CRAES, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences uses EasySensor DGT to publish the article as below:
Highlights
• Plant Cd uptake was predicted during a vegetation restoration in tailings reservoir.•
• Soil total Cd was the best predictor of plant Cd uptake.•
• DGT technique only predicted plant Cd uptake effectively at a low Cd supply.•
• Soil properties had a limited role in improving the prediction.•
• Anthropogenic Cd inputs increased the uncertainty of the prediction.
Abstract
Plant uptake can reduce soil cadmium (Cd) pollution, while how to exactly predict plant Cd uptake in industrial or mining areas during vegetation restoration remains unexplored. Taking Heteropogon contortus as the object plant, we predicted plant Cd uptake in the Majiatian tailings reservoir during 48-year vegetation restoration by the methods of soil total Cd, DGT (diffusive gradients in thin films technique) and acetic acid (HAc) extraction. Meanwhile, we explored the effects of soil properties on the accuracy of the prediction. Total Cd concentrations in the soils exhibited a better prediction of plant Cd uptake relative to the methods of HAc extraction and DGT. However, the DGT method effectively predicted plant Cd uptake at low Cd supply (lower than 0.42 μg/L), probably because of the dominant diffusion limitation by plants. The prediction of plant Cd uptake by HAc extraction was improved when combined with soil pH. Our results indicate that with increasing external Cd inputs during the vegetation restoration, soil total Cd and traditional extraction method in combination with soil properties are effective ways to predict plant Cd uptake, especially when the Cd fractions cannot be measured by DGT. However, the DGT method works once plant Cd uptake dominated by diffusion limitation despite the interference in soil properties.
Writers:
Zhijie Long, He Zhu, Haijian Bing, Xin Tian, Xiaofang Wang, Zhongjian Ma, Daming Yu, Yanhong Wu, Predicting soil cadmium uptake by plants in a tailings reservoir during 48-year vegetation restoration, Science of The Total Environment, Volume 818, 2022, 151802, ISSN 0048-9697, https://doi.org/10.1016/j.scitotenv.2021.151802.
Link:
https://www.sciencedirect.com/science/article/abs/pii/S0048969721068789?via%3Dihub#!