Lecture on Causal Loop Diagrams

Speaker: Dr. Donna Gurule

Introduction

• Purpose of Causal Loop Diagrams:
  • Clarify mental models and improve thinking clarity
  • Identify common archetypes in systems behavior
  • Facilitate the sharing and modification of mental models
• Components:
  • Variables: Things, actions, or feelings
  • Causal Links: Arrows with positive ( + ) or negative ( - ) signs
  • Delays: Indicated by double lines

Basic Concepts

• Feedback Loops:
  • Positive and Negative feedback loops describe cause and effect
• Population Example:
  • Births and Deaths:
    • More births increase population (positive polarity)
    • More deaths decrease population (negative polarity)
• Feedback Addition:
  • Birth feedback loop: More population -> more births -> more population (Reinforcing loop)
  • Death feedback loop: More deaths -> decreased population -> fewer deaths in the future (Balancing loop)

Types of Feedback Loops

• Reinforcing Loop (R):
  • Cause of exponential growth (e.g., birth rates leading to more births in the future)
• Balancing Loop (B):
  • Stability in systems (e.g., body temperature regulation through sweating and shivering)

Practical Examples

• Bank Account:
  • Interest reinvested leads to more future interest (Reinforcing loop)
• Body Temperature Regulation:
  • Sweating and shivering as homeostatic mechanisms (Balancing loops)
• Technology Adoption:
  • Product adoption and word-of-mouth lead to more sales (Reinforcing loop)
  • Market saturation reduces sales (Balancing loop)

Complex Systems Example

• Population in Developing Countries:
  • Resource constraints lead to reduced life expectancy -> more deaths -> smaller population (Balancing loop)
  • Increased infant mortality -> desire for larger families -> more population (Reinforcing loop)

Importance of Context

• Context-Dependent Outcomes:
  • Different situations and cultures can result in different outcomes from the same model
  • Resource constraints and cultural beliefs play significant roles

Models and Theories

• Purpose of Models:
  • Frame problems and answer questions
  • Identify factors and predict outcomes
  • Allow for the suggestion of corrections and improvements

Pop Quiz Examples

• Traffic Density:
  • More traffic density leads to decreased speed (Inverse relationship)
• Racial Tension:
  • Increased inequality leads to more conflict (Directly proportional relationship)
• Greenhouse Gases and Climate Change:
  • More emissions -> more greenhouse gases -> higher temperature -> more thawing organic matter -> more emissions (Reinforcing loop)
• Cows and Fields:
  • More grass -> more seeding -> more new growth (Reinforcing loop)
  • More grass -> less soil erosion -> more new growth (Reinforcing loop)
  • More grass -> decreased cattle death -> larger herd -> higher grazing intensity -> less grass (Balancing loop)

Conclusion

• Understanding Causal Loop Diagrams: Key Take-away:
  • Help describe system behavior and dynamics

Speaker Thank You Note:

• Dr. Donna Gurule thanks for watching and hopes audience has a better understanding of causal loop diagrams.