PhD (or PostDoc) position: Linking aggregate pore geometry to microbial interactions and functions in soil – SomSOM – Self-organization of microbial soil organic matter turnover (OT127)

Project summary

Microbial turnover of soil organic matter (SOM) is key for the terrestrial carbon (C) cycle. Its underlying mechanisms, however, are not fully understood. The role of soil microbes for organic matter turnover has so far been studied mainly from the point of view of microbial physiology, stoichiometry or community composition. In this project, we aim to shed new light on it from the perspective of complex systems science.

Microbial decomposition of organic matter requires the concerted action of functionally different microbes interacting with each other in a spatially structured environment. From complex systems theory, it is known that interactions among individuals at the microscale can lead to an ‘emergent’ system behavior, or ‘self-organisation’, at the macroscale, which adds a new quality to the system that cannot be derived from the traits of the interacting agents. Importantly, if microbial decomposer systems are self-organised, they may behave in a different way as currently assumed, especially under changing environmental conditions.

The aim of this project is to investigate i) if microbial decomposition of organic matter is driven by emergent behaviour, and ii) what consequences this has for soil C and nitrogen cycling. Combining state-of-the-art methods from soil biogeochemistry, microbial ecology, and complex systems science we will

• Investigate mechanisms of spatial self-organization of microbial decomposer communities by linking microscale observations from experimental microcosms to mathematical, individual-based modelling,
• Elucidate microbial interaction networks across the soil’s microarchitecture by linking microbial community composition, process rates and chemical composition of spatially explicit soil micro-units at an unprecedented small and pertinent scale.
• Explore fundamental patterns of self-organisation by applying the framework of complex systems science to high-resolution spatial and temporal data of soil microstructure and process rates.

I am looking for enthusiastic PhD students and postdoctoral researchers interested in carrying out research at the interface between Soil Microbial Ecology, Soil Biogeochemistry and Complex Systems Science in a creative, interdisciplinary team.

I am offering fully funded PhD (4 years) or PostDoc (2.5 years) positions at the Division for Terrestrial Ecosystem Research at the Centre for Microbiology and Environmental Systems Science of the University of Vienna. Our Division and Centre offers excellent opportunities for scientific interactions and collaborations and a vivid, cooperative and friendly working environment, in a city with one of the best living conditions in the world.

More about

Christina Kaiser’s team and research: http://ter.csb.univie.ac.at/people/christina-kaiser

Division for Terrestrial Ecosystem Research: http://ter.csb.univie.ac.at/

Centre for Microbiology and Environmental Systems Science: http://cmess.csb.univie.ac.at/

Open positions are available in the different project parts as described below. Applicants must have good communication skills and should be highly motivated and committed to pursuing interdisciplinary research in an international team. Excellent English in speaking and writing is mandatory. The University of Vienna values equal opportunities, as well as diversity (http://diversity.univie.ac.at/), and lays special emphasis on increasing the number of women in senior and in academic positions. Women are encouraged to apply.

Please send your application including

• a motivation letter (1-2 pages max; please clearly specifiy the project part/position you are applying for – see below)
• CV (including scientific publication and presentation activities, if any)
• Contact details of two possible references

to christina.kaiser@univie.ac.at. Positions will be filled as soon as possible and remain open until filled. Evaluation of applications starts in May 2019.

For questions please contact christina.kaiser@univie.ac.at.

An updated version of this document is available at http://ter.csb.univie.ac.at/open-positions

Introduction

Pore geometry of soil aggregates are essential for microbial dynamics as it determines i) habitability, ii) accessibility of substrates to microbes and iii) accessibility of microbes for predators. Geometric properties of the pore network, such as connectivity and fragmentation, greatly influence potential microbial interactions. At a high fragmentation (i.e. islands of reasonable habitats separated by long distance connections with limited resource access), for example, species with a small range of dispersal will have access only to a small fraction of the network while species with a long range of dispersal, such as fungi can percolate through the network.

In this project part I am looking for a motivated PhD student or a postdoctoral researcher, who is interested in soil microscale interactions, ecology, graph theory and complex systems science.

The successful candidate will extract geometric properties and pore size distribution data from 3D micro-CT images of soil aggregates. This data will be used to generate ‘model pore network landscapes’ reflecting characteristic geometric properties of pore networks of certain aggregate types, in a refined (i.e. 3D) version of an existing individual-based microbial community model (Kaiser et al., 2014, 2015; Evans et al., 2016). The resulting model will be – together with measured parameters - used to investigate how certain spatial structures and pore geometric properties affect microbial interactions and, in turn, soil organic matter decomposition. Percolation-, graph theory and other mathematical approaches will be used to analyse results.

The successful candidate should have the following skills:

• Background in soil microbial ecology or soil science
• Alternatively, a background in mathematics, physics, informatics or complex systems science
• Programming skills (ideally JAVA, other programming languages also ok)
• Good command of R
• Experience with image processing/image processing software is an advantage

He or she will work closely together with the rest of the project team.

More information available here.