Based on data collected from 2054 saplings of Larix gmelinii forest in 55 fixed plots in 2018-2019 in Cuigang Forestry Station, Daxing'anling area, we classified the stand density index (SDI) into four classes, i.e., Class Ⅰ (SDI1<1863 plants·hm-2), Class Ⅱ (1863 plants·hm-2≤SDI2<2155 plants·hm-2), Class Ⅲ (2155 plants·hm-2≤SDI3<2459 plants·hm-2) and Class Ⅳ (SDI4≥2459 plants·hm-2) by using the quartile method. We constructed a dummy variable model and quantile regression model for the height-breast diameter of saplings of L. gmelinii with dummy variable method introduced SDI. The results showed that among the five selected representative non-linear tree height curve models, the Richards model fitted the best, with Ra2, RMSE and MAE of 0.7637, 0.8250 m and 0.5696 m. The dummy variable model including the SDI constructed based on the Richards model showed a 1.3% increase in Ra2 compared with the base model, while RMSE, MAE, and AIC decreased by 2.1%, 1.5%, and 11.2%, respectively. When the quantile τ was 0.5, Ra2 of quantile regression model was the maximum, and RMSE, MAE, AIC was the minimum, being 0.7612, 0.8294 m, 0.5657 m, and -767.19, respectively. Compared with SDI1, sapling height in SDI2-SDI4 was increased by 5.6%, 5.6%, and 11.3%, suggesting reasonable that regulation of stand density was conducive to increase the height growth of saplings in regeneration.
本研究以大兴安岭地区翠岗林场2018—2019年55块固定样地2054株兴安落叶松幼树为对象,采用四分位数法将林分密度指数(SDI)划分为4个等级,即等级Ⅰ(SDI1<1863株·hm-2)、等级Ⅱ(1863≤SDI2<2155株·hm-2)、等级Ⅲ(2155≤SDI3<2459株·hm-2)和等级Ⅳ(SDI4≥2459株·hm-2),并采用哑变量方法引入SDI构建兴安落叶松幼树树高-胸径的哑变量模型和分位数回归模型。结果表明: 选取的5个代表性非线性树高曲线模型中,Richards模型的拟合效果最好,其Ra2、RMSE、MAE分别为0.7637、0.8250 m、0.5696 m;基于Richards模型构建的包含SDI的哑变量模型,其Ra2较基础模型提高了1.3%,而RMSE、MAE、AIC分别降低了2.1%、1.5%和11.2%;当分位点τ=0.5时,分位数回归模型的Ra2最大,RMSE、MAE、AIC最小,分别为0.7612、0.8294 m、0.5657 m、-767.19。相较于SDI1,SDI2～SDI4林分内幼树的树高分别增加5.6%、5.6%和11.3%。因此,合理调控兴安落叶松林的林分密度有利于增加更新幼树的高生长。.
Keywords: diameter at breast height; dummy variable; quantile regression; stand density index; tree height.