Introduction to network analysis in biogeography


Eric A Treml, University of Melbourne  (


Many key and unresolved problems in ecology, biogeography, and conservation are influenced by population connectivity. Where do animals move through their landscape? What is the spatial temporal structure of population connectivity? To what degree are distant populations interbreeding? Where are, and how strong, are dispersal barriers? How far can propagules and young disperse? What is the optimal distance and placement of reserves? Network analysis has become particularly useful in many disciplines, including population genetics, landscape ecology, biogeography, community ecology, and conservation. Graph theory is an area of mathematics that deals with problems of connectivity, flow, routing, and community structure of networks ranging across many disciplines.

This workshop offers participants an introduction to this diverse field and highlights key papers and ideas in marine and terrestrial ecology and biogeography. The goal is to provide a broad introduction to network thinking, and enable participants to develop and analyse a habitat network of their choice. By the end of this workshop, individuals will be familiar with graph theory, network analysis, and the tools and data available. Finally, students will gain an appreciation for the power of communicating and engaging communities with the intuitive graph structure.

The workshop uses brief lectures, discussions of the key literature, and individual based study to provide hands on experience. This workshop is open to anyone interested in network questions, no previous knowledge or expertise is required besides basic R programming skills and a basic understanding of GIS. All presentation materials, example code, and datasets are made available to participants.
By the end of the workshop, participants will be able to:

  1. Develop a broad understanding of network analysis across various disciplines;
  2. Understand key network properties and behaviours and associated algorithms;
  3. Become familiar with network analysis programs and tools;
  4. Develop and analyse a habitat network of their choice.

Software requirements for students


Workshop structure:

I. Introduction to Network Thinking

  •  Overview & brief introductions
  •  Networks across science
  •  Graph/network definitions
  •  Workshop: defining your ecological network

II. Building Networks

  •  Scale independence
  •  Modelling habitat–the nodes
  •  Quantifying connectivity–the edges
  •  Workshop:Building&visualizing networks in R

III. Network Analysis

  • Local to global network perspectives
  • Connectivity & routing problems
  • Community structure & clusters
  • Centrality measures

IV. Advanced topics

  • Graph manipulation Plotting and queries
  • Spatial analysis
  • Null Models
  • Hypothesis testing