We will conduct a sensitivity analysis to examine how errors in base maps propagate into analysis results. Our approach will be based on Monte Carlo simulation. In this approach known errors and uncertainties are used to simulate multiple versions of the input datasets, which are then used to repeat analyses and produce a new set of results. The results are compared to each other to measure the variability and reliability of results. We will develop our methodology using trial datasets consisting of a grizzly bear habitat map derived from several input maps including land cover and roads. Methodological details and results will be provided as the project progresses.