Supervisor: Andrew Tanentzap (Plant Sciences)
Importance of the area of research:
Predicting the conditions that allow species to proliferate in diversity is a central question in evolutionary biology and has practical implications for modern conservation. In many parts of the world, recent and rapid radiations have accompanied the expansion of habitats due to climatic and geological changes (Linder 2008). However, the importance of niche-based ecological processes in not only generating diversity, but also influencing evolutionary dynamics, remains understudied.
This studentship aims to test how different types of niche formation influence species diversification at micro- and macro-evolutionary scales. The first component involves adapting a widely-used mathematical model of adaptive evolution to track genetic and trait responses of individual plants over thousands of generations in response to different ecological conditions (Gavrilets and Vose 2005). This will generate hypotheses, such as faster rates of niche expansion and contraction promote species diversity, which we will test experimentally in the laboratory by evolving a model organism, such as Pseudomonas fluorescens, under different conditions (e.g. Koeppel et al. 2013). The second part of the project will adopt a synthetic approach to relate features of different biogeographic regions (e.g. climatic stability) to macro-evolutionary dynamics of their corresponding floras.
What the student will do:
The student will code the theoretical model in a programming language and refine the modelling scenarios that will be tested. They will also design and execute the laboratory experiment, measuring phenotypic responses and genetic variation among populations. In the second part of the project, they will use phylogenetic comparative methods to reconstruct the evolutionary history of plant lineages in different biogeographic regions. Our group has already identified a number of biogeographic regions and plant lineages for which this analysis would be tractable. In the first instance, the student will estimate phylogenetic trees for different lineages using pre-existing barcode data on GenBank. Speciation and extinction rates will then be estimated using established maximum-likelihood and Bayesian approaches, and associated with regional characteristics using standard regression techniques, e.g. PGLS.
Please contact the lead supervisor directly for further information relating to what the successful applicant will be expected to do, training to be provided, and any specific educational background requirements.
Gavrilets, S. & Vose, A. 2005. Dynamics patterns of adaptive radiation. Proceedings of the National Academy of Sciences, vol. 102, pp.10840-10845.
Koeppel, A.F. et al. 2013. Speedy speciation in a bacterial microcosm: new species can arise as frequently as adaptations within a species. International Society for Microbial Ecology Journal, vol. 7, pp.1080-1091.
Linder, H.P. 2008. Plant species radiations: where, when, why? Philosophical Transactions of the Royal Society B, vol. 363, pp.3097-3105.