The concentrations of heavy metals in sediments and marine organisms in Daya Bay were investigated, and the Monte Carlo method was used to analyze the uncertainty of the results of geo-accumulation characteristics and ecological and health risks. The mean concentrations of metal elements in sediments were in the following order: Zn > Cr > Cu > As > Cd > Hg, while those in marine organisms were Zn > Cu > As > Cr ≈ Cd > Hg. The geo-accumulation index (Igeo) indicated that the primary pollutant was Hg, with 5.46% moderately polluted, and 39.52% for unpolluted to moderately polluted. Potential ecological risks (RI) were between low and high risks, and the contributions of Hg, Cd, and As to ecological risks were 50.85%, 33.92%, and 11.47%, respectively. The total hazard coefficients (THQ) were less than 1, but on the basis of total carcinogenic risks (TCR), the probability of children and adults exceeded the unacceptable risk threshold of 22.27% and 11.19%, respectively. Sensitivity analysis results showed that the concentrations of carcinogenic elements contributed to risk in the order of As > Cd > Cr. Therefore, in order to effectively control heavy metals contamination in Daya Bay, it is necessary to strengthen the management of Hg, Cd, and As emissions.
The biological trait analysis (BTA) is regarded as a promising approach to unravel how ecosystem functions respond to human-induced disturbances. This study considered the four sampling locations associated with different human activities in Daya Bay, that is, the domestic and industrial sewage discharge area (SED), mariculture area (MRC), nuclear power plants thermal discharge area (NTD), and an area with relatively low human disturbance as a reference (REF). Thirty modalities of nine traits were selected in BTA. Our results showed a clear shift in the functional structure of macrobenthic communities between the sampling locations, except for the case between NTD and REF. The trait composition in the communities did not highlight any seasonal patterns. Bioturbation, longevity, tolerance, body size, feeding habit, and environmental position were the key traits to characterize the functional structure of macrobenthic communities and demonstrated predictable responses along the environmental gradients. Water depth, DO, Chl-a, NH4+, and petroleum contaminants in sediments were the main variables influencing the trait composition. In addition, the taxonomic index (H′) and functional diversity index (Rao’s Q) showed clear differences among the sampling locations. Although there were no significant differences between NTD and REF in terms of the trait composition and functional diversity, a potential function loss in NTD still can be detected through the integrated analysis with taxonomic diversity. We suggest that the traits (except for fragility, larval development, and living habits) selected and the diversity indices (H′ and Rao’s Q) could serve as promising indicators of ecological conditions in Daya Bay.
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