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A long-term study was conducted between 1985 and 2003 on rehabilitation trials at Sishen Iron Ore Mine, South Africa, to identify grass species that would survive in the artificial growth medium applied to the sites, and to determine the most suitable medium for sustainable vegetation growth. Vegetation establishment was tested at slopes of 18° and 34° and with five different cover materials. After 17 years of rehabilitation, investigations showed that weathered limestone sloped at 18° produced the highest percentage of plant cover and least erosion. Sixteen grass species were introduced and identified in the survey, with Eragrostis sp. and Cenchrus ciliaris as the dominant species. In 2004, new trials were initiated at the same mine to evaluate the effectiveness of different seeding methods and supplementation of the growth medium with organic material. After 4 years, hydro seeding was found to be the best method to distribute seeds evenly and to ensure uniform vegetation growth. Different engineering designs, such as changing the contour length and slope, had little influence on the measured parameters. A total of 28 grass species were identified in the sampling plots, with Enneapogon cenchroides and Cenchrus ciliaris as the dominant ones. Dehydrogenase activity was used as a proxy for microbial activity, and a positive association was observed between microbial activity and percentage organic carbon, emphasising the importance of soil organic matter in the soil development process

Asbestos mining has left a legacy of pollution in former mining areas that continues to negatively affect both the environment and local communities. In 2007, the Rehabilitation Prioritisation Index was developed as a scientific tool to indicate the preferred sequence for mine site rehabilitation and served as a departure point for the present investigation in which a database for the rehabilitation success of asbestos sites was developed. Broad-based quantitative and qualitative data, typically used for monitoring rehabilitation success, including amongst others, soil cover depth, physical and chemical soil properties, microbial activity, vegetation properties and small mammal abundance were analysed using multivariate statistics, specifically a redundancy analysis. The most representative model was subsequently selected for the classification of the rehabilitated sites. The multivariate analysis revealed those factors typically associated with rehabilitation success or failure, as well as essentials to be addressed. The feasibility of development of a rule set for rehabilitated site classification was firstly investigated using neural networks which also assisted in the selection of significant parameters. Results from the neural network approach were then used to guide parameter selection for the evolutionary algorithm software. The coordinate scores for the first two axes of the redundancy analysis served as targets for the evolutionary algorithms. Overall, a targeting match of 71 % for the first axis coordinates and 38 % for the second axis coordinates were obtained. Contributing parameters for the rule set included: Cl, K, pH, percentage organic carbon, Zn, NH4 and SO4 content of the sites.

Asbestos mining has left a legacy of pollution in former mining areas that continues to negatively affect both the environment and local communities. In 2007, the Rehabilitation Prioritisation Index was developed as a scientific tool to indicate the preferred sequence for mine site rehabilitation and served as a departure point for the present investigation in which a database for the rehabilitation success of asbestos sites was developed. Broad-based quantitative and qualitative data, typically used for monitoring rehabilitation success, including amongst others, soil cover depth, physical and chemical soil properties, microbial activity, vegetation properties and small mammal abundance were analysed using multivariate statistics, specifically a redundancy analysis. The most representative model was subsequently selected for the classification of the rehabilitated sites. The multivariate analysis revealed those factors typically associated with rehabilitation success or failure, as well as essentials to be addressed. The feasibility of development of a rule set for rehabilitated site classification was firstly investigated using neural networks which also assisted in the selection of significant parameters. Results from the neural network approach were then used to guide parameter selection for the evolutionary algorithm software. The coordinate scores for the first two axes of the redundancy analysis served as targets for the evolutionary algorithms. Overall, a targeting match of 71 % for the first axis coordinates and 38 % for the second axis coordinates were obtained. Contributing parameters for the rule set included: Cl, K, pH, percentage organic carbon, Zn, NH4 and SO4 content of the sites.

A long-term study was conducted between 1985 and 2003 on rehabilitation trials at Sishen Iron Ore Mine, South Africa, to identify grass species that would survive in the artificial growth medium applied to the sites, and to determine the most suitable medium for sustainable vegetation growth. Vegetation establishment was tested at slopes of 18° and 34° and with five different cover materials. After 17 years of rehabilitation, investigations showed that weathered limestone sloped at 18° produced the highest percentage of plant cover and least erosion. Sixteen grass species were introduced and identified in the survey, with Eragrostis sp. and Cenchrus ciliaris as the dominant species. In 2004, new trials were initiated at the same mine to evaluate the effectiveness of different seeding methods and supplementation of the growth medium with organic material. After 4 years, hydro seeding was found to be the best method to distribute seeds evenly and to ensure uniform vegetation growth. Different engineering designs, such as changing the contour length and slope, had little influence on the measured parameters. A total of 28 grass species were identified in the sampling plots, with Enneapogon cenchroides and Cenchrus ciliaris as the dominant ones. Dehydrogenase activity was used as a proxy for microbial activity, and a positive association was observed between microbial activity and percentage organic carbon, emphasising the importance of soil organic matter in the soil development process

This study investigated maturation and stability levels during composting of Quercus robur (QR) woodchips mixed with different nitrogen sources (horse manure, HM and lake mud, LM) for potential agronomic utilisation. The woodchips were mixed with HM and LM, respectively, at mixing ratios of 1QR:2HM or 1QR:2LM. The experiment was conducted in a greenhouse over 100 days. During composting, organic carbon and its fractioning and humification constituents were quantified. In the final compost product, pH, organic matter (OM), cation exchange capacity (CEC) and selected available nutrients were measured. Thermostability of compost, compared with that of soil and compost mixed with charcoal were also quantified. Results showed OM evolution during the composting process with total organic and extractable carbons and humification indices decreasing, while the degree of humification increased. Compost produced from the 1QR:2HM mix resulted in the highest available nutrients, CEC and OM content values in the final product. Thermogravimetric profiles indicated that compost OM thermostability was higher than that in soil and higher for the 1QR:2HM than the 1QR:2LM mix. Application of charcoal revealed no additional stabilising effect of OM in wood compost.

This study investigated maturation and stability levels during composting of Quercus robur (QR) woodchips mixed with different nitrogen sources (horse manure, HM and lake mud, LM) for potential agronomic utilisation. The woodchips were mixed with HM and LM, respectively, at mixing ratios of 1QR:2HM or 1QR:2LM. The experiment was conducted in a greenhouse over 100 days. During composting, organic carbon and its fractioning and humification constituents were quantified. In the final compost product, pH, organic matter (OM), cation exchange capacity (CEC) and selected available nutrients were measured. Thermostability of compost, compared with that of soil and compost mixed with charcoal were also quantified. Results showed OM evolution during the composting process with total organic and extractable carbons and humification indices decreasing, while the degree of humification increased. Compost produced from the 1QR:2HM mix resulted in the highest available nutrients, CEC and OM content values in the final product. Thermogravimetric profiles indicated that compost OM thermostability was higher than that in soil and higher for the 1QR:2HM than the 1QR:2LM mix. Application of charcoal revealed no additional stabilising effect of OM in wood compost.