Linking land use with bird community dynamics and ecosystem function in Europe and Africa

In other world regions such as the tropics, much less resolved data are available, despite the urgent requirement for evidence-based approaches to guide environmental management. Most of the world’s biodiversity is found in these regions and they also have the highest rates of land-use change. The student will analyse such an Afrotropical dataset, comprising, interpolated presence-absence data, trait data averaged by species or interpolated using phylogenetic relationships. This will require the development of new analytical approaches linking global land-use and climate change to ecosystem functions. Crucially, the student will develop validation approaches to quantify uncertainty by using the same simplified methods on the well resolved datasets and conducting sensitivity analysis on predictions. In addition, the student will devise new methods to test the suitability of using phylogenetic diversity as a proxy for functional traits, where the latter may be absent for other species groups.
The project will pave the way to a clearer methodological framework for understanding land-use impacts on biological communities and associated ecosystem function in data poor scenarios. The outcome will be a set of innovative methods which can link land use to community composition and ecosystem function, which will also be applicable to other species groups.
A multidisciplinary project
This project integrates quantitative population ecology (e.g. population dynamics mediated by land use and weather interactions; led by supervisor Dr. Oliver; https://www.reading.ac.uk/biologicalsciences/about/staff/t-oliver.aspx), with mathematical ecology (supervisor Prof. Petchey), functional ecology and ecosystem science (through trait based approaches and phylogenetic inference; led by supervisor Dr. Tobias; https://www.imperial.ac.uk/people/j.tobias), and conservation ecology (quantifying the accuracy of more simple models where data are sparse).
Excellent training opportunities
The student will gain training in:
• Development of statistical and computational tools, large data set assimilation and analysis, development of theory and integration into mathematical models, quantitative population ecology,
• Integration of data from the wider environmental sciences. Accessing and querying large environmental datasets (e.g. land use, climate, phylogenies, function trait databases)
• Statistical modelling of population data, land use and weather/climate interaction coupled with theory and new methods for functional ecology (e.g. incorporating intraspecific trait variability)
• Ability to scale from complex models to simpler models with increased transferability, using sensitivity analysis to understand trade-offs in model predictive capacity
• Liaising with a range of conservation stakeholders
To apply please email a CV, cover letter and two contacts to provide references to Dr. Tom Oliver [Email Address Removed] before 19th January 2017