A PhD position is open in the highly collaborative Research Training Group “Spatial and Temporal Scaling of Biodiversity and Environment”. Environmental conditions and biodiversity both vary across a wide range of temporal and spatial scales and are tightly connected (Stein & Kreft, Biological Reviews). Understanding how environmental conditions and heterogeneity affect the distributions of individuals and species is thus vital for our general understanding of emergent properties at the level of communities such as species diversity or endemism. Oceanic islands are particular suited to study how the scaling of environmental variables affects biodiversity as islands represent thousandfold replicated model systems in space (e.g. different island sizes, climate regimes) and in time (e.g. different ages, geological ontogenies).
The main aims of this project are i) to develop and apply novel methods to quantify environmental heterogeneity across spatial and temporal scales taking advantage of novel global environmental data sets, ii) to establish scaling relationships between island area, age, and different dimensions of environmental heterogeneity, and iii) to relate those to macroecological and biogeographical patterns and processes. Central research questions of this project are i) How does spatial environmental heterogeneity increase with island area? ii) How does environmental heterogeneity change through time over the ontogeny of oceanic islands (from emergence to subsidence) and are there consistent and predictable patterns within archipelagos? iii) How do the spatial and temporal dynamics of heterogeneity affect ecological and evolutionary drivers of biodiversity?
To this end, oceanic islands serve as a model system, and the PhD project takes advantage of unique macroecological data sets of island environments and plants worldwide (see e.g. Weigelt et al. 2013, PNAS; Weigelt et al. 2016, Nature). At a later stage of the project, it is planned to transfer the analytical framework to study other island-like system (such as mountain tops or habitat fragment). The project will employ a variety of modern statistical and analytical methods from ecoinformatics, geostatistics, and macroecology. The project will closely collaborate with the other projects in the Research Training Group as well as a network of international collaborators.
Deadline for application: 15 May 2016.
For full project description and a link to the online application platform see here.