Historically nations have traded-off environmental degradation to achieve economic development. However, a turning point is sometimes observed above a certain level of wealth where countries invest in pro-environmental efforts. This inverted U-shape relationship between environmental degradation and a country’s GDP is the environmental Kuznets curve (EKC). If the Sustainable Development Goals are to be achieved by 2030, then mechanisms by which nations can ‘skip’ to the EKC turning point (whilst avoiding outsourcing degradation) need to be identified. Mining can be environmentally destructive but generate huge economic value from relatively small areas of land (in contrast to, for example, extensive agriculture). Can mining allow poorer nations rich in biodiversity to minimise the environmental trade-offs faced during development? We will use technological innovation (e.g. remote sensing and mobile phone data to quantify the spread of illegal mining) combined with knowledge of mineral resources and ecosystem services science to advance our understanding of sustainable development. The aim is to understand the net environmental impacts of different trajectories s involving mining and conservation (e.g. continued proliferation of artisanal mines in protected areas, strict control and regulation of mining sector including in protected areas).
We will use the case study of mining in Madagascar – an extremely poor country rich in mineral reserves, whose government and citizens are highly committed to rapid development but also to conserving the country’s unique biodiversity. This research has high impact potential – Madagascar needs to benefit from its mineral wealth but faces huge challenges particularly around mineral deposits underlying protected areas. The research involves analysis of secondary data sets, spatial modelling, scenario development with stakeholders in Madagascar, and some limited fieldwork.
Applicants should hold a minimum of a UK Honours Degree at 2:1 level or equivalent in subjects such as Environmental Science, Geography or Natural Sciences. Experience of fieldwork within Africa, spatial modelling (e.g. GIS) and writing computer code would be advantageous. Proficiency in written and spoken French is also desirable.
For further details please contact Simon Willcock, firstname.lastname@example.org.