4.5 Article

Environmental factors affecting vegetation composition in the Alxa Plateau, China

期刊

JOURNAL OF ARID ENVIRONMENTS
卷 69, 期 3, 页码 473-489

出版社

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jaridenv.2006.10.005

关键词

classification; ordination; multi-variate analysis; grassland management; environmental characteristics

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The aim of this study was to provide an analysis of vegetation and environment relationships in the Alxa Plateau of Inner Mongolia, China. Seventy species representing 46 genera and 16 families were collected. The largest families were Leguminosae, Polygonaceae, Gramineae and Compositae, representing 20.0%, 15.7%, 14.3% and 14.3% of the total flora, respectively. Phanerophytes and hemicryptophytes were the most abundant life-form. Classification of the vegetation was analysed using two-way indicator species analysis (TWINSPAN) techniques. This resulted in the recognition of six vegetation groups, each of definite vegetation and soil characteristics, which could be linked to a specific geomorphologic unit. Ordination techniques as detrended correspondence analysis (DCA) and canonical correspondence analysis (CCA) were used to examine the relationship between the vegetation and environmental parameters. Analysis with DCA gave results similar to CCA, suggesting that there is a relatively strong correspondence between vegetation and environmental factors. CCA axis 1 was highly associated with organic matter, total nitrogen, silt and clay content, elevation, Kira moisture index and relative humidity, while CCA axis 2 showed significant correlation with chlorine, calcium ion, magnesium ion and electrolytic conductivity. These gradients were related closely to the first two canonical axes, and accounted for 60% of the species-environment relationship in the study sites. Understanding relationships between environmental variables and vegetation distribution in this area helps us to apply these findings in management, reclamation, and development of arid and semi-arid grassland ecosystems. (c) 2006 Elsevier Ltd. All rights reserved.

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