长白落叶松人工林单木和林分水平的相容性生物量模型研究

Compatible Biomass Models for Larix olgensis Plantation Based on Tree-Level and Stand-Level

[目的]构建落叶松人工林单木和林分水平的相容性生物量模型,使之既在数据采集区域内能够表征不同水平下的差异程度,又具有较强的通用性。[方法]基于64株长白落叶松人工林样木生物量实测数据和40个每木检尺样地数据,在考虑和未考虑林龄2种情形下,利用哑变量和非线性似然无关回归方法相结合,构建单木和林分水平的一元相容性生物量模型。[结果]表明:(1)地上及全株生物量模型单木水平下的 R^ 2 adj 均大于0.95,林分水平下的 R ^2 adj 均大于0.78,(2)利用哑变量考虑林龄因素后,单木水平下各评价指标总体稳定,参数 b 值范围从0.905 5-2.512 5减小为1.047 0-2.202 8。林分水平下 R^2提升0.201 9,参数 b 值范围从0.071 1-1.560 7减小为0.781 1-1.055 1;且具有更小的 TRE、MPE和MSE 。(3)利用对数转换的线性回归模型,全株及各组分生物量模型残差的分布趋势均平行于横轴。[结论]非线性似然无关回归和哑变量相结合的方法灵活、建模过程简单、模型稳定性好,适用于不同因素下落叶松人工林相容性生物量模型构建。林龄因素对林分模型拟合效果的改善更显著,在建模过程中,单木模型可以不考虑林龄的影响,而林分模型需要考虑林龄的影响。

[Objective]Compatible models for the single tree biomass and stand biomass of Larix olgensis were established to represent different levels of variations and to improve generalization capability of models.[Method] Based on the biomass data of 64 trees in 40 sample plots of L. olgensis plantation, the compatible models were established by combining dummy variable and nonlinear seemingly unrelated regression under the conditions of considering or not considering stand age.[Result](1) The models have good estimation precision with R^2 adj >0.95 and R^2 adj >0.78 for single tree biomass and stand biomass, respectively.(2) Under the consideration of stand age with dummy variable, the fitting goodness of model is improved with smaller TRE, MPE and MSE , the evaluation statistics are stable overall and the range of parameter b reduces form 0.905 5-2.512 5 to 1.047 0-2.202 8 for single level and R 2 adj increases by 0.201 9 and the range of parameter b reduces form 0.071 1- 1.560 7 to 0.781 1-1.055 1 for stand level.(3) Using the linear regression model of logarithmic transformation, the distribution trends of model residual error of the whole plant and its components are parallel to the transverse axis.[Conclusion] The method of combing dummy variable and nonlinear seemingly unrelated regression is flexible, simple and applicable to the establishment of single tree biomass and stand biomass models. The fitting goodness of biomass model is improved with the consideration of stand age, especially in stand biomass model. Thus, the influence of stand age should be considered in the process of stand biomass modeling.