Undergraduate Course: Modelling Ecosystem Processes (ECSC10040)
Course Outline
| School | School of Geosciences |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 10 (Year 4 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This course introduces the key approaches to modelling in the ecological and environmental sciences. It will provide students with the conceptual understanding of how to represent complex ecosystems within a model framework and practical experience of model design, construction, sensitivity analysis, calibration, validation/evaluation and analysis to address specific objectives. The students will learn how models can provide real-world, actionable evidence for sustainable ecosystem interventions against a backdrop of global environmental change. The students will learn how models can help test and generate new hypotheses to understand ecosystem functions. Students are challenged to formulate testable hypotheses, and design suitable models of differing complexity, including both discrete (i.e. agent-based) and continuous (i.e. pool-based), approaches. They will use existing real-world applicable terrestrial ecosystem models (e.g. DALEC and MORPH) to test student-created hypotheses of ecosystem function in response to external factors (i.e. climate and disturbance).
The course will consist of 10 three-hour sessions. These sessions include lectures and practical exercises that offer hands-on experience and reinforce the concepts introduced in the lectures.
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| Course description |
Computer-based models are widely used in many areas of science, especially in the ecological and environmental sciences. The emphasis of this course will be on the application and development of models within ecosystems.
The course consists of two components:
1) Weekly one-hour lectures provide conceptual information on models and the stages in their creation, calibration, evaluation and use. Examples provided will be derived from published datasets giving context to each analysis. The lectures provide the foundation for practical exercises.
The lectures will cover the following topics:
¿ Model approaches and potential uses in ecological and environmental sciences
¿ Model validation/evaluation
¿ Introduction to agent-based modelling (ABM)
¿ Model design and building using ABMs
¿ Calibration approaches
¿ Forecasting time-series data
¿ Sensitivity analysis
¿ Using models to address global challenges
2) Weekly two-hour computer practical sessions will provide experience to reinforce the concepts introduced in the lectures. These sessions will involve individual and group-working opportunities. Sessions will be based on published models and datasets, where possible, to place the activities in context. Each practical session will have a tangible outcome based on a realistic scenario, which can feed into decision-making processes.
The practical sessions will cover:
Week 1: Simple model design - from hypotheses to graphical representation
Week 2: Model evaluation ¿ T-Rex scavenger case study
Week 3: ABM 1 ¿ Using NetLogo (predator/prey model)
Week 4: ABM 2 ¿ Model design and building
Week 5: Reading data into R. Calibrating linear and non-linear models using least squares approach
Week 6: Time-series ¿ Forecasting climatic changes
Week 7: Building pool-based models. Investigating model sensitivity
Week 8: Diagnosing the impact of future climate on steady-state and regrowth dynamics in forest ecosystems
Week 9: Supported project development
Week 10: Supported project development
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | None |
Course Delivery Information
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| Academic year 2022/23, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 8,
Seminar/Tutorial Hours 6,
Supervised Practical/Workshop/Studio Hours 16,
Online Activities 5,
Feedback/Feedforward Hours 3,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
158 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Coursework: 100%«br /»
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Coursework will consist of four assignments:«br /»
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1. Design and create a graphical representation of a simple model (Learning outcomes 1 and 2; formative)«br /»
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2. Agent-based modelling - simple model design and build (Learning outcomes 1 and 2; 20%)«br /»
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3. Short assignment - model calibration, evaluation and validation (Learning outcomes 3 and 4; 30%)«br /»
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4. Long modelling assignment ¿ project on individual topic chosen by the student (Learning outcomes 2, 3 and 4; 50%)«br /»
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| Feedback |
Staff to student feedback:
Staff will provide timely and consistent individual written feedback for each coursework assignment. Students will use the first coursework submission to receive formative feedback.
Student to staff feedback:
The students will provide mid-course constructive feedback to allow staff to identify and respond to student concerns early. Students will have the opportunity to communicate this feedback through a discussion forum and anonymously via a feedback form.
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| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Understand the role and nature of modelling ecological and environmental systems using different modelling approaches (e.g. empirical and process-orientated)
- Apply their understanding of the basic principles of model building to generate hypotheses, outline new model structures and analyse and interpret model outputs
- Understand the strengths and limitations of different types of model approaches
- Have a clearer understanding of the challenges and decisions associated with calibration, evaluation, validation and implementation of models used in ecological and environmental sciences
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Reading List
Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S.K., Huse, G. and Huth, A., 2006. A standard protocol for describing individual-based and agent-based models. Ecological modelling, 198(1-2), pp.115-126.
Soetaert, K. and Herman, P.M., 2009. A practical guide to ecological modelling: using R as a simulation platform (Vol. 7, No. 7). New York: Springer.
Bloom, A.A. and Williams, M., 2015. Constraining ecosystem carbon dynamics in a data-limited world: integrating ecological" common sense" in a model¿data fusion framework. Biogeosciences, 12(5), pp.1299-1315.
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Additional Information
| Graduate Attributes and Skills |
Research and enquiry
Students will integrate the information and knowledge gained from the lectures to increase their understanding of ecological and environmental model design and application in practical contexts. They will apply analytical and critical thinking to identify and evaluate options to complex modelling problems and creatively develop possible solutions. Students will build upon existing IT skills, particularly coding, data visualisation, and data analysis.
Personal and intellectual autonomy
Students will build upon the data science skills gained from other Ecological and Environmental courses and recognise the importance of developing lifelong skills as part of their personal development. Through practical tasks, students will think independently and creatively and develop personal resilience using higher-order thinking and sound reasoning to overcome setbacks and failures.
Personal effectiveness
By completing coursework assessments, students will develop time management skills to plan and effectively use resources, prioritise tasks and recover from setbacks to manage a project. Collaborative working during the practical sessions will allow students to build and maintain relationships with peers, effectively perform in group environments, and recognise the experience and skills of other group members.
Communication
The course will develop communication skills, both oral and written. Group tasks will develop interpersonal skills and allow students to become interactive verbal communicators through listening, questioning and articulately explaining to other group members. They will be able to understand the needs of others, adapt their communication style for different people and deal with potential conflict effectively. Students will communicate complex ideas and arguments through written assessments and produce clear, structured work.
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| Keywords | Ecological modelling,environmental modelling,empirical models; individual/agent-based models |
Contacts
| Course organiser | Mr Stacey Fairhurst
Tel:
Email: |
Course secretary | Mrs Nicola Clark
Tel: (0131 6)50 4842
Email: |
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