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We quantified the sensitivity of predicted rates of growth and consumption to parameter variation for models of yellow perch (Perca flavescens), largemouth bass (Micropterus salmoides), and alewife (Alosa pseudoharengus). We used statistical analyses of the results of Monte Carlo simulations to rank parameter importance. The order of parameter importance was model specific, although the results emphasized the need for accurate estimation of the realized fraction of maximum consumption rate (P) and allometric parameters for consumption (a1, b1) and respiration (a2, b2). Excretion and egestion parameters contributed little to prediction errors. The Monte Carlo methods were used to examine the relative importance of parameter variation and diet composition, an external forcing function, on forecasts of alewife growth. If standard deviations of model parameters were known within 2% of their expected values, uncertainty in diet composition could contribute as much as 47% of the variance in predicted alewife weight. When standard deviations of model parameters are realistically defined, diet uncertainty contributed less than 10% of the variance in predicted weight.

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The comprehensive aquatic systems model for atrazine (CASM(ATZ)) estimates the potential toxic effects of atrazine on populations of aquatic plants and consumers in a generic lower-order midwestern stream. The CASM(ATZ) simulates the daily production of 20 periphyton and 6 aquatic vascular plant species. The modeled consumer community consists of 17 functionally defined species of zooplankton, benthic invertebrates, bacteria, and fish. Daily values of population biomass (grams of carbon per square meter) are calculated as nonlinear functions of population bioenergetics, physical-chemical environmental parameters, grazing/predator-prey interactions, and population-specific direct and indirect responses to atrazine. The CASM(ATZ) uses Monte Carlo methods to characterize the implications of phenotypic variability, environmental variability, and uncertainty associated with atrazine toxicity data in estimating the potential impacts of time-varying atrazine exposures on population biomass and community structure. Comparisons of modeled biomass values for plants and consumers with published data indicate that the generic reference simulation realistically describes ecological production in lower-order midwestern streams. Probabilistic assessments were conducted using the CASM(ATZ) to evaluate potential modeled changes in plant community structure resulting from measured atrazine exposure profiles in 3 midwestern US streams representing watersheds highly vulnerable to runoff. Deviation in the median values of maximum 30-d average Steinhaus similarity index ranged from 0.09% to 2.52% from the reference simulation. The CASM(ATZ) could therefore be used for the purposes of risk assessment by comparison of site monitoring-based model output to a biologically relevant Steinhaus similarity index level of concern. Used as a generic screening technology or in site-specific applications, the CASM(AT) provides an effective, coherent, and transparent modeling framework for assessing ecological risks posed by pesticides in lower-order streams.