Lotka-Volterra Predator-Prey Dynamical Model
The following are the Lotka-Volterra equations which can be used to model populations of predators and prey over time:
\[\begin{aligned}
\dot{x} &= \alpha x - \beta x y\\
\dot{y} &= \delta x y - \gamma y
\end{aligned}\]
where:
- \(x\) is the population size of prey (e.g. rabbits)
- \(y\) is the population size of predators (e.g. foxes)
the components of the model represent:
- \(\alpha x\): the growth rate of prey
- \(\beta x y\): the death rate of prey
- \(\delta x y\): the growth rate of predators
- \(\gamma y\): the death rate of predators
The assumptions of the model are:
- prey find ample food at all times
- the food supply of predators depends entirely on the prey population
- the rate of change of the population is proportional to its size
- the environment does not change
Simulate the behaviour of this system over time. Start with the following values for the initial states, and the constants:
- \((x_{0},y_{0}) = (0.5,0.5)\)
- \(\alpha=0.1\), \(\beta=0.1\), \(\delta=0.1\), \(\gamma=0.1\)
- set up a time vector from 0 to 500 in steps of 1
- Plot the population size of predators over time. Overlay a plot of the population size of prey over time.
- Plot the trajectory of the system in state-space, in other words plot \(x(t)\) on the horizontal axis and \(y(t)\) on the vertical axis.
- Increase the \(\alpha\) constant to \(0.2\) and re-run the simulation. What happens?
- Set all constants to 0.20 and re-run the simulation. What happens?
- Try the following: \((\alpha,\beta,\delta,\gamma) = (0.2,0.2,0.2,0.0)\). What happens and why?