Modeling uncertainty in population dynamics

Characterization and analysis of deterministic uncertainties associated with population dynamics models are often of critical importance, especially where pertinent environmental or demographic variables are employed in modeling concepts related to species conservation or invasion. However, uncertainty analysis using conventional methods such as standard Monte Carlo and hypercube sampling may not be efficient, or even feasible, for complex, computationally demanding generalized growth models. We use a nonstochastic approach for the analysis of deterministic uncertainty associated with the model parameters for a prototype generalized growth model in population dynamics, which encapsulates a myriad of submodels. Examples are drawn from environmental noise types and estimates of extinction time for observed trends are determined