Project Description
Supervisors
Professor Rachel Warren, Environmental Sciences, University of East Anglia – contact me
Professor Tim Osborn, UEA, ENV
Dr Jeff Price, UEA, ENV
Scientific background
Climate change is affecting biodiversity. Species distributions are changing and spring is advancing. In the future, risks are projected to become even greater. At UEA, the Wallace Initiative (wallaceinitiative.org) has used computer models to examine potential impacts of climate change on 125,000 plant and animal species. However, like most other studies, this is based on changes in average climate.
Yet we know that biodiversity responds strongly to extreme climatic events (e.g., 2018’s hot, dry summer and 2024’s wet spring). Thus, projected impacts based only on changes in average climate may be underestimates. In this project, you will have the opportunity to develop ground-breaking new approaches to explore how species respond to an expected increase in extreme climatic events. You will greatly improve standard tools and develop entirely new ways to project impacts of climate change on biodiversity, both globally and in the UK.
Method
You will begin with existing computer models that predict the geographical range of species, and existing future projections of daily and monthly climate data, to explore how species ranges respond to transient changes in climate as opposed to mean climate. You will explore how to adapt these existing computer models to incorporate variables indicative of drought, heavy precipitation events and extreme heat. Finally you will feed this information into computer models to improve projections of climate change impacts on biodiversity to better inform climate policy and conservation planning. You will test your predictions and methods using data from various regions around the world.
Training
You will acquire enhanced computational, coding, statistical and spatial analysis (GIS) skills increasing your employability. You will join the Tyndall Centre for Climate Change Research which informs climate change related decision-making.
Person specification
Computational and statistical skills including GIS are essential. Knowledge of R or similar coding preferred. Degree in biological, ecological, computational or climate sciences preferred.
Acceptable first degree subjects: Biological, ecological, computational or climate sciences preferred, but other quantitative or natural sciences disciplines are suitable.