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Application of Geo-Statistic and Data-Mining for Determining Sampling Number and Interval for Monitoring Microbial Diversity in Tidal Mudflat  

Yang, Ji-Hoon (School of Civil and Environmental Engineering, Yonsei University)
Lee, Jae-Jin (School of Civil and Environmental Engineering, Yonsei University)
Yoo, Keun-Je (School of Civil and Environmental Engineering, Yonsei University)
Park, Joon-Hong (School of Civil and Environmental Engineering, Yonsei University)
Publication Information
Journal of Korean Society of Environmental Engineers / v.32, no.12, 2010 , pp. 1102-1110 More about this Journal
Abstract
Tidal mudflat is a reservoir for diverse microbial resources. Microbial diversity in tidal mudflat sediment can be easily influenced by various human activities. It is necessary to take representative samples to monitor microbial diversity in tidal mudflat sediments. In this study, we analyzed the microbial diversity and chemical characteristics of vegetation and non-vegetation tidal mudflat regions in the Kangwha tidal mudflat using geo-statistics and data-mining. According to the geo-statistical analysis, most correlation range values for the vegetation region were smaller than those for the non-vegetation region, which suggested that the shorter number and interval of sampling are required for the vegetation tidal mudflat environment due to its higher degree of chemical and biological complexity and heterogeneity. The data-mining analysis suggested that the organic content and nitrate were the major environmental factors influencing microbial diversity in the vegetation region while pH and sulfate were the major influencing factors in the non-vegetation region. Using the geo-statistical and data-mining integration approach, we proposed a guideline for determining the sampling interval and number to monitor microbial diversity in tidal mudflat.
Keywords
Tidal Mudflat; Microbial Diversity; Number of Sample; Geo-statistic; Data-mining;
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Times Cited By KSCI : 4  (Citation Analysis)
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