Research and Development of Compatible and Additive Individual Tree Biomass Model Systems for Eucalyptus

doi:10.13466/j.cnki.lyzygl.2023.01.011

Abstract

Abstract:

Eucalyptus is an important fast-growing tree species in southern China,which plays a significant role in ensuring national timber safety and enhancing forest carbon sequestration capacity.However,there are still no reliable tree biomass models for Eucalyptus.In this study,based on the data of above-ground biomass (including the components of stem wood,stem bark,branches and forages) from 183 sample trees and underground biomass from 124 sample trees of Eucalyptus spp.in Guangxi which was the key distribution region of Eucalyptus plantations in China,one- and two-variable biomass model systems with compatibility and additivity were developed using the new combined estimation technique integrating dummy variable modeling approach and error-in-variable simultaneous equations approach.The results showed that the determination coefficients (R²) of above- and underground biomass models were all more than 0.95,and the mean prediction errors (MPEs) were less than 3% and 6%,respectively.From the comparison of estimates resulted from 3 sets of above- and underground biomass models for Eucalyptus published before,it was found that only one set of the models could met the precision needs of relevant technical regulation,and other two sets of the models resulted in significant biased estimates,where the highest estimate error of underground biomass model had even more than 100% of relative error.The compatible and additive tree biomass models systems for Eucalyptus developed in this study would provide a basis for accurately estimating the biomass and carbon storage in Guangxi,even in the whole country.

Key words: above-ground biomass, underground biomass, simultaneous equations, error-in-variable, dummy variable, Eucalyptus

CLC Number:

S758.5

CAI Huide, LU Feng, XU Zhanyong, PAN Huangru, MENG Xiang, ZENG Weisheng. Research and Development of Compatible and Additive Individual Tree Biomass Model Systems for Eucalyptus[J]. FOREST RESOURCES WANAGEMENT, 2023, (1): 87-93.

Figures/Tables 4

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变量	平均值	最小值	最大值	标准差	变动系数
胸径(D)/cm	13.1	1.0	33.6	7.0	53.44
树高(H)/m	17.1	2.1	35.5	8.1	47.56
材积(V)/dm³	185.02	0.20	1438.50	227.25	122.83
地上生物量(M_a)/kg	109.44	0.18	874.54	134.68	123.07
干材生物量(M₁)/kg	85.90	0.09	742.59	110.28	128.39
干皮生物量(M₂)/kg	7.93	0.01	35.11	7.74	97.54
树枝生物量(M₃)/kg	11.22	0.05	90.54	16.59	147.82
树叶生物量(M₄)/kg	4.38	0.03	18.71	4.39	100.17
地下生物量(M_b)/kg	18.22	0.04	152.15	25.10	137.76
转换因子(BCF)/(kg/dm³)	0.6609	0.3640	2.0294	0.2158	32.65
根茎比(RSR)	0.1927	0.0111	0.4433	0.0731	37.95

参数	参数估计值
参数	一元模型	二元模型
a₀	0.12576	0.082784
a₁	2.46209	2.08311
a₂	/	0.48997
b₀	0.020214	0.028715
b₁	2.54746	3.12276
b₂	/	-0.64399
c₀	0.10040	0.060351
c₁	2.72924	2.04583
c₂	/	0.79805
f₀	0.46836	1.0278
f₁	-0.53619	0.40837
f₂	/	-1.1350
g₀	0.55316	1.6723
g₁	-0.49669	1.5980
g₂	/	-2.3324
h₀	1.5953	3.7115
h₁	-1.1759	0.37261
h₂	/	-1.7196

模型系统	检验方法	统计指标	目标变量
模型系统	检验方法	统计指标	M_a	M_b	V	M₁	M₂	M₃	M₄
一元模型	自检	R²	0.975	0.955	0.951	0.959	0.934	0.720	0.588
		SEE	21.29	5.39	50.53	22.47	2.00	8.83	2.83
		MPE/%	2.84	5.25	3.98	3.81	3.68	11.48	9.42
		TRE/%	1.98	0.94	-2.77	2.09	-1.78	4.82	-0.07
	5折交叉检验	R²	0.974	0.953	0.951	0.958	0.933	0.720	0.589
		SEE	21.69	5.49	50.55	22.85	2.01	8.83	3.44
		MPE/%	2.89	5.36	3.98	3.88	3.70	11.47	11.47
		TRE/%	1.95	0.75	-2.88	2.02	-1.80	4.92	0.15
二元模型	自检	R²	0.978	0.958	0.992	0.972	0.927	0.831	0.585
		SEE	19.97	5.18	21.03	18.76	2.11	6.89	2.85
		MPE/%	2.66	5.05	1.66	3.18	3.87	8.95	9.49
		TRE/%	1.31	-0.20	-1.42	1.04	-2.30	6.55	0.58
	5折交叉检验	R²	0.977	0.954	0.991	0.970	0.925	0.838	0.585
		SEE	20.42	5.43	21.24	19.35	2.14	6.73	2.85
		MPE/%	2.72	5.30	1.67	3.28	3.93	8.75	9.49
		TRE/%	1.37	-0.74	-1.45	1.15	-2.32	6.41	0.39

模型	目标变量	结构式	相对误差/%
1	地上生物量地下生物量	M_a=0.1746D^2.333 M_b=0.0599D^2.16	-7.04 -4.17
2	地上生物量地下生物量	M_a=0.05884D^2.301H^0.3521 M_b=0.005656(D²H)^0.939	-13.38 -24.79
3	地上生物量地下生物量	M_a=0.044D^1.891H^1.014/(1+0.027D^-0.552H^1.353) M_b=0.044D^1.891H^1.014/[1+1/(0.027D^-0.552H^1.353)]	12.37 114.56