Spatio-temporal distribution and driving factors of phytoplankton biomass in Lake Yangzong under the background of arsenic pollution treatment

被引:0
|
作者
Zheng X. [1 ]
Chen L. [1 ]
Qiu F. [1 ]
Zhang T. [1 ]
Zhang Z. [1 ]
Shang L. [1 ]
Bai N. [1 ]
Chen X. [1 ]
Zhao S. [1 ]
Kong L. [1 ]
Chen G. [1 ]
机构
[1] Yunnan Key Laboratory of Plateau Geographical Processes and Environmental Change, Faculty of Geography, Yunnan Normal University, Kunming
来源
Hupo Kexue/Journal of Lake Sciences | 2024年 / 36卷 / 01期
关键词
arsenic pollution; biomass; Lake Yangzong; phytoplankton; pollution treatment;
D O I
10.18307/2024.0111
中图分类号
学科分类号
摘要
Arsenic contamination has become an important environmental issue of some water bodies in China under the background of economic development and basin exploitation. However, limited attention has been paid to the effects of arsenic pollution prevention and ecological restoration. Phytoplankton is the key primary producer in lake ecosystems. Arsenic can directly affect the phytoplankton growth, species succession and primary productivity, and has become a sensitive indicator of arsenic pollution and its ecological effects. Lake Yangzong has a long history of arsenic pollution and subsequent remediation efforts. We conducted a seasonal survey on phytoplankton and environmental factors of Lake Yangzong covering the south, central and north parts of the lake from 2015 to 2019. The survey data were used to identify the spatio-temporal pattern and driving factors of phytoplankton biomass, and to evaluate the mechanism of phytoplankton biomass changes and effect of eco-restoration under arsenic pollution and treatment. The results showed that the phytoplankton was mainly composed of Cyanophyta. The phytoplankton biomass was in a range of 0.7-30.4 mg/L, with the lowest value in 2016 ((3.0±1.8) mg/L) and the highest value in 2017 ((10.5±8.9) mg/L). The phytoplankton biomass showed significant seasonal variations, but did not show significant spatial difference. The correlation analysis showed that the phytoplankton biomass had a significantly negative correlation with arsenic concentration and transparency, but had a significantly positive correlation with water temperature and pH. The multivariable linear regression model further showed that temperature and arsenic were the key environmental factors in driving the change of phytoplankton biomass. Thus, the arsenic residues in water body still inhibit phytoplankton growth after remediation in heavy metal polluted lakes, indicating that heavy metal pollutants may have long-term effects due to sediment release and enduring ecotoxicological impacts. © 2024 Science Press. All rights reserved.
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页码:34 / 42
页数:8
相关论文
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