A comprehensive evaluation of the uncertainty of acoustic-trawl survey estimates is needed to appropriately include them in stock assessments. However, this evaluation is not straightforward because various data types (acoustic backscatter, length, weight, and age composition) are combined to produce estimates of abundance- and biomass-at-age. Uncertainties associated with each data type and those from functional relationships among variables need to be evaluated and combined. Uncertainty due to spatial sampling is evaluated using geostatistical conditional (co-) simulations. Multiple realizations of acoustic backscatter were produced using transformed Gaussian simulations with a Gibbs sampler to handle zeros. Multiple realizations of length frequency distributions were produced using transformed multivariate Gaussian co-simulations derived from quantiles of the empirical length distributions. Uncertainty due to errors in functional relationships was evaluated using bootstrap for the target strength-at-length and the weight-at-length relationships and for age–length keys. The contribution of each of these major sources of uncertainty was assessed for acoustic-trawl surveys of walleye pollock in the eastern Bering Sea in 2006–2010. This simulation framework allows a general computation for estimating abundance- and biomass-at-age variance–covariance matrices. Such estimates suggest that the covariance structure assumed in fitting stock assessment models differs substantially from what careful analysis of survey data actually indicate.