toward creating an aggregated, single pesticide database toward use in ecological risk assessment. This methodology includes (1) standardization and reformatting practices, (2) data error and duplicate record identification protocols, (3) missing or inconsistent limit of detection and quantification reporting, and (4) site metadata scoring and ranking procedures to flag likely duplicate records. We applied this methodology to develop an aggregated (multiple-source), nationalscale database for atrazine from a diverse set of surface water monitoring programs. The resultant database resolved and/or removed approximately 31% of the total ~ 385,000 records that were due to duplicated records. Identification of sample replicates was also developed. While the quality control and assurances methodologies developed in this work were applied to atrazine, they generally demonstrate how a properly constructed and aggregated single pesticide database
Mechanistic models are invaluable in ecological risk assessment (ERA) because they facilitate extrapolation of organism-level effects to population-level effects while accounting for species life history, ecology, and vulnerability. In this work, we developed a model framework to compare the potential effects of the fungicide chlorothalonil across four listed species of cyprinid fish and explore species-specific traits of importance at the population level. The model is an agent-based model based on the dynamic energy budget theory. Toxicokinetic-toxicodynamic sub-models were used for representing direct effects, whereas indirect effects were described by decreasing food availability. Exposure profiles were constructed based on hydroxychlorothalonil, given the relatively short half-life of parent chlorothalonil. Different exposure magnification factors were required to achieve a comparable population decrease across species. In particular, those species producing fewer eggs and with shorter lifespans appeared to be more vulnerable. Moreover, sequentially adding effect sub-models resulted in different outcomes depending on the interplay of life-history traits and density-dependent compensation effects. We conclude by stressing the importance of using models in ERA to account for species-specific characteristics and ecology, especially when dealing with listed species and in accordance with the necessity of reducing animal testing.
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