Linking the Species to Grow Dynamic Population Models with MATLAB

A current growth area in stock management (fish within a fishery, trees within forestry corps, or feral animal control) is the use of dynamic agent-based simulations. Agent-based simulations are becoming popular because of their flexibility and power. With relatively simple coding, complex emergent behaviors can accurately represent chaotic real-world systems. For example, a set of agents within a fishery might represent the fish population both spatially and temporally, while other agents represent fishing fleets that make cost benefit analyses to decide whether to fish or not based on commodity pricing.

Walk through the process of building a complex population dynamics model using a plug-and-play coding approach. Using the classic three-species predator-prey model with grass, sheep, and dingoes, you'll create the world in which the simulation runs. You'll also learn how to dynamically generate a food web—so that as you add new species, they can automatically be preyed upon—and how to add mathematically simple rules to generate emergent properties.