干旱区生态环境知识资源中心(Arid): SELF-ORGANIZING FEATURE MAP CLASSIFICATION AND ORDINATION OF ENDANGERED MEDICINAL PLANT (GLYCYRRHIZA URALENSIS) COMMUNITIES IN NORTH CHINA

Arid

DOI	10.15666/aeer/2004_36193629
	SELF-ORGANIZING FEATURE MAP CLASSIFICATION AND ORDINATION OF ENDANGERED MEDICINAL PLANT (GLYCYRRHIZA URALENSIS) COMMUNITIES IN NORTH CHINA
	Song, N. Q.; Xu, B.; Zhang, J. T.
通讯作者	Zhang, JT
来源期刊	APPLIED ECOLOGY AND ENVIRONMENTAL RESEARCH
ISSN	1589-1623
EISSN	1785-0037
出版年	2022
英文摘要	Glycyrrhiza uralensis is an endangered medicinal plant and is mainly distributed in semiarid and arid areas in Northern China. The conservation of this species and its communities is important and urgent. In the present work, we examined, by artificial neural network theory and methods, the ecological relationships of G. uralensis communities in Northern China, which is the basis for conservation. Data from 100 samples of 2 ?? 2 m were collected along a precipitation gradient from east to west in Northern China. Species composition data and environmental data were measured and recorded for each sample. Self-organizing feature map (SOFM) is an important and superior network in neural network theory, and SOFM clustering and SOFM ordination was used to analyze ecological relations of these community data. The results showed that there were twelve communities dominated by G. uralensis in Northern China. These communities represent almost all community types and distribution of G. uralensis in China. They had different characteristics in composition, structure and environment. Precipitation was the key environmental factor affecting G. uralensis populations and communities. Water condition was a limited factor for plant community distribution in semiarid and arid areas in Northern China. Topographical variables, such as elevation, slope and slope direction, were also important to the studied communities. Conservation for G. uralensis populations and communities must consider these relations. SOFM clustering and ordination were effective and useful techniques in the study of endangered medicinal plant community and should be applied more frequently.
英文关键词	neural network quantitative analysis medicinal plant conservation G uralensis communities semi-arid and arid area
类型	Article ; Early Access
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000834354800001
WOS关键词	GRADIENT ; CONSERVATION ; DIVERSITY
WOS类目	Ecology ; 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/2XILL650/391846
推荐引用方式 GB/T 7714	Song, N. Q.,Xu, B.,Zhang, J. T.. SELF-ORGANIZING FEATURE MAP CLASSIFICATION AND ORDINATION OF ENDANGERED MEDICINAL PLANT (GLYCYRRHIZA URALENSIS) COMMUNITIES IN NORTH CHINA[J],2022.
APA	Song, N. Q.,Xu, B.,&Zhang, J. T..(2022).SELF-ORGANIZING FEATURE MAP CLASSIFICATION AND ORDINATION OF ENDANGERED MEDICINAL PLANT (GLYCYRRHIZA URALENSIS) COMMUNITIES IN NORTH CHINA.APPLIED ECOLOGY AND ENVIRONMENTAL RESEARCH.
MLA	Song, N. Q.,et al."SELF-ORGANIZING FEATURE MAP CLASSIFICATION AND ORDINATION OF ENDANGERED MEDICINAL PLANT (GLYCYRRHIZA URALENSIS) COMMUNITIES IN NORTH CHINA".APPLIED ECOLOGY AND ENVIRONMENTAL RESEARCH (2022).