Changes of Soil Water, Organic Matter, and Exchangeable Cations Along a Forest Successional Gradient in Southern China

Information on the distribution patterns of soil water content （SWC）, soil organic matter （SOM）, and soil exchangeable cations （SEC） is important for managing forest ecosystems in a sustainable manner. This study investigated how SWC, SOM, and SEC were influenced in forests along a successional gradient, including a regional climax （monsoon evergreen broad-leaved forest, or MEBF）, a transitional forest （coniferous and broad-leaved mixed forest, or MF）, and a pioneer forest （coniferous Masson pine （Pinus rnassoniana） forest, or MPF） of the Dinghushan Biosphere Reserve in the subtropical region of southern China. SWC, SOM, and SEC excluding Ca^2＋ were found to increase in the soil during forest succession, being highest in the top soil layer （0 to 15 cm depth） except for Na^＋. The differences between soil layers were largest in MF. This finding also suggested that the nutrients were enriched in the topsoil when they became increasingly scarce in the soil. There were no significant differences （P = 0.05） among SWC, SOM, and SEC. A linear, positive correlation was found between SWC and SOM. The correlation between SOM and cation exchange capacity （CEC） was statistically significant, which agreed with the theory that the most important factor determining SEC is SOM. The ratio of K^＋ to Na^＋ in the topsoil was about a half of that in the plants of each forest. MF had the lowest exchangeable Ca^2＋ concentration among the three forests and Ca^2＋：K^＋ in MPF was two times higher than that in MF. Understanding the changes of SWC, SOM, and CEC during forest succession would be of great help in protecting all three forests in southern China.

Cokriging of Soil Cation Exchange Capacity Using the First Principal Component Derived from Soil Physico-Chemical Properties

As soil cation exchange capacity （CEC） is a vital indicator of soil quality and pollutant sequestration capacity,a study was conducted to evaluate cokriging of CEC with the principal components derived from soil physico-chemical properties.In Qingdao,China,107 soil samples were collected.Soil CEC was estimated by using 86 soil samples for prediction and 21 soil samples for test.The first two principal components （PC1 and PC2） together explained 60.2% of the total variance of soil physico-chemical properties.The PC1 was highly correlated with CEC （r=0.76,P0.01）,whereas there was no significant correlation between CEC and PC2 （r=0.03）.The PC1 was then used as an auxiliary variable for the prediction of soil CEC.Mean error （ME） and root mean square error （RMSE） of kriging for the test dataset were-1.76 and 3.67 cmolc kg-1,and ME and RMSE of cokriging for the test dataset were-1.47 and 2.95 cmolc kg-1,respectively.The cross-validation R2 for the prediction dataset was 0.24 for kriging and 0.39 for cokriging.The results show that cokriging with PC1 is more reliable than kriging for spatial interpolation.In addition,principal components have the highest potential for cokriging predictions when the principal components have good correlations with the primary variables.