The puma-prey simulator is currently being rebuilt on modern technology.
It will be available on this page as soon as it is ready.
The Puma-Prey Simulator demonstrates the natural balance of a healthy ecosystem, in contrast with the changes that occur as a result of human encroachment.
In a natural ecosystem, the interaction between predator and prey is a delicately balanced process. When the prey population is large, more predators will succeed in finding prey, which then causes the predator population to grow. As the predator population grows, more of the prey get eaten, which then reduces the prey population. With the prey population reduced, fewer predators find prey, and the predator population also then decreases.
In a natural system, this cyclic pattern continues in a state of balance. When human development intrudes into a natural ecosystem such as this, the natural balance is thrown off and the ecosystem is forever changed.
The left side of the simulator shows icons for puma and deer, appearing and disappearing in highly accelerated cycles of predation and reproduction.
The sliders in the middle let you adjust the parameters of the population model, in order to increase or decrease the predation success rate, the birth rates for puma and prey, and the natural puma death rate.
The buttons at the top of the simulator let you select the amount of human encroachment in the environment, from none to significant.
The bar graphs to the left and right of the population model show cycling population levels for both a natural ecosystem and one with human encroachment.
This simulation is based on the Lotka-Volterra equations for predator-prey interaction. These equations, developed in the early 1900's, describe the relationship between predator and prey populations using the following principles:
- predation amount = prey population x predator population x predation rate
- change in prey population = (population x birth rate) - predation
- change in predator pop = (prey pop x pred pop x birth rate) - (pred pop x death rate)
These equations produce an oscillating pattern such as that shown below, and the four key constants (predation rate, prey birth rate, predator birth rate, predator death rate) determine the size and shape of that oscillation.
These equations, however, do not take into account many factors that affect the outome in real world scenarios, such as the skill of the predator and prey, the occurrence of natural disaster and disease, environmental factors such as temperature and rainfall, etc. In addition, the type of terrain and amount of vegetation makes a big difference in predator-prey interactions, not only for food, but for shelter and places to hide. Finally, there may be many species of predators and prey that overlap into complex food webs.