Accelerated climate change and environmental degradation make it necessary to improve our understanding of, and ability to predict, species’ responses to environmental change. The availability of large-scale species distribution databases and information on environmental change, e.g. from satellite measurements, has resulted in thousands of studies using data on species’ geographical ranges to predict their movements in response to future environmental change. This approach is increasingly criticised on the grounds of key assumptions being problematic.
This project addresses these assumptions, asking fundamental questions about plant responses to environmental change by harnessing the immense opportunities offered by the ‘sPlot’ database (www.idiv.de/sPlot, plant abundance records from ~2 million vegetation plots worldwide), archives in botanical gardens such as Kew, and collaborations with world-leading international experts.
The successful applicant will have excellent networking and training opportunities, taking advantage of the expertise of our impressive set of collaborators, who are all enthusiastic to be part of this project – including placements with Helge Bruelheide (external supervisor, Germany), Steven Bachman (external supervisor, Kew Gardens), Brian McGill (USA) and Ole Vetaas (Norway). The project involves processing and numerically analysing large datasets, statistical modelling and, subject to the interests of the successful candidate, field work and/or work on records in botanical gardens around the world.
Analysis and manuscript writing will proceed quickly. All the data needed for four important papers have already been amassed by the supervisory team and collaborators – though one paper would benefit from targeted field work in botanical gardens.
Applicants must have grounding in biogeography/ecology/geology or mathematics/statistics and be excited to learn about the other area of expertise. Programming (ideally in R/Python), ecological field experience/plant identification, database management, statistical analysis/GIS skills are assets, but enthusiasm for nature, curiosity about the impact of environmental change on ecosystems and willingness to take opportunities are the most important requirements.
Applicants should hold a minimum of a UK Honours degree at 2:1 level, or equivalent, in a subject such as Biology, Ecology, Physical Geography, Environmental/Natural Sciences or Mathematics/Statistics.
We expect the most competitive applicants will have a Master’s qualification or equivalent, and/or substantial practical experience. The project may be undertaken on either a full- or part-time basis.
For further details (recommended), please contact Dr Franziska Schrodt ([email protected]
) and Dr Richard Field ([email protected]
) – we would prefer it if you send your email to both of us, please.