Syllabus for Population and Community Ecology

Populations- och samhällsekologi

A revised version of the syllabus is available.


  • 15 credits
  • Course code: 1BG309
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Biology A1N
  • Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
  • Established: 2007-03-15
  • Established by: The Faculty Board of Science and Technology
  • Revised: 2010-04-15
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: Autumn 2010
  • Entry requirements:

    150 credits complete courses including alternative 1) 60 credits biology and 30 credits chemistry or 30 credits earth sciences; alternative 2) 90 credits biology. In both cases, the biology should contain Ecology or Limnology.

  • Responsible department: Biology Education Centre

Learning outcomes

The course intends to provide advanced knowledge in ecological theory in population and community ecology. The course also gives skills in using mathematical models as tools to understand the development of populations and community ecology processes. After completing the course, the student should be able to

  • explain how and why one uses models in ecology. How to design, analyse and test population models
  • Identify the difference between phenomenological and mechanistic models
  • use basic models of intraspecific interactions (density dependent population dynamics) and interspecific interactions (predatory-pray models, mechanisms for coexistence; equilibrium, not equilibrium)
  • compare stage and age structured row population dynamics: demographic effects, effects of different life history strategies
  • apply the niche concept and alternative models (for example neutral theory) for biodiversity and species composition and evaluate the importance of the species composition and the diversity for population and community dynamics
  • assess the importance of interactions in food webs for the development of populations and communities. Trophic dynamics, direct and indirect effects in food webs
  • explain the importance of spatial scale for interactions within and between populations and account for interactions between metapopulations and metacommunities
  • handle ecological data, critically review research results/theories and formulate new questions communicate scientific results orally and in written form.


The course is based on the students' background knowledge of ecology from basic courses and provides a deeper knowledge of ecological theory. The course comprises a considerable part of group assignments stressing the planning of scientific investigations and the analysis of ecological data (computer simulations, numerical and statistical calculations) that are presented orally and in written form.

The course gives training in evaluation and critical assessment of research results. The emphasis is on how to handle ecological data to solve problems relevant for ecological research and for practical applications within conservation and sustainable development. The course gives skills in using mathematical and graphical models to analyse population and community processes and from these interpreting results and formulating new hypotheses.


The teaching is given in the form of lectures, laboratory practicals, seminars, computer exercises, literature assignments and project work. Participation in lab practicals, seminars, computer exercises, literature assignment and project work is compulsory.


Modules: Theory 10 credits; Exercises (computer-based laboratory sessions, group assignments) 5 credits

The theory part is comprised by a written examination. The module exercises require active participation in computer-based laboratory sessions and group assignments and is followed up by oral and written presentation.

Reading list

Reading list

Applies from: Autumn 2014

Some titles may be available electronically through the University library.

  • Mittelbach, Gary George. Community ecology

    Sunderland, Mass.: Sinauer Associates, c2012

    Find in the library

Last modified: 2022-04-26