Leveraging Bayesian network to reveal the importance of water level in a shallow lake ecosystem: A study based on Paleo-diatom and fish community

doi:10.1016/j.scitotenv.2024.172341

IMECH-IR > 流固耦合系统力学重点实验室

	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
通讯作者	Li, Yu([email protected]) ; Yao, Bo([email protected])
发表期刊	SCIENCE OF THE TOTAL ENVIRONMENT
	2024-06-20
卷号	930 页码:12
ISSN	0048-9697
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.
关键词	Lake Hulun Ecosystem Water management Bayes Network
DOI	10.1016/j.scitotenv.2024.172341
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:001238089000001
关键词[WOS]	REGIME SHIFTS ; ECOLOGICAL IMPACTS ; FLUCTUATIONS ; INDICATORS ; HULUN
WOS研究方向	Environmental Sciences & Ecology
WOS类目	Environmental Sciences
资助项目	Key R & D Program of Shandong Province[2021CXGC011202] ; National Key Research and Development Project of China[2019YFC0409201]
项目资助者	Key R & D Program of Shandong Province ; National Key Research and Development Project of China
论文分区	一类
力学所作者排名	1
RpAuthor	Li, Yu ; Yao, Bo
引用统计	被引频次：2[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://dspace.imech.ac.cn/handle/311007/95594
专题	流固耦合系统力学重点实验室
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.Rp_Au:Li, Yu, Yao, Bo
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.