Welcome!

The junior research group for Eco-Evolutionary Modelling, led by Dr. Korinna Allhoff, was founded in April 2022. Our research projects are diverse and rooted in various sub-disciplines of ecology. All of them have the common goal to understand how complex ecosystems are structured and how this structure affects their functioning and stability. We are particularly interested in questions related to the eco-evolutionary emergence of complex interaction networks, as well as their long-term responses to disturbances and changing environmental conditions. We address our research questions from a theoretical perspective using a mix of tools, including individual-based modelling, dynamical systems theory and adaptive dynamics.

If you are interested in joining the team or if you have questions concerning the courses that we teach (see below!) then please don't hesitate to get in touch. We are always happy to chat about our current research projects as well as about theoretical ecology in general! :-)

NEWS: We are hiring!! The first of two job postings for a PhD position in theoretical ecology is now online. It will be part of a larger, interdisciplinary DFG project that investigates fitness consequences of biotic interactions in various systems. More information can be found here.

 

 

Contact

Dr. Korinna T. Allhoff

Institut für Biologie
FG Eco-Evo Modelling (190m)
Garbenstraße 30
D-70599 Stuttgart

Office: Bio II, 1.OG, Zi. 195/196
Tel.: +49 (0)711 459 24239
E-Mail


This is us...

...in March 2023, after taking a walk around our beautiful Campus, in the botanical garden in Hohenheim.

From left to right: Elisabeth Lang (Msc student), Avril Weinbach (postdoc), Korinna T. Allhoff (group leader), Franziska Koch (doctoral researcher), Sebastian Krüger (MSc student) and Malina Palmer (doctoral researcher).

...in June 2023, after taking a well-deserved break from maths and coding in the "Waldseilgarten" in Herrenberg.

From left to right: Franziska Koch (doctoral researcher), Deborah Doe (guest student from Ghana), Korinna T. Allhoff (group leader), Knut Reindl (BSc student), Malina Palmer (doctoral researcher) and Felix Jäger (doctoral researcher). 

... in September 2023, after organising a session about feedback loops at the European Conference on Ecological Modelling in Leipzig.

From left to right: Avril Weinbach (postdoc), Korinna T. Allhoff (group leader), Felix Jäger (doctoral researcher), Malina Palmer (doctoral researcher) and Franziska Koch (doctoral researcher).


Active group members (March 2024)

NameTitleRoleContact / more information
Allhoff, Korinna TheresaDr. rer. nat.group leaderE-mail / Google Scholar / ORCID / ResearchGate
Koch, FranziskaM.Sc.doctoral researcherE-mail / Google Scholar / ORCID / ResearchGate
Jäger, FelixM.Sc.doctoral researcherE-mail / Google Scholar / ORCID
Doe, DeborahB.Sc.guest student
Baer, MiraBSc student
Németh, ÁdámBSc student
Seidt, RobinBSc student

Alumni

NameRoleYearContact
Palmer, Malinadoctoral researcher2022-2024
Weinbach, AvrilPostdoc2022-2023Google Scholar / ORCID / ResearchGate

Completed theses

NameTitle / RoleYearContact
Neumann, JuleM.Sc.2024
Reindl, KnutB.Sc.2023
Lang, ElisabethM.Sc.2023
Krüger, Lorenz SebastianM.Sc.2023
Palmer, MalinaM.Sc.2022
Weyerer, FranzM.Sc.2022

Preprints

  • Koch, F., Neutel, A. M., Barnes, D. K. & Allhoff, K. T. (2024). Skewness enables stabilising effect of hierarchy in complex competition networks. BioRxiv preprint.

Publications

  • Weyerer, F., Weinbach, A., Zarfl, C., & Allhoff, K. T. (2023). Eco-evolutionary dynamics in two-species mutualistic systems: One-sided population decline triggers joint interaction disinvestment. Evolutionary Ecology.

    https://doi.org/10.1007/s10682-023-10264-2

  • Koch, F., Neutel, A. M., Barnes, D. K., Tielbӧrger, K., Zarfl, C., & Allhoff, K. T. (2023). Competitive hierarchies in bryozoan assemblages mitigate network instability by keeping short and long feedback loops weak. Communications Biology, 6(1), 690.

    https://doi.org/10.1038/s42003-023-05060-1

  • Koch, F., Tietjen, B., Tielbörger, K., & Allhoff, K. T. (2023). Livestock management promotes bush encroachment in savanna systems by altering plant–herbivore feedback. Oikos, 2023(3), e09462.

    https://doi.org/10.1111/oik.09462

Older publications by the individual group members can be found on their online profiles (see above).


Teaching

Computational Ecology: Modelling Systems Across Scales

This course is an introduction to agent-based modelling, designed for BSc students. It takes place during the winter semester. The main goal is to learn how to use computer simulations as virtual laboratories or virtual field stations. More precisely, participants practise (a) how to translate ecological questions into agent-based models, (b) how to implement and analyse these models using NetLogo, and (c) how to finally place their simulation results in the context of current literature. Based on these three skills, all participants carry out an independent modelling project at the end of the course. Students with very little (or even no) experience in modeling or programming are explicitly welcome. All relevant techniques and skills will be explained when needed so that no special prior knowledge is required.

Theoretical Ecology: From Chaos to Coexistence (-> ILIAS for SS24)

This course is an introduction to dynamical systems theory, designed for MSc students. It takes place during the summer semester. During each session, we start with an ecological question, translate this question into a mathematical model and then investigate this model using a combination of analytical tools and computer simulations. Amongst other topics, we discuss early warning signals for tipping points, deterministic chaos, the paradox of enrichment, the competitive exclusion principle, adaptive dynamics, eco-evolutionary feedback and random matrix theory. We start with relatively simple models describing the dynamics of single populations, such as exponential or logistic growth. In a second step, we then move on to models of pairwise species interactions, such as Lotka-Volterra predation or competition. Finally, we also investigate more complex systems, such as interaction networks or systems with trait evolution. Each model is analyzed in an interactive manner, using jupyter notebooks, with lots of opportunities for practical hands-on experiences. The structure of the course is similar to the first course, meaning that all participants learn how to carry out their own modelling project. Previous participation in the summer course can be an advantage, but is not a compulsory requirement.