Application of multivariate statistical analysis in ecological environment research
Main Article Content
Abstract
Multivariate statistics has proven many outstanding advantages and has been used extensively in various studies in the ecological environment field. They supported ecologists to discover the structure and previous relatively objective summary of the primary features of the data. In this paper, some important statistical techniques, including principal component analysis (PCA), canonical correspondence analysis (CCA) and cluster analysis, are explained briefly. Each of them is also examined by a corresponding case-study. The PCA is applied to identify and analyze the relationship between mangrove plant communities and soil factors. Meanwhile, the CCA is put in an application to analyze the relationship between the two sets of species and soil data, from which to determine the effect of soil on the distribution of dominant species. Finally, cluster analysis is examined to analyze the similarities among species in the studied area.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Keywords
Canonical correlation analysis, cluster analysis, data analysis, ecology, environment, principal component analysis
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