西伯利亚落叶松天然林立木生物量估算模型研究

Research on Natural Larix sibirica Buck Biomass Estimation Model in Xinjiang

【目的】构建西伯利亚落叶松地上、地下及各组分器官的生物量估测模型。【方法】基于54株伐倒样木实测数据,运用相关回归分析方法,构建西伯利亚落叶松各组分生物量估测模型,并对比分析各种模型估测精度。【结果】以胸径、树高构建的落叶松各组分二元估测模型优于一元模型,其中地上、树干、树冠和树枝生物量预估精度提高了2.84%~5.00%,而树叶和地下生物量仅提高了0.33%和0.15%。落叶松树干生物量和地上总生物量最优估测模型为W=a D^bH^c、树冠和树枝生物量最优模型为W=a(D^3/H)~b、树叶生物量最优模型为W=a D^b;其中地上总生物量预估精度最高,达96.38%;树叶生物量预估最低,为84.07%;地下生物量以实测数据直接建模法与根茎比建模法对比,根茎比建模法预估精度高,其最优模型精度为90.50%。【结论】研究确定西伯利亚落叶松天然立木单株各组分生物量的最优估测模型,根据现地实测数据,可进行立木生物量估测,但人工落叶松立木生物量和天然落叶松不同林分的生物量估测还有待进一步研究。

[ Objective ] The study aims to construct the natural Lar/x sibirica biomass estimation model of the ground, underground and organ of components in Xinjiang. [Method] Based on the measured data of 54 strains cut down sample wood, using regression analysis method to build the biomass estimation model, and a- nalysis of all kinds of model estimation precision. [ Results ] The results showed that： DBH and tree height building binary estimation model of components of larch was better than a Meta model, thereinto the ground, tree trunks, canopy and branch biomass forecast precision was increased by 2.84% - 5.0%, but the leaves and underground biomass only increased by 0.33% and 0.15%. The optimal biomass models for predicting of L. sibirica ground and trunk was W = aDbI~, canopy and biomass branches optimal model was W = （D3/H）b, leaves and underground biomass optimal model was W = aDb. The aboveground biomass forecast precision was the highest, reaching 96.38% ; Leaves biomass estimate was the lowest, 84.07%. Underground biomass direct modeling method with experimental data and compared with root - shoot ratio modeling method, forecast precision of root- shoot ratio model was higher; the optimal model accuracy was 90.50%. [ Conclusion]The research identified natural L. sibirica optimal estimation model of each component biomass per plant, and ac- cording to the in situ measured data, the buck biomass can be estimated.