Aiming for Nature Recovery: Data Science to Inform Biodiversity Conservation and Restoration


Aiming for Nature Recovery: Data Science to Inform Biodiversity Conservation and Restoration


Project Description


Dr Martin Wilkes, University of Essex – Contact Me

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

Dr Joe Cooper, British Trust for Ornithology

Dr Cecilia Larrosa, Biodiversify

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.


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 and coaching, as well as 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.


  • Wagner, D.L., Grames, E.M., Forister, M.L., Berenbaum, M.R. and Stopak, D., 2021. Insect decline in the Anthropocene: Death by a thousand cuts. Proceedings of the National Academy of Sciences, 118, e2023989118.
  • Brown, L.E., Khamis, K., Wilkes, M., Blaen, P., Brittain, J.E., Carrivick, J.L., Fell, S., Friberg, N., Füreder, L., Gislason, G.M. and Hainie, S., 2018. Functional diversity and community assembly of river invertebrates show globally consistent responses to decreasing glacier cover. Nature Ecology & Evolution, 2(2), pp.325-333.
  • Wilkes, M.A., Edwards, F., Jones, J.I., Murphy, J.F., England, J., Friberg, N., Hering, D., Poff, N.L., Usseglio‐Polatera, P., Verberk, W.C. and Webb, J., 2020. Trait‐based ecology at large scales: Assessing functional trait correlations, phylogenetic constraints and spatial variability using open data. Global Change Biology, 26, 7255-7267.
  • Thompson, P.L., Guzman, L.M., De Meester, L., Horváth, Z., Ptacnik, R., Vanschoenwinkel, B., Viana, D.S. and Chase, J.M., 2020. A process‐based metacommunity framework linking local and regional scale community ecology. Ecology Letters, 23, 1314-1329.
  • Harrison, P.A., Cooper, J. et al. 2022. ERAMMP Report-60. Environment and Rural Affairs Monitoring & Modelling Programme (ERAMMP). Available from: [accessed 26 August 2022].

Key Information

  • This project has been shortlisted for funding by the ARIES NERC DTP and will start on 1st October 2023. The closing date for applications is 23:59 on 11th January 2023.
  • 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.
  • ARIES students benefit from bespoke graduate training and ARIES provides £2,500 to every student for access to external training, travel and conferences, on top of all Research Costs associated with the project. 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 non-academic experience, and our recruitment process considers potential with the same weighting as past experience.
  • All ARIES studentships may be undertaken on a part-time or full-time basis, visa requirements notwithstanding
  • For further information, please contact the supervisor. To apply for this Studentship follow the instructions at the bottom of the page or click the 'apply now' link.
  • ARIES is required by our funders to collect Equality and Diversity Information from all of our applicants. The information you provide will be used solely for monitoring and statistical purposes; it will remain confidential, and will be stored on the UEA sharepoint server. Data will not be shared with those involved in making decisions on the award of Studentships, and will have no influence on the success of your application. It will only be shared outside of this group in an anonymised and aggregated form. You will be ask to complete the form by the University to which you apply.

Applications are open

To apply for this studentship please send a CV and cover letter to