Reevaluating copper algaecide dosing to manage water quality: A multiple linear regression approach

Authors: MCDONALD, M - Auburn University; HENNESSEY, A - Auburn University; JOHNSON, P - Auburn University; GLADFELTER, M - Auburn University; MERRILL, K - Auburn University; TENISON, S - Auburn University; GANEGODA, J - Auburn University; HOANG, T - Auburn University; Torbert Iii, Henry; Beck, Benjamin; WILSON, A - Auburn University

Submitted to: Environmental Toxicology and Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/26/2025
Publication Date: 9/30/2025
Citation: Mcdonald, M.B., Hennessey, A.V., Johnson, P.P., Gladfelter, M.F., Merrill, K.L., Tenison, S.E., Ganegoda, J.S., Hoang, T.C., Torbert III, H.A., Beck, B.H., Wilson, A.E. 2025. Reevaluating copper algaecide dosing to manage water quality: A multiple linear regression approach. Environmental Toxicology and Chemistry. 44(10):2957-2966. https://doi.org/10.1093/etojnl/vgaf175.
DOI: https://doi.org/10.1093/etojnl/vgaf175

Interpretive Summary: Copper sulfate pentahydrate has been used extensively to control the growth of nuisance algae in freshwater systems for over a hundred years. While the use of copper is well-studied, the dosing methodologies employed are less understood and lack a rigorous scientific basis. This study aimed to develop a predictive multiple linear regression (MLR) model based on basic water quality parameters that can be used to determine an optimal algicidal dose that minimizes non-target effects on the overall aquatic ecosystem.. Results from this experiment show that the MLR derived dose, which contained 60% less copper than the standard dose, resulted in equivalent control of harmful algae (95% reduction). Furthermore, the MLR dose caused less harm to the overall phytoplankton and zooplankton communities than the alkalinity-based dose. These results hold promise in the development of more sustainable water management practices that allow for harmful algal control while also preserving natural ecosystem function.

Technical Abstract: Copper sulfate pentahydrate has been used extensively to control the growth of nuisance algae in freshwater systems for over a hundred years. While the use of copper is well-studied, the dosing methodologies employed are less understood and lack a rigorous scientific basis. This study aimed to develop a predictive multiple linear regression (MLR) model based on basic water quality parameters that can be used to determine an optimal algicidal dose that minimizes non-target effects on the overall aquatic ecosystem. This model was developed from a series of comprehensive controlled laboratory bioassays relating key water quality parameters such as pH, hardness, alkalinity and dissolved organic carbon (DOC) to algal copper toxicity. These bioassays demonstrated that DOC and pH were the most important predictors of algal toxicity (R2 = 0.813, P < 0.0001). Subsequently, a field-based application of the novel MLR derived dose was conducted using a replicated, 28-day experiment in an active aquaculture pond. Results from this experiment show that the MLR derived dose, which contained 60% less copper than the standard dose, resulted in equivalent control of harmful algae (95% reduction). Furthermore, the MLR dose caused less harm to the overall phytoplankton and zooplankton communities than the alkalinity-based dose. These results hold promise in the development of more sustainable water management practices that allow for harmful algal control while also preserving natural ecosystem function.