Inbreeding is a problem experienced by many organizations attempting to revive endangered species. Inbreeding is when a small, isolated population of animals breeds with highly genetically similar members of the species. In species revival programs, small gene pools that result in inbreeding magnify species’ genetic problems, which then hurt the animals’ populations further. With a larger population, these detrimental traits can instead be suppressed.
This project aims to find the minimum size for a gene pool that would prevent excessive inbreeding. Such information would assist the previously described breeding programs form more successful populations in facilities with limited room, like zoos, where these programs often take place.
We created a computer model of a population defined by a number of parameters, such as the initial number of males and females and the number of organisms with a certain genetically defined trait. Each animal had an ID number and were grouped by gender. The model then created the animals and allowed them to mate at random with the other gender. The program successfully showed that larger gene pools resulted in more successful populations because they prevented inbreeding. Basically, any population where the number of matings between two closely related individuals is the healthiest for a population of organisms.
This project successfully modeled a population using an innovative approach. This method of creating individual animals with specific traits for each animal was innovative compared to the traditional approaches to simulation populations. Additionally, the approach allows for further expanding to widen the areas of use.