Supervisory Team

Dr Martin Wilkes (School of Life Sciences, University of Essex)

Dr Kyle Jerro (Department of Language and Linguistics, University of Essex)

Dr Joe Cooper (British Trust for Ornithology)

Dr Ceclilia Larrosa (Biodiversity)

Scientific background

Rapid biodiversity loss is degrading the social and economic value of ecosystems. Globally, vertebrate numbers fell by 68% since 1970, and insect abundances are declining by as much as 2% per year(1). According to World Bank estimates, the global annual cost of inaction on biodiversity loss will be $2.7 trillion by 2030. As climate change progresses and our demands on landscapes shift under policy and market forces, locations where species currently thrive are at a risk of becoming unsuitable in the near future(2), whilst already threatened species may be driven to extinction. For conservation initiatives to be successful, we need to accurately predict how habitats will change in the future and anticipate the consequences for wildlife and society. This necessitates better understanding of the relationships between climate, land-use, species communities, and people.

Research methodology

Focusing primarily on the UK, you will harness the value of rich biological, socioeconomic and environmental datasets through ecological modelling and “big data” analytics(3). Baseline population status for 100s of plant, invertebrate and vertebrate species will be estimated using millions of biological records from citizen science initiatives and statutory monitoring programmes. A mechanistic model(4) will be developed to forecast UK biodiversity under alternative climate and management scenarios(5). Natural language processing techniques will be applied to social media data to analyse public discourses on UK biodiversity, enabling the integration of public opinion and social conflict into conservation planning.

Training

You will be supported by scientists from the University of Essex, the British Trust for Ornithology and the innovative sustainability consultancy, Biodiversify. Through their supervision, coaching, and formal training, you will build upon your skills in statistics and programming. You will gain new capabilities and understanding in high-performance computing, ecological theory, natural language processing, public policy, environmental consulting, publishing, public speaking and networking.

Person specification

This opportunity would suit a data scientist with an interest in ecology, or an ecologist with an interest in data science, with a degree in Data Science/Ecology/related subjects. Applicants with numerate degrees would be acceptable. Basic understanding of statistics and programming (e.g., R, Python) is essential.

Funding

This project has been shortlisted for funding by the ARIES NERC DTP.

Successful candidates who meet UKRI’s eligibility criteria will be awarded a NERC studentship, which covers fees, stipend (£17,668 p.a. for 2022/23) and research funding. International applicants are eligible for fully-funded ARIES studentships including fees. Please note however that ARIES funding does not cover additional costs associated with relocation to, and living in, the UK.

Excellent applicants from quantitative disciplines with limited experience in environmental sciences may be considered for an additional 3-month stipend to take advanced-level courses.

ARIES is committed to equality, diversity, widening participation and inclusion in all areas of its operation. We encourage enquiries and applications from all sections of the community regardless of gender, ethnicity, disability, age, sexual orientation and transgender status. Academic qualifications are considered alongside significant relevant non-academic experience.

For further information, please visit www.aries-dtp.ac.uk