Geostatistical analysis on the spatial pattern of Quercus mongolica population in different communities.

Abstract

Taking Quercus mongolica population in the secondary forest of Q. mongolica as the research object, two plots in different stages of succession (A and B) were set up in Tazigou Forest Farm of Wangqing Forestry Bureau, Jilin Province. By applying the method of adjacent grid survey, each plot was divided into 100 units of 10 m×10 m and the spatial coordinates of each tree in the unit were accurately located to survey all the basic information of trees with diameter at breast height (DBH)≥1 cm. The degree, composition, scale and pattern of spatial heterogeneity of individual tree of Q. mongolica were analyzed by means of semi-variance function and fractal dimension of geostatistics. By using Kriging interpolation method, unbiased estimation of tree attribute with spatial autocorrelation was carried out, distribution map was drawn and spatial distribution pattern was analyzed. The results showed that the best semi-variance function of tree attributes in two plots was mainly distributed in an exponential model and a spherical model with an aggregated distribution. The degree of spatial autocorrelation and continuity of plot A were higher than that of plot B. The DBH and the east-west crown (CEW) had strong spatial heterogeneity and autocorrelation in the two plots. The tree attributes of both plots showed strong spatial heterogeneity in the north-south direction. In addition, there was strong spatial heterogeneity in the northwest-southeast direction of plot A and in the northeast-southwest of plot B. The strength of the spatial heterogeneity was higher and the scale being larger in plot A. The variations of DBH and CEW were obvious in plot A, while the variations of CEW and south-north crown (CSN) were obvious in plot B. The fractal dimension and semi-variogram function showed the same result. The tree attributes of plot A were mainly patchy and stripe, and the variation trend of spatial distribution pattern was obvious. The tree attributes of plot B was broken, with complex pattern. Those results indicated that the characteristics of population, community development, spatial scale and spatial horizontal direction might affect the spatial pattern of populations. The geostatistical analysis method is helpful to quantitatively and directly describe population growth and development trend, which can provide a theoretical basis for the sustainable management of Q. mongolica secondary forests in Northeast China.