Investigating Predator–Prey Relationships with Simulation Models

 

Investigating Predator–Prey Relationships with Simulation Models

GCSE & A-Level Biology | Blog & Social Media

Why use simulation models?

Predator–prey relationships are a core idea in ecology, but they’re difficult (and unethical!) to study directly in real ecosystems. Simulation models allow students to explore these interactions safely, repeatedly, and quantitatively — making them ideal for both GCSE and A-Level Biology.

Using models helps students move beyond memorising definitions to understanding dynamic systems.

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The Biology Behind Predator–Prey Relationships

In a simple predator–prey system:

• An increase in prey leads to more predators (more food available)

• More predators cause prey numbers to fall

• With less food, predator numbers then decline

• Prey populations recover… and the cycle repeats

This produces the classic oscillating population curves seen in many ecosystems.

📌 Key idea: Predator population changes lag behind prey population changes.

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What Is a Simulation Model?

A simulation model uses rules and variables to imitate how real biological systems behave over time.

In predator–prey models, students can change:

• Initial population sizes

• Birth rates

• Death rates

• Predation rate

• Environmental limits (carrying capacity)

The model then calculates how populations change step by step.

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GCSE Biology Focus

At GCSE level, simulation models help students:

• Describe predator–prey cycles

• Understand interdependence within ecosystems

• Explain how changes in one population affect another

• Interpret population graphs

📌 Exam link: Ecology, food chains, food webs, and population dynamics.

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A-Level Biology Focus

At A-Level, models are used more analytically:

• Explaining cyclical population changes

• Evaluating assumptions of models

• Linking to carrying capacity and limiting factors

• Discussing why real ecosystems deviate from models

Students may encounter mathematical representations (e.g. population rate equations) and must critically assess how realistic a model is.

📌 Higher skill: Evaluating the strengths and limitations of models.

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Strengths of Simulation Models

Advantages

• Ethical and safe

• Cheap and repeatable

• Easy to test “what if?” scenarios

• Helps visualise complex systems

Limitations

• Oversimplify real ecosystems

• Often ignore disease, migration, climate change

• Assume constant conditions

📌 Exam phrase: “Models are useful representations, but they cannot capture all the complexity of real ecosystems.”

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Practical Classroom Ideas

• Spreadsheet-based predator–prey models

• Online interactive simulations

• Coding simple models (A-Level extension)

• Graphing population changes over time

• Comparing model predictions with real-world data (e.g. hare–lynx cycles)

These approaches fit perfectly with working scientifically and data analysis skills.

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Perfect 6–9 Mark Answer Structure

Simulation models allow biologists to investigate predator–prey relationships without disturbing ecosystems. They show how changes in prey population affect predator numbers, often producing cyclical patterns. However, models are simplified and may not include factors such as disease or migration, so real populations may not behave exactly as predicted.