Abstract

Mine ecological monitoring schemes are often conducted only to address compliance and in some cases do not have the sufficient statistical power or understanding of ecological systems to assess, quantitatively, the meeting of rehabilitation targets or mine impacts. Monitoring schemes for rehabilitation commonly rely on analogue sites or premining baselines (reference sites) to assess whether rehabilitation sites are ecologically similar and thus successfully rehabilitated. In the case of monitoring for mine impacts, if the impacted sites diverge from reference data, the site is considered to be impacted. Fundamental to any monitoring scheme is testing the sampling design to ensure that it can detect these differences if they are present through adequate sample sizes (ie statistical power). However, a good understanding of the ecological system is required to ensure that differences detected are ecologically significant. Modelling ecosystem properties can provide a quantitative understanding of how ecosystems change over time and space, in response to natural environmental variations and thus aid in determining significant ecological differences. Furthermore, modelling methods can be used to predict future ecosystem states. Within the ecological literature, guidelines for robust statistical monitoring designs and modelling methods exist but are not routinely being used in the mining industry. This paper uses simple examples to discuss: problems with current compliance monitoring methods; importance of robust statistical techniques; and how modelling can assist rehabilitation assessment and guide monitoring schemes. The aim of this paper is to describe general monitoring and modelling methods that could be potentially used for mine site monitoring and closure assessment. These methods are often considered by mining companies as an extra expense that provide little practical benefit, and the domain of academia; however, engaging these methods may be more cost-effective in the long-run than conducting untargeted monitoring schemes that give no confidence to regulators on whether rehabilitation criteria have been met. Furthermore, monitoring programs in mining contexts provide a good opportunity to better understand long-term ecological patterns and test the application of more rigorous modelling approaches as the life of many mines tends to be greater than ten years.