思茅松林树高与土壤因子关系的估测模型研究

Tree Height Prediction Model Based on the Correlation of Height of Pinus kesiya var. langbianensis and Soil Factors

应用逐步回归分析,建立思茅松3代林分高生长与土壤因子关系的估测模型.结果为:原始林林分的回归模型为Y=0.141519X1+0.040696X5-0.04748X6+91.40769;第2代林林分的回归模型为Y=0.0392409X1+0.010129X5-0.04748X6+83.80179;人工林林分的回归模型为Y=0.23225X1+0.006735X5-0.00658X6+3.60846.思茅松高生长与土层厚度(X5)具有紧密的相关关系;其次是海拔高度(X6)和有效N的含量(X1),林分树高生长与海拔呈负相关关系.该模型可作为3代相应林龄的思茅松高生长的估测模型,可对思茅松林立地退化进行评价.思茅松轮栽后,立地生产力是先衰退后增强.

Tree height prediction models were set up based on successive regression analyses on the correlation of plant height in 3 types of Pinus kesiya var. langbianensis forests and the soil factors. The height prediction model for the primitive forest of Pinus kesiya var. langbianensis was as： Y = 0. 141 519 X1＋ 0.040 696X5 - 0.047 48X6 ＋91.407 69; the model for the 2^nd generation of Pinus kesiya var. langbianensis forest was： Y = 0.039 240 9X1＋0.010 129 X5 - 0.047 48X6 ＋ 83.801 79; and the model for the artificial plantation of Pinus kesiya var. langbianensis was as： Y = 0.232 25 X1 ＋ 0.006 735X5 - 0.006 58X6 ＋ 3.608 46. It was found out that the soil depth （X6） was closely correlated to height growth of Pinus kesiya var. langbianensis trees （dependability = 99%）; and the altitude （X6）and effective N content（ X1 ）were also closely correlated to the tree height （dependability = 95% ）. The altitude was negatively correlated to height growth of Pinus kesiya var. langbianensis trees. Except for the tree height prediction, these models might also be used to evaluate the site degradation for Pinus kesiya var. langbianensis stands. It was showed by the study that the productivity of rotationally planted Pinus kesiya var. langbianensis forests dropped at the beginning and increased afterwards.