干旱区生态环境知识资源中心(Arid): Thriving arid oasis urban agglomerations: Optimizing ecosystem services pattern under future climate change scenarios using dynamic Bayesian network

Arid

DOI	10.1016/j.jenvman.2023.119612
	Thriving arid oasis urban agglomerations: Optimizing ecosystem services pattern under future climate change scenarios using dynamic Bayesian network
	Huang, Hao; Xue, Jie; Feng, Xinlong; Zhao, Jianping; Sun, Huaiwei; Hu, Yang; Ma, Yantao
通讯作者	Feng, XL
来源期刊	JOURNAL OF ENVIRONMENTAL MANAGEMENT
ISSN	0301-4797
EISSN	1095-8630
出版年	2024
卷号	350
英文摘要	The effects of global climate change and human activities are anticipated to significantly impact ecosystem services (ESs), particularly in urban agglomerations of arid regions. This paper proposes a framework integrating the dynamic Bayesian network (DBN), system dynamics (SD) model, patch generation land use simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model for predicting land use change and optimizing ESs spatial patterns that is built upon the SSP-RCP scenarios from CMIP6. This framework is applied to the oasis urban agglomeration on the northern slope of the Tianshan Mountains in Xinjiang (UANSTM), China. The findings indicate that both the SD model and PLUS model can accurately forecast the distribution of future land use. The SD model shows a relative error of less than 2.32%, while the PLUS model demonstrates a Kappa coefficient of 0.89. The land use pattern displays obvious spatial heterogeneity under different climate scenarios. The expansion of cultivated land and construction land is the main form of land use change in UANSTM in the future. The DBN model proficiently simulates the interactive relationships between ESs and diverse factors. The classification error rates for net primary productivity (NPP), habitat quality (HQ), water yield (WY), and soil retention (SR) are 20.04%, 3.47%, 4.45%, and 13.42%, respectively. The prediction and diagnosis of DBN determine the optimal ESs development scenario and the optimal ESs region in the study area. It is found that the majority of ESs in UANSTM are predominantly influenced by natural factors with the exception of HQ. The socio-economic development plays a minor role in such urban agglomerations. This study offers significant insights that can contribute to the fields of ecological protection and land use planning in arid urban agglomerations worldwide.
英文关键词	Climate change Ecosystem service optimization Dynamic bayesian network PLUS model Uncertainty Urban agglomeration
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:001130007700001
WOS关键词	BELIEF NETWORKS ; CHINA ; MODEL ; TOOL
WOS类目	Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/404444
推荐引用方式 GB/T 7714	Huang, Hao,Xue, Jie,Feng, Xinlong,et al. Thriving arid oasis urban agglomerations: Optimizing ecosystem services pattern under future climate change scenarios using dynamic Bayesian network[J],2024,350.
APA	Huang, Hao.,Xue, Jie.,Feng, Xinlong.,Zhao, Jianping.,Sun, Huaiwei.,...&Ma, Yantao.(2024).Thriving arid oasis urban agglomerations: Optimizing ecosystem services pattern under future climate change scenarios using dynamic Bayesian network.JOURNAL OF ENVIRONMENTAL MANAGEMENT,350.
MLA	Huang, Hao,et al."Thriving arid oasis urban agglomerations: Optimizing ecosystem services pattern under future climate change scenarios using dynamic Bayesian network".JOURNAL OF ENVIRONMENTAL MANAGEMENT 350(2024).