东北林区10种主要森林类型的蓄积量、生物量和碳储量模型研建

【目的】林分水平的蓄积量、生物量和碳储量模型或数表,是开展森林资源规划设计调查的必备计量工具。研建东北林区10种主要森林类型的蓄积量、生物量和碳储量模型,既是方法学探索,也为生产实践提供参考成果。【方法】基于东北林区云冷杉林、落叶松林、红松林、樟子松林、栎树林、桦树林、杨树林、榆树林、椴树林和水胡黄林10种主要森林类型的2 000个样地的实测数据,分别利用非线性独立回归估计、非线性误差变量联立方程组和含哑变量的非线性误差变量联立方程组方法,建立了林分水平的蓄积量、生物量和碳储量模型。【结果】基于全部样地通过误差变量联立方程组方法建立的蓄积量、生物量和碳储量总体平均模型,其确定系数分别为0.945、0.805和0.839,而包含森林类型参数的蓄积量、生物量和碳储量哑变量模型,其确定系数分别达到0.959、0.949和0.951。10种主要森林类型的蓄积量、生物量和碳储量模型,确定系数(R2)都在0.86以上,平均预估误差(MPE)都在3%以内,平均百分标准误差(MPSE)大多数在10%以内。蓄积量模型的R2在0.876～0.980之间,MPE在0.90%～1.95%之间,MPSE在5.1...

Developing stand volume,biomass and carbon stock models for ten major forest types in forest region of northeastern China

[Objective]Stand-level volume,biomass and carbon stock models or tables are necessary quantitative tools for implementing forest management inventory.Developing stand volume,biomass and carbon stock models for ten major forest types in forest region of northeastern China is not only an exploration of methodology,but also provides reference results for practice.[Method]Based on the field measurement data of 2000 sample plots distributed in 10 forest types in northeastern China,i.e.spruce&fir(Picea spp.&Abies spp.),larch(Larix spp.),Mongolian scotch pine(Pinus sylvestris var.mongolica),Korean pine(Pinus koraiensis),oak(Quercus spp.),birch(Betula spp.),poplar(Populus spp.),elm(Ulmus spp.),linden(Tilia spp.),and other three precious broadleaved species(Fraxinus mandshurica,Juglans mandshurica&Phellodendron amurense),the stand-level volume,biomass and carbon stock models were developed through independent nonlinear regression(INR),simultaneous error-in-variable equations(SEIVE),and SEIVE with dummy variable modeling approach.[Result]The coefficients of determination(R2)of the population-averaged stand-level volume,biomass and carbon stock models based on all sample plots were 0.945,0.805 and 0.839,respectively;and those of tthe models with type-specific parameters were 0.959,0.949 and 0.951,respectively.The R2 values of stand-level volume,biomass and carbon stock models for 10 forest types were all more than 0.86,the mean prediction errors(MPE)were all less than 3%,and the mean percent standard errors(MPSE)were almost less than 10%.For the volume stock models,the R2 values were between 0.876-0.980,MPE were between 0.90%-1.95%,and MPSE were between 5.14%-11.89%;for the biomass stock models,the R2 values were between 0.864-0.988,MPE were between 0.66%-2.07%,and MPSE were between 3.61%-11.60%;and for carbon stock models,the R2 values were between 0.866-0.988,MPE were between 0.67%-1.96%,and MPSE were between 3.65%-11.57%.[Conclusion]The volume stock per hectare of different forest types mainly depends upon basal area and mean tree height of forest stands,and the biomass stock mainly relates to volume stock and mean tree height.The SEIVE with dummy variable modeling approach is a feasible method for developing stand-level stock models.The developed volume,biomass and carbon stock models for 10 major forest types in northeastern China in this study meet the need of precision requirements to the regulation on forest management inventory,indicating that the models can be applied in practice.