1. Where system components are affected by random variability. For example, when fishery stock projections are elaborated, future recruitments are projected with a stochastic component (i.e. the values introduced in the projection randomly vary from year to year); 2. A stochastic model is a model whose behavior is not fully specified by its form and parameters, but which contains an allowance for unexplained effects represented by random variables.