John Wiley & Sons, Ltd.

Modeling the potential effects of atrazine on aquatic communities in midwestern streams

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The comprehensive aquatic systems model for atrazine (CASMATZ) estimates the potential toxic effects of atrazine on populations of aquatic plants and consumers in a generic lower‐order midwestern stream. The CASMATZ 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 CASMATZ 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 CASMATZ 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 CASMATZ 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 CASMATZ provides an effective, coherent, and transparent modeling framework for assessing ecological risks posed by pesticides in lower‐order streams. Environ Toxicol Chem 2013;32:xx–xx. © 2013 SETAC

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