Ideal Free Distribution

Overview

The Ideal Free Distribution (IFD) theory predicts that animals will distribute themselves among resource patches in proportion to the resources available at each patch. If patch A has twice the food of patch B, you'd expect twice as many foragers at patch A. It's an elegant prediction—and in practice, organisms aren't perfectly ideal or perfectly free, so deviations from the prediction reveal interesting behavioral constraints.

Maybe animals can't assess patch quality perfectly. Maybe dominant individuals monopolize the best spots. Maybe there are travel costs that keep individuals from redistributing as quickly as the model assumes. Each deviation tells you something about the biology of the system you're studying.

What You'll Do

Choose from five animal systems (see below). Set the resource distribution across two or more patches. Run the simulation and count how many individuals settle at each patch over time. Compare your observed distributions against the IFD prediction using chi-square goodness-of-fit tests. Then manipulate patch quality—double one patch, halve another—and watch how the animals redistribute.

You can also track redistribution dynamics: how quickly do individuals switch patches after a resource change? Do some systems reach equilibrium faster than others? These time-series data give you a richer picture than static counts alone.

Learning Objectives

1. State and test the predictions of ideal free distribution theory
2. Quantify deviation from expected distributions using chi-square goodness-of-fit tests
3. Identify factors that cause organisms to deviate from IFD predictions (interference, perceptual limits, travel costs)
4. Compare IFD patterns across taxa and evaluate whether some species match predictions better than others

Animal Systems

• American Coots — Foraging on a lake with patchy aquatic vegetation
• Mallard Ducks — Bread tossed at two locations on a pond (the classic Harper 1982 setup)
• Three-spined Sticklebacks — Lab tank with two food-delivery pipes at different rates
• European Starlings — Feeding stations in an open field with variable provisioning
• Bumblebees — Visiting artificial flower patches with different nectar rewards

Background

Fretwell and Lucas published the IFD model in 1970. The core assumptions are straightforward: animals are "ideal" (they have perfect knowledge of patch quality) and "free" (they can move between patches at no cost). Under these conditions, the predicted outcome is input matching—the number of foragers at each patch is proportional to the resource input rate.

Real animals violate both assumptions to varying degrees. Interference competition among foragers is common, especially in species with dominance hierarchies. Perceptual limitations mean animals often can't assess patch quality until they've sampled it. And travel between patches always takes time and energy. The IFD works best as a null model: you test it, find deviations, and then ask what's causing them. That's where the interesting biology lives.