Lecture B3 (2021-01-28): Chapter 2, Introduction to Feedback Systems Thinking (Morecroft, 2015)

In this lecture, we discuss Chapter 2 from Morecroft (2015), which introduces feedback systems thinking. Morecroft contrasts feedback systems thinking with an event-oriented world view. To aid in taking the systems perspective, causal loop diagrams (CLDs) are introduced with connections to the fundamental modes of behavior through time that are associated with common causal structures. Examples are given in the chapter from a number of different application spaces, but the lecture focuses on examples from road construction and manufacturing.

Lecture B2 (2021-01-26): Causal Loop Diagrams in Vensim

In this lecture, we start drawing Causal Loop Diagrams (introduced in the previous lecture) in the System Dynamics Modeling tool Vensim (from Ventana Systems). This serves as a brief introduction to Vensim without getting into the stock-and-flow diagrams that we will learn to draw, simulate, and analyze later in the semester. This lecture also provides more practice in drawing CLD's, which help to diagram the causal structure in complex systems and identify the possibly many feedback loops that enrich the dynamics of such systems.

Lecture B1 (2021-01-21): Introduction to Causal Loop Diagrams

In this lecture, we move from mental/qualitative models toward building quantitative modeling tools to do strategic modeling and scenario planning, as described in Chapter 1 of Morecroft (2015). This involves giving a preview of stock-and-flow diagrams (introducing stocks and flows) and then moving into introducing causal loop diagrams (CLD's). Causal loop diagrams provide a graphical accounting of all causal connections in a model of a system and help to identify both negative and positive feedback loops that are informative about likely dynamical modes of behavior.

Lecture A3 (2021-01-19): Chapter 1, The Appeal and Power of Strategic Modeling (Morecroft, 2015)

In this lecture, we cover topics from Chapter 1 (The Appeal and Power of Strategic Modeling) by Morecroft (2015). This chapter helps to motivate the use of quantitative, simulation models for learning, as opposed to just prediction. It uses a board game (Monopoly) to motivate how overly simplistic models can nevertheless provide more generalizable insights, which is one of the reasons why computer simulation models can still be very useful even if they do not include every detail. We close with a simple fisheries example that helps to underscore the importance of choosing the correct functional response (type-I or type-II, for example) when modeling predator--prey dynamics.

Lecture A2 (2021-01-14): Introduction to Modeling

In this lecture, we build upon the basic definition of a model as a tool for answering a "What If" question. We point out that there are mental (qualitative) models as well as quantitative models, and we need to learn how to recognize our internal mental models. We then discuss the benefits of the different modeling types and setup the foundation for entering into more quantitative modeling approaches that are focused on in the rest of the class.

Lecture A1 (2021-01-12): Course Introduction

In this lecture, SOS 212 (Systems, Dynamics, and Sustainability) is introduced to Spring 2021 semester students at Arizona State University. The basic learning outcomes for the course are presented as well as the course structure and policies.