Preface

Networks are useful descriptors of ecological systems that put the emphasis on the interactions between multiple elements. They provide a conceptual framework to assess the consequences of perturbations at the community level. This may serve to assess relevant questions such as how overfishing can cause trophic cascades, or how the disruption of mutualisms may reduce the pollination service within a community. Networks are also a means to introduce heterogeneity into our previously homogeneous theories of populations, diseases, and societies. Finally, networks have allowed us to find generalities among seemingly different systems that, despite their disparate nature, may experience similar constraints on their architecture in order to be functional.

This block course – aimed at bachelor (3rd year) and master students – will involve morning lectures and afternoon exercise sessions. The lectures will provide an introduction to complex networks and their application to characterizing the structure and robustness of networks of species interactions, genetic networks, and spatial networks. The exercises will use a public repository of ecological networks that will be analyzed quantitatively by means of open-source code using an interactive platform. Overall, this course will provide a way to look at old ecological topics, such as community robustness or habitat fragmentation, with novel quantitative approaches. The course may also be of interest for students interested in applying network theory to other fields.

Learning goals of the course

By the end of this course, students should:

  • Be acquainted with techniques used to represent and visualize networks.
  • Understand measures of network structure such as degree distribution, modularity, and nestedness.
  • Be familiar with approaches to assess network robustness.
  • Build a macroscopic understanding of systems composed of interacting elements such as species within a community or habitat patches linked through dispersal.

Lecture plan

The full timetable of the course is available here. Below you can find the lecture plan with links to slides being progressively updated:

lecture instructor topic slides
March 14 morning Vindigni Outline and Intro slides
March 14 afternoon Vindigni Toolkit for network analysis
March 15 morning Cosmo The role of species in networks slides
March 15 afternoon Román Species-level metrics
March 19 afternoon Knop/Grognuz Sampling an ecological network slides
March 20 morning Cosmo Topological patterns in ecological networks slides
March 20 afternoon Bhandary/Vindigni Networks-level metrics
March 21 morning Pedraza Null models slides
March 21 afternoon Pedraza Null models
March 22 morning Vindigni Network robustness slides
March 22 afternoon Vindigni Measuring network robustness
March 26 afternoon Gawecka/Vindigni Students’ short talks slides
March 27 morning Bhandary Models of ecological dynamics slides
March 27 afternoon Bhandary Models of ecological dynamics
March 28 morning Román Genetic Networks slides
March 28 afternoon Román Analyzing genetic networks
April 9 afternoon Gawecka/Vindigni Students’ short talks slides
April 10 morning Gawecka Spatial networks slides
April 10 afternoon Gawecka Comparing networks in space
April 11 morning Cosmo Coevolution slides
April 11 afternoon Cosmo Models of evolution in networks
April 12 afternoon Vindigni Exam

Working settings

Slides of mornings’ lectures and suggested readings will be available on OLAT. Slides will also be distributed by updating the links in the table above. The material for exercise sessions will be accessible through the RStudio Server, but you need to be connected to the UZH or ETHZ VPN.

Assessment

Your grade will be determined by the exercise sessions (up to 3 points) and by the final exam (up to 2 points). Each exercise sessions (afternoons) will be graded on a scale from 1 to 6 by the instructor responsible for that session. Your performance on this practical part of the course will then be determined by the average of all grades obtained in the exercise sessions. Students are expected to complete the assignments directly on the RStudio Server, after having logged in with their personal credentials. Assignments must be completed on this RStudio environment and there should run/compile, as it will be explained during the first exercise session. Each afternoon assignment must be submitted on OLAT by midday of the next day. An exception is the exercise session Sampling an ecological network, for which data can be collected throughout the course and the report handed in by Saturday, April 13th at 1:00 pm.
The exam consists of a single-choice test on the topics of the morning lectures.

General readings

  • Several authors (2009). Complex Systems and Networks. (Special Section). Science 325: 405-432.
  • Bascompte, J. and Jordano, P. (2013). Mutualistic Networks. Princeton University Press.
  • Pascual, M. and Dunne, J.A. (2006). Ecological Networks: Linking Structure to Dynamics in Food Webs. Oxford University Press.
  • Pimm, S.L. (1982). Food Webs. Chicago University Press.
  • Barabási, A.-L. (2016). Network Science. Cambridge University Press.
  • Barabási, A.-L. (2002). Linked: The New Science of Networks. Perseus Books Group.
  • Newman, M. (2018). Networks. Oxford University Press.

Acknowledgements

We would like to thank previous instructors of this course across the years: C. Melián, M. A. Fortuna, L. Gilarranz, N. Georgomanolis, G. Losapio, D. Wechsler, J. Evans, C. Graham, C. Bello, M. Gaiarsa, M. Barbour, M. Hutchinson, and R. Cámara-Leret. We also thank Karin Isler for useful feed-back on the structure of the course.