Supervisors

Lead Supervisor: Professor David Roy, CEC, University of Exeter

Dr Jason Chapman, CEC, University of Exeter
Dr Jenna Lawson, UK Centre for Ecology & Hydrology, Wallingford, Oxfordshire
Professor Tom Oliver,  University of Reading

Location: 

Centre for Ecology and Conservation, Penryn Campus, Cornwall

The University of Exeter’s Centre for Ecology and Conservation is inviting applications for a PhD studentship funded by the Faculty of Environment, Science and Economy to commence on 23 September 2024 or as soon as possible thereafter.  For eligible students the studentship will cover Home or International tuition fees plus an annual tax-free stipend of at least £19,237 for 3.5 years full-time, or pro rata for part-time study.  International applicants need to be aware that you will have to cover the cost of your student visa, healthcare surcharge and other costs of moving to the UK to do a PhD. The following project is one of four being advertised as part of a competitive process for funding, there is one award available.

Project keywords: biodiversity, climate extremes, insects, AI, ecological modelling, bats

Project Background

Declines in wildlife are increasingly being reported across the globe, giving stark warnings for the perilous state of biodiversity. The state of insect population trends is attracting increased research interest due the vital role they play in all ecosystems (e.g. as food for birds and mammals, recycling nutrients, pollinating crops) and as indicators of climate change impacts. Recent droughts across Europe have highlighted a research need to understand their short-term (within and between days, weeks and months) responses to climate extremes in the context of longer-term (inter-annual, decadal) trends.

Emerging camera and acoustic technologies offer huge potential for a step-change in the quality and quantity of biodiversity data to study these short-term population dynamics. Automated sensors, deep learning, bioacoustics and computer vision are starting to deliver continuous, high temporal resolution and more standardised monitoring of insects, bats and birds. There is a need to test novel technologies alongside traditional ways of sampling biodiversity, and to then integrate data for high profile research questions.
Project Aims and Methods

Aim 1. This PhD project will compare novel sensors alongside traditional sampling methods for estimating biodiversity metrics (abundance/activity measures and diversity metrics).  This PhD studentship will capitalise on new insect cameras being deployed in the UK (n = 20 locations) across a gradient of land-use intensity, plus access to data from 40+ similar systems operating elsewhere in Europe, North and Central America, South-east Asia. 

Aim 2. Use traditional and novel data streams to understand short and long-term biodiversity responses to extreme events, including how these cascade through food chains.
A) How do insect activity patterns and biomass relate to weather extremes (e.g. heatwaves and cold snaps);
B) How do predators (bats and insectivorous birds) respond to short-term fluctuations in food availability, particularly during critical periods such as when provisioning young.

Aim 3. How are drought-sensitive insects predicted to respond to future climate and land-use scenario in the next 50 years.

Student Experience
The Exeter supervisory team (David Roy & Jason Chapman) will meet with the student on a fortnightly basis throughout the studentship. David Roy will provide expertise in analysis and interpretation of monitoring data, and Jason Chapman will lead field testing and provide mentoring on surveying and identification of moths. You will work closely with Jenna Lawson to receive training in working with data from automate biodiversity monitoring systems (both image and acoustic data), and Tom Oliver for climate-biodiversity impacts research. The full supervisory team will meet in the first and third month of the studentship and will then formally meet on a six-monthly basis.  The student will also receive peer-to-peer support and mentoring from the large cohort of PhD students based in the CEC, including a student-led coding support group that will be important for this analysis-based studentship. There will also be opportunities to engage in teaching support via demonstrating on practicals and field trips, including some of the locations where the AI sensors are operated.

Candidate requirements
We seek highly numerate candidates with an interest in novel technologies and developing skills in ecological modelling and conservation biology. Ideally, candidates will have an MSc with previous research project experience involving quantitative analysis. A broad outlook on wider environmental issues would help put these biodiversity change results in context and best realise impact from the research in this topical area. Field skills would be beneficial, particularly in survey methods for insects and identification of Lepidoptera.
Training

You will receive training in data science approaches that are revolutionising ecology research. In particularly, working with sensor data and the challenges of working with big data. Data science training will include high performance computing, AI and machine learning for image and bioacoustics data, together with Bayesian approaches for data analysis and model fitting. You will also learn how to translate your research into practical advice for climate change adaptation for nature conservation.

Useful links/Information
AI will play a crucial role in tackling biodiversity crisis - News (exeter.ac.uk)

Entry requirements

Applicants for this studentship must have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science or technology. 

If English is not your first language you will need to meet the required level as per our guidance at https://www.exeter.ac.uk/pg-research/apply/english/

How to apply

Apply now

In the application process you will be asked to upload several documents. 
• CV
• Letter of application (outlining your academic interests, prior research experience and reasons for wishing to undertake the project).
• Transcript(s) giving full details of subjects studied and grades/marks obtained (this should be an interim transcript if you are still studying)
• Names of two referees familiar with your academic work. You are not required to obtain references yourself. We will request references directly from your referees if you are shortlisted.
• If you are not a national of a majority English-speaking country you will need to submit evidence of your proficiency in English.

The closing date for applications is midnight on 29 July 2024. 

If you have any general enquiries about the application process please email PGRApplicants@exeter.ac.uk or phone 0300 555 60 60 (UK callers) +44 (0) 1392 723044 (EU/International callers)  Project-specific queries should be directed to the main supervisor.

Summary