Background
The urban forest encompasses all trees within the urban realm, from isolated street trees to ancient woodland fragments, and forms the backbone of green infrastructure networks and urban Nature‑Based Solutions (NbS), which are increasingly central to tackling the interlinked climate, biodiversity and public health crises.
In Scotland, urban tree cover remains relatively low (18.8% compared to a European average of 38%) and is unevenly distributed, with canopy cover approximately 40% higher in high‑income neighbourhoods [1]. This disparity has prompted renewed efforts to expand urban canopy cover and address inequalities (e.g. the UK Tree Equity Score). At the same time, national planning and biodiversity policies increasingly expect the urban forest to contribute to nature recovery and landscape-scale connectivity.
At present, there is limited biodiversity monitoring associated with urban trees, leaving significant evidence gaps regarding the ecological condition, biodiversity value, and functional connectivity of the urban forest, which in turn limits our understanding on how best to design and manage newly created or expanded forest habitats [2, 3]. Evidence from agricultural landscapes shows that biodiversity benefits of tree planting develop over time and depend on factors such as patch size, structural complexity and surrounding habitat permeability [4, 5]. However, urban environments are more heterogeneous and fragmented, and the drivers of biodiversity outcomes in these settings are likely to differ. Improving our understanding of the ecological condition, connectivity and biodiversity potential of urban forests is a key research priority urgently needed to inform more effective planting and management decisions [2, 6, 7, 8].
This PhD will address these knowledge gaps through an action-research approach that conceptualises urban woods and trees as components of interconnected, multi-scale ecological networks rather than isolated green assets. By establishing an Urban Forest Observatory for Scotland, this studentship will generate evidence on the habitat condition, structure, management and biodiversity value of urban forests, and improve understanding of how different forms of urban tree cover support ecological networks. Working with policy and delivery partners, the research will support improved planning and decision-making to enhance the ecological value of Scotland’s urban forest and strengthen its contribution to landscape-scale nature recovery.
The Research
The aim of this PhD is to assess the biodiversity value, ecological health and connectivity of urban woods and trees in Scotland and identify planting and management approaches that improve their contribution to landscape‑scale nature recovery.
Research questions include:
- What is the current biodiversity value and ecological condition of Scotland’s urban forest ecosystems?
- How do different forms of urban tree cover contribute to ecological connectivity across urban and peri‑urban landscapes?
- How do habitat structure and management approaches influence biodiversity outcomes associated with urban forest ecosystems?
- How can action‑research improve policy guidance and delivery mechanisms for nature-positive urban woodland creation and management?
The PhD will adopt an action-research approach giving the student the opportunity to develop a wide range of policy and practice-relevant research skills. Methods are likely to include:
- Evidence reviews on the biodiversity value of urban woods and trees.
- Stakeholder engagement and co-design within a ‘Living Lab’ approach.
- GIS and historical mapping to create an 'urban forest observatory’ of study sites across Scotland’s central belt from individual street trees and “wee forests” to peri-urban and ancient woods (e.g. [9]).
- Biodiversity assessment across multiple indicator taxa (e.g. birds, bats, invertebrates, ground flora) using high-throughput monitoring techniques (e.g. audiomoths, camera traps, eDNA).
- Experimental conservation-horticultural trials to test biodiversity-enhancing understorey planting and management treatments around established trees.
- Statistical analytical methods such as Generalised Linear Mixed Modelling and Bayesian Joint Species Occupancy Modelling (e.g. [10]).
Research Environment
The student will have dual access to the research communities within the Royal Botanic Garden Edinburgh (RBGE) and the University of Stirling (UoS).
The project is embedded within RBGE’s Plants with Purpose action-research programme, which focuses on nature‑ and community‑based solutions for urban environments. It will leverage RBGE’s expertise in adaptive management of multi-functional urban landscapes and its globally significant Living Collection, including an arboretum of more than 730 species, to support experimental and translational research. The successful applicant will contribute within a cohort of PhD students with access to an internationally renowned group of Scientists and Postgraduate Researchers within our Science department.
The student will be registered at the University of Stirling, within the Biological and Environmental Sciences department, and will benefit from Stirling’s expertise on landscape-scale woodland restoration. This research will build on the work of the WrEN project, a large-scale natural experiment designed to investigate the effects of past woodland creation on current biodiversity to inform future conservation actions. The student will have access to office space, laboratory and testing facilities on the UoS campus and access to a large cohort of PhD students and training opportunities.
The student will split their time between RBGE and UoS. The primary supervisors are Dr Emma Bush (RBGE) and Dr Elisa Fuentes-Montemayor (UoS), alongside Prof Kirsty Park (UoS) and Caitlyn Johnstone (RBGE).
Student Profile
We are looking for a student with a strong background in a discipline such as Ecology, Biological Sciences, Conservation Biology and/or Forestry. Applicants should have at minimum an upper 2nd class undergraduate degree or equivalent, with an MSc (or relevant experience) preferred. The applicant should ideally have demonstratable experience in ecological fieldwork, data analysis (e.g. using R) and scientific writing/publication, although training can be provided. A desire to work across disciplines including academia, policy and practice is essential and a UK Driving License is required.
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