Community benefits of landscape restoration in Scotland – measuring, mapping and monitoring social impacts


   School of Geosciences

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  Prof Marc Metzger, Dr Janet Fisher, Dr D Moseley, Dr Calum Brown  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Summary

Landscape restoration is expanding in Scotland, with unclear and contested impacts on local communities. This PhD project will identify ways to capture those impacts and assess whether appropriate benefits are created.

Project background

Nature restoration features prominently in climate policy and sustainable development agendas as an essential step towards social, economic and environmental goals (Svenning, 2020). The UN declared the 2020s as the Decade of Restoration, calling for the restoration of one billion hectares of land. In recognition, national governments have made ambitious landscape and nature restoration commitments, which they are struggling to meet. Meanwhile, there is a proliferation of initiatives to secure private investment for landscape restoration –including rewilding and reforestation– by offering carbon and biodiversity credits or ESG investment opportunities for clients who mostly live and work far away from the landscapes that will be restored (Löfqvist et al., 2023). Despite the potential to provide social and economic benefits locally (Martin et al., 2021), these are not always realised and rarely measured. 

In Scotland, landscape scale restoration for carbon and biodiversity has been framed as the latest chapter in a long history of contentious land use changes forced on and negatively impacting communities (McIntosh, 2023). Debates on this topic are increasingly polarised, while understanding of the actual community benefits that landscape restoration can provide under different governance models, including community ownership and collaborative approaches, remains limited. As ‘natural capital’ metrics are developed and refined, it is crucial to also understand how to measure, map and monitor community benefits, without limiting these to financial benefits, or other easily measurable economic indicators that communities may not always prioritise. This will allow projects to report not just carbon storage and biodiversity improvements, but also evidence how communities have benefited in context-specific ways. 

Research questions

1) What community benefits are targeted and measured in existing good practice in landscape restoration in the UK and internationally, and do these vary with ownership, governance and management objectives? 

2) How would donors, investors, and community groups like to see community benefits defined and reported? 

3) How can spatial models and methods capture benefits and monitor success? 

4) Can measuring, mapping and monitoring the social impacts of landscape restoration reduce tensions and conflict?

Methodology

This is a highly collaborative project with the aim of producing scientifically robust outcomes that are useful, usable and widely used. This will be achieved by co-design and testing approaches with a range of stakeholder groups, and full support from the supervisory team and their colleagues. Document analysis of landscape scale restoration approaches and case-studies, supplemented by interviews, will identify good practice and state-of-the-art knowledge (RQ1). Collaborative stakeholder consultation will identify common ground in social impact reporting requirements (RQ2) and explore if spatial modelling of community benefits could help negotiate trade-offs and identify synergies between restoration objectives and community benefits (RQ3). This learning will be applied in suitable case-studies to understand if the developed approach reduces tensions or conflict (RQ4). 

Year 1Research planning and design, research skills courses. Document analysis and interviews for RQ1. Stakeholder mapping and identifying potential case-studies. National workshops and conference attendance. Year 2Stakeholder consultation to understand social impact reporting requirements (RQ2). Developing and testing opportunity mapping. International conference attendance. Year 3Tests social impact measuring and mapping approach in case-studies and reflect if it reduces tensions and conflict. Write up the thesis. 

Training

A comprehensive training programme will be provided comprising both specialist scientific training and generic transferable and professional skills, such as science communication, stakeholder engagement and organisational planning. Spatial analysis and modelling training is available at the University of Edinburgh and will be complemented by the placements at Forest Research. The student will benefit being part of the Centre for Sustainable Forests and Landscapes and inclusion in conservation and policy networks and will be encouraged to attend relevant national and international meetings. 

Requirements

This project would suit a student with an interdisciplinary environmental or ecological sciences background, and with a strong interest in stakeholder engagement, along with a desire to develop cross-disciplinary skills in landscape ecology and spatial analysis. Experience in spatial analysis and modelling is desirable. 

CASE partner: Forest Research

Biological Sciences (4) Environmental Sciences (13) Geography (17)

Funding Notes

Detail about the E4 DTP can be found here: http://www.ed.ac.uk/e4-dtp

References

Löfqvist S., Garrett R.D., Ghazoul J. (2023) Incentives and barriers to private finance for forest and landscape restoration.Nature Ecology & Evoultion 7: 707–715.
McIntosh A. (2023) The Cheviot, the Stag and the Black, Black Carbon Natural Capital, the Private Finance Investment Pilot and Scotland’s Land Reform. Discussion paper for the Scottish Land Commission.
Martin A., Fischer A., McMorran R., Smith M. (2021). Taming Rewilding - from the Ecological to the Social: How Rewilding Discourse in Scotland Has Come to Include People. Land Use Policy 111: 105677
Svenning J.-C. (2020) Rewilding Should Be Central to Global Restoration Efforts. One Earth 3: 657–60.

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