Detection and Prediction of Toxic Aluminum Concentrations in High-Priority Salmon Rivers in Nova Scotia.

Environ Toxicol Chem

Hydrology and Climate Change Research Group, Department of Earth and Environmental Sciences, Dalhousie University, Halifax, Nova Scotia, Canada.

Published: December 2024

AI Article Synopsis

  • * A recent study (2015-2022) found that 80% of sampled sites had aluminum concentrations exceeding safe levels, with increasing trends observed at large sampling locations.
  • * The research utilized a Bayesian model to analyze factors affecting aluminum levels and offers a predictive tool for monitoring and potentially mitigating aluminum toxicity in freshwater ecosystems.

Article Abstract

Elevated concentrations of toxic cationic aluminum (Al) are symptomatic of terrestrial and freshwater acidification and are particularly toxic to salmonid fish species such as Atlantic salmon (Salmo salar). Speciated metal samples are rarely included in standard water monitoring protocols, and therefore the processes affecting Al dynamics in freshwater remain poorly understood. Previous analysis of Al concentrations in Nova Scotia (Canada) rivers found that the majority of study rivers had concentrations exceeding the threshold for aquatic health, but a wide-scale survey of Al in Nova Scotia has not taken place since 2006 (Dennis, I. F., & Clair, T. A., 2012, Canadian Journal of Fisheries and Aquatic Sciences, 69(7), 1174-1183). The observed levels of dissolved aluminum in Atlantic salmon (Salmo salar) rivers of Atlantic Canada have potential serious and harmful effects for aquatic populations. We present the findings of the first large-scale assessment of the Al status of Nova Scotia rivers in 17 years; we measured Al concentrations and other water chemistry parameters at 150 sites throughout the Southern Uplands region of Nova Scotia from 2015 to 2022. We found that Al concentrations exceeded toxic thresholds at least once during the study period at 80% of the study sites and that Al concentrations increased during the study period at all four large-sample study sites. Modeling of relationships between Al concentrations and other water chemistry parameters showed that the most important predictors of Al are concentrations of the dissolved fractions of Al, iron, titanium, and calcium, as well as dissolved organic carbon and fluoride. We developed a fully Bayesian linear mixed model to predict Al concentrations from a test data set within 15 μg/L. This model may be a valuable tool to predict Al concentrations in rivers and to prioritize areas where Al should be monitored. Environ Toxicol Chem 2024;43:2545-2556. © 2024 The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11619745PMC
http://dx.doi.org/10.1002/etc.5997DOI Listing

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