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KININMONTHS on King Island

  
 
 
 
 

 
 

Stuart Kininmonth

Curriculum Vitae
Publications
Doctorate

Network Theory in Ecology Course

Previoulsy taught at Murdoch University, Woolongong University, University of Queensland, Auckland University, James Cook University, University of La Luguna (Spain).

This course developed with Dr. Eric Treml can be conducted upon request or email.

 

Course Description
Many key and unresolved problems in ecology and conservation are concerned with connectivity. Where do animals move through their landscape? To what degree are distant populations interbreeding? Where are the multi-species dispersal barriers? How far can 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, 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 short course offers participants an introduction to this diverse field and highlights key papers and ideas in marine and terrestrial ecology and conservation. 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 course, 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 course uses brief lectures, discussions of the key literature, and individual-based workshops to provide hands-on experience.

Required Software; (will be available on disk on the day)

  • Pajek, free (http://pajek.imfm.si/doku.php)
  • R with igraph, free (http://www.r-project.org/ & install packages("igraph"))

Length of Course
           2 to 4 days

Course Objectives
By the end of the course, participants will:

  1. Develop a broad understanding of network analysis across various disciplines;
  2. Understand key network properties and behaviours;
  3. Become familiar with a variety of network analysis programs and tools;
  4. Understand the steps required to develop and analyse a habitat network
  5. Gain insights into effective communication and visualisation with networks

Instructional equipment required:
Digital projector
Participants will need own laptop or provided PC
White board
Internet access would be ideal, though not absolutely necessary.

Maximum number of students:
            min: 8 students
            max: 25 students, depending on space.

Can agencies use the information, if so, how?
Any agency interested in studying, understanding, managing, or communicating concepts of connectivity would gain valuable information from this short course. This course should appeal to a multidisciplinary audience and participants will be encouraged to use their own data. The information provided will allow agencies to skip the long learning curve for analysing social, ecological, and habitat networks with graph theory.