结构方程模型在兴安落叶松林生长中的应用

doi:10.12302/j.issn.1000-2006.202104028

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南京林业大学学报（自然科学版） ›› 2023, Vol. 47 ›› Issue (1): 38-46.doi: 10.12302/j.issn.1000-2006.202104028

所属专题：智慧林业之森林参数遥感估测

• 专题报道Ⅰ:智慧林业之森林参数遥感估测 • 上一篇下一篇

结构方程模型在兴安落叶松林生长中的应用

高羽(), 李静, 刘洋(), 乌雅瀚, 巩家星, 辛启睿

内蒙古农业大学林学院,内蒙古呼和浩特 010019

收稿日期:2021-04-17 接受日期:2022-03-22 出版日期:2023-01-30 发布日期:2023-02-01
通讯作者: 刘洋
基金资助:
国家自然科学基金项目(32160363);内蒙古自治区自然科学基金项目(2021MS03096)

Application of structural equation model in growth of Larix gmelinii stand

GAO Yu(), LI Jing, LIU Yang(), WU Yahan, GONG Jiaxing, XIN Qirui

College of Forestry, Inner Mongolia Agricultural University, Hohhot 010019, China

Received:2021-04-17 Accepted:2022-03-22 Online:2023-01-30 Published:2023-02-01
Contact: LIU Yang

摘要/Abstract

摘要： 【目的】 通过结构方程模型,确定气候、土壤和海拔对兴安落叶松林生长指标的影响以及路径关系。【方法】 选取年平均气温、年平均降水量、太阳辐射、土壤全氮含量、土壤有机碳密度和海拔作为影响因素,探究兴安落叶松地上生物量、地下生物量、树高与这些影响因素的关系,并利用AMOS 21.0软件构建衡量兴安落叶松生长的3个指标与气候、土壤和海拔的结构方程模型。【结果】 兴安落叶松的地上生物量、地下生物量随着海拔、年平均降水量的增大呈现先增大后减少的趋势,树高随着海拔的增加而增加。地上和地下生物量随着土壤有机碳密度的增加而增加。海拔对兴安落叶松生长的总效应系数为0.200且是正向效应,海拔对兴安落叶松生长的直接效应(0.224)大于间接效应(-0.024);气候因子对兴安落叶松林生长的总影响系数为-0.771且是负向效应;土壤因子对兴安落叶松生长的总影响系数为-0.216,其对兴安落叶松林生长起到一定的抑制作用。【结论】 根据结构方程模型的路径系数,气候因子的总影响系数绝对值最大,其次是土壤和海拔,兴安落叶松林静态生长主要受到气候因子的制约。

关键词: 兴安落叶松, 影响系数, 气候因子, 土壤因子, 海拔, 地上和地下生物量, 树高, 结构方程模型

Abstract:

【Objective】 Structural equation modelling (SEM) was used to determine the effects of climate, soil, and altitude on growth indicators and pathway relationships in Xing’an larch (Larix gmelinii) forests. 【Method】 The annual mean temperature, annual mean precipitation, solar radiation, soil total nitrogen content, soil organic carbon density, and altitude were selected as influencing factors to explore the relationships between aboveground biomass, underground biomass, and tree height and these underlying factors. A structural equation model of climate, soil, and altitude was constructed using AMOS 21.0 software to measure the growth of Larix gmelinii stand. 【Result】 The aboveground and underground biomass of Larix gmelinii first increased and then decreased with an increase in altitude and annual mean precipitation, and the tree height increased with increasing altitude. The aboveground and underground biomass increased with an increase in soil organic carbon density. The total effect coefficient of altitude on the growth of Larix gmelinii was positive (0.200), and the direct effect (0.224) of altitude on the growth of Larix gmelinii was greater than the indirect effect (-0.024). The total effect coefficient of the climatic factors on the growth of Larix gmelinii was negative, at -0.771. The total influence coefficient of soil factors on the growth of Larix gmelinii was -0.216, which means these factors can slightly inhibit the growth of Larix gmelinii. 【Conclusion】 According to the path coefficient of the structural equation model, the absolute value of the total influence coefficient of climate factors was the largest, followed by that of soil and altitude. The static growth of Larix gmelinii forest is mainly restricted by climatic factors, which has guiding significance for predicting and evaluating changes in forest growth at high latitudes under the condition of global climate change.

Key words: Larix gmelinii, influence coefficient, climate factor, soil factor, elevation, aboveground and belowground biomass, tree height, structural equation model

中图分类号:

S791.22

高羽,李静,刘洋,等. 结构方程模型在兴安落叶松林生长中的应用[J]. 南京林业大学学报（自然科学版）, 2023, 47(1): 38-46.

GAO Yu, LI Jing, LIU Yang, WU Yahan, GONG Jiaxing, XIN Qirui. Application of structural equation model in growth of Larix gmelinii stand[J].Journal of Nanjing Forestry University (Natural Science Edition), 2023, 47(1): 38-46.DOI: 10.12302/j.issn.1000-2006.202104028.

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统计值 statistics	地形因子 topographic factor
统计值 statistics	海拔/m altitude	坡度/ (°) slope	SR/ (kJ·m^-2· d^-1)	MAT/ ℃	MAP/ mm	SOCD/ (Mg· hm^-2)	STNC/ (g·kg^-1)	CMF/%	d_o/cm	树高/m tree height	AGB/ (Mg· hm^-2)	BGB/ (Mg· hm^-2)	树龄/a tree age	疏密度 stocking degree
最小值min	233.40	1.00	19 046	-0.57	563.02	70.26	2.68	6.00	20.00	10.00	0.26	1.36	7.00	0.08
最大值max	1 087.70	26.00	20 569	6.57	973.03	269.14	21.50	28.00	150.00	29.00	369.10	106.00	201.00	0.65
平均值mean	587.59	9.41	19 839.19	2.79	752.01	156.55	11.01	22.41	58.42	21.56	140.52	31.62	26.00	0.26
标准差SD	212.15	6.90	441.67	2.74	122.14	60.29	5.06	4.64	23.09	4.51	79.56	21.64	32.00	0.12

评价指标 index	参数名称 parameter name	评价标准 evaluation criteria standard	模型参数 model parameters
绝对拟合指数 absolute fitting index	卡方自由度比(x²/df)	<3	1.513
	适配度指数(GFI)	>0.90	0.971
	显著性概率值(P)	>0.05	0.097
	近似误差均方根 (RMSEA)	<0.08	0.056
相对拟合指数 relative fitting index	规准适配指数(NFI)	>0.90	0.983
	非规准适配指数(TLI)		0.985
	比较适配指数(CFI)		0.994
	增值适配指数(IFI)		0.994

结构方程模型在兴安落叶松林生长中的应用

Application of structural equation model in growth of Larix gmelinii stand

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