Assessing the Relationship Between Sedimentary Microbial Community Structure and Pollutants in Stormwater Wetlands Using eDNA Metabarcoding

Abstract

Environmental pollution is regarded as one of the most substantial threats facing freshwater ecosystems. Two contaminant types in particular, metals and pesticides, represent both long-term and widespread hazards to aquatic environments. Contamination negatively affects the health of aquatic flora and fauna. Constructed wetlands are an important mitigation measure for managing stormwater in urban landscapes. Given that constructed wetlands are designed to capture and retain contaminants from stormwater in sediments, the resulting chemical profiles are largely representative of contamination in the surrounding local catchment and aquatic environments. Environmental DNA is expanding the field of aquatic monitoring, introducing the ability to assess biological profiles quickly and reliably, and expanding the knowledge of how contamination affects ecosystems down to a microbial level. Here, we used environmental DNA (eDNA) metabarcoding to characterize the sedimentary microbial profiles of nine urban stormwater wetlands and one rural wetland with low levels of contamination and assess the variation in community structures between sites as well as between the inlet and outlet within each site. We found significant variation in microbial communities between the rural (reference) wetland and stormwater wetlands, variation between some stormwater wetlands, and between over half of the inlets to outlets. The bacterial phyla Cyanobacteria and Proteobacteria were mostly driving this variation, along with Planctomycetota and Bacteroidota. We also found correlations between microbial community structure and chemical occurrences, particularly zinc and barium, with the latter not previously reported to be associated with microbial dynamics in freshwater environments. Our study validates the ability of eDNA metabarcoding to reliably evaluate sedimentary microbial profiles in stormwater wetlands and highlights its value in the assessment and prediction of contamination in these environments.