The predictability of temperature effects on ecological dynamics

Predicting the consequences of environmental change requires an understanding of their effects across multiple levels of ecological organisation: individual, population, community, and ecosystem. Also required is an understanding of how effects at one level of organisation create knock-on effects at other levels of organisation. For example, how changes in individual behaviour translate into a change in population dynamics. Laboratory-based experiments with communities of aquatic microorganisms (e.g. ciliates) provide an excellent test bed for studying environmental change across levels of ecological organisation. Long-term experiments (many generations of the dominant organisms) can be carried out during quite short experiments, and observations can be made across levels of ecological organisation. Carefully constructing communities in terms of species composition, i.e. containing few to many species, short to long food chains, and low to high trophic diversity will further allow to manipulate ecological complexity, as found in natural systems. Mathematical models fitted to the observed data can be used to link observations across levels of organisation and make predictions. Joined together, these features allow for thorough, novel, and exciting research about the predictability of ecological dynamics in changing environments.

The PhD is part of a SNF funded research project concerning the predictability of temperature effects on ecological dynamics. The PhD student will conduct a series of experiments using microbial communities under controlled laboratory settings. Communities will be subjected to a combination of temperature and nutrient availability treatments and monitored with the help of automated video techniques (www.bemovi.info). Additional data collected by the student will help him/her to parameterize a process-based model of the community. To evaluate the ecological predictability of temperature effects, we then confront model predictions with data from the community experiment. The PhD student will be guided and assisted by the postdoctoral position in the project, whose focus otherwise is on conceptual work and synthesis. The SNF project is joined in the Predictive Ecology Group by numerous related projects researching ecological predictability.

The PhD will be jointly supervised by Prof. Owen Petchey and Dr. Frank Pennekamp, in the Predictive Ecology Group of the Institute of Evolutionary Biology and Environmental Studies at the University of Zürich, Switzerland. Funding is available for at least 3.5 years. We look for motivated candidates interested in combining experimental work with theoretical developments; prior laboratory experience with microbial systems is an advantage, but not obligatory. Applicants must have a Masters Level Degree in Ecology or a closely related subject, and should provide as a single pdf a CV, including the names and contact details of three academic referees, and a cover letter including relevant information (e.g., highlighting relevant previous experience and interests). Applications and enquiries should be send to [Email Address Removed] or [Email Address Removed]. Applicants will be considered till the position is filled. We invite outstanding applicants to visit.

For more information:
Owen Petchey (www.ieu.uzh.ch/staff/professors/petchey.html)
Frank Pennekamp (www.ieu.uzh.ch/staff/postdocs/fpennekamp.html)
Predictive Ecology Group (www.ieu.uzh.ch/research/ecology/extinction.html)