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 the podcasts and slides being progressively updated:

lecture instructor topic slides
March 16 morning Bascompte Outline and Intro slides
March 16 afternoon Vindigni Toolkit for network analysis
March 17 morning Bascompte Food webs slides
March 17 afternoon Vindigni Measuring modularity
March 21 afternoon Knop Sampling an ecological network slides
March 22 morning Bascompte Mutualistic networks slides
March 22 afternoon Gawecka Measuring nestedness
March 23 morning Bascompte Null models slides
March 23 afternoon Pedraza Null models
March 24 morning Gawecka Spatial networks slides
March 24 afternoon Gawecka Comparing networks in space
March 28 afternoon Pedraza/Vindigni Simulating networks slides
March 29 morning Vindigni Network robustness slides
March 29 afternoon Vindigni Measuring network robustness
March 30 morning Román Genetic Networks slides
March 30 afternoon Román Analyzing genetic networks
March 31 morning Pedraza Evolution in networks slides
March 31 afternoon Pedraza Models of evolution in networks
April 5 afternoon Bascompte/Vindigni General discussion slides
April 6 morning Bascompte/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 8th at 1:00 pm.
The exam consists of a multiple-choice test on the topics of the morning lectures.

General readings

  • Several authors (2009). Complex Systems and Networks. (Special Section). Science 325: 405-432.
  • Barabási, A.-L. (2016). Network Science. Cambridge University Press.
  • 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.
  • Barabási, A.-L. (2002). Linked: The New Science of Networks. Perseus Books Group
  • Pimm, S.L. (1982). Food Webs. Chicago 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.