Details
The project sits within the Biodiversity Observatory and is part of the CBSI Science and Capacity Plan. The Observatory will support PhD and MSc students in the Catholic University of Congo and the University of Lubumbashi in DRC and the University of Stirling in the UK. Work on this PhD project will collaborate closely with the work of the other observatories and CBSI partners, particularly CENAREST in Gabon and the partner company Okala, which operates in Gabon, DRC and the UK and wider collaborative partnerships that the Observatory staff have established in the region.
The studentship will ask how different taxa are impacted by the major habitat modifiers of our time: forestry, agriculture, mining, roads and cities. First, we will build on recent surveys of biodiversity using camera-traps (terrestrial vertebrates), bioacoustics (birds, soundscape intensities), and eDNA (all taxa) as these are the largest sources of animal biodiversity monitoring data currently available. For example, approximately 20% of Gabon has been surveyed by camera-trap monitoring in the past 7 years and around 3-4% also surveyed with eDNA and bioacoustics. CENAREST, Okala and University of Stirling already hold significant databases and we will work to collate available data from other partners in the region to support the studentship. The successful candidate will utilise and analyse some of this data.
The successful candidate will first use existing data, together with information on land use, human populations and infrastructure, geography, topography and climate to understand the way in which wildlife community structure and species respond to different habitat modifiers, both human and climatic, using statistical analyses. Predictions generated from the statistical models will be used to generate expectations for how species and communities may vary in un-surveyed regions. New ground data collected in the second year, and additional data contributed by CBSI partners and the Biodiversity Observatory team will then be used to test the accuracy of the statistical model predictions.
Targeting areas of high uncertainty for additional data collection will we used to improve the statistical models. , to allow the project to produce robustly modelled estimations of how wildlife species diversity, richness and evenness vary across the Basin and how they are impacted by human pressure and climate.
Finally, the student will use the newly created knowledge, in collaboration with colleagues in the Biodiversity Observatory, the Vegetation Observatory and the AfriTRON network, to compare patterns of diversity and abundance across our surveyed taxa: trees, lianas, mammals, birds and fish, to elucidate drivers of responses common across all taxa and functional groups, and those that have uneven effects, disproportionately impacting certain taxa or groups. In this way, the most impactful human activities, and the zones most likely to be impacted by climate change will be identified, helping policy-makers to direct mitigation resources to the most critically endangered areas, and avoid the most harmful human activities taking place in the most vulnerable areas.
The student will work within the African Forest Ecology Group at the University of Stirling and collaborate closely with Okala, whose offices are also in Stirling. Within the CBSI, the studentship sits within the Biodiversity Observatory which is a team of 4 Senior Research staff, 2 Postdocs, 3 PhD students, 2 MSc students and 2 field technicians. To carry out this project, the student will be expected to spend around 3 years in the UK, around 1 year collecting data in the Congo Basin region.
Info
Degree type:
Duration:
CBSI Observatory:
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Host institution:
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Supervisors
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Secondary:
Funding
Funder:
Award programme:
Funding eligibility criteria:
Must be a national of and ordinarily resident in Cameroon, Democratic Republic of the Congo, Gabon or Republic of the Congo, including at the time of application (28 February 2025). Proof of eligibility will be required.
Monthly stipend:
Students receive standard CBSI stipend, currently:
USD 1,000 per month PhD in central Africa
USD 700 per month MSc in central Africa.
GBP 1,603 per month in UK (the UK standard maintenance stipend).
Funding for University fees included:
Other funding included:
Relevant costs to purchase equipment, field costs, English language training, and travel for training and attending scientific conferences are included in the funding. For applications to UK universities funding includes intensive training to help you prepare for English language tests that you will need to pass in order to meet University entry requirements.
- A PhD thesis
- A new quantified model of how climate and different human activities are driving patterns of terrestrial biodiversity loss across the Basin
- A new understanding of how key drivers affect taxa differently
- New maps of the most highly vulnerable areas for biodiversity under the likely trajectories of climate change and planned development over the next two decades.
- A Bachelor’s degree at Upper Second (2:1) equivalent level, in a relevant discipline focussed on land-use and ecosystems, such as (but not limited to) ecology, forestry, environmental science, conservation, remote sensing,
- Demonstration of good skills in data analysis and fluency in statistics
- Some knowledge of GIS and spatial data analysis
- Aptitude in English. Training will be given, but must reach IELTS 6.5 by October 2025, therefore should already possess a minimum fluency equivalent to an IELTS 4 level to enter the pre-sessional English in June 2025, if required. Fieldwork experience in Congo Basin forests, such as being a field assistant or having lived in a forest community
- Willingness and aptitude to undertake long field missions in remote forest areas.
- Willingness to live for prolonged periods in the UK and to undertake regular international travel
- Proven success in teamwork and collaboration
Abernethy et al. 2016. Environmental Issues in Central Africa. Annual Review of Environment and Resources 41:1–33. https://doi.org/10.1146/annurev-environ-110615-085415.
Bessone et al. 2024. Bonobo (Pan paniscus) Density and Distribution in Central Africa’s Largest Rainforest Reserve: Long‑term Survey Data Show Pitfalls in Methodological Approaches and Call for Vigilance International Journal of Primatology. Early Online. https://doi.org/10.1007/s10764-024-00468-w
Whytock et al. 2021. Robust Ecological Analysis of Camera Trap Data Labelled by a Machine Learning Model. Methods in Ecology and Evolution 2041-210X.13576. https://doi.org/10.1111/2041-210X.13576.
Fonteyn et al. 2023. Biogeography of central African forests: Determinants, ongoing threats and conservation priorities of mammal assemblages. Diversity and Distributions 29(6): 698-712. https://doi.org/10.1111/ddi.13677
Beekmann et al. 2024. Uncertain future for Congo Basin biodiversity: A systematic review of climate change impacts. Biological Coinservation 297:e110730. https://doi.org/10.1016/j.biocon.2024.110730
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Research outcomes
- A PhD thesis
- A new quantified model of how climate and different human activities are driving patterns of terrestrial biodiversity loss across the Basin
- A new understanding of how key drivers affect taxa differently
- New maps of the most highly vulnerable areas for biodiversity under the likely trajectories of climate change and planned development over the next two decades.
Pre-requisite skills
- A Bachelor’s degree at Upper Second (2:1) equivalent level, in a relevant discipline focussed on land-use and ecosystems, such as (but not limited to) ecology, forestry, environmental science, conservation, remote sensing,
- Demonstration of good skills in data analysis and fluency in statistics
- Some knowledge of GIS and spatial data analysis
- Aptitude in English. Training will be given, but must reach IELTS 6.5 by October 2025, therefore should already possess a minimum fluency equivalent to an IELTS 4 level to enter the pre-sessional English in June 2025, if required. Fieldwork experience in Congo Basin forests, such as being a field assistant or having lived in a forest community
- Willingness and aptitude to undertake long field missions in remote forest areas.
- Willingness to live for prolonged periods in the UK and to undertake regular international travel
- Proven success in teamwork and collaboration
References
Abernethy et al. 2016. Environmental Issues in Central Africa. Annual Review of Environment and Resources 41:1–33. https://doi.org/10.1146/annurev-environ-110615-085415.
Bessone et al. 2024. Bonobo (Pan paniscus) Density and Distribution in Central Africa’s Largest Rainforest Reserve: Long‑term Survey Data Show Pitfalls in Methodological Approaches and Call for Vigilance International Journal of Primatology. Early Online. https://doi.org/10.1007/s10764-024-00468-w
Whytock et al. 2021. Robust Ecological Analysis of Camera Trap Data Labelled by a Machine Learning Model. Methods in Ecology and Evolution 2041-210X.13576. https://doi.org/10.1111/2041-210X.13576.
Fonteyn et al. 2023. Biogeography of central African forests: Determinants, ongoing threats and conservation priorities of mammal assemblages. Diversity and Distributions 29(6): 698-712. https://doi.org/10.1111/ddi.13677
Beekmann et al. 2024. Uncertain future for Congo Basin biodiversity: A systematic review of climate change impacts. Biological Coinservation 297:e110730. https://doi.org/10.1016/j.biocon.2024.110730
Apply
How to apply:
Please read our Application Guide. You must submit your application and supporting documents via our online portal by 28 February 2025. We will not be able to assess your application without all required supporting documents.
In the online portal, you will need to:
- Choose a name to identify your application. Name the application: PhD U. of Stirling (What drives patterns of biodiversity in the Congo Basin?)
- Select the scholarship that you are applying for. Select the scholarship entitled: PhD U. of Stirling (What drives patterns of biodiversity in the Congo Basin?)
Application deadline:
February 28, 2025
Expected project start date:
October, 2025
Possibility for pre-sessional English from June 2025, more information here.
Entry to the Doctoral Programme is permitted throughout the year, allowing for adjustment of dates if required.
Language of application:
You will need to submit your scholarship application form, statements and CV in English.
You can upload your supporting documents and references in English or in French.
How we assess your application:
Please read our application guide.
Degree Awarding Institution
The application procedure here, as part of CBSI, is to win funding and a supervisory team for the project. Successful applicants will then need to apply to their degree awarding institution to secure a place. Scholarships can only be awarded to successful applicants who have met all conditions required for entry to their degree awarding institution and then officially accepted a place at that institution. Below are details of the criteria needed to apply for a place at the degree awarding institution.
Admissions criteria of the degree awarding institution:
- UK BSc degree at 2:1 or above, or international equivalent, in a related subject. This usually equates to a Licence, with a score of 13/20 or above from a state university, or a National Forestry school degree (ITEF) but please contact us if you are unsure of your degree status.
- If your undergraduate degree was not awarded in English, then proof of a IELTS level 6.5 (6.0 in all bands) is needed within the past 2 years.
How to apply to the degree awarding institution:
Information on how to apply to the University of Stirling.
You should apply immediately after you hear the outcome of the CBSI Scholarship application process.
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Contact
For enquiries about…
This project:
Contact Prof. Katharine Abernethy by email: k.a.abernethy@stir.ac.uk
Your scholarship application:
Contact: info@congobasinscience.net
Applications to the degree awarding institution:
The Institute for Advanced Studies ias@stir.ac.uk can help with any enquiries from prospective students.
Or infocentre@stir.ac.uk can help with the application process once you are filling in the online application.