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Updated: May 22, 2026

An Anaerobic Biosensor Assay for the Detection of Mercury and Cadmium
Published on: December 17, 2018
Decoupling of cyanotoxin and mercury bioaccumulation peaks along browning and eutrophication gradients
Maude Lachapelle1, Irene Gregory-Eaves2, Susanne Kraemer3
1Environmental Effects Research Division, Environment and Climate Change Canada, Canada; Groupe de Recherche Interuniversitaire en Limnologie (GRIL), Canada; Department of Biology, McGill University, Canada.
Abstract:
Many freshwater ecosystems are increasingly altered by browning (coloured dissolved organic matter enrichment) and eutrophication (phosphorus and nitrogen enrichment). Recently, Creed et al. (2018) proposed that these stressors will differentially modify microcystins (MC, produced by cyanobacteria) and methylmercury (MeHg, methylated by bacteria) production and bioaccumulation, with MC peaking under high nutrient, low browning conditions, while MeHg peaks at higher dissolved organic carbon (DOC) concentrations. However, this prediction remains largely untested. To explore whether environmental stressors, trophic interactions, and contaminant dynamics follow this predicted framework, we conducted two multi-season mesocosm experiments testing how browning and eutrophication shaped MC and MeHg concentrations in water and biota (plankton and periphyton). We observed distinct DOC-dependent maxima consistent with predictions: MC concentrations in biota peaking at low DOC (3.3 ± 0.3 mg L-1 (2021) and 3.0 ± 1.1 mg L-1 (2022)), while MeHg peaked at higher DOC (6.9 ± 0.9 mg L-1 (2021) and 9.5 ± 4.6 mg L-1 (2022)). These asynchronous peaks demonstrate that contaminants reach maximum concentrations under different browning conditions, requiring multiple risk windows for management frameworks. Further, contaminant uptake was jointly shaped by abiotic drivers and shifts in community composition. In particular, the MeHg bioaccumulation factor (ratio of contaminant in biota: water) was mediated by both DOC and nutrients. Taken together, by linking nutrient enrichment and browning to predicted contaminant dynamics, our study provides a mechanistic framework to guide monitoring programs and management strategies aimed at predicting peak contaminant exposure under changing environmental conditions.
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