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Conservation and society are intimately linked; conservation cannot work without the support of societies, and societies can’t function without biodiverse ecosystems. Rewilding (the restoration of degraded ecosystems through the reintroduction of missing species) has both grabbed and polarised the public, with research suggesting a suite of potential benefits, including increasing biodiversity and stimulating local economies. Thus, with careful planning of where and how rewilding is carried out, both biodiversity and deprived rural areas stand to benefit. However, to achieve this requires tensions between local stakeholders (e.g. farmers) and conservation proponents (e.g. rewilding charities) to be resolved.
This project consists of two linked PhD scholarships: one in ecology and one in social sciences. These two PhD’s will run in parallel and feed results into one another, combining ecological habitat suitability modelling and a social survey, along with qualitative research, to identify areas of the UK where rewilding is both societally supported and ecologically possible. Doing so will:
· Identify what areas of the UK provide the best initial sites for rewilding
· Identify the best species to reintroduce to restore missing functions
· Identify which areas have the greatest potential social and economic impact from rewilding
· Understand the challenges and opportunities of rewilding, particularly the tensions and trade-offs with agriculture
The students will be embedded in vibrant, early career research groups, and will spend time in both the School of Biological Sciences and the School of Geographical Sciences, with regular meetings between the two students on this project to ensure that there is synthesis between the results and analyses of the ecological and socio-political data.
Aims and methods:
Studentship 1 will focus on the ecological feasibility of rewilding in the UK. Using species distribution modelling, the student will (1) identify suitable habitat in the UK to reintroduce a range of species covering a range of ecological functions (from predators to ecosystem engineers), (2) identify potential rewilding hotspots – areas where multiple species can be simultaneously reintroduced into the same area, (3) incorporate economic data to identify which of these sites could have the greatest economic benefit to local areas, and (4) integrate the outputs from studentship 2 (social sciences) to give a holistic understanding where rewilding might have positive environmental and social impact.
Requirements:
The successful student will have a strong interest in conservation, a background in quantitative analysis methods/statistics, and motivation for self-learning. Applicants must hold/achieve by the start date of the project a minimum of a master’s degree in biology/geography or related subjects, and a minimum of a 2:1 at undergraduate.
A strong background in coding (particularly R) is highly desirable, with a preference for candidates with experience fitting species distribution models.
Applicants should submit a research statement of no more than 1000 words (not including bibliography) reflecting on recent developments in this field, potential methodological approaches, sources of data, hypotheses to test, and both specific training and future ambition with respect to the project.
We especially welcome and encourage student applications from under-represented groups.
Project keywords: biodiversity, conservation, rewilding, functional diversity
For further information see: https://www.experimentalconservation.com/
Useful link: http://www.bristol.ac.uk/biology/courses/postgraduate/
How to apply:
Use the following link to apply: Start your application | Study at Bristol | University of Bristol
You should apply to the Faculty of Life Sciences, School of Biological Sciences selecting the programme: Biological Sciences (PhD)
Please ensure you upload all supporting documents as per the admissions statement link on the webpage: PhD Biological Sciences | Study at Bristol | University of Bristol
Clearly indicate the supervisor name and project title in the relevant section of the application form.
Research output data provided by the Research Excellence Framework (REF)
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