Tensile strength and organic matter fractions in aggregates of a grass-covered mined soil under early stage recovery

Several physico-chemical attributes are usually selected to evaluate the quality of mined soils under a process recovery. Although tensile strength and organic matter densiometric fractions extracted from aggregates are consolidated indicators of quality of agricultural soil, these attributes are rarely monitored in mined soils. We hypothesized that combining tensile strength, stability of aggregates and organic matter fractionation in free light and occluded light fractions is a potential strategy to detect effects of the root system of different plant species on soil quality. Therefore, we aimed to identify the most suitable plant species for promoting the recovery of soil quality, mainly with respect to soil structure improvement. The study was carried out in a coal mining area located in Candiota/Rio Grande do Sul State, Brazil. The evaluated plant species were Hemarthria altissima, Paspalum notatwn cv. Pensacola, Cynodon dactylon cv. Tifton, and Urochloa brizantha. Roots improved soil structure by disrupting highly compacted soil aggregates caused by compression due to traffic of heavy machinery during the topographic recomposition of the area. Based on the higher root density of Urochloa brizantha and consequently greater potential to improve soil structure and quality, our work strongly recommends the adoption of this plant species as a strategy to accelerate the recovery of the mined soil. Correlation of total organic carbon and carbon indensiometric fractions (free and ocluded light) with other soil/plant attributes was not clear, most probably due to the incipient stage of recovery of the soil. Therefore, these attributes were not efficient as indicators of soil quality at this point time. Our study highlighted that interpretation of non-mined soil attribute correlations cannot be directly transferred to mined soils, reinforcing the need to assume constructed soils as a new system, where monitoring of soil attributes in the long-term is key to anticipate improvement of soil quality.