Dietary exposure of potentially toxic elements to freshwater mammals in the Ganga river basin, India.

The threatened Gangetic dolphin (Platanista gangetica) and smooth-coated otter (Lutrogale perspicillata) occuring in the Ganga River Basin (GRB), are experiencing a decline in their population and distribution range owing to multiple anthropogenic pressures, including pollution by Potentially Toxic Elements (PTEs). Apex predators primarily encounter contaminants through dietary exposure. Yet, notable gaps persist in our understanding of the risks associated with the ingestion of PTE-contaminated prey for Gangetic dolphins and smooth-coated otters. In this study, we examined the occurrence and spatial variation of PTEs in the prey (fish) of both these riverine mammals across three major rivers of the Basin, while also evaluating the associated risk of ingesting contaminated prey. Our assessment revealed no statistical variation in bioaccumulation profiles of PTEs across the three rivers, attributable to comparable land use patterns and PTE consumption within the catchment. Zn and Cu were the most dominant PTEs in the prey species. The major potential sources of pollution identified in the catchment include agricultural settlements, vehicular emissions, and the presence of metal-based additives in plastics. Zn, As and Hg accumulation vary with the trophic level whereas some PTEs show concentration (Hg) and dilution (As, Cr, Pb and Zn) with fish growth. The Risk Quotient (RQ), based on the dietary intake of contaminated prey calculated using Toxicity Reference Value was consistently below 1 indicating no significant risk to these riverine mammals. Conversely, with the exception of Co and Ni, the Reference Dose-based RQs for all other PTEs indicated a substantial risk for Gangetic dolphins and smooth-coated otters through dietary exposure. This study serves as a pivotal first step in assessing the risk of PTEs for two threatened riverine mammals in a densely populated river basin, highlighting the importance of their prioritization in regular monitoring to reinforce the ongoing conservation efforts.

Withdrawal Notice: Analysing the Quality of Food using Convolution Neural Network and Fuzzy Classifier in Hyperspectral Imagery

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