Research in Scientific Computing in Undergraduate Education

Stochastic Modeling of the viability analysis of tiger populations

We analyze the dynamics and risk of extinction of the Amur tiger found in a Russian natural reserve. Stochastic models allow prediction of a population’s viability by measuring its probability of extinction using statistical methods. Our model integrates the birth and death rates of tiger populations as random variables. The differences between stochastic and deterministic modeling are illustrated by analyzing both the discrete logistic equation and a linear birth and death process. We demonstrate how sensitive the models are to the parameters; carrying capacity, birth and death rates.


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