华东地区亚热带典型常绿阔叶林地上生物量与环境因子的关系

doi:10.12302/j.issn.1000-2006.202302027

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南京林业大学学报（自然科学版） ›› 2024, Vol. 48 ›› Issue (1): 74-80.doi: 10.12302/j.issn.1000-2006.202302027

所属专题：森林生态系统生物多样性研究专题

• 专题报道Ⅱ:森林生态系统生物多样性研究专题(执行主编薛建辉方炎明) • 上一篇下一篇

华东地区亚热带典型常绿阔叶林地上生物量与环境因子的关系

董玉洁(), 毛岭峰(), 张敏, 鲁旭东, 吴秀萍

南京林业大学生态与环境学院,江苏南京 210037

收稿日期:2023-02-15 修回日期:2023-07-24 出版日期:2024-01-30 发布日期:2024-01-24
通讯作者: 毛岭峰
基金资助:
中国科学院战略性先导科技专项(XDB31000000)

Relationship between aboveground biomass and environmental factors of subtropical typical evergreen broad-leaved forest in east China

DONG Yujie(), MAO Lingfeng(), ZHANG Min, LU Xudong, WU Xiuping

College of Ecology and Environment, Nanjing Forestry University, Nanjing 210037, China

Received:2023-02-15 Revised:2023-07-24 Online:2024-01-30 Published:2024-01-24
Contact: MAO Lingfeng

摘要/Abstract

摘要：

【目的】以华东地区亚热带典型常绿阔叶林中的栲类(Castanopsis spp.)类林和木荷(Schima superba)林两种林分类型为研究对象,研究环境因子对林分乔木层地上生物量的影响。【方法】基于各植物种的异速生长方程计算群落的地上生物量,利用相关性检验(Pearson)分析不同类型常绿阔叶林地上生物量与环境因子的关系,通过偏最小二乘法结构方程模型(PLS-SEM)构建环境因素与地上生物量之间的作用机制。【结果】①华东地区亚热带典型常绿阔叶林地上生物量随林龄的增长表现出极显著的增加趋势。②栲类天然林和木荷天然林地上生物量在研究区范围内与土壤pH呈极显著正相关,气温与太阳辐射总强度因子对木荷天然林地上生物量的变化有显著影响。③环境因素与栲类天然林地上生物量构建的结构方程模型中,气候因素对其地上生物量的直接作用系数要显著高于土壤因素。【结论】太阳辐射总强度、土壤pH、土壤容重因子对华东地区亚热带典型常绿阔叶林地上生物量的变化有显著影响。其中,栲类天然林地上生物量与土壤pH呈极显著正相关。木荷天然林地上生物量与气温因子呈显著负相关,与太阳辐射总强度因子呈极显著负相关,与土壤pH因子呈极显著正相关。

关键词: 亚热带, 常绿阔叶林, 地上生物量, 太阳辐射, 土壤pH, 土壤容重

Abstract:

【Objective】Taking the Castanopsis spp. and Schima superba forests in subtropical typical evergreen broad-leaved forests in east China as the research subjects, the effects of environmental factors on aboveground biomass of the tree layer were studied.【Method】The aboveground biomass of the community was calculated based on the allometric growth equation of various plant species, and the Pearson correlation test was used to analyze the relationship between aboveground biomass and environmental factors in different types of evergreen broad-leaved forests. The mechanism of action between environmental factors and aboveground biomass was constructed by the partial least squares structural equation model (PLS-SEM), which was employed to analyze the relationship between multiple sets of variables.【Result】(1) The aboveground biomass of subtropical typical evergreen broad-leaved forests in east China showed a extremely significant increasing trend with forest age. (2) The aboveground biomass of Castanopsis and S. superba natural forests positively correlated with soil pH in the study area, and for the S. superba natural forest, air temperature and total solar radiation intensity factors significantly affected the aboveground biomass. (3) In the structural equation model constructed using environmental factors and the aboveground biomass of Castanopsis natural forests, the direct effect coefficient of climate factors on aboveground biomass was significantly greater than that of soil factors.【Conclusion】The total solar radiation intensity, soil pH, and soil bulk density significantly affected the aboveground biomass of subtropical typical evergreen broad-leaved forests in east China. Among them, in the Castanopsis natural forest, aboveground biomass positively correlated with air the soil pH factor. In the S. superba natural forest, aboveground biomass negatively correlated with air temperature factor and total solar radiation intensity factor and positively correlated with soil pH factor.

Key words: subtropical, evergreen broad-leaved forest, aboveground biomass, solar radiation intensity, soil pH, soil bulk

中图分类号:

S718

董玉洁,毛岭峰,张敏,等. 华东地区亚热带典型常绿阔叶林地上生物量与环境因子的关系[J]. 南京林业大学学报（自然科学版）, 2024, 48(1): 74-80.

DONG Yujie, MAO Lingfeng, ZHANG Min, LU Xudong, WU Xiuping. Relationship between aboveground biomass and environmental factors of subtropical typical evergreen broad-leaved forest in east China[J].Journal of Nanjing Forestry University (Natural Science Edition), 2024, 48(1): 74-80.DOI: 10.12302/j.issn.1000-2006.202302027.

图/表 6

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参考文献 21

[22]	HAIR J F, RISHER J J, SARSTEDT M, et al. When to use and how to report the results of PLS-SEM[J]. Eur Bus Rev, 2019, 31(1): 2-24. DOI: 10.1108/ebr-11-2018-0203.
[23]	HUI D F, JACKSON R B. Geographical and interannual variability in biomass partitioning in grassland ecosystems: a synthesis of field data[J]. New Phytol, 2006, 169(1): 85-93. DOI: 10.1111/j.1469-8137.2005.01569.x.
[24]	CALEÑO-RUIZ B L, GARZÓN F, LÓPEZ-CAMACHO L, et al. Soil resources and functional trait trade-offs determine species biomass stocks and productivity in a tropical dry forest[J]. Front Vet Sci, 2023, 6: 1028359.DOI: 10.3389/ffgc.2023.1028359.
[25]	王晓濛, 侯继华, 何念鹏. 中国植物群落生产力由东向西分布格局及其驱动因素[J]. 生态学报, 2023, 43(6):2488-2500.
	WANG X M, HOU J H, HE N P, et al. Distribution pattern and driving factors of plant community productivity from east to west in China[J]. Acta Ecol Sin, 2023, 43(6): 2488-2500. DOI: 10.5846/stxb202203100578.
[26]	GONMADJE C, PICARD N, GOURLET-FLEURY S, et al. Altitudinal filtering of large-tree species explains aboveground biomass variation in an Atlantic Central African rain forest[J]. J Trop Ecol, 2017, 33(2): 143-154. DOI: 10.1017/s0266467416000602.
[27]	孙丽娜. 山西省森林生物量碳密度空间格局和影响因素研究[D]. 太原: 山西大学, 2020.
	SUN L N. Spatial pattern and influencing factors of forest biomass carbon density in Shanxi Province[D]. Taiyuan: Shanxi University, 2020. DOI: 10.27284/d.cnki.gsxiu.2020.002024.
[28]	PIEDALLU C, PEDERSOLI E, CHASTE E, et al. Optimal resolution of soil properties maps varies according to their geographical extent and location[J]. Geoderma, 2022, 412(15): 115723. DOI: 10.1016/j.geoderma.2022.115723.
[29]	MALHI Y, WOOD D, BAKER T R, et al. The regional variation of aboveground live biomass in old-growth Amazonian forests[J]. Glob Change Biol, 2006, 12(7): 1107-1138. DOI: 10.1111/j.1365-2486.2006.01120.x.
[30]	KITAYAMA K, AIBA S I. Ecosystem structure and productivity of tropical rain forests along altitudinal gradients with contrasting soil phosphorus pools on Mount Kinabalu, Borneo[J]. J Ecol, 2002, 90(1): 37-51. DOI: 10.1046/j.0022-0477.2001.00634.x.
[31]	MOSER G, HERTEL D, LEUSCHNER C. Altitudinal change in LAI and stand leaf biomass in tropical montane forests: a transect study in Ecuador and a pan-tropical meta-analysis[J]. Ecosystems, 2007, 10: 924-935. DOI: 10.1007/s10021-007-9063-6.
[32]	钱春花, 李明阳, 郑超. 苏南丘陵山区森林生物量时空变化驱动因素分析[J]. 江苏农业学报, 2021, 37(2):382-388.
	QIAN C H, LI M Y, ZHENG C. Analysis on driving factors of spatiotemporal changes of forest biomass in hilly areas of southern Jiangsu[J]. Jiangsu J Agr Sci, 2021, 37(2):382-388.DOI:10.3969/j.issn.1000-4440.2021.02.014.
[33]	PENG L, XU X J, LIAO X F, et al. Ampelocalamus luodianensis (Poaceae), a plant endemic to Karst, adapts to resource heterogeneity in differing microhabitats by adjusting its biomass allocation[J]. Glob Ecol Conserv, 2023, 41: e02374. DOI: 10.1016/j.gecco.2023.e02374.
[34]	FIALA K, TUMA L, HOLUB P. Effect of nitrogen addition and drought on aboveground biomass of expanding tall grasses Calamagrostis epigejos and Arrhenatherum elatius[J]. Biologia, 2011, 66: 275-281. DOI: 10.2478/s11756-011-0001-x.
[35]	GATTI R C, CASTALDI S, LINDSELL J A, et al. The impact of selective logging and clearcutting on forest structure, tree diversity and aboveground biomass of African tropical forests[J]. Ecol Res, 2014, 30(1): 119-132. DOI: 10.1007/s11284-014-1217-3.
[36]	IMANI G, BOYEMBA F, LEWIS S, et al. Height-diameter allometry and aboveground biomass in tropical montane forests: insights from the Albertine Rift in Africa[J]. Plos One, 2017. 12(6): e0179653. DOI: 10.1371/journal.pone.0179653.
[37]	WANG C T, SUN Y, CHEN H Y H, et al. Meta-analysis shows non-uniform responses of above-and belowground productivity to drought[J]. Sci Total Environ, 2021, 782: 146901. DOI: 10.1016/j.scitotenv.2021.146901.
[38]	文国卫, 黄秋良, 吕增伟, 等. 气候变化情境下木荷潜在地理分布及生态适宜性分析[J]. 生态学报, 2023, 43(16): 1-10.
[1]	芦伟, 余建平, 任海保, 等. 古田山中亚热带常绿阔叶林群落物种多样性的空间变异特征[J]. 生物多样性, 2018, 26(9):1023-1028.
	LU W, YU J P, REN H B, et al. Spatial variation characteristics of species diversity of subtropical evergreen broad-leaved forest community in Gutian Mountain[J]. Biodivers Sci, 2018, 26(9): 1023-1028. DOI: 10.17520/biods.2018138.
[2]	DIXON R K, SOLOMON A M, BROWN S, et al. Carbon pools and flux of global forest ecosystems[J]. Science, 1994, 263(5144): 185-190. DOI: 10.1126/science.263.5144.185.
[3]	HOUGHTON R A. Aboveground forest biomass and the global carbon balance[J]. Glob Change Biol, 2005, 11(6): 945-958. DOI: 10.1111/j.1365-2486.2005.00955.x.
[4]	GONZALEZ-AKRE E, PIPONIOT C, LEPORE M, et al. Allodb: an R package for biomass estimation at globally distributed extratropical forest plots[J]. Methods Ecol Evol, 2021, 13(2): 330-338. DOI: 10.1111/2041-210X.13756.
[5]	SLIK J W F, PAOLI G, MCGUIRE K, et al. Large trees drive forest aboveground biomass variation in moist lowland forests across the tropics[J]. Glob Ecol Biogeogr, 2013, 22(12): 1261-1271. DOI: 10.1111/geb.12092.
[6]	LIU Y C, YU G R, WANG Q F, et al. How temperature, precipitation and stand age control the biomass carbon density of global mature forests[J]. Glob Ecol Biogeogr, 2014, 23: 323-333. DOI: 10.1111/geb.12113.
[7]	LARJAVAARA M, MULLER-LANDAU H C. Temperature explains global variation in biomass among humid old-growth forests: temperature and old-growth forest biomass[J]. Glob Ecol Biogeogr, 2012, 21(10): 998-1006. DOI: 10.1111/j.1466-8238.2011.00740.x.
[8]	BARALOTO C, RABAUD C, MOLTO Q, et al. Disentangling stand and environmental correlates of aboveground biomass in Amazonian forests[J]. Glob Change Biol, 2011, 17(8): 2677-2688. DOI: 10.1111/j.1365-2486.2011.02432.x.
[9]	杨远盛, 张晓霞, 于海艳, 等. 中国森林生物量的空间分布及其影响因素[J]. 西南林业大学学报, 2015, 35(6):45-52.
	YANG Y S, ZHANG X X, YU H Y, et al. Spatial distribution of forest biomass and its influencing factors in China[J]. J Southwest For Univ, 2015, 35(6): 45-52. DOI: 10.11929/j.issn.2095-1914.2015.06.008.
[10]	NIE X Q, WANG D, ZHOU G Y, et al. Storage and controlling factors of soil organic carbon in alpine wetlands and meadow across the Tibetan Plateau[J]. Eur J Soil Sci, 2023, e13383. DOI: 10.1111/ejss.13383.
[11]	MALEKI S, KHORMALI F, BODAGHABADI M B, et al. Role of geomorphic surface on the aboveground biomass and soil organic carbon storage in a semi-arid region of Iranian Loess Plateau[J]. Quat Int, 2020, 552(30): 111-121. DOI: 10.1016/j.quaint.2018.11.001.
[12]	CABRERA M, DUIVENVOORDEN J F. Drivers of aboveground biomass of high mountain vegetation in the Andes[J]. Acta Oecol-Int J Ecol, 2019, 102: 103504. DOI: 10.1016/j.actao.2019.103504.
[13]	KRAMER M G, CHADWICK O A. Controls on carbon storage and weathering in volcanic soils across a high-elevation climate gradient on Mauna Kea, Hawaii[J]. Ecology, 2016, 97(9): 2384-2395. DOI: 10.1002/ecy.1467.
[14]	WANG X H, KENT M, FANG X F. Evergreen broad-leaved forest in eastern China: its ecology and conservation and the importance of resprouting in forest restoration[J]. For Ecol Manage, 2007, 245: 76-87. DOI: 10.1016/j.foreco.2007.03.043.
[15]	孔祥海. 福建梅花山国家级自然保护区常绿阔叶林生态学研究[D]. 厦门: 厦门大学, 2008.
	KONG X H. Ecological study on evergreen broad-leaved forest in Meihuashan national nature reserve in Fujian Province[D]. Xiamen: Xiamen University, 2008.
[16]	樊海东, 陈海燕, 吴雁南, 等. 金华北山南坡主要植被类型的群落特征[J]. 植物生态学报, 2019, 43(10):921-928.
	FAN H D, CHEN H Y, WU Y N, et al. The community characteristics of main vegetation types on the south slope of north mountain in Jinhua[J]. J Plant Ecol, 2019, 43(10): 921-928. DOI: 10.17521/cjpe.2019.0114.
[17]	温远光, 周晓果, 朱宏光, 等. 桉树生态营林的理论探索与实践[J]. 广西科学, 2019, 26(2):159-175+252.
	WEN Y G, ZHOU X G, ZHU H G, et al. Theoretical exploration and practice of Eucalyptus ecological forest management[J]. Guangxi Sci, 2019, 26(2): 159-175+252. DOI: 10.13656/j.cnki.gxkx.20190419.012.
[18]	赖江山, 张谧, 谢宗强. 三峡库区常绿阔叶林优势种群的结构和格局动态[J]. 生态学报, 2006(4):1073-1079.
	LAI J S, ZHANG M, XIE Z Q. The structure and pattern dynamics of dominant populations in evergreen broad-leaved forests in the Three Gorges Reservoir Area[J]. Acta Ecol Sin, 2006 (4): 1073-1079. DOI: 10.3321/j.issn:1000-0933.2006.04.013.
[19]	胡喜生, 洪伟, 吴承祯, 等. 木荷天然种群生命表分析[J]. 广西植物, 2007, 7(3):469-474.
	HU X S, HONG W, WU C Z, et al. Life table analysis of Schima superba natural population[J]. Guihaia, 2007, 7(3): 469-474. DOI: 10.3969/j.issn.1000-3142.2007.03.019.
[20]	李川, 张廷军, 陈静. 近40年青藏高原地区的气候变化——NCEP和ECMWF地面气温及降水再分析和实测资料对比分析[J]. 高原气象, 2004(S1):97-103.
	LI C, ZHANG T J, CHEN J. Climate change in the Qinghai Tibet Plateau region over the past 40 years: reanalysis and comparative analysis of NCEP and ECMWF surface temperature and precipitation data[J]. Plateau Meteor, 2004 (S1): 97-103. DOI: 10.3321/j.issn:1000-0534.2004.z1.016.
[38]	WEN G W, HUANG Q L, LYU Z W, et al. Analysis of potential geographical distribution and ecological suitability of Schima superba under climate change[J]. Acta Ecol Sin, 2023, 43(16): 1-10. DOI: 10.5846/stxb202201130121.
[21]	WANG B L, FRENCH H M. Climate controls and high-altitude permafrost, Qinghai-Xizang (Tibet) Plateau, China[J]. Permafrost Periglacial Process, 1994, 5(2): 87-100. DOI: 10.1002/ppp.3430050203.

群落类型 community type	样方个数 number of plots	海拔范围/m altitude range	经纬度范围 latitude and longitude range	优势种 dominant species
栲类林Castanopsis spp. forest	40	220~1 154	116.93°~120.59°E, 24.51°~30.34°N	栲(C. fargesii)、甜槠(C. eyrei)、青冈(Q. glauca)、柯(L. glaber)、硬壳柯(L. hancei)、米槠(C. carlesii)、毛锥(C. fordii)
木荷林Schima superba forest	20	60~1 050	117.03°~119.80°E, 25.09°~30.25°N	木荷(S. superba)

群落类型 community type	经度 longitude	纬度 latitude	海拔 altitude
栲类林Castanopsis forest	-0.51^**	-0.50^**	0.15
木荷林S. superba forest	-0.64^**	-0.47^*	-0.26
典型常绿阔叶林typical evergreen broad-leaved forest	-0.53^**	-0.51^**	0.11

群落类型 community type	气温 air temperature	降水量 precipitation	太阳辐射总强度 total solar radiation intensity	土壤容重 soil bulk	土壤浅层有机碳 shallow soil organic carbon	pH
栲类林 Castanopsif forest	-0.07	0.10	-0.23	0.26	-0.27	0.62^**
木荷林 S. superba forest	-0.53^*	0.32	-0.60^**	0.43	0.40	0.62^**
典型常绿阔叶林 typical evergreen broad-leaved forest	-0.23	0.16	-0.32^*	0.33^**	-0.10	0.63^**

路径 path	假设的机制 hypothetical mechanism
气候climate →地上生物量aboveground biomass	生物量的分布模式受到气候的强烈影响^[23]
土壤soil →地上生物量aboveground biomass	在同一个生态系统的环境条件下,位于营养丰富的土层会储存较高的生物量^[24]
地理地形geography and topography→ 地上生物量aboveground biomass	在中国东西样带上植物群落地上生物量(AGB)随着经度的增加而增加,表现出明显的经度地带性特征^[25]。对AGB沿海拔梯度变化得出了不同的结果,一些认为AGB随着海拔的增加而减少,另一些认为AGB随着海拔的增加而增加^[26]
地理地形geography and topography→气候climate	地理位置和立地环境条件可以影响森林生长的微气候环境^[27]
地理地形geography and topography→土壤soil	土壤性质因地理位置而异^[28]
气候climate →土壤soil	不同气候影响下进化出不同的土壤特性^[13]

华东地区亚热带典型常绿阔叶林地上生物量与环境因子的关系

Relationship between aboveground biomass and environmental factors of subtropical typical evergreen broad-leaved forest in east China

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[15]	薛岑,刘茂松,康昕,郑阿宝,侯嫦英,关庆伟,徐驰. 苏南丘陵山区典型次生森林群落的点格局分析[J]. 南京林业大学学报（自然科学版）, 2016, 59(02): 107-112.