Course Catalogue

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The course focuses on hands-on social-ecological modelling and demonstrates how models can provide real-world, actionable evidence for sustainable environmental risk management decision making. This course advances students' conceptual understanding of model design within a framework and practical experience in model development and implementation (policy and scenario analysis) to address specific objectives. Students gain experience in data driven and process based modelling applied in a number of case studies that allow students the opportunity to relate their learning to real world scenarios. Students are introduced to modelling basic aspects of programming, model building, data manipulation, and visualisation in modelling software (e.g., STELLA, R, ArcGIS) to simulate social-ecological changes and risk.

The course is delivered through online materials, seminars, intensive practical sessions and is assessed through a combination of group and individual case studies (conceptualization to implementation of models), and a mock presentation to stakeholders. This assessment will be submitted in the stages during the term to enable ongoing feedback throughout the semester. 

2-hour lecture and either 2-hour seminar/practical/workshop session weekly

Admission to programme

None

The assessment will be delivered in stages over the semester to enable iterative feedback:

1. Written assessment (Policy brief: 25%) based on set exercise (25%) (ILOs1-2)

2. Group work (modelling exercise and report) to understand model development, validation and implementation (30%) (ILOs1-5)

3. A 10-minute group presentation, aimed at a broad range of stakeholders, including outputs from the modelling exercises (20% - including peer feedback element (5%)) (ILOs 5-6)

The aims of the course are to:

■ Introduce a range of modelling applications for climate change, and sustainable environmental risk management.

■ Develop an understanding of models available for climate change and environmental risk management, with special attention to data-driven and process-based models for the analysis of social-ecological systems and their interactions.

■ Explore theoretical and practical limitations of social-ecological models to inform decision-making on social-ecological changes and risk

By the end of this course students will be able to:

1. Describe the fundamental principles of social-ecological modelling;

2. Explain the role and key principles of data-driven and process-based social-ecological models in climate change and environmental risk management; 

3. Design and evaluate conceptual and empirical social-ecological models and test them (validation, sensitivity); 

4. Implement a model (scenario and policy analysis) for addressing a sustainability challenge focusing environmental risk and identify alternatives from a stakeholder perspective;

5. Encourage a critical approach to the evaluation and application of model-based environmental risk and climate change science, including the challenge of model with stakeholders;

6. Develop social-ecological system thinking ability and written and oral communication skills;

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.