基于林分及地形因子的落叶松人工林林分生物量模型构建

doi:10.12302/j.issn.1000-2006.202110024

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南京林业大学学报（自然科学版） ›› 2023, Vol. 47 ›› Issue (3): 129-136.doi: 10.12302/j.issn.1000-2006.202110024

基于林分及地形因子的落叶松人工林林分生物量模型构建

孙宇(), 李凤日, 谢龙飞, 董利虎()

东北林业大学林学院,黑龙江哈尔滨 150040

收稿日期:2021-10-12 接受日期:2022-01-07 出版日期:2023-05-30 发布日期:2023-05-25
通讯作者: 董利虎
基金资助:
国家自然科学基金项目(31971649);中央高校基本科研业务费专项资金项目(2572020DR03);黑龙江头雁创新团队计划项目(森林资源高效培育技术研发团队)

Construction of the stand-level biomass model of Larix olgensis plantations based on stand and topographic factors

SUN Yu(), LI Fengri, XIE Longfei, DONG Lihu()

College of Forestry, Northeast Forestry University, Harbin 150040, China

Received:2021-10-12 Accepted:2022-01-07 Online:2023-05-30 Published:2023-05-25
Contact: DONG Lihu

摘要/Abstract

摘要：

【目的】落叶松在我国东北地区广泛分布,是重要的造林和用材树种,具有生长速度快、耐寒等优点。为了准确地估算落叶松人工林林分生物量,构建了落叶松林分可加性生物量模型。【方法】以落叶松人工林为研究对象,基于黑龙江省的304块人工落叶松固定样地数据,采用非线性似乎不相关回归的方法建立了可加性生物量模型系统,使用留一交叉验证法对建立的模型进行检验。【结果】林分断面积和林分平均高对树干、树枝、树叶和树根生物量模型有显著影响,林龄和海拔也显著影响林分树干、树叶、树根生物量;坡率和坡向对树枝生物量有显著影响。树叶生物量与林分平均高、林龄和海拔呈显著负相关,树干与树根生物量则与之呈显著正相关,树枝生物量与林分平均高呈显著正相关。在所建立的可加性生物量模型中,调整后决定系数( $R a d j 2$ )均在0.94以上,均方根误差(RMSE)较小。检验指标平均误差(MPE)和平均误差百分比(MPE%)均接近0,拟合指数(I_F)均大于0.93,平均绝对误差(MAE)较小,且平均绝对误差百分比(MAE%)均小于11%。【结论】建立的落叶松人工林可加性生物量模型的拟合与预测效果均较好,可以进行黑龙江省林分尺度的落叶松人工林生物量预测。

关键词: 落叶松人工林, 林分生物量, 地形因子, 似乎不相关回归, 异方差, 可加性模型

Abstract:

【Objective】Larix olgensis is widely distributed in northeastern China and it is considered to be an important afforestation and timber species with advantages like the rapid growth and cold tolerance. To accurately estimate the biomass of larch plantations, an additive system of biomass equations for larch plantations was established. 【Method】This study investigated larch plantations using the forestry inventory data of 304 larch plantations in Heilongjiang Province. An additive system of biomass equations was established using the method of non-linear and seemingly uncorrelated regression and employed a leave-one-out cross method for the model validation. 【Result】The stand basal area and stand mean tree height had a significant effect on the stem, branch, foliage and root biomass, the stand age and elevation also significantly affect the stem, foliage and root biomass. The branch rate and aspect had a significant effect on branch biomass. Foliage biomass was negatively correlated with stand mean tree height, stand age and elevation, whereas stem and root biomasses were positively correlated with the explanatory variables, and branch biomass was positively correlated with stand mean tree height. In terms of the additive system of the biomass equation, the adjusted coefficients of determination ( $R a d j 2$ ) were greater than 0.94, and the root mean square error (RMSE) was small. The average bias (MPE) and average bias percentage (MPE%) were both close to 0, the fit indices were all greater than 0.93, the average absolute bias (MAE) was small, and the average absolute bias percentage (MAE%) was less than 11%. 【Conclusion】The additive biomass model of larch plantations established in this study is effective for fitting and prediction, and can be used to predict the stand-level biomass of larch plantations in Heilongjiang Province.

Key words: larch (Larix olgensis) plantation, stand-level biomass, topographic factor, seemingly uncorrelated regression, regression heteroscedasticity, additive equation

中图分类号:

S758

孙宇,李凤日,谢龙飞,等. 基于林分及地形因子的落叶松人工林林分生物量模型构建[J]. 南京林业大学学报（自然科学版）, 2023, 47(3): 129-136.

SUN Yu, LI Fengri, XIE Longfei, DONG Lihu. Construction of the stand-level biomass model of Larix olgensis plantations based on stand and topographic factors[J].Journal of Nanjing Forestry University (Natural Science Edition), 2023, 47(3): 129-136.DOI: 10.12302/j.issn.1000-2006.202110024.

图/表 6

表1

表2

加入地形因子与未加入地形因子林分生物量模型拟合指标对比"

拟合指标 fitting index	树干生物量模型 stem biomass model		树枝生物量模型 branch biomass model		树叶生物量模型 foliage biomass model		树根生物量模型 root biomass model
拟合指标 fitting index	A	B	A	B	A	B	A	B
$R a d j 2$	0.961 4	0.963 9	0.945 9	0.948 9	0.943 1	0.947 9	0.952 9	0.956 0
RMSE	6.130 0	5.930 0	0.826 7	0.803 9	0.271 7	0.267 5	2.055 4	1.986 2

表2

表3

落叶松人工林林分可加性生物量模型系统拟合结果"

各组分 component	估计值(标准误) estimate(SE)					$R a d j 2$	RMSE	权函数系数 weighted function coefficient
各组分 component	$β i 0$	$β i 1$	$β i 2$	$β i 3$	$β i 4$	$R a d j 2$	RMSE	权函数系数 weighted function coefficient
树干 stem	-0.818 1 (0.077 8)	0.009 2 (0.000 8)	0.600 8 (0.029 4)	0.980 5 (0.012 2)	0.040 2 (0.011 9)	0.962 2	6.060 4	1.404 0
树枝 branch	-1.301 4 (0.031 2)	0.167 8 (0.017 7)	1.014 6 (0.009 11)	-0.053 5 (0.015 8)		0.947 7	0.813 5	2.194 1
树叶 foliage	-0.198 8 (0.074 9)	-0.007 3 (0.000 7)	-0.483 9 (0.029 1)	1.023 2 (0.012 7)	-0.032 2 (0.011 2)	0.941 4	0.275 8	1.075 5
树根 root	-2.716 7 (0.086 8)	0.697 3 (0.037 7)	0.960 1 (0.015 4)	0.220 4 (0.025 2)	0.044 8 (0.014 6)	0.952 5	2.060 2	1.498 8
总量total						0.967 4	8.073 4	1.245 3

表3

图1

表4

表5

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统计项 statistic item	指标 index	样本数 sample size	最小值 min	最大值 max	均值 mean	标准差 standard deviation
林分因子 stand factor	林分平均高/m stand mean tree height	304	5.00	22.80	12.61	3.96
	林分断面积/(m²·hm^-2) stand basal area	304	1.43	30.86	14.36	7.19
	林龄/a stand age	304	6.00	54.00	28.00	11.00
地形因子 topographic factor	海拔/m altitude	304	56.00	640.00	313.50	117.23
	坡向/(°) aspect	304	0.00	315.00	151.73	102.56
	坡度/(°) slope	304	0.00	27.00	6.47	5.07
	坡率值slope rate	304	0.00	0.51	0.11	0.09
	SLS	304	-0.40	0.40	-0.01	0.10
	SLC	304	-0.49	0.34	-0.05	0.11
各器官生物量 biomass of stand organs	林分树干生物量/(Mg·hm^-2) stand stem biomass	304	2.51	162.40	48.61	31.19
	林分树枝生物量/(Mg·hm^-2) stand branch biomass	304	0.54	16.71	6.35	3.56
	林分树叶生物量/(Mg·hm^-2) stand foliage biomass	304	0.39	5.85	2.44	1.14
	林分树根生物量/(Mg·hm^-2) stand root biomass	304	0.68	50.22	14.43	9.45
	林分总生物量/(Mg·hm^-2) stand total biomass	304	4.12	230.96	71.83	44.70

生物量 biomass	树干 stem	树枝 branch	树叶 foliage	树根 root	总量 total
树干stem	1
树枝branch	0.21	1
树叶foliage	-0.82	0.07	1
树根root	0.91	0.20	-0.83	1
总量total	0.99	0.31	-0.78	0.93	1

生物量 biomass	MAE/ (Mg·hm^-2)	MAE%	MPE/ (Mg·hm^-2)	MPE%	I_F
树干stem	4.071 1	9.316 7	-0.010 1	-0.020 7	0.961 1
树枝branch	0.449 2	5.935 7	0.039 2	0.616 7	0.946 9
树叶foliage	0.204 1	9.103 8	0.000 5	0.020 0	0.939 7
树根root	1.387 6	10.922 5	0.004 3	0.029 6	0.951 1
总量total	5.383 7	7.986 6	0.033 8	0.047 1	0.966 6

基于林分及地形因子的落叶松人工林林分生物量模型构建

Construction of the stand-level biomass model of Larix olgensis plantations based on stand and topographic factors

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