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Interpreting the groundwater attributes influencing the distribution patterns of groundwater-dependent vegetation in northwestern China

Authors

  • Juntao Zhu,

    1. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
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  • Jingjie Yu,

    Corresponding author
    1. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    • Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A, Datun Road, Chaoyang District, Beijing 100101, P. R. China.

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  • Ping Wang,

    1. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
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  • Yichi Zhang,

    1. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
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  • Qiang Yu

    1. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
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ABSTRACT

Groundwater-dependent vegetation (GDV) must have access to groundwater to maintain their growth and function. GDV distribution patterns are an important issue in arid vegetation ecology. Using groundwater attributes to explore the distribution patterns of GDV have been very limited. In this article, we selected the Ejina Desert Oasis as an area to investigate GDV and groundwater attributes. Twenty plant species and 31 plant plots of data were collected. Two-way indicator species analysis (TWINSPAN) was performed to determine GDV types. Detrended correspondence analysis (DCA) and detrended canonical correspondence analysis (DCCA) were performed to analyse the relationships between GDV and groundwater attributes. The results indicated that (1) six plant community types were classified by TWINSPAN; (2) DCA ordination analyses showed that the groundwater depth (Dep) was the main factor restricting the distribution patterns of GDV, and the distribution of the dominant species and corresponding vegetation types had strong similarities; (3) in the DCCA diagram, the first axis represented variations of Dep, while the second axis was related to the pH values; (4) with increased Dep, the community types made the transition from I to VI; and (5) the DCCA diagram was similar to the DCA. However, the distribution patterns of GDV were more compact in the DCCA, while the DCA showed that each association group appeared within a limited range and had a clear border against other communities. This study shows that ordination methods can be used to explain the relationships between the distribution patterns of GDV and groundwater attributes. Copyright © 2011 John Wiley & Sons, Ltd.

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