Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 402685
Title Potential plant species distribution in the Yellow River Delta under the influence of groundwater level and soil salinity
Author(s) Fan Xiaomei, ; Pedroli, B.; Liu Gaohuan, ; Liu Hongguang, ; Song Chuangye, ; Shu Longcang,
Source Ecohydrology 4 (2011)6. - ISSN 1936-0584 - p. 744 - 756.
DOI https://doi.org/10.1002/eco.164
Department(s) CL - Crossing Borders
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 2011
Keyword(s) canonical correspondence-analysis - environmental-factors - olifants-estuary - south-africa - vegetation - patterns - ecology - models
Abstract This article describes a multidisciplinary approach to assessing potential vegetation types. The relation between vegetation distribution as derived from field survey and habitat characteristics in the Yellow River Delta (YRD) was analyzed using detrended canonical correspondence analysis (DCCA). The three-dimensional groundwater numerical simulation model MODFLOW yielded an accurate distribution of the shallow groundwater table within the study area. Groundwater table and soil salinity appeared to have the largest influence on the distribution patterns of specific indicator species. The quantitative relationships between species presence and environmental factors were further explored using logistic regression, allowing for the prediction of potential species distribution in relation to fluctuations in groundwater depth and soil salinity. Based on this, potential distribution maps for specific plant species and their communities were generated using ArcGIS. The potential vegetation map was compared to the actual vegetation map (interpreted from SPOT imagery), which leads to a discussion of the main factors responsible for fragmentation and degradation of the local vegetation system
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