The analysis of the national wetlands vegetation database: freshwater lowland palustrine wetlands
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The South African wetlands vegetation is not well known. Number studies were conducted to classify vegetation focusing mostly in small areas throughout the country. Data from all studies were collated and used to build the National Wetlands Vegetation database. This study was aimed at grouping the similar vegetation plots in the NWVD into plant communities, to find what extent environmental factors can explain patterns in plant species composition, to find which species can be used as environmental indicators in wetlands and to determine how the species respond to the environmental variables that drive the ecosystem. The database contains eight Main Clusters that are further subdivided into communities. Each of these Main Clusters is used as a starting point for further, more detailed analysis. Two of the Main Clusters, Sclerophyllous Wetlands Vegetation and Temperate Grassy Wetland vegetation w~re used for the purpose of the study. In order to understand the various types of wetlands and their environmental drivers, data analytical data analytical techniques were used to reveal patterns in species composition and their correlation with environmental factors. The multivariate methods used for the analysis of the database were cluster analysis, indicator species analysis, ordination, group testing, and species response curves. All of the above-mentioned methods make use of similarity measures among sample units. S0renson similarity measure was the measure of choice. Analysis was performed using the two data analytical I packages PC-Ord 6 and HyperNiche 2. The most contrasting influential environmental variables for South African wetlands are Soil texture, Hydrogeomorphic type and the Wetness index. This study also contributes to the management and conservation of water resources. Recommendations are made as to how the vegetation can be used in the assessment of wetlands health/quality and monitoring of wetlands, as well as management.
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