Dr Kyle Jerro, University of Essex, Department of Language and Linguistics
Dr Joe Cooper, British Trust for Ornithology
Dr Cecilia Larrosa, Biodiversify
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.
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.
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.