What is a model?
A model is a simplified version of reality.
Models help us understand how a system works and what might happen if conditions change.
They are used because real systems are usually too complex to study in full.
A model is a simplified representation of reality used to understand, explain, or predict a system.
Why do models simplify reality?
Models do not include every detail of the real world.
When creating a model, scientists choose:
- what information is important
- what details can be left out
This makes models easier to understand and use, but less accurate than reality.
All models involve a trade-off: simpler models are easier to use but less precise.
Examples of models
The water cycle
[Diagram: water-cycle] - Available in full study mode
Shows evaporation, condensation and precipitation.
A food chain
[Diagram: food-chain] - Available in full study mode
Shows feeding relationships between organisms.
A population graph
[Diagram: population-graph] - Available in full study mode
Shows how population size changes over time.
A climate model
[Diagram: climate-model] - Available in full study mode
Uses data and equations to predict future climate conditions.
None of these models show every detail of the real system.
Types of models
[Model Types Grid] - Available in full study mode
ESS examples
- Diagram — A food web showing feeding relationships in a coral reef ecosystem.
- Mathematical — An equation predicting population growth: N = N₀eʳᵗ.
- Physical — A scale model of a river catchment to study flooding.
- Computer — A climate simulation predicting temperature rise under different CO₂ scenarios.
- Written — A text description explaining how deforestation leads to soil erosion and biodiversity loss.
Uses of models
Models help us to:
- understand complex systems
- identify key components
- make predictions
- test different scenarios
- communicate ideas
- recognise patterns
Example: Climate models help predict future temperature rise under different emission scenarios.
Limitations of models
Because models are simplified, they have limitations.
Limitations:
- They are based on assumptions
- Important information may be missing
- Predictions may be inaccurate
- Results depend on data quality
If assumptions are wrong, conclusions can also be wrong.
Models and values
Models are influenced by:
What scientists think is important, Current knowledge, Human values and priorities
As new knowledge is gained, models must be updated.
Key idea: Models should never be treated as perfect or final.
Models of sustainability
Different models have been used to show the relationship between environment, society, and economy.
[Diagram: sustainability-models] - Available in full study mode
Exam Tips:
- Always mention simplification when defining models
- State at least one strength and one limitation
- Link models to prediction and decision-making
- Remember: models change as knowledge and values change
Models simplify reality to help us understand and predict systems, but this simplification always causes loss of accuracy.