Leveraging Bayesian network to reveal the importance of water level in a shallow lake ecosystem: A study based on Paleo-diatom and fish community
Huang, Yuqi; ,Li, Yu; Guo, Ying; Yao B(姚波); Wang, Shengrui; Ni, ShouQing
刊名SCIENCE OF THE TOTAL ENVIRONMENT
2024-06-20
卷号930页码:12
关键词Lake Hulun Ecosystem Water management Bayes Network
ISSN号0048-9697
DOI10.1016/j.scitotenv.2024.172341
通讯作者Li, Yu(yu.li@bnu.edu.cn) ; Yao, Bo(yaobo@imech.ac.cn)
英文摘要Lake ecological processes and nutrient patterns are increasingly affected by water level variation around the world. Still, the long-term effects of water level change on lake ecosystems and their implications for suitable lake level management have rarely been studied. Here, we studied the ecosystem dynamics of a mesotrophic lake located in the cold and arid region of northern China based on long-term paleo-diatom and fishery records. Utilizing a novel Copula-Bayesian Network model, possible hydrological -driven ecosystem evolution was discussed. Results show that increased nutrient concentration caused by the first water level drop in the early 1980s incurred a transition of sedimental diatoms towards pollution -resistant species, and the following water level rise in the mid -1980s brought about considerable external loading, which attributed to eutrophication and caused the miniaturization of fishery structure. In the 21st century, a continuous water level plummet further reduced the sediment diatom biomass and the fish biomass by altering nutrient concentration. However, with the implementation of the water diversion project in 2011, oligotrophic species increased, and the ecosystem developed for the better. From the perspective of water quality protection requirements and the ecological well-being of Lake Hulun, the appropriate water level should be around 542.42 - 544.15 m. In summary, our study highlights the coupling effect of water level and water quality on Lake Hulun ecosystem and gives shed to lake water level operation and management under future climate change and human activities.
分类号一类
资助项目Key R & D Program of Shandong Province[2021CXGC011202] ; National Key Research and Development Project of China[2019YFC0409201]
WOS关键词REGIME SHIFTS ; ECOLOGICAL IMPACTS ; FLUCTUATIONS ; INDICATORS ; HULUN
WOS研究方向Environmental Sciences & Ecology
语种英语
WOS记录号WOS:001238089000001
资助机构Key R & D Program of Shandong Province ; National Key Research and Development Project of China
其他责任者Li, Yu ; Yao, Bo
内容类型期刊论文
源URL[http://dspace.imech.ac.cn/handle/311007/95593]  
专题力学研究所_流固耦合系统力学重点实验室(2012-)
推荐引用方式
GB/T 7714
Huang, Yuqi,,Li, Yu,Guo, Ying,et al. Leveraging Bayesian network to reveal the importance of water level in a shallow lake ecosystem: A study based on Paleo-diatom and fish community[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2024,930:12.
APA Huang, Yuqi,,Li, Yu,Guo, Ying,姚波,Wang, Shengrui,&Ni, ShouQing.(2024).Leveraging Bayesian network to reveal the importance of water level in a shallow lake ecosystem: A study based on Paleo-diatom and fish community.SCIENCE OF THE TOTAL ENVIRONMENT,930,12.
MLA Huang, Yuqi,et al."Leveraging Bayesian network to reveal the importance of water level in a shallow lake ecosystem: A study based on Paleo-diatom and fish community".SCIENCE OF THE TOTAL ENVIRONMENT 930(2024):12.
个性服务
查看访问统计
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。


©版权所有 ©2017 CSpace - Powered by CSpace