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Consequences of biases in representation of drivers of change in evidence synthesis for environmental decision-making and stewardship

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

Research Group: Applied Ecology Research Group (AERG) -

Proposed supervisory team
Dr Helen Wheeler ()

Several other members of staff with interest in this subject area could be part of the team e.g. Dr Nikoleta Jones (Global Sustainability Institute), Dr Peter Brown (AERG), Dr Dannielle Green (AERG). This project is also likely to involve a number of external collaborators.

Environmental change, social-ecological systems

Summary of the research project

Global environmental change is creating some of the highest likelihood and most impactful risks to humans, and the species upon which they depend. This is intensely felt in arctic and northern environments, where rapid warming is driving biophysical and socio-ecological transformation. As the north transforms, we see a rapid expansion of stakeholders, the emergence of novel drivers of change and increased likelihood of new synergies and antagonisms between impacts of drivers of change. Where concurrent rapid changes in the environment and the stakeholder community occur, conflicts over resource use and conservation can be severe. In these contexts, there is a critical need for information to inform decision-making which is both accurate, and provides just outcomes for stakeholders.

PhD projects are available which explore the consequences of biases in research and monitoring for our understanding of social-ecological systems and decision-making outcomes. Enquiries are particularly welcomed from those interested in analysing these trends in the Arctic and alpine environments and that relate to wildlife and wildlife management but we are also happy to discuss interest in other regions and systems. There are opportunities for the use of both social science and natural science methods and we particularly encourage those who which to work in an interdisciplinary setting. There are also opportunities for both analysis-driven projects of existing data (spatial data and imagery) and for more field-based work.

Where you’ll study

Cambridge (

Next steps

If you wish to be considered for this project, you will need to apply for our Biology PhD ( In the section of the application form entitled ’Outline research proposal’, please quote the above title and include a research proposal.

Funding Notes

This project is self-funded.
Details of studentships for which funding is available are selected by a competitive process and are advertised on our jobs website (View Website) as they become available.

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