It is announced that the call for registrations to ERACOM MSc program will open at 20 February 2016



Core course






Theodore Karacostas, Antonios Matzaris, John M. Haley, Prodromos Zanis



Ecological modelling as a rather new scientific discipline offers a series of tools and techniques towards improving our understanding on the functionality and structure of ecological systems in order to support conservation, management, and policy development. Ecological modelling combines biological sciences, mathematics, physics, and computer sciences. In this course students will learn the modelling tools and research activities to provide the basis for evaluating patterns of diversity and problems arising at different ecosystems and to describe basic ecological process and ecosystems.  A series of different techniques and research examples be presented including: spatial and temporal population models, coupled ecological-economic models, simulation dynamic models, individual based models, and population viability analyses. The basic goal of this course is to improve the understanding on ecological modelling toolsets and develop the ability to use such tools for studying environment issues and processes. Main ecological components, key concepts and principles in ecological modeling scientific branch are described. Also the course explores the benefits of climate modelling for understanding the climate system and assessing climate variability and climate changes. The course begins with a description of the climate system, its feedback mechanisms and the chemistry-climate interactions. It continues with a historical review of climate models and a description of the basic components of a climate model including the dynamical core and the physical parameterizations. It follows an introduction to Global Climate Models (GCMs) and Regional Climate Models (RCMs).Then the theoretical part of the course ends with analysis of the errors and uncertainties in climate future projections related to initial and boundary conditions, the natural forcing and anthropogenic forcing and the importance of stochastic projections for future climate change. At the end of the theoretical part of the course a training course will follow using a simple climate model for the assessment of greenhouse-gas induced climate change and a regional climate scenario generator to produce spatially detailed information of this climatic change. 


Learning outcomes

  1. To provide a background in fundamental aspects of environmental science and
    ecological modelling issues and tools.
  2. To address the links between natural environments, real data and predictive
    modelling tools.
  3. To become familiar with simulation models and learn how to develop system-
    dynamic models that could be applied in scientific, environmental, and social
  4. To provide a general structure and toolsets for ecological modelling that
    incorporates models at different structural levels operating at different spatial
    and temporal scales.
  5. The ability to describe and analyse environmental datasets by using specific
    modelling processes.
  6. Develop a theoretical framework upon which conceptual models will be developed
    and used to study historical and current data in order to select effective
    conservation policies. Students will gain insights into climate modelling and its
    applications in global and regional scale.
  7.  Students will be able to critically assess the use of GCMs and RCMs for studies at
    coastal environments.
  8. Students will become familiar with setting up a GCM model experiment through
    the training course.
  9. The training course will allow the students to determine changes in greenhouse-
    gas concentrations, global-mean surface air temperature, and sea level resulting
    from anthropogenic emissions.
    Students will be able to set up GCMs projects for the assessment of greenhouse-
    gas induced climate change under different future emission scenarios, and write
    reports and policy recommendations.


  1. Two writing assignment (50%)
  2. Student seminars/Class presentation (50%)
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