The global transition to electrified transport is driving unprecedented demand for battery minerals such as lithium and cobalt, frequently extracted in ecologically sensitive biodiversity hotspots -notably, nickel-cobalt production in Indonesia and the Philippines and copper/lithium production in the high-Andes. However, biodiversity risks remain poorly mapped and weakly integrated into risk assessment, with existing approaches operating at mismatched spatial scales, from localised environmental impact assessments (EIAs) to global sustainability reporting. This creates a disconnect between local ecological impacts and strategic supply chain decisions.
This PhD addresses this gap by combining spatial ecological analysis, comparative tool evaluation and case study evidence to develop a spatially explicit, evidence-based approach to identifying and evaluating biodiversity risk across lithium supply chains, using case studies from the UK and South America, structured around four research questions.
First, what are the strengths, limitations and data gaps of existing biodiversity assessment approaches for supply-chain decision-making? The project critically compares analytical tools (life cycle assessment, EIAs, spatial mapping, emerging risk modelling) and frameworks (the mitigation hierarchy, ICMM principles) for their ability to inform CSRD, TNFD and SBTN implementation.
Second, where are the highest biodiversity risks located across lithium supply chains, and how do these vary by region and production stage? Building on UoB/BGS spatial mapping methods, the project overlays biodiversity hotspot data (IBAT, IUCN Red List, Key Biodiversity Areas, protected areas, species-richness layers), strengthened by eDNA and bioacoustic monitoring, with georeferenced supply chain data (Geographic Information Systems (GIS), Earth Observation (EO) and hydrological modelling) to distinguish direct impacts (habitat loss, fragmentation) from indirect impacts (land-use change, water stress, pollution).
Third, what risks identified through spatial analysis are omitted or underrepresented in existing reporting frameworks? Findings are compared against submitted EIAs to identify reporting gaps and inform EIA methodology.
Fourth, what mitigation strategies exist, and how can they best be deployed? The project evaluates siting, technology choice and pollution control mechanisms for their effectiveness and practical constraints.
In collaboration with industry, NGOs, regulators and sustainability practitioners, the student will synthesise their findings into a practical, coherent and transferable framework for integrating biodiversity risk into mineral governance and responsible sourcing.
This project does not offer a CASE studentship
Each host has a slightly different application process.
Find out how to apply for this studentship.
All applications must include the CENTA application form.
Choose your application route
The conceptual biodiversity risk framework will be developed through three phases, using case studies.
Phase 1 – Tool evaluation: A comparison of established and emerging biodiversity assessment tools against defined criteria (spatial resolution, data availability, relevance to strategic decision-making) to determine which combinations are best suited to protecting ecosystems at supply chain resolution.
Phase 2 – Spatial risk mapping: Drawing on existing UoB/BGS methodological expertise and incorporating novel monitoring techniques where feasible, the student will construct a geodatabase linking supply chain infrastructure to ecological sensitivity indicators. Analytical outputs will be cross-checked against publicly available documentation to highlight where current practice may overlook risks.
Phase 3 – Mitigation analysis: Assessment of intervention strategies against real-world feasibility, cost and ecological effectiveness, drawing on precedent case studies and stakeholder input. This phase draws together the preceding evidence base into a single, coherent risk-monitoring and mitigation framework, tested for transferability beyond initial case studies.
DRs will be awarded CENTA Training Credits (CTCs) for participation in CENTA-provided and ‘free choice’ external training. One CTC can be earned per 3 hours training, and DRs must accrue 100 CTCs across the three and a half years of their PhD.
The student will be trained in relevant aspects of the battery life cycle, including structure and content materials, as well as Life Cycle Assessment (LCA) and the use of Geographical Information Systems. In addition, training will be supported for skills such as presentations, grant writing and project management.
The BGS supervisors will provide guidance on the geological aspects of the project, as well as planning of any field work and access to data, resources and experts on a range of skills, including GIS, EO, hydrological modelling, supply chains etc. BGS are also happy to host the student at their offices for short periods.
Collaboration with the Faraday Institution will provide access to a global network of key stakeholders and opportunities for wider dissemination and impact pathways.
Year 1: Systematic review of tools and metrics for biodiversity risk assessment and design specification for a holistic biodiversity framework.
Year 2: Mapping of direct and indirect biodiversity risks for lithium supply chains and comparative evaluation of tools, including EIAs, using the case study data.
Year 3: Critical analysis of mitigation/protection strategy trade-offs (e.g. certification vs. conservation), grounded in the case data. Assessment of their effectiveness for delivering the Kunming-Montreal Global Biodiversity Framework goals. Engaging industry bodies, NGOs and policymakers for impact.
Sharma S. S., Edge J. S. and Mumford J. D. (2025) ‘Connecting rising electric vehicle demand to potential land use impacts and threats to biodiversity near key lithium mining areas’, Sustainable Science and Technology, 2, 044004, 10.1088/2977-3504/ae158a.
For any enquiries related to this project please contact Jacqueline S. Edge, [email protected].
To apply to this project:
Applications must be submitted by 23:59 GMT on Wednesday 6th January 2027.