The Effects of Physico-chemical Soil Properties on the Site Index of Sawtooth Oak [Quercus acutissima Carruth.] in the Korean Peninsula - Including Offshore Islands and Coastal Areas -
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Site productivity for Quercus acutissima Carruth. stands was estimated for unstocked land in the Republic of Korea including offshore islands and coastal areas, using the relationship between site index (SI, the average height of dominant trees at a fixed age) and physical and chemical soil properties. Site index is the most common measure of forest site productivity for tree growth. A total of 147 plots were selected in 22 sawtooth oak stands in the central temperate forest zone. A multiple regression model was derived for predicting site index using 13 soil properties. Multicollinearity diagnostic tests were performed, and stepwise regression and principal components regression (PCR) models compared. In the final regression model, the independent variables were fitted using the most significant principal components (PCs). In this statistical process, we focused on relationships among soil properties that can result in multicollinearity problems. In PCR, we applied principal component analysis (PCA) based on the correlation matrix to the independent variables. We then selected the two most significant PCs and derived a regression using these PCs. This procedure yielded reliable estimates of regression coefficients. In terms of the magnitude and sign of the regression coefficients in the final SI model derived from all of the soil variables using the significant PCs performed better than the preliminary SI model derived using stepwise regression. In this final model, the most important soil properties in descending order of importance for predicting Q. acutissima SI were total nitrogen (T.N.), exch. Na+, exch. K+, organic matter (O.M.), and pH. These results provide important criteria for establishing Q. acutissima stands especially in unstocked land, and provide guidance for aforestation in new plantations.
Abstract
Site productivity for Quercus acutissima Carruth. stands was estimated for unstocked land in the Republic of Korea including offshore islands and coastal areas, using the relationship between site index (SI, the average height of dominant trees at a fixed age) and physical and chemical soil properties. Site index is the most common measure of forest site productivity for tree growth. A total of 147 plots were selected in 22 sawtooth oak stands in the central temperate forest zone. A multiple regression model was derived for predicting site index using 13 soil properties. Multicollinearity diagnostic tests were performed, and stepwise regression and principal components regression (PCR) models compared. In the final regression model, the independent variables were fitted using the most significant principal components (PCs). In this statistical process, we focused on relationships among soil properties that can result in multicollinearity problems. In PCR, we applied principal component analysis (PCA) based on the correlation matrix to the independent variables. We then selected the two most significant PCs and derived a regression using these PCs. This procedure yielded reliable estimates of regression coefficients. In terms of the magnitude and sign of the regression coefficients in the final SI model derived from all of the soil variables using the significant PCs performed better than the preliminary SI model derived using stepwise regression. In this final model, the most important soil properties in descending order of importance for predicting Q. acutissima SI were total nitrogen (T.N.), exch. Na+, exch. K+, organic matter (O.M.), and pH. These results provide important criteria for establishing Q. acutissima stands especially in unstocked land, and provide guidance for aforestation in new plantations.
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