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

Zhu, J; Yu, J; Wang, P; Zhang, Y; Yu, Q

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

Zhu, J Yu, J Wang, P Zhang, Y Yu, Q

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Publication Type:: Journal Article
Citation:: Ecohydrology, 2012, 5 (5), pp. 628 - 636
Issue Date:: 2012-09-01

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Field	Value	Language
dc.contributor.author	Zhu, J	en_US
dc.contributor.author	Yu, J	en_US
dc.contributor.author	Wang, P	en_US
dc.contributor.author	Zhang, Y	en_US
dc.contributor.author	Yu, Q https://orcid.org/0000-0001-6950-1821	en_US
dc.date.issued	2012-09-01	en_US
dc.identifier.citation	Ecohydrology, 2012, 5 (5), pp. 628 - 636	en_US
dc.identifier.issn	1936-0584	en_US
dc.identifier.uri	http://hdl.handle.net/10453/31433
dc.description.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. © 2011 John Wiley & Sons, Ltd.	en_US
dc.relation.ispartof	Ecohydrology	en_US
dc.relation.isbasedon	10.1002/eco.249	en_US
dc.title	Interpreting the groundwater attributes influencing the distribution patterns of groundwater-dependent vegetation in northwestern China	en_US
dc.type	Journal Article
utslib.citation.volume	5	en_US
utslib.for	0701 Agriculture, Land and Farm Management	en_US
utslib.for	05 Environmental Sciences	en_US
utslib.for	06 Biological Sciences	en_US
utslib.for	07 Agricultural and Veterinary Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	closed_access
pubs.issue	5	en_US
pubs.publication-status	Published	en_US
pubs.volume	5	en_US

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. © 2011 John Wiley & Sons, Ltd.

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http://hdl.handle.net/10453/31433