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Effect modeling quantifies the difference between the toxicity of average pesticide concentrations and time-variable exposures from water quality monitoring
Ashauer, R., Kuhl, R., Zimmer, E., & Junghans, M. (2020). Effect modeling quantifies the difference between the toxicity of average pesticide concentrations and time-variable exposures from water quality monitoring. Environmental Toxicology and Chemistry, 39(11), 2158-2168. https://doi.org/10.1002/etc.4838
CRED: criteria for reporting and evaluating ecotoxicity data
Moermond, C. T. A., Kase, R., Korkaric, M., & Ågerstrand, M. (2016). CRED: criteria for reporting and evaluating ecotoxicity data. Environmental Toxicology and Chemistry, 35(5), 1297-1309. https://doi.org/10.1002/etc.3259
Investigating alternatives to the fish early-life stage test: a strategy for discovering and annotating adverse outcome pathways for early fish development
Villeneuve, D., Volz, D. C., Embry, M. R., Ankley, G. T., Belanger, S. E., Léonard, M., … Wehmas, L. (2014). Investigating alternatives to the fish early-life stage test: a strategy for discovering and annotating adverse outcome pathways for early fish development. Environmental Toxicology and Chemistry, 33(1), 158-169. https://doi.org/10.1002/etc.2403
Effect-based tools for monitoring and predicting the ecotoxicological effects of chemicals in the aquatic environment
Connon, R. E., Geist, J. P., & Werner, I. (2012). Effect-based tools for monitoring and predicting the ecotoxicological effects of chemicals in the aquatic environment. Sensors, 12(9), 12741-12771. https://doi.org/10.3390/s120912741