Lecture on Causal Loop Diagrams by Dr. Donna Gurule

Introduction

• Purpose of Causal Loop Diagrams (CLDs):
  • Clarify mental models
  • Identify common archetypes in systems behavior
  • Share and modify mental models, fostering dialogue

Components of Causal Loop Diagrams

Variables

• Represent things, actions, or feelings

Causal Links/Arrows

• Polarities:
  • Positive (directly proportional, +)
  • Negative (inversely proportional, -)
• Delays: Indicated by double yellow lines

Feedback Loops

• Positive Feedback Loops (Reinforcing Loops):
  • Example: Population and births
    • More births → increased population → more births (+)
• Negative Feedback Loops (Balancing Loops):
  • Example: Population and deaths
    • More deaths → reduced population → fewer deaths (-)

Detailed Explanation with Examples

Births and Deaths in Population

• Positive Polarity:
  • More births lead to increased population (+)
• Negative Polarity:
  • More deaths lead to decreased population (-)
• Feedback:
  • More births (→ + → more population → + → more births)
    • Reinforcing loop
  • More deaths (→ - → fewer population → - → fewer deaths)
    • Balancing loop

Delays in the System

• Example with Population:
  • Time delay in population affecting births (age to childbearing)

More Examples

• Bank Account Interest:
  • Money → interest → more money in future (+)
• Body Temperature Regulation:
  • Increase temp → sweat → cool down → temp decrease
  • Decrease temp → shiver → heat up → temp increase

Supply and Demand (Technology Example)

• Reinforcing Loop (Sales):
  • More consumers → more sales → more word-of-mouth → more consumers
• Balancing Loop (Market Saturation):
  • Too many products → reduced demand → fewer sales

Advanced Population Model

• New Balancing Loop: Resource Constraint
  • Population increase → fewer resources → lower life expectancy → higher death rate → population decrease
• New Reinforcing Loop: Larger Families due to High Infant Mortality
  • Lower life expectancy → desire for larger families → more children → population increase

Context Importance

• Models should reflect specific contexts: e.g., technological progress and resource constraints

Reading Causal Loop Diagrams (CLDs)

Traffic Model Example

• Inverse Relationship:
  • More traffic density → decreased speed

Racial Tension Example

• Direct Proportional Relationship:
  • Increased inequality → more conflict

Greenhouse Gas Emissions (GHG) and Climate Change

• Reinforcing Loop: (R)
  • More GHG emissions → more GHGs in atmosphere → temp increase → more thawing organic matter → more GHG emissions

Cows and Grassland Example

• Reinforcing Loop (Grass Growth):
  • More grass → more seeding → more new grass growth → more grass
• Balancing Loop (Grazing):
  • More grass → fewer cattle deaths → larger herd size → higher grazing intensity → less grass

Conclusion

• Understanding CLDs: Essential for describing system behaviors effectively.