Abstract
Streams are susceptible to pesticide pollutants which are transported outside of the intended area of application from surrounding agricultural fields. It is essential to monitor the occurrence and levels of pesticides in aquatic ecosystems to comprehend their effects on the aquatic environment. The common sampling strategy used for monitoring pesticides in stream ecosystems is through the collection and analysis of grab water samples. However, grab water sampling may not effectively monitor pesticides due to its limited ability to capture temporal and spatial variability, potentially missing fluctuations and uneven distribution of pesticides in aquatic environments. Monitoring using periphyton and sediment sampling may offer a more comprehensive approach by accounting for accumulative processes and temporal variations.Periphyton are a collective of microorganisms that grow on hard surfaces in aquatic ecosystems. They are responsive to chemical and biological changes in the environment, and therefore have the potential to act as a cost-effective, integrated sampling tool to monitor pesticide exposures in aquatic ecosystems. The objective of this study was to assess pesticides detected through periphyton, suspended sediment, and conventional grab water sampling methods and identify the matrix that offers a more comprehensive characterization of a stream's pesticide exposure profile. Ten streams across Southern Ontario were sampled in 2021 and 2022. At each stream site, water, sediment and periphyton, colonizing both artificial and natural substrates, were collected and analyzed for the presence of ~500 pesticides. Each of the three matrices detected distinctive pesticide exposure profiles. The frequency of detection in periphyton, sediment and water matrices were related to pesticides' log Kow and log Koc (P < 0.05). In addition, periphyton bioconcentrated 22 pesticides above levels observed in the ambient water. The bioconcentration factors of pesticides in periphyton can be predicted from their log Kow (simple linear regressions, P < 0.05). The results demonstrate that sediment and periphyton accumulate pesticides in stream environments. This highlights the importance of monitoring pesticide exposure using these matrices to ensure a complete and comprehensive characterization of exposure in stream ecosystems.
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