Spatial distribution, fractionation, toxicity and risk assessment of surface sediments from the Baiyangdian Lake in northern China

Zhang, Chao; Shan, Baoqing; Zhao, Yu; Song, Zhixin; Tang, Wenzhong

doi:10.1016/j.ecolind.2018.03.078

Cited by 54 publications

(12 citation statements)

References 38 publications

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“…The Xiongan New Area (XANA) was in the center of the triangle. From the perspective of the integrated analysis in this study, it was revealed that the construction of the XANA faced higher ecological risk, which was verified by many studies (Zhang et al 2018;Xue et al 2019). It also showed that Zhejiang Province had very high ecological risk probabilities at both the LC/EC/IC 50 and NOEC/LOEC levels, as it ranked within the top two, while the Pearl River Basin had higher Cd-induced ecological risk than other areas.…”

Section: Characteristics Of CD Contamination Distributionsupporting

confidence: 66%

Ecological risk assessment of soil cadmium in China’s coastal economic development zone: a meta-analysis

Sun

Wang

et al. 2020

Ecosyst Health Sustain

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The coastal area of China has faced major strategic planning and environmental pollution, including heavy metals pollution. This study aimed to provide a comprehensive evaluation of the effects of Cd pollution on the ecology in coastal areas of China. A soil Cd pollution database of 300 counties or districts in coastal areas was screened from academic dissertations and academic journal papers. Based on the database, the ecological risk was evaluated using entropy methods and probabilistic ecological risk assessment (PERA), and the advantages and disadvantages of these methods were analyzed. In China's coastal areas, the soil Cd content in 10.33% of the counties was higher than the minimum of risk control value (1.5 mg/kg), and in 4.00% of the counties was higher than the maximum of risk control value (4.0 mg/kg). The ecological risks were highly compatible with national strategic planning areas. Guangxi Province, Zhejiang Province, and Guangdong Province ranked among the top three coastal areas for soil Cd contamination, and the ecological risks were 18.80%, 17.89%, and 15.77% at the maximum no-effect concentration/lowest effect concentration (NOEC/LOEC) level. This study can provide insights to policymakers regarding the protection of ecosystems threatened by heavy metals in the process of regional strategic planning.

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Section: Characteristics Of CD Contamination Distributionsupporting

confidence: 66%

Ecological risk assessment of soil cadmium in China’s coastal economic development zone: a meta-analysis

Sun

Wang

et al. 2020

Ecosyst Health Sustain

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“…The transport and enrichment of HMs in reservoir bottom sediments have been intensively studied, including concentration, spatial distribution, source identification and pollution assessment [13,[49][50][51], temporal variability [52], bioavailability [53], ecological risk and organism toxicity [4,54,55]. Moreover, some studies relate to HM concentrations in reservoir tributaries [16,56].…”

Section: Introductionmentioning

confidence: 99%

Heavy Metals in Bottom Sediments of Reservoirs in the Lowland Area of Western Poland: Concentrations, Distribution, Sources and Ecological Risk

Sojka

Jaskuła

Siepak

2018

Water

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The paper presents the results of a study of heavy metals (HMs) concentrations in six retention reservoirs located in the lowland area of western Poland. The objectives of this study were to analyze the Cd, Cr, Cu, Ni, Pb and Zn concentrations, assess contamination and ecological risk, analyze the spatial variability of HM concentrations and identify potential sources and factors determining the concentration and spatial distribution. The bottom sediment pollution by HMs was assessed on the basis of the index of geo-accumulation (Igeo), enrichment factor (EF), pollution load index (PLI) and metal pollution index (MPI). To assess the ecological risk associated with multiple HMs, the mean probable effect concentration (PEC) quotient (Qm-PEC) and the toxic risk index (TRI) were used. In order to determine the similarities and differences between sampling sites in regard to the HM concentration, cluster analysis (CA) was applied. Principal component analysis (PCA) was performed to assess the impact of grain size, total organic matter (TOM) content and sampling site location on HM spatial distribution. Additionally, PCA was used to assess the impact of catchment, reservoir characteristics and hydrological conditions. The values of Igeo, EF, MPI and PLI show that Cd, Cr, Cu, Ni and Pb mainly originate from geogenic sources. In contrast, Zn concentrations come from point sources related to agriculture. The mean PEC quotient (Qm-PEC) and TRI value show that the greatest ecological risk occurred at the inlet to the reservoir and near the dam. The analysis showed that the HMs concentration depends on silt and sand content. However, the Pb, Cu, Cd and Zn concentrations are associated with TOM as well. The relationship between individual HMs and silt was stronger than with TOM. The PCA results indicate that HMs with the exception of Zn originate from geogenic sources—weathering of rock material. However, the Ni concentration may additionally depend on road traffic. The results show that a reservoir with more frequent water exchange has higher HMs concentrations, whereas the Zn concentration in bottom sediments is associated with agricultural point sources.

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“…Most previous studies of the lake's macrobenthos communities focused on the lake, with few studies in the tributaries. These studies showed that the macrobenthos richness and biodiversity in Baiyangdian Lake and its rivers have decreased significantly since the 1960s (Zhang et al, 2018;. In the present study, we selected China's Baiyangdian Lake-Fu River system as a case study, with the goals being to (1) compare the spatial distributions of the macrobenthos community structure among the river, riverlake ecotones, and lake; (2) explore the spatial patterns and differences of multiple aspects of macrobenthos biodiversity (including taxonomic and functional diversity) in different ecosystem types (the river, river and lake mouths, and lake); and (3) determine which functional traits respond to specific environmental factors and quantify the effects of the water environment and sediment heavy metal contents on the macrobenthos taxonomic and functional diversity in the river-lake system.…”

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confidence: 99%

Spatial patterns of macrobenthos taxonomic and functional diversity throughout the ecotones from river to lake: A case study in Northern China

Yang

et al. 2022

Front. Ecol. Evol.

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Macrobenthos taxonomic and functional diversity are key indicators of ecosystem health. River–lake ecotones are key macrobenthos habitats. However, we don’t fully understand macrobenthos biodiversity patterns in these ecotones. We studied water environment, sediment heavy metal contents, and macrobenthos community, which we sampled simultaneously from 29 sampling sites along the Fu River–Baiyangdian Lake gradient in Northern China with five field surveys from 2018 to 2019. Six trait classes resolved into 25 categories were allocated to macrobenthos through a binary coding system. We used the RLQ framework (R, environmental variables; L, species of taxa; Q, traits) and fourth-corner analyses to evaluate the relationship between environmental variables and macrobenthos traits. Finally, we carried out variance partitioning to assess the contributions of environmental variables to variation of macrobenthos diversities. As the results, TN and TP contents in the river and lake mouths were lower than those in the adjacent river and lake, indicating that the river–lake ecotones played a role in purifying the water and buffering pollution. High taxonomic diversity of macrobenthos in the lake mouth and the presence of unique taxa in the two ecotones revealed edge effects, but the macrobenthos abundance and biomass were extremely low compared with those in the adjacent river and lake. We found no significant correlation between the taxonomic and functional diversity indices in the river and lake mouths. Water depth, water transparency, TN, and TP were the main water environmental drivers of macrobenthos taxonomic and functional diversity, explaining up to 45.5% and 56.2% of the variation, respectively. Sediment Cd, Cr, Cu, Pb, and Zn contents explained 15.1% and 32.8%, respectively, of macrobenthos taxonomic and functional diversity. Our results suggest that functional diversity approaches based on biological traits can complement taxonomic approaches in river–lake ecotones. Furthermore, improving water depth, transparency, eutrophication, and heavy metal pollution will improve macrobenthos diversity in these ecotones and maintain ecosystem health.

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Spatial distribution, fractionation, toxicity and risk assessment of surface sediments from the Baiyangdian Lake in northern China

Cited by 54 publications

References 38 publications

Ecological risk assessment of soil cadmium in China’s coastal economic development zone: a meta-analysis

Ecological risk assessment of soil cadmium in China’s coastal economic development zone: a meta-analysis

Heavy Metals in Bottom Sediments of Reservoirs in the Lowland Area of Western Poland: Concentrations, Distribution, Sources and Ecological Risk

Spatial patterns of macrobenthos taxonomic and functional diversity throughout the ecotones from river to lake: A case study in Northern China

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