Application deadline finishes 16.11.2020
OFFER DESCRIPTION
The position is funded by the Swiss National Science Foundation project "An experimental assessment of how trophic interaction modifications affect community stability and predictability."
Understanding and predicting the dynamics of ecological communities is challenging for all but the simplest communities. Even well-studied systems sometimes display unforeseen dynamics and sudden changes, which may be so unexpected that they can only be described as “ecological surprises”. One reason for these surprises lies in the multitude of indirect effects that arise in complex communities. Such indirect effects occur whenever species interact in more than pairs, which is the rule for most ecological communities. Indirect effects can be both density- and trait-mediated, and we currently do not have a good understanding of how they affect the stability and predictability of ecological communities.
We will develop a new experimental system – a tritrophic community of protists in a flow-through system – to collect long-term, high-frequency time series of community dynamics to which community models can be fitted. At the same time, we will estimate interactions strengths from short-term experiments (functional responses) and parameterize community models. Trophic interaction modifications and strengths from both approaches will be compared to elucidate differences in time scales and their ability to predict out-of-sample dynamics. Furthermore, we will test hypotheses regarding the long-term stability of the food webs based on the distribution of interaction strengths observed.
The project will be embedded in the Biotic responses to environmental change research group led by Dr. Frank Pennekamp in the Department of Evolutionary Biology and Environmental Studies at the University of Zurich. Access to state-of-the-art infrastructure, a diverse and interactive scientific atmosphere, and an international, largely English-speaking working environment is provided. The modeling part will be supported by Prof. Jordi Bascompte (University of Zurich) and Louis-Félix Bersier (University of Fribourg). Opportunities for professional development, e.g. in project management, leadership, mentoring, teaching and grant writing, are available and encouraged.
How to apply: Application review will begin mid-November 2020. Send your application as a single pdf file to Maja Weilenmann (maja.weilenmann@ieu.uzh.ch). Include in your application: a cover letter explaining your interest in and suitability for the position, your CV including your publication record, a copy of your Ph.D. diploma and courses taken, and names, institutional affiliations, email addresses and phone numbers of three referees.
Starting date is early in 2021 (ideally 1.1.2021), but to be determined by mutual agreement. The position has funding for three years in total.
OFFER DESCRIPTION
The position is funded by the Swiss National Science Foundation project "An experimental assessment of how trophic interaction modifications affect community stability and predictability."
Understanding and predicting the dynamics of ecological communities is challenging for all but the simplest communities. Even well-studied systems sometimes display unforeseen dynamics and sudden changes, which may be so unexpected that they can only be described as “ecological surprises”. One reason for these surprises lies in the multitude of indirect effects that arise in complex communities. Such indirect effects occur whenever species interact in more than pairs, which is the rule for most ecological communities. Indirect effects can be both density- and trait-mediated, and we currently do not have a good understanding of how they affect the stability and predictability of ecological communities.
We will develop a new experimental system – a tritrophic community of protists in a flow-through system – to collect long-term, high-frequency time series of community dynamics to which community models can be fitted. At the same time, we will estimate interactions strengths from short-term experiments (functional responses) and parameterize community models. Trophic interaction modifications and strengths from both approaches will be compared to elucidate differences in time scales and their ability to predict out-of-sample dynamics. Furthermore, we will test hypotheses regarding the long-term stability of the food webs based on the distribution of interaction strengths observed.
The project will be embedded in the Biotic responses to environmental change research group led by Dr. Frank Pennekamp in the Department of Evolutionary Biology and Environmental Studies at the University of Zurich. Access to state-of-the-art infrastructure, a diverse and interactive scientific atmosphere, and an international, largely English-speaking working environment is provided. The modeling part will be supported by Prof. Jordi Bascompte (University of Zurich) and Louis-Félix Bersier (University of Fribourg). Opportunities for professional development, e.g. in project management, leadership, mentoring, teaching and grant writing, are available and encouraged.
How to apply: Application review will begin mid-November 2020. Send your application as a single pdf file to Maja Weilenmann (maja.weilenmann@ieu.uzh.ch). Include in your application: a cover letter explaining your interest in and suitability for the position, your CV including your publication record, a copy of your Ph.D. diploma and courses taken, and names, institutional affiliations, email addresses and phone numbers of three referees.
Starting date is early in 2021 (ideally 1.1.2021), but to be determined by mutual agreement. The position has funding for three years in total.
OFFER REQUIREMENTS
Skills/Qualifications
Skills/Qualifications
- Knowledge of ecological concepts and theory, particularly those pertinent to community stability, species interactions and food webs.
- Experience designing, running, and analysing ecological experiments.
- Relevant publications in peer-reviewed scientific journals.
- Prior work with time series and mathematical modeling are beneficial.
- A relevant Ph.D. degree.
- Project management skills.
- Ability to work in a team and independently.
