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Ecotoxicology ; 22(10): 1526-37, 2013 Dec.
Article in English | MEDLINE | ID: mdl-24114185

ABSTRACT

Recovery of arsenic contaminated areas is a challenge society faces throughout the world. Revegetation associated with microbial activity can play an essential role in this process. This work investigated biological attributes in a gold mining area with different arsenic contents at different sites under two types of extant revegetation associated with cover layers of the soil: BS, Brachiaria sp. and Stizolobium sp., and LEGS, Acacia crassicarpa, A. holosericea, A. mangium, Sesbania virgata, Albizia lebbeck and Pseudosamanea guachapele. References were also evaluated, comprising the following three sites: B1, weathered sulfide substrate without revegetation; BM, barren material after gold extraction and PRNH (private reserve of natural heritage), an uncontaminated forest site near the mining area. The organic and microbial biomass carbon contents and substrate-induced respiration rates for these sites from highest to lowest were: PRNH > LEGS > BS > B1 and BM. These attributes were negatively correlated with soluble and total arsenic concentration in the soil. The sites that have undergone revegetation (LEGS and BS) had higher densities of bacteria, fungi, phosphate solubilizers and ammonium oxidizers than the sites without vegetation. Principal component analysis showed that the LEGS site grouped with PRNH, indicating that the use of leguminous species associated with an uncontaminated soil cover layer contributed to the improvement of the biological attributes. With the exception of acid phosphatase, all the biological attributes were indicators of soil recovery, particularly the following: microbial carbon, substrate-induced respiration, density of culturable bacteria, fungi and actinobacteria, phosphate solubilizers and metabolic quotient.


Subject(s)
Arsenic/toxicity , Soil Microbiology , Soil Pollutants/toxicity , Soil/chemistry , Biodegradation, Environmental , Biomass , Brazil , Environmental Monitoring , Mining , Photometry , Spectrophotometry, Atomic
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