干旱区生态环境知识资源中心(Arid): Ecosystem health assessment based on deep learning in a mountain-basin system in Central Asia's arid regions, China

Arid

DOI	10.1016/j.ecolind.2024.112148
	Ecosystem health assessment based on deep learning in a mountain-basin system in Central Asia's arid regions, China
	Bi, Xu; Fu, Yongyong; Wang, Ping; Zhang, Yushuo; Yang, Zihan; Hou, Fen; Li, Bo
通讯作者	Li, B
来源期刊	ECOLOGICAL INDICATORS
ISSN	1470-160X
EISSN	1872-7034
出版年	2024
卷号	165
英文摘要	Arid pastoral ecosystems are particularly vulnerable to degradation and desertification, exacerbated by factors such as overgrazing, land use changes, and climate change impacts. Therefore, research on ecosystem health is imperative for ecosystem management and restoration in arid pastoral areas. Although ecosystem health studies have been conducted in various regions, research on ecological health assessment in arid pastoral areas of Central Asia remains limited, especially within a mountain-basin system (MBS). Taking the Chinese pastoral region of Fuyun County in Altay Prefecture, Xinjiang, as our study area, we improved an evaluation framework in terms of Vigor-Organization-Resilience-Service (VORS) based on remote sensing and GIS technology, and innovatively employed a deep learning method to assess the ecological system health status and spatiotemporal patterns for the years 2000, 2010, and 2020. Our results indicate the following: (1) The evaluation method based on deep learning can achieve a more comprehensive, efficient and objective evaluation of ecosystem health. (2) The ecosystem health index (EHI) ranged from 0.0759 to 0.5735 in 2000, 0.0798 to 0.5952 in 2010, and 0.0415 to 0.5657 in 2020. (3) The distribution pattern of EHI exhibited spatial heterogeneity, with the indexes decreasing from north to south. The highest proportion of high ecosystem health level (EHL) was found in summer pastures, followed by those in north of spring/autumn pastures and along the Irtysh and Ulungur rivers. On the other hand, the EHLs were relatively low in spring/autumn and winter pasture areas. The EHL exhibited minimal alteration between 2000 and 2010. From 2010 to 2020, areas experiencing an increase in EHL were primarily concentrated along the Ulungur River, with another part of the region focused on the interface between winter pastures and spring/ autumn pastures. Based on the results, rotational grazing and grazing prohibition should be put into place for the winter pastures in the central and southern regions of the study area, as well as for the spring and autumn pastures. Meanwhile, it is recommended to plant premium, high-yield artificial forage grass alongside the Irtysh and Ulungur rivers. These findings will assist ecosystem managers in implementing effective measures to enhance ecosystem health in arid pastoral areas. Moreover, the presented evaluation framework and method enable a more objective, comprehensive, and efficient assessment of complex ecosystems, and they can be applied to ecosystem health assessments in similar regions.
英文关键词	Ecosystem health Assessment method Vigor -Organization -Resilience -Service (VORS) Deep learning Mountain -basin system
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:001246440500001
WOS关键词	FORAGE-LIVESTOCK BALANCE ; LAND-USE CHANGE ; GRASSLAND ECOSYSTEM ; ECOLOGICAL RESTORATION ; INNER-MONGOLIA ; SERVICES ; VEGETATION ; SECURITY ; CLIMATE ; BAY
WOS类目	Biodiversity Conservation ; Environmental Sciences
WOS研究方向	Biodiversity & Conservation ; Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/403405
推荐引用方式 GB/T 7714	Bi, Xu,Fu, Yongyong,Wang, Ping,et al. Ecosystem health assessment based on deep learning in a mountain-basin system in Central Asia's arid regions, China[J],2024,165.
APA	Bi, Xu.,Fu, Yongyong.,Wang, Ping.,Zhang, Yushuo.,Yang, Zihan.,...&Li, Bo.(2024).Ecosystem health assessment based on deep learning in a mountain-basin system in Central Asia's arid regions, China.ECOLOGICAL INDICATORS,165.
MLA	Bi, Xu,et al."Ecosystem health assessment based on deep learning in a mountain-basin system in Central Asia's arid regions, China".ECOLOGICAL INDICATORS 165(2024).