【摘要】 TRIPLEX模型是一种新兴混合模型,提供了一种整合目前模型并能有效解决所面临问题的观念和方法。本文以浙江省21个县4种主要林型(常绿阔叶林、针阔混交林、马尾松林和杉木林)、林龄5~50 a的147个样地森林生长和产量调查实测作为模型模拟和检验的数据,用TRIPLEX模型模拟和检验了样地的林分密度、树高、胸径、凋落物库、地上和总生物量,结果表明:4种主要林型的林地生长和产量模拟值和野外实测值的相关系数极高(p<0.001),两者之间的偏差也较小;各个林型的地上及总生物量的模拟值和实测值相关性均极高(p<0.001),决定系数r2均以马尾松林的最高(分别为0.95和0.94),以杉木林的最低;除杉木林外,常绿阔叶林、针阔混交林和马尾松林的地上及总生物量对于温度增长均是负相关,4种主要林型的地上及总生物量对于相对湿度增长均是正相关,对于降水量变化不相关。TRIPLEX模型最小化了输入参数,对于参数要求低,但未降低预测能力,而且能够在浙江省复杂气候和土壤条件下预测地上和总生物量。更多还原

【Abstract】 Inventory data of growth and yield from 147 sample plots aged from 5 to 50 years of four common forest types in 21 counties of Zhejiang province was used to test the process-based model of TRIPLEX. The four main forest types are evergreen broad-leaved forest(EF), coniferous and broad-leaved mixed forest(MF), Pinus massoniana forest(PF) and Cunninghamia lanceolatae forest(CF). Simulation values by TRIPLEX model with stand density, diameter at breast height(DBH), height(H), litterfall pool, aboveground and total biomass were compared with measured ones. The results showed that significant correlation(p<0.001) between the simulated and measured values of forest stands for four main forest types in Zhejiang province was found and the coefficients of determination(r2) was 0.92 for density, 0.77 for DBH, 0.80 for H, 0.53 for litterfall pool, 0.92 for aboveground biomass and 0.91 for total biomass, with small errors of-0.32 for DBH,-0.59 for H, 1.15 for litterfall pool,-0.51 for the aboveground biomass and-2.64 for the total biomass, except for stand density(53.56), and low biases(2.7% for density,-3.3% for DBH,-8.6% for H,-1.0% for the aboveground biomass and-1.5% for the total biomass) except for litterfall pool(16.8%). The simulated and measured values had significant correlation(p<0.001) for the aboveground and total biomass for each forest type, PF had highest coefficient of determination within 0.95 and 0.94 respectively, and CF had lowest coefficient of determination. For the four main forest types, Aboveground and total biomass of tested forest types had negative correlation with temperature except CF, and positive relation with relative humidity, and no correlation with precipitation. Simulated values of biomass and NPP of four forest types in Zhejiang by TRIPLEX model were much closer to the surveyed ones than those by the CEVSA and CASA models. These results suggest that TRIPLEX model did not decrease the predictive accuracy at the low demand for parameters, which can simulate and predict biomass with complex conditions in climate and soil.更多还原