Project Description
Supervisor
Dr Matthew Struebig, School of Natural Sciences, University of Kent – contact me
Professor Bob Smith, University of Kent
Dr Stephanie Brittain, University of Kent
Dr Nurul Winarni, Universitas Indonesia, Research Centre for Climate Change
Dr Adam Miller, Yayasan Planet Indonesia
Dr Nicolas Deere, DICE Kent
Scientific Background
Community-managed forests are among the most promising Nature-based Solutions (NbS) for tackling climate change and biodiversity loss. Yet to deliver lasting impact, NbS must align ecological goals with community governance and generate evidence in cost-effective ways. This is especially urgent in Borneo, where Indigenous and Local Communities steward vast tracts of carbon- and biodiversity-rich forests. In one of the region’s largest such initiatives, Planet Indonesia is supporting 12 villages to secure legal tenure over >300,000 ha of forests and agroforestry systems. This PhD offers a timely opportunity to integrate biodiversity science, ecological modelling, and participatory decision-making to strengthen conservation and climate outcomes.
Research Methodology
The student will develop integrated evidence and decision support to assess biodiversity and inform land-use zoning to help ensure community tenure safeguards both biodiversity and carbon. Specifically, they will:
- Validate and refine AI-generated classifications of mammal and bird detections from extensive camera-trap and acoustic datasets, and identify indicator species for further monitoring.
- Model landscape-level biodiversity patterns using advanced spatial statistical approaches.
- Integrate biodiversity data with remote-sensing and community patrol datasets to assess habitat condition, carbon value and anthropogenic threats.
- Build on an initial spatial optimisation plan to evaluate and refine candidate zones for conservation and sustainable use.
- Co-develop land-use planning scenarios with communities to explore synergies and trade-offs between biodiversity, carbon, landscape connectivity, and livelihoods.
Fieldwork will take place in Kalimantan; data analysis at University of Kent. There may also be an opportunity to apply and develop the approach in a second community-managed landscape.
Training
The student will receive interdisciplinary training in biodiversity monitoring, AI classification, spatial analysis, and participatory conservation planning. They will be supervised by experts in ecology, remote sensing, and geospatial modelling, and work closely with Planet Indonesia, gaining valuable field experience and exposure to applied conservation governance. The project offers flexibility to develop independent research questions – for example, how human pressure and governance interact with habitat and biodiversity.
Person Specification
Applicants should have ecological field experience, strong analytical skills (including GIS), and familiarity with wildlife monitoring in challenging environments. Prior experience of programming and interest in interdisciplinary approaches is desirable.
Acceptable first degree subject(s): Biology, ecology, conservation, wildlife management