values close to 50 mg of C Kg of soil−1 in the affected area, to around 200, statistically equal to the reference. qCO2 also varied in the affected area to values statistically equal to those of the reference over time, variated in the first collection to 0.25 mg of C-CO2 mg of C−1 h−1 in the affected area against 0.1 in the reference area; in the last collection, both areas presented values close to 0.2. Enzymatic activity had superior values in the reference area about the affected area, being urease, and arylsulfatase more sensitive to show differences between areas over time. The metataxonomic data again revealed indicator species for each environment, including genera such as Bacillus, Mycobacterium, Acidibacter, and Burkholderia representative of the reference, and the genera Ramlibacter, Sinomonas, Psedarthrobacter, and Knoellia indicators of the affected area. By the end of this study, the applicability of microbial indicators for monitoring soil microbiota and its ecosystem services was successfully demonstrated. In addition, specific microbial indicators were proposed for monitoring areas affected by iron mining tailings.

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Publication Details

Journal
Mining
Published
2025-02-26
DOI
https://doi.org/10.3390/mining5010016
Citations
1
Primary Topic
Sustainability and Ecological Systems Analysis
Type
article
Field-Weighted Citation Impact
0.80

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article

Microbial Indicators Show the Rehabilitation Flow of Soil Microbiota After the Brumadinho Dam Collapse

Paul J. Goulart, Igor Rodrigues de Assis, Wiane Meloni Silva, Amanda Tristão Santini et al.
1 citations
Mining
Sustainability and Ecological Systems Analysis
0.80
article

Microbial Indicators Show the Rehabilitation Flow of Soil Microbiota After the Brumadinho Dam Collapse

Paul J. Goulart, Igor Rodrigues de Assis, Wiane Meloni Silva, Amanda Tristão Santini, Sérgio Oliveira de Paula, Alan Emanuel Silva Cerqueira, Cynthia Canêdo da Silva, Diego Aniceto, Lutecia Rigueira Medina, Alex Castro Gazolla
article en
1 citations

Abstract

Iron ore extraction can lead to significant environmental degradation, particularly due to the generation of tailings during the beneficiation process. This issue was highlighted by the B1 dam collapse in Brumadinho, Brazil, in 2019. Therefore, the study and monitoring of affected areas is essential to assess soil quality throughout the rehabilitation process, whether through natural recovery or active rehabilitation practices. Microbial indicators can serve as valuable tools to track the recovery of these areas, given their high sensitivity and rapid response to environmental changes. The aim of this study was to evaluate soil microbial indicators, such as enzyme activity, microbial biomass carbon, microbial basal respiration and microbial diversity, and to select microbial approaches for monitoring the area affected by mining tailings in Brumadinho. The results indicated that the reference area initially outperformed the affected area on all evaluated bioindicators, highlighting environmental stress in the affected zone. Over the course of the study, the two areas began to show greater similarity, suggesting a natural recovery of the soil together with the return of natural vegetation. Indicators such as microbial carbon biomass went from values close to 50 mg of C Kg of soil−1 in the affected area, to around 200, statistically equal to the reference. qCO2 also varied in the affected area to values statistically equal to those of the reference over time, variated in the first collection to 0.25 mg of C-CO2 mg of C−1 h−1 in the affected area against 0.1 in the reference area; in the last collection, both areas presented values close to 0.2. Enzymatic activity had superior values in the reference area about the affected area, being urease, and arylsulfatase more sensitive to show differences between areas over time. The metataxonomic data again revealed indicator species for each environment, including genera such as Bacillus, Mycobacterium, Acidibacter, and Burkholderia representative of the reference, and the genera Ramlibacter, Sinomonas, Psedarthrobacter, and Knoellia indicators of the affected area. By the end of this study, the applicability of microbial indicators for monitoring soil microbiota and its ecosystem services was successfully demonstrated. In addition, specific microbial indicators were proposed for monitoring areas affected by iron mining tailings.

MiningVol. 5(1)
Universidade Federal de Viçosa (BR), Vale (Brazil) (BR), The University of Texas at Austin (US)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação de Amparo à Pesquisa do Estado de Minas Gerais
Openalex Percentile: Top 32%
Sustainability and Ecological Systems Analysis
0.80
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