Modelling of Systems for Sustainability

MOSS: Schedule

mcorey — Fri, 04 Aug 2023 14:28:00 +0000

MOSS: Schedule mcorey Fri, 04/08/2023 - 15:28

The schedule below lists the learning activities, which are coordinated with each other and the assessment.

For times of activities see the MoSS Timetable.

The abbreviations in the reading column refer to the course texts that you can find in the Resource List:

RG: Agent-based and individual-based modeling: a practical introduction. Second Edition. Steven F. Railsback and Volker Grim. Princeton: Princeton University Press 2019. View online.
MK: Principles of systems science. George E. Mobus and Michael C. Kalton. New York: Springer 2014. View online.
M: Thinking in systems a primer. Donella H. Meadows ; edited by Diana Wright. White River Junction, Vermont: Chelsea Green Publishing 2008. View online

Week	Lecture 1	Lecture 2	Lab	Tutorial	Q&A	Reading
W01 18-22 Sep	Introduction: Systems Thinking, Example System, Release CW1	Models and the modelling cycle			Getting to know each other	MK 1,2, 13.1-13.3 M 1 RG 1
W02 25-29 Sep	Formulating a Model: Overview, Design Concepts, Details (ODD)	Agent-based modelling in NetLogo	Getting started with NetLOGO	Formulate an ODD	More example models	MK 12, 13.4.2 RG 2, 3
W03 2-6 Oct	System dynamics (SD) framework: Example models	Model Properties: Emergent phenomena – tipping points, phase changes, oscillations, dynamic stability	Constructing an Agent-based model in NetLOGO	Paper summarisation	Examples of model properties. Example SD model.	MK 10, 13.4.1 M 2 RG 4-6, 8, 18
W04 9-13 Oct	Model Properties: Uncertainty, Parameter sensitivity, Distributions	Illustrative ecosystem models (ABM and SD) noting system properties	Constructing SD models in NetLOGO Zipfile	Formulating models with influence diagrams	Example issues	RG 22, 23
W05 16-20 Oct	Illustrative social system models (ABM and SD)	Communication: public, policymakers, media	Model experiments; analysing and visualising results SimpleBirth.zip WildDog.zip WildDogData.zip	Communication practice Communication slides	Q/A. Other modelling paradigms
W06 23-27 Oct	Integrated Assessment Models	Group Project preparation/allocation	Project groups, drop-in	No tutorial	No Q/A
W07 30 Oct-3 Nov	Project phase: No lecture	Project phase: No lecture	Drop-in lab for help with project	No tutorial
W08 6-10 Nov	Project phase: No lecture	Project phase: No lecture	Drop-in lab for help with project	No tutorial
W09 13-17 Nov	Project phase: No lecture	Project phase: No lecture	Drop-in lab for help with project	No tutorial
W10 20-24 Nov	Project phase: No lecture	Project phase: No lecture	Drop-in lab for help with project	No tutorial

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MOSS: Course Contacts

flittlet — Thu, 03 Aug 2023 16:09:19 +0000

MOSS: Course Contacts flittlet Thu, 03/08/2023 - 17:09

The full list of people teaching and supporting MoSS are on the Course Contacts page in Learn Ultra. Here we introduce the course lecturers.

Nigel Goddard is a Reader in the School of Informatics. He changed his research direction in 2007 from computational neuroscience to sustainability, with a focus on energy and in particular its essential role in both the economy and climate change.

David Sterratt is a Lecturer in the School of Informatics. He researches and is co-author of a textbook on computational neuroscience. He has a long-standing interest in the environment, including acting as the Energy Coordinator in the Informatics Forum.

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MOSS: Assessment

flittlet — Thu, 03 Aug 2023 16:09:16 +0000

MOSS: Assessment flittlet Thu, 03/08/2023 - 17:09

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MOSS: Resource List

flittlet — Thu, 03 Aug 2023 16:09:12 +0000

MOSS: Resource List flittlet Thu, 03/08/2023 - 17:09

Modelling of Systems for Sustainability Resource List

You can access the reading list for this course by selecting the link above. In order to view some resources on the list, you must be logged in with your EASE account.

For more information on getting the most out of your courses Resource List, have a look at this video.

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MOSS: Course Materials

flittlet — Thu, 03 Aug 2023 16:09:10 +0000

MOSS: Course Materials flittlet Thu, 03/08/2023 - 17:09

Slides, tutorial and lab sheets

All materials are linked to from the Schedule.

Lecture Recordings

All lecture recordings should be accessed via Learn; you will need to log in using your EASE account. (Learn provides you with access to any lecture recordings available for this course. You will need to select the "lecture recording" link once, before you can access any direct links to a lecture recording.)

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MOSS: Modelling of Systems for Sustainability

flittlet — Thu, 03 Aug 2023 16:09:09 +0000

MOSS: Modelling of Systems for Sustainability flittlet Thu, 03/08/2023 - 17:09

Welcome to Modelling of Systems for Sustainability

Learning Outcomes

On successful completion of this course, you should be able to:

explain how computational modelling frameworks can be used to understand the behaviours of complex interacting systems involved in sustainability such as social, economic and ecological systems
investigate a sustainability system question, identify system elements and their interactions, and codify a system model using an appropriate model description framework
critique and interpret the results / output of models of sustainability systems
communicate findings of sustainability modelling studies, including uncertainty, to a variety of audiences
work collaboratively and accountably with other students to formulate, explore and communicate a sustainability system model

Course Outline

The fundamental aim of this course is for students from a variety of backgrounds, including Informatics, to get hands-on experience with specifying, implementing, exploring and presenting results from models of real-world systems that are key to planetary sustainability. The range of such systems is vast, encompassing large parts of earth sciences, engineering, health sciences, social and political sciences. Some key systems include the climate system, many ecosystems, agricultural systems, water systems, public health systems, social systems, international political systems, energy systems and transport systems. We will describe a subset of these systems, and there will be opportunity to develop deeper understanding in the project.

Most of these are what are known as "complex systems", meaning: their behaviour and evolution often cannot be reduced to a few equations or paragraphs of description; they exhibit patterns of emergent global behaviour that are not explicitly encoded in any local interactions; they often exhibit multiple potential stable states, with not-easily-triggered "tipping points" to move to another stable state; stability is often exhibited as a dynamic pattern over time rather than as a fixed state. We will touch on the science of complex systems, focussing on those aspects that are of most relevance to the particular real-world systems we study.

A ubiquitous challenge in sustainability is to appreciate how these individually complex systems interact with each other in the real world to produce unexpected outcomes. The key methodology we will bring to the study of these systems and how they interact is computational modelling and visualisation. We will study specific systems for which there are reasonably tractable computational models and visualisations. For each, we will explore the underlying computational framework, be it a statistical model of observed data, a physical model of known physical / chemical / biological interactions, or an abstract model of ecological or social systems. The modelling paradigms studied and used in practical work will include system dynamics and agent-based modelling, with brief mention of other paradigms such as discrete event and finite-step simulations.

The first half will consist of lecture material covering the key system concepts, the specific systems to be studied, and the computational modelling and visualisation methods used for each system. These will be supplemented by hands-on lab sessions, to explore computational models and visualisations using tools such as NetLogo and Python; and small-group tutorial sessions aimed at multidisciplinary discussions of specific systems. The second half of the semester will be devoted to a group project in which each 3/4-person group will have students from at least 2 and ideally 3 or 4 disciplines; the project will aim to construct and explore a model of one or two complex systems related to sustainability (e.g., energy, economic and political); and project supervision will be provided by staff and PhD students familiar with the project systems and models.

Assessment will be by coursework, aimed at the material covered in the first half of the semester, (systems and modelling paradigms) and a group project report and presentation for the work in the second half of the semester.

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