Establishment of Biomass Density Model of Spruce in Tibet

doi:10.13466/j.cnki.lyzygl.2018.01.006

Abstract

Abstract:

Biomass density models are the basis for estimating biomass and carbon stocks.Taking spruce of the main coniferous forest species in Tibet as research object,the spruce forest biomass density models were established by using measured sample plot and sample tree data of continuous forest resources inventory.The results showed that biomass density increased with the increase of tree height,canopy closure,DBH and forestage,and decreased with the increase of altitude and longitude.The determination coefficient of biomass density nonlinear model is 0.716,the total relative error and the average system error are controlled within±1%,and the estimated accuracy is 91.9%.Since the model is constructed with altitude,canopy closure,mean diameter at breast height and longitude as explanatory variables,it can be applied to the measured or visual sample or small class biomass estimation.The determination coefficient of biomass density nonlinear model is 0.626,the total relative error and the average system error are controlled within ±2%,and the estimated accuracy is 90.6%.Since the model is constructed with elevation,canopy closure,forest age and longitude as explanatory variables,which can be applied to remote sensing sample or small class biomass estimation.The determination coefficient of biomass density nonlinear model is 0.717,the total relative error and the average system error are controlled within ±2%,and the estimated accuracy is 91.9%.Since the model is constructed with elevation,canopy closure,mean diameter at breast height and forest age as explanatory variables,it can be applied to estimate the biomass or carbon sinks of spruce forest in a given period.Combined with the data of continuous forest resources inventory or forest resources planning and design in Tibet,it can be used for estimating the biomass of the spruce forest on the scale of the whole region.The biomass model established by the factors such as age can be used for grasping the biomass and carbon sink distribution law,and carbon sink estimates for a certain period.

Key words: spruce, biomass, carbon sink, biomass density, forest age

CLC Number:

S718.55

LIU Jinshan, ZHANG Bei, ZHOU Xuewu, XING Yuanjun, ZHANG Wanlin. Establishment of Biomass Density Model of Spruce in Tibet[J]. FOREST RESOURCES WANAGEMENT, 2018, 0(1): 38-43.

Figures/Tables 2

References 28

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拟合公式	统计指标
拟合公式	R²	SEE/(t/hm²)	TRE/%	MSE/%	MPE/%	MPSE/%
(1)B=136.222+10.128h-0.063H+2.019p	0.625	73.3	-0.44	8.1	9.3	70.5
(2)B=107.843+5.505h-0.061H+2.419p+2.420D	0.671	69.0	0.90	6.6	8.7	61.7
(3)B=998.524-0.058H+2.874p+4.124D-9.150Lo	0.655	70.7	0.00	3.9	8.9	64.6
(4)B=113.854-0.059H+3.000p+4.047D	0.634	72.4	-0.06	3.2	9.2	51.2
(5)B=3.171×10¹⁰×H^-0.900×p^0.909×D^0.935×Lo^-4.035	0.716	64.2	-0.64	-0.5	8.1	37.3
(6)B=284.575×H^-0.896×p^0.937×D^0.909	0.697	65.9	-0.55	-0.8	8.3	38.6
(7)B=107.902×H^-0.943×p^1.063×D^0.758×a^0.297	0.717	64.0	0.54	1.2	8.1	38.2

拟合公式	统计指标
拟合公式	R²	SEE/(t/hm²)	TRE/%	MSE/%	MPE/%	MPSE/%
(8)B=951.369+1.030a-0.064H+2.881p-8.111Lo	0.557	79.7	-1.1	3.6	10.2	61.6
(9)B=165.342+1.019a-0.065H+2.972p	0.542	80.7	0.5	-8.1	10.4	47.3
(10)B=6.444×10⁹×a^0.812×H^-1.379×p^1.073×Lo^-3.080	0.626	73.2	0.5	-1.8	9.4	44.2
(11)B=4232.431×a^0.814×H^-1.373×p^1.100	0.616	73.9	-0.1	-1.7	9.5	44.9