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

国家林草科技领军期刊
中国精品科技期刊
中国高校百佳科技期刊
江苏省新闻出版政府奖期刊奖
RCCSE林学权威期刊（A+）
CSCD核心期刊
Scopus数据库收录期刊
中文核心期刊
SCD核心期刊

作者加群：102861116

微信公众号：南京林业大学学报

高级检索

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
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

1. 结构方程模型在兴安落叶松林生长中的应用——补充材料.zip(2210KB)

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.

图/表 7

表1

图1

图2

图3

表2

图4

图5

参考文献 30

[1]	程开明. 结构方程模型的特点及应用[J]. 统计与决策, 2006(10):22-25.
	CHENG K M. Characteristics and application of structural equation model[J]. Stat Decis, 2006(10):22-25.DOI:10.3969/j.issn.1002-6487.2006.10.008. doi: 10.3969/j.issn.1002-6487.2006.10.008
[2]	张娅, 孙舒蕊, 张文会, 等. 基于结构方程模型的居住区停车泊位共享意愿研究[J]. 森林工程, 2021, 37(6): 143-150, 158.
	ZHANG Y, SUN S R, ZHANG W H, et al. Parking space sharing willingness research in a residential area based on structural equation model[J]. Forest Engineering, 2021, 37(6): 143-150, 158.DOI:10.16270/j.cnki.slgc.2021.06.016. doi: 10.16270/j.cnki.slgc.2021.06.016
[3]	舒树淼, 赵洋毅, 段旭, 等. 基于结构方程模型的云南松次生林林木多样性影响因子[J]. 东北林业大学学报, 2015, 43(10):63-67.
	SHU S M, ZHAO Y Y, DUAN X, et al. Impact factors of forest diversity in Yunnan pine secondary forest based on structural equation model[J]. J Northeast For Univ, 2015, 43(10):63-67.DOI:10.13759/j.cnki.dlxb.2015.10.007. doi: 10.13759/j.cnki.dlxb.2015.10.007
[4]	楚春晖, 佘济云, 陈冬洋, 等. 大围山杉木林林分生长与影响因子耦合分析[J]. 西南林业大学学报, 2016, 36(2):108-112.
	CHU C H, SHE J Y, CHEN D Y, et al. Coupling analysis of growth and influencing factors of Cunninghamia lanceolata[J]. J Southwest For Univ, 2016, 36(2):108-112.DOI:10.11929/j.issn.2095-1914.2016.02.018. doi: 10.11929/j.issn.2095-1914.2016.02.018
[5]	黄兴召, 许崇华, 徐俊, 等. 利用结构方程解析杉木林生产力与环境因子及林分因子的关系[J]. 生态学报, 2017, 37(7):2274-2281.
	HUANG X Z, XU C H, XU J, et al. Structural equation model analysis of the relationship between environmental and stand factors and net primary productivity in Cunninghamia lanceolata forests[J]. Acta Ecol Sin, 2017, 37(7):2274-2281.DOI:10.5846/stxb201512132482. doi: 10.5846/stxb201512132482
[6]	王冬至, 张志东, 牟洪香, 等. 结构方程模型在落叶松林经营中的应用[J]. 北京林业大学学报, 2015, 37(3):69-75.
	WANG D Z, ZHANG Z D, MU H X, et al. Applications of structural equation model in the management of Larix principis-rupprechtii plantations[J]. J Beijing For Univ, 2015, 37(3):69-75.DOI:10.13332/j.1000-1522.20140326. doi: 10.13332/j.1000-1522.20140326
[7]	KANG M Y, DAI C, JI W Y, et al. Biomass and its allocation in relation to temperature,precipitation,and soil nutrients in Inner Mongolia grasslands,China[J]. PLoS One, 2013, 8(7):e69561.DOI:10.1371/journal.pone.0069561. doi: 10.1371/journal.pone.0069561
[8]	SHA Z Y, XIE Y C, TAN X C, et al. Assessing the impacts of human activities and climate variations on grassland productivity by partial least squares structural equation modeling(PLS-SEM)[J]. J Arid Land, 2017, 9(4):473-488. doi: 10.1007/s40333-017-0022-6
[9]	ZHONG Q M, ZHANG S R, CHEN H L, et al. The influence of climate,topography,parent material and vegetation on soil nitrogen fractions[J]. CATENA, 2019, 175:329-338.DOI:10.1016/j.catena.2018.12.027. doi: 10.1016/j.catena.2018.12.027
[10]	DAI L J, GE J S, WANG L Q, et al. Influence of soil properties,topography,and land cover on soil organic carbon and total nitrogen concentration:a case study in Qinghai-Tibet Plateau based on random forest regression and structural equation modeling[J]. Sci Total Environ, 2022, 821:153440.DOI:10.1016/j.scitotenv.2022.153440. doi: 10.1016/j.scitotenv.2022.153440
[11]	KITAGAMI Y, MATSUDA Y. Temperature changes affect multi-trophic interactions among pines,mycorrhizal fungi,and soil nematodes in a microcosm experiment[J]. Pedobiologia, 2020, 78:150595.DOI:10.1016/j.pedobi.2019.150595. doi: 10.1016/j.pedobi.2019.150595
[12]	SUTTON-GRIER A E, KENNEY M A, RICHARDSON C J. Examining the relationship between ecosystem structure and function using structural equation modelling:a case study examining denitrification potential in restored wetland soils[J]. Ecol Model, 2010, 221(5):761-768.DOI:10.1016/j.ecolmodel.2009.11.015. doi: 10.1016/j.ecolmodel.2009.11.015
[13]	KIM T N, HOLT R D. The direct and indirect effects of fire on the assembly of insect herbivore communities:examples from the Florida scrub habitat[J]. Oecologia, 2012, 168(4):997-1012.DOI:10.1007/s00442-011-2130-x. doi: 10.1007/s00442-011-2130-x
[14]	靳天恩, 马彦红, 李善文. 影响人工油松林生长的相关因子的研究[J]. 防护林科技, 1999(3):12-14,59.
	JIN T E, MA Y H, LI S W. Study on the related factors affecting the growth of artificial Pinus tabulaeformis forest[J]. Prot For Sci Technol, 1999(3):12-14, 59.DOI:10.13601/j.issn.1005-5215.1999.03.005. doi: 10.13601/j.issn.1005-5215.1999.03.005
[15]	张长现. 不同生态条件下五脉绿绒蒿生物碱与黄酮成分研究[D]. 兰州: 中国科学院西北高原生物研究所, 2009.
	ZHANG C X. Studies on alkaloids and flavonoids of Meconopsis pentaphylla under different ecological conditions[D]. Lanzhou: Institute of Northwest Plateau Biology, Chinese Academy of Sciences, 2009.
[16]	王文杰, 孙伟, 邱岭, 等. 不同时间尺度下兴安落叶松树干液流密度与环境因子的关系[J]. 林业科学, 2012, 48(1):77-85.
	WANG W J, SUN W, QIU L, et al. Relations between stem sap flow density of Larix gmelinii and environmental factors under different temporal scale[J]. Sci Silvae Sin, 2012, 48(1):77-85.DOI:10.11707/j.1001-7488.20120113. doi: 10.11707/j.1001-7488.20120113
[17]	台秉洋. 大兴安岭北部高山兴安落叶松树木生长与气候变化的关系[D]. 哈尔滨: 东北林业大学, 2012.
	TAI B Y. The relationship between the growth of Larix gmelinii in the north alpine of great Khingan and the climate change[D]. Harbin: Northeast Forestry University, 2012.
[18]	孙振静, 赵慧颖, 朱良军, 等. 大兴安岭北部不同降水梯度下兴安落叶松生长对升温的响应差异[J]. 北京林业大学学报, 2019, 41(6):1-14.
	SUN Z J, ZHAO H Y, ZHU L J, et al. Differences in response of Larix gmelinii growth to rising temperature under different precipitation gradients in northern Daxing’an Mountains of northeastern China[J]. J Beijing For Univ, 2019, 41(6):1-14.DOI:10.13332/j.1000-1522.20190007. doi: 10.13332/j.1000-1522.20190007
[19]	高涛. 大气环流和海温变化对兴安落叶松生长的气候影响:以根河地区为例[D]. 呼和浩特: 内蒙古农业大学, 2013.
	GAO T.Climate influence of the atmospheric circulation and sea surface temperature on Larix gmelinii(rupr.) Rupr.growth-focus on Genhe region as an example[D]. Hohhot: Inner Mongolia Agricultural University, 2013.
[20]	ERDENEBILEG E, YE X H, WANG C W, et al. Positive and negative effects of UV irradiance explain interaction of litter position and UV exposure on litter decomposition and nutrient dynamics in a semi-arid dune ecosystem[J]. Soil Biol Biochem, 2018, 124:245-254.DOI:10.1016/j.soilbio.2018.06.013. doi: 10.1016/j.soilbio.2018.06.013
[21]	KUJANSUU J, YASUE K, KOIKE T, et al. Climatic responses of tree-ring widths of Larix gmelinii on contrasting north-facing and south-facing slopes in central Siberia[J]. J Wood Sci, 2007, 53(2):87-93.DOI:10.1007/s10086-006-0837-9. doi: 10.1007/s10086-006-0837-9
[22]	罗云建, 王效科, 逯非. 中国主要林木生物量模型手册[M]. 北京: 中国林业出版社, 2015.
	LUO Y J, WANG X K, LU F. Comprehensive database of biomass regressions for China’s tree species[M]. Beijing: China Forestry Publishing House, 2015.
[23]	吴明隆. 结构方程模型:AMOS的操作与应用万卷方法统计分析方法丛书[M]. 重庆: 重庆大学出版社, 2009.
	WU M L. Structural equation modeling:operation and application of AMOS:Series of 10,000 volumes of statistical analysis methods[M]. Chongqing: Chongqing University Press, 2009.
[24]	何晓群. 多元统计分析[M]. 北京: 中国人民大学出版社, 2004.
	HE X Q. Multivariate statistical analysis[M]. Beijing: China Renmin University Press, 2004.
[25]	侯杰泰. 结构方程模型及其应用[M]. 北京: 教育科学出版社, 2004.
	HOU J T. Structural equation model and its applications[M]. Beijing: Educational Science Publishing House, 2004.
[26]	周健平. 基于结构方程模型的林分特征因子间耦合关系分析[D]. 哈尔滨: 东北林业大学, 2015.
	ZHOU J P. An analysis of the coupling relationship of stand characteristic factors based on structural equation model[D]. Harbin: Northeast Forestry University, 2015.
[27]	HOOPER D, COUGHLAN J, MULLEN M R. Structural equation modelling:guidelines for determining model fit[J]. Electron J Bus Res Methods, 2008, 6(1):53-60.
[28]	孟军贵, 铁牛. 气温、降水对兴安落叶松生长的影响研究[J]. 科学技术创新, 2019(18):143-144.
	MENG J G, TIE N. Effects of temperature and precipitation on growth of Larix gmelinii[J]. Sci Technol Innov, 2019(18):143-144.
[29]	白学平. 海拔对大兴安岭落叶松径向生长与气候响应的影响研究[D]. 沈阳: 沈阳农业大学, 2019.
	BAI X P. The study of altitude effects on radial growth and climate response of Larix gmelinii in the great Xing’an Mountains[D]. Shenyang: Shenyang Agricultural University, 2019.
[30]	杨志香, 周广胜, 殷晓洁, 等. 中国兴安落叶松天然林地理分布及其气候适宜性[J]. 生态学杂志, 2014, 33(6):1429-1436.
	YANG Z X, ZHOU G S, YIN X J, et al. Geographic distribution of Larix gmelinii natural forest in China and its climatic suitability[J]. Chin J Ecol, 2014, 33(6):1429-1436.DOI:10.13292/j.1000-4890.2014.0122. doi: 10.13292/j.1000-4890.2014.0122

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

RichHTML

PDF

详细数据

可视化

摘要/Abstract

引用本文

使用本文

图/表 7

参考文献 30

相关文章 15

编辑推荐

Metrics

本文评价

作者

读者

审稿

[1]	陆其伟, 脱云飞, 郑阳, 骆伟, 代勤龙, 何霞红. 栗子坪自然保护区不同海拔梯度土壤入渗特性研究[J]. 南京林业大学学报（自然科学版）, 2025, 49(2): 143-152.
[2]	孔得伦, 邢艳秋. GEDI与ICESat-2星载激光雷达数据反演树高研究[J]. 南京林业大学学报（自然科学版）, 2025, 49(2): 175-184.
[3]	王耀仪, 王宏翔, 王永强, 曾文豪, 叶绍明. 雅长保护区老龄林不同林层功能性状多样性及其影响因素分析[J]. 南京林业大学学报（自然科学版）, 2024, 48(5): 28-38.
[4]	李岩松, 杨艳蓉, 张文艺, 张乐英, 黄傲, 张贻荣. 西南地区不同下垫面雷电活动特征与森林雷击火的关系[J]. 南京林业大学学报（自然科学版）, 2024, 48(3): 219-228.
[5]	韩新宇, 高露双, 秦莉, 庞荣荣, 刘鸣谦, 朱一泓, 田益雨, 张金. 林分密度对兴安落叶松径向生长-气候关系的影响[J]. 南京林业大学学报（自然科学版）, 2024, 48(2): 182-190.
[6]	左壮, 张韫, 崔晓阳. 火烧对兴安落叶松林土壤氮形态和含量的初期影响[J]. 南京林业大学学报（自然科学版）, 2024, 48(1): 147-154.
[7]	罗楚滢, 佘济云, 唐子朝. 基于SSPs气候场景的濒危植物银杉潜在分布区预测[J]. 南京林业大学学报（自然科学版）, 2024, 48(1): 161-168.
[8]	萨如拉, 王子瑞, 滑永春, 呼日查, 刘磊, 高明龙, 于晓雨. 基于结构方程模型的大兴安岭北部天然林森林生态系统恢复能力评价研究[J]. 南京林业大学学报（自然科学版）, 2024, 48(1): 196-204.
[9]	路文燕, 董灵波, 田园, 汪莎杉, 曲宣怡, 魏巍, 刘兆刚. 基于树种组成的大兴安岭天然林主要树种树高-胸径曲线研究[J]. 南京林业大学学报（自然科学版）, 2023, 47(4): 157-165.
[10]	盖军鹏, 陈东升, 贾炜玮, 王政. 基于种源和气候效应的日本落叶松树高生长模型研究[J]. 南京林业大学学报（自然科学版）, 2023, 47(4): 51-60.
[11]	郭常酉, 郭宏仙, 王宝华. 基于气候因子的杉木单木胸径生长模型构建[J]. 南京林业大学学报（自然科学版）, 2023, 47(1): 47-56.
[12]	郭弘婷, 纪小芳, 汪成, 邹汉鲁, 王丽艳, 姜姜. 我国人工林林下灌木层植物多样性空间变异及影响要素[J]. 南京林业大学学报（自然科学版）, 2022, 46(4): 144-152.
[13]	谢立红, 黄庆阳, 曹宏杰, 杨帆, 王继丰, 倪红伟. 气候变暖对黑龙江省五大连池兴安落叶松径向生长的影响[J]. 南京林业大学学报（自然科学版）, 2022, 46(2): 150-158.
[14]	吴帆, 朱沛煌, 季孔庶. 马尾松分布格局对未来气候变化的响应[J]. 南京林业大学学报（自然科学版）, 2022, 46(2): 196-204.
[15]	徐晶园, 圣倩倩, 王伟希, 刘聪哲, 祝遵凌. 南京典型城市道路植物多样性与土壤因子的耦合关系[J]. 南京林业大学学报（自然科学版）, 2021, 45(6): 119-126.