Identifying appropriate reference ecosystems based on soil indicators to evaluate postmining reclamation: A multivariate framework

  • Alves M
  • Assis I
  • Oliveira F
  • et al.
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Abstract

Large-scale mining operations, such as those associated with iron extraction, disturb soils and vegetation and create the need for effective rehabilitation practices. The Iron Quadrangle region of southeastern Brazil is one of the world’s biodiversity hotspots; however, iron mining activities threaten many natural and seminatural ecosystem types in which many rare/protected species occur. The Iron Quadrangle has four main ecosystem types: Atlantic Forest (AF), ferruginous rupestrian grassland with dense vegetation (FRG-D); ferruginous rupestrian grassland with sparse vegetation (FRG-S); and quartzite rupestrian grassland (QRG). To support rehabilitation and monitoring plans, we evaluated reference areas and identified soil and vegetative attributes that best differentiated between these four ecosystems. We measured thirty-four physical, chemical, and biological soil properties and two vegetation parameters and, using a multivariate analysis, detected: 1) correlations between properties and 2) differences between areas. We identified twelve properties that best differentiated the areas (in order from most to least relevant): nickel content; exchangeable aluminum; clay content; above-ground vegetation volume; aluminum saturation; particle density; bulk density; arsenic content; zinc content; lead content, fine sand plus silt content; and fine sand content. Soil physicochemical properties proved to be more sensitive to differences in ecosystem type, and in particular, parameters related to fertility and the presence of metals and semi-metals differentiated the AF from the FRG-D and FRG-S. Soil physical properties, including fine sand and silt content, were most important for differentiating QRG from the other ecosystems, possibly resulting from the exposure of quartzite material to erosive processes. This study demonstrates the importance of identifying appropriate reference areas for post-mining reclamation.

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APA

Alves, M. Q., Assis, I. R. de, Oliveira, F. Z., Neves, J. C. L., & Stewart, R. D. (2023). Identifying appropriate reference ecosystems based on soil indicators to evaluate postmining reclamation: A multivariate framework. Revista Brasileira de Ciência Do Solo, 47. https://doi.org/10.36783/18069657rbcs20230014

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