Population Structure Characteristic Of Quercus Wutaishanica In Natural Secondary Forest Of Huanglong Mountain

Quercus wutaishanica(Q. wutaishanica), as one of the dominant tree species in natural secondary forest of Huanglong Mountain, is one of the zonal vegetation and constructive species of climax community in this region. In the study, according to the sample set technical requirements and research objectives, through comprehensive reconnaissance of the Hugoumen Woodland, two pieces of Q. wutaishanica growth in good condition and has the typical characteristics of the plots were set up: Plot I, PINE- OAK- BIRCH mixed forest plot and plot II, Q. wutaishanica pure forest plot. Study the spatial distribution pattern, growth model and saplings update space research in the two plots to analysis the population structure and characteristics of the Q. wutaishanica.The principal conclusions of this analysis are as follows:(1) Spatial distribution patternThe spatial distribution pattern of Q. wutaishanica is closely related to the scale: In the two typical natural secondary forest plots, Q. wutaishanica showed aggregated distribution on the small scale, with increasing of the scale, the aggregation characteristics gradually weaken and eventually manifested as random distribution. Two plots of the Liaodong oak show slightly different in the small scale: in plot I, Q. wutaishanica individuals showed significant aggregation distribution within 0-11 m and gradually weakened with the scale increases; while in plot II, Q. wutaishanica showed aggregated distribution in 2-6 m scale, and the variation with scale characteristics is not obvious.The spatial distribution of the same growth stage in the two plots is different: The distribution of plot I is random and in plot II, young, middle-aged individuals show aggregated distribution at small scales. The distribution law of the whole space of Liaodong oak is consistent with Yi Lita and Hu Xiujuan.etc.The relationships between different growth stages of the two plots are not the same: there is no much relationships between each stage in the plot I. While in the plot II, the young and middle-aged individuals respectively on a small scale, and the nearly and over mature individuals have certain negative correlation. The forest canopy density in the two plots were 0.79, 0.48. It is found that, the upper layer of wood in plot I have great influence on the shielding effect of sunlight on the lower update. The conditions relative to the ratio in plot II is more conducive to the forest.(2) Growth model analysisSample I, II, there is good linear relationship between crown width and diameter at breast height(DBH). Through regression analysis, the correlation between DBH and crown in plot I is 0.2 0.693 I ICW ?D ?; the correlation between DBH and crown in plot II is 0.146 0.287 II IICW ?D ?. The comparison in the same coordinate system shows that, under the condition of the same DBH, the crown in plot I is greater than the individual in plots II.In plots I II, there is good linear relationship between tree height and diameter at breast height(DBH). Through regression analysis, the correlation between DBH and hight,quadratic and logarithmic functions are performing well in the two plots. Obtain the predicted value by the sample data and model, and do the residual analysis of the predicted value and the real value. Final results showed that: the correlation between DBH and tree height in two plots were: 4.319 ln 1.02 I IH ?D ?; 4.853 ln 4.36 II IIH ?D ?. The comparison in the same coordinate system shows that, under the condition of the same DBH, the tree hight in plot I is greater than the individual in plots II.The total area more suitable for seedling growth in two plots are 792.68, 810.39. With the areas are almost the same, so the difference can be ignored. We can consider that in the two plots, the chance of Quercus liaotungensis for secondary update is roughly equivalent.With the optimization of the environment for the growth of Liaodong oak, the area is reduced. On the low rating, the data are 385.63, 396.83 in the two plots, basically at the flat state. The differences began to appear in the middle level. The data in plot I is 58.97 lager than in plot II. On the grade level, The data in plot II is 65.48 lager than in plot I.