Contact

Prof. Dr. Bernd Blasius

Institute of Chemistry and Biology of the Marine Environment (ICBM) Phone  +49 (0)441 798 3997 eMail

A5

A5 Biogeography, community assembly and biodiversity in dynamic landscapes

PI: Bernd Blasius, Co-PIs: Gerhard Zotz, Helmut Hillebrand

Background

Most theoretic and experimental approaches on functional biodiversity research have been devoted to communities in static landscapes with time-constant environmental parameters. In contrast, not much is known about biodiversity patterns in dynamic landscapes, characterized by temporal changes in key abiotic factors. In dynamic landscapes the community structure will typically be far from equilibrium and is driven by a complex interplay of stochastic extinction, colonization and community assembly processes. A conceptual framework is formed by the theory of island biogeography which describes the number of species in an isolated habitat as a dynamic equilibrium of local extinctions and immigrations from a regional species pool. Recently, this framework was extended within the neutral theory of biogeography, which captures diversity and relative species abundances by stochastic drift based on the assumption of per-capita ecological equivalence of species. In these theories, the equilibrium species richness is closely related to the size of the habitat, which is usually assumed to be constant. A constant habitat size, however, does not reflect the reality of many natural environments. Landscapes often change in time, for example caused by ecological, geological, climatic, biophysical, or anthropogenic drivers. In this project we will use theoretical approaches to study biodiversity patterns in communities in which key environmental parameters, such as habitat size, are changing in time.

 

Outline

The PhD thesis will comprise mathematical modeling, data analysis, and experiments to analyze the biogeography, community assembly and biodiversity of dynamic landscapes. In particular, we will address habitats that are increasing in size with time. One compelling example is provided by communities that use other organisms as living substrate, such as epiphyte communities on trees in tropical forests. Thereby, the trees can be seen as islands of benign environments, that are growing in size but may also disappear due to tree fall, in a dynamic forest matrix. Other examples are arthropod communities on trees, invertebrate communities in tank bromeliads, mesofaunal communities in moss cushions, faunal communities on coral reefs, or microbial communities in the human gut.

The PhD student will develop stochastic population models to describe the population dynamics, biodiversity, and species assembly of a community on a growing or temporally changing habitat. A first model for an epiphyte community on a growing tree has already been developed in a BSc thesis by Jost Hellwig. The models will include key community processes (e.g., immigration, reproduction, extinctions) but will also describe the dynamic change of the habitat parameters (e.g., deterministic tree growth and stochastic tree fall). Using the model, the PhD student will study biodiversity, rank-abundance curves, species turnover, the percentage of occupied habitat, species-area relationships, and species-time relationships as a function of the age of the habitat. In a second step, a spatially explicit approach will explore the composition of a meta-community of local communities, which exist on dynamic habitats with temporally changing capacity. The modeling will be complemented by data analyses of field communities. In particular, we will investigate data on the distribution and number of different vascular epiphyte communities in a lowland rain forest in Panama. Finally, the PhD student will have the opportunity to test these ideas in colonization experiments on artificial tiles. Tiles of different size and time-varying assemblages and geometry will be exposed to sea-water under controlled conditions. Using this set-up we will measure the colonization of phytoplankton for different time instances.

(Stand: 19.01.2024)  | 
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