Construction of Compatibility Models for Aboveground Biomass of Individual Trees in Larix gmelinii var.principis-rupprechtii plantation

doi:10.13466/j.cnki.lczyyj.2024.06.015

Abstract

Abstract:

Based on the measured biomass data from 44 Larix gmelinii principis-rupprechtii trees in Sumushan Forest Farm of Inner Mongolia,different tree measurement factors were used to construct a single-tree independent basic model and a compatibility model under three methods(total direct control adjustment method,total direct control simultaneous equations method and algebraic sum control method).1)The determination coefficient of the optimal independent basic model and the compatibility model with DBH as the independent variable ranged from 0.766 to 0.943,the root mean square error(RMSE)was less than 20.030 kg,the total relative error was within±1.905%,and the absolute value of the average relative error was less than 16.905%.The prediction accuracy of each biomass model ranged from 93.7% to 95.6%.2)The determination coefficient of the optimal independent basic model,the compatibility model with DBH,and tree height as independent variables was from 0.767 to 0.985,the RMSE was less than 11.636 kg,the total relative error was less than 1.893%,and the absolute value of the average relative error was less than 16.823%.The prediction accuracy of each biomass model was 93.7%~97.9%.3)All models showed a good fitting effect,no significant systematic deviation,strong degree of fit with the sample points,and high prediction accuracy.4)All models could well predict the biomass of Larix gmelinii,var.principis-rupprechtii and the binary model was better than the unary model.The compatibility model could effectively solve the problem of incompatibility between the total aboveground biomass and the components of each organ,and the algebraic and control methods were better than the other two methods.Considering the modeling efficiency and accuracy,it is recommended to use the binary compatible biomass model of algebra and control method as the biomass prediction model of larch plantation in this area.

Key words: Larix gmelinii var.principis-rupprechtii, aboveground biomass, independent model, compatibility model, simultaneous equations

CLC Number:

S718.5

MA Yuan, WANG Zhibo, YE Dongmei, LIU Fengling. Construction of Compatibility Models for Aboveground Biomass of Individual Trees in Larix gmelinii var.principis-rupprechtii plantation[J]. Forest and Grassland Resources Research, 2024, (6): 129-139.

Figures/Tables 9

Tab.1

Tab.2

Tab.3

Compatibility model expressions of different modeling methods

方法	模型表达式	方法编号
总量直接控制平差法	W₂= $f 2 (x) f 2 (x) + f 3 (x) + f 3 (x)$ W'₁ W₃= $f 3 (x) f 2 (x) + f 3 (x) + f 3 (x)$ W'₁ W₄= $f 4 (x) f 2 (x) + f 3 (x) + f 3 (x)$ W'₁	Ⅰ
总量直接控制联立方程组法	$W 2 = f 2 (x) f 2 (x) + f 3 (x) + f 3 (x) W' 1 W 3 = f 3 (x) f 2 (x) + f 3 (x) + f 3 (x) W' 1 W 4 = f 4 (x) f 2 (x) + f 3 (x) + f 3 (x) W' 1$	Ⅱ
代数和控制法	$W 2 = f 2 (x) W 3 = f 3 (x) W 4 = f 4 (x) W 1 = f 2 (x) + f 3 (x) + f 4 (x)$	Ⅲ

Tab.3

Tab.4

Tab.5

Tab.6

Fig.1

Fig.2

Fig.3

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统计量	林龄/a	胸径/cm	树高/m	生物量/kg
统计量	林龄/a	胸径/cm	树高/m	树干	树枝	树叶	地上部分
平均值	34.977	19.476	14.326	103.703	27.353	5.984	103.703
标准差	9.610	4.768	3.798	68.135	14.113	2.313	68.135
最大值	49.000	29.730	22.910	294.892	62.267	10.914	294.892
最小值	16.000	10.670	7.650	18.607	5.884	1.850	18.607

模型类型	模型表达式	模型编号
一元	W=aD^b	1
一元	W=aH^b	2
二元	W=a(D²H)^b	3
二元	W=a(D^bH)^c	4

模型类型	部位	模型编号	参数			评价指标
模型类型	部位	模型编号	a	b	c	R²	RMSE/kg	TRE/%	MAPE/%	P/%
一元	树干	1	0.036 0	2.637 4		0.925	18.459	1.473	13.129	94.5
	树干	2	0.126 8	2.471 1		0.958	13.807	0.950	13.615	95.9
	树枝	1	0.052 2	2.082 0		0.862	5.179	1.606	16.470	94.1
	树叶	1	0.099 0	1.370 0		0.766	1.107	1.905	16.905	94.2
	地上	1	0.085 7	2.447 9		0.941	20.030	1.051	11.412	95.5
二元	树干	4	0.047 2	1.403 0	1.278 0	0.984	8.517	0.124	6.411	97.5
	树枝	4	0.052 5	2.055 5	0.027 4	0.862	5.183	1.596	16.453	94.1
	树叶	4	0.100 7	1.293 0	0.079 8	0.767	1.105	1.893	16.823	94.2
	地上	4	0.104 7	1.530 1	0.950 3	0.980	11.636	0.256	7.370	97.4

部位	方法编号	参数估计值		评价指标
部位	方法编号	a	b	R²	RMSE/kg	TRE/%	MAPE/%	P/%
树干	Ⅰ	0.039 6	2.632 0	0.924	18.530	1.188	13.107	94.2
	Ⅱ	0.041 8	2.615 4	0.924	18.580	1.310	13.113	93.9
	Ⅲ	0.033 4	2.666 7	0.927	18.216	-0.007	12.879	94.6
树枝	Ⅰ	0.070 3	2.012 1	0.863	5.170	0.613	16.240	93.9
	Ⅱ	0.066 4	2.033 5	0.863	5.165	0.229	16.265	93.7
	Ⅲ	0.065 3	2.013 9	0.863	5.160	0.001	16.341	94.2
树叶	Ⅰ	0.086 0	1.445 3	0.768	1.100	0.701	16.647	94.1
	Ⅱ	0.087 9	1.440 6	0.769	1.100	0.368	16.563	93.8
	Ⅲ	0.080 6	1.443 3	0.770	1.096	0.291	16.521	94.3
地上总量	Ⅰ	0.085 7	2.447 9	0.941	20.030	1.051	11.412	95.5
	Ⅱ	0.085 7	2.447 9	0.941	20.030	1.051	11.412	95.5
	Ⅲ			0.943	19.675	0.007	11.278	95.6

部位	方法编号	参数估计值			评价指标
部位	方法编号	a	b	c	R²	RMSE/kg	TRE/%	MAPE/%	P/%
树干	Ⅰ	0.060 5	1.235 4	1.405 5	0.984	8.449	0.178	6.503	97.3
	Ⅱ	0.057 8	1.321 8	1.318 6	0.984	8.523	0.192	6.471	97.6
	Ⅲ	0.056 1	1.215 3	1.424 1	0.985	8.184	0.016	6.507	97.9
树枝	Ⅰ	0.063 1	2.143 5	-0.101 8	0.863	5.161	0.450	16.369	93.7
	Ⅱ	0.059 5	2.109 2	-0.050 0	0.864	5.150	0.462	16.335	94.6
	Ⅲ	0.064 8	2.025 7	-0.010 3	0.863	5.160	0.002	16.346	95.0
树叶	Ⅰ	0.087 0	1.372 6	0.081 6	0.768	1.102	0.718	16.679	93.8
	Ⅱ	0.091 0	1.320 5	0.116 6	0.769	1.100	0.421	16.474	94.7
	Ⅲ	0.082 1	1.364 9	0.080 5	0.771	1.095	0.324	16.436	95.2
地上总量	Ⅰ	0.104 7	1.530 1	0.950 3	0.980	11.636	0.256	7.370	97.4
	Ⅱ	0.104 7	1.530 1	0.950 3	0.980	11.636	0.256	7.370	97.4
	Ⅲ				0.981	11.385	0.027	7.417	97.2