Authors: Mucina, L; Tsakalos, JL; Macintyre, PD

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Mucina, L, Tsakalos, JL & Macintyre, PD 2019, 'Ecology, biodiversity and mining: science and solving the challenges', in AB Fourie & M Tibbett (eds), Mine Closure 2019: Proceedings of the 13th International Conference on Mine Closure, Australian Centre for Geomechanics, Perth, pp. 19-34,

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Mining has an impact on the ecology and biodiversity of an area, and this impact is required to be mitigated under regulatory requirements. The mitigation is achieved by applying measures, deeply rooted in scientific knowledge, of the functioning of the impacted (and rehabilitated) ecosystems and the biota supported by these ecosystems. This paper focusses on selected issues of the pre-mining ecology and biodiversity surveys and the scientific basis of regulatory requirements. Using Western Australian experience and drawing on comparisons from other countries, this paper addresses two challenges. The first is the classification of vegetation of mining tenements to inform on the variability of vegetation using a series of data-analytical experiments. The paper reveals flaws in the current practise aimed at recognition and description of plant communities in vegetation surveys. Concrete steps serving and enhancing the clarity and plausibility of regulatory tools (guidance manuals) are identified. It also advises on what we should do if we find discrepancies between the regulatory expectations and the level they reflect current scientific knowledge. The second is the comparative and spatial aspects of the identification of communities of conservation interest. The paper further identifies the missing vital information of the vegetation mapping procedures and briefly analyses the need for tools assisting assessment of conservation value of the vegetation classifications, including the building of a centralised vegetation database, formulation of vegetation and habitat classification systems, and construction of scientifically sound and ecologically informative vegetation maps at various scales of complexity.

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