宝天曼8种阔叶树木材密度的解剖学决定因素及其与叶性状的协同与权衡

doi:10.11707/j.1001-7488.LYKX20230646

摘要/Abstract

摘要：

目的: 探究影响木材密度的解剖学机制，揭示茎叶解剖和生理性状的协同与权衡关系，有助于阐明不同树种适应环境的生理生态机制。方法: 选择宝天曼天然林中常见的8种落叶阔叶树，测定木材密度、木质部导管及纤维等解剖性状、叶片压力-容积曲线参数等21个茎叶性状，探究决定木材密度的解剖学性状，分析茎叶性状的协同和权衡关系。结果: 1） 8个树种的木材密度与组成木质部的导管、薄壁组织和纤维组织这3大组织的比例都不相关，更多受到纤维细胞性状的影响。2）对木材密度影响最大的木质部性状是纤维细胞腔占横截面的比例，其次是纤维细胞壁占纤维细胞的比例、纤维细胞壁厚与腔直径比、纤维细胞壁厚度等性状。3）木材密度与叶片单叶面积、失膨压时相对含水量和弹性模量呈负相关。4）失膨压时相对含水量与导管水力直径、最大导管直径、平均导管直径、纤维细胞腔面积、纤维细胞腔直径呈正相关；与导管密度、纤维细胞壁厚与腔直径比、纤维细胞壁占横截面比例呈负相关。结论: 木材密度主要由纤维细胞性状决定，而非导管和薄壁组织性状；高的叶片忍耐失水能力耦合于致密的茎纤维细胞和木材密度。

关键词: 木材密度, 功能性状, 木质部解剖, 纤维性状, 失膨压时相对含水量

Abstract:

Objective: This study aims to explore the anatomical mechanisms that affect wood density and reveal the coordination and trade-off relationships of anatomy and physiological traits between stems and leaves traits can deepen the understanding of physiological and ecological mechanisms of different tree species adapting to the environment. Method: Eight common deciduous broad-leaved tree species in the natural forest of Baotianman were selected as the research objects. Twenty-one stem and leaf traits of these tree species, including wood density, xylem vessels and fibers and other anatomical traits, and leaf pressure volume curve parameters, were measured to explore the anatomical traits that determine wood density and to analyze the coordination and trade-off between stem and leaf traits. Result: 1) The wood density of 8 tree species in this study was not correlated with the proportions of the three major tissues that make up the xylem: vessels, parenchyma tissue and fiber tissue. Wood density was more influenced by traits of fiber cells. 2) The xylem traits that have the greatest impact on wood density was the ratio of fiber lumen to cross-sectional area, followed by the ratio of fiber wall to fiber cell, the ratio of fiber wall thickness to lumen diameter and the fiber cell wall thickness. 3) Wood density was negatively correlated with individual leaf area, relative water content at turgor loss point and elasticity modulus. 4) The relative water content at turgor loss point was positively related to hydraulic vessel diameter, maximum vessel diameter, mean vessel diameter, fiber cell lumen area and fiber cell lumen diameter, and negatively related to vessel density, the ratio of fiber wall thickness to lumen diameter and the ratio of fiber wall to cross-sectional area. Conclusion: The wood density is mainly determined by the fiber cell traits, rather than the traits of vessel and parenchyma tissue. The strong capacity of leaves to tolerate dehydration is coupled with the dense stem fiber cells and wood density.

Key words: wood density, functional trait, xylem anatomy, fiber trait, relative water content at turgor loss point

中图分类号:

S718.43

杭宇杰,陈志成,王林,牛保亮,刘松松,于博,王晓,刘世荣. 宝天曼8种阔叶树木材密度的解剖学决定因素及其与叶性状的协同与权衡[J]. 林业科学, 2024, 60(4): 62-70.

Yujie Hang,Zhicheng Chen,Lin Wang,Baoliang Niu,Songsong Liu,Bo Yu,Xiao Wang,Shirong Liu. Anatomical Determinants of Wood Density of Eight Broad-Leaved Tree Species in Baotianman and Their Coordination and Trade-off with Leaf Traits[J]. Scientia Silvae Sinicae, 2024, 60(4): 62-70.

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参考文献 0

	陈志成, 陆海波, 刘晓静, 等. 宝天曼三桠乌药对降雨减少后的生理生态响应. 林业科学研究, 2017, 30 (3): 430- 435.
	Chen Z C, Lu H B, Liu X J, et al. Ecophysiological responses of Lindera obtusiloba to rainfall reduction in Baotianman nature reserve. Forest Research, 2017, 30 (3): 430- 435.
	刘　尧, 于　馨, 于　洋, 等. R程序包“rdacca. hp”在生态学数据分析中的应用: 案例与进展. 植物生态学报, 2023, 47 (1): 134- 144. doi: 10.17521/cjpe.2022.0314
	Liu Y, Yu X, Yu Y, et al. Application of "rdacca. hp” R package in ecological data analysis: case and progress. Chinese Journal of Plant Ecology, 2023, 47 (1): 134- 144. doi: 10.17521/cjpe.2022.0314
	曾凡江, 李向义, 张希明, 等. 2010. 极端干旱条件下多年生植物水分关系参数变化特性. 生态学杂志, 29(2): 207–214.
	Zeng F J, Li X Y, Zhang X M , et al. 2010. Variation characteristics of perennial plant species water relation parameters under extreme arid condition. Chinese Journal of Ecology, 29(2): 207–214. ［in Chinese］
	Arenas-Navarro M, Oyama K, García-Oliva F, et al. The role of wood anatomical traits in the coexistence of oak species along an environmental gradient. AoB Plants, 2021, 13 (6): plab066. doi: 10.1093/aobpla/plab066
	Bartlett M K, Scoffoni C, Sack L. The determinants of leaf turgor loss point and prediction of drought tolerance of species and biomes: a global meta-analysis. Ecology Letters, 2012, 15 (5): 393- 405. doi: 10.1111/j.1461-0248.2012.01751.x
	Chave J, Coomes D, Jansen S, et al. Towards a worldwide wood economics spectrum. Ecology Letters, 2009, 12 (4): 351- 366. doi: 10.1111/j.1461-0248.2009.01285.x
	Chen Z C, Liu S R, Lu H B, et al. Interaction of stomatal behaviour and vulnerability to xylem cavitation determines the drought response of three temperate tree species. AoB Plants, 2019, 11 (5): plz058. doi: 10.1093/aobpla/plz058
	Chen Z C, Zhang Y T, Yuan W J. et al. Coordinated variation in stem and leaf functional traits of temperate broadleaf tree species in the isohydric–anisohydric spectrum. Tree Physiology, 2021, 41 (9): 1601- 1610. doi: 10.1093/treephys/tpab028
	Chen Z C, Zhu S D, Zhang Y T, et al. Tradeoff between storage capacity and embolism resistance in the xylem of temperate broadleaf tree species. Tree Physiology, 2020, 40 (8): 1029- 1042. doi: 10.1093/treephys/tpaa046
	Gartner B L, Moore J R, Gardiner B A. Gas in stems: abundance and potential consequences for tree biomechanics. Tree Physiology, 2004, 24 (11): 1239- 1250. doi: 10.1093/treephys/24.11.1239
	Lai J S, Zou Y, Zhang J L, et al. Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca. hp Rpackage. Methods in Ecology and Evolution, 2022, 13 (4): 782- 788. doi: 10.1111/2041-210X.13800
	Liu C C, Sack L, Li Y, et al. Relationships of stomatal morphology to the environment across plant communities. Nature Communications, 2023, 14, 6629. doi: 10.1038/s41467-023-42136-2
	Martínez-Cabrera H I, Jones C S, Espino S, et al. Wood anatomy and wood density in shrubs: responses to varying aridity along transcontinental transects. American Journal of Botany, 2009, 96 (8): 1388- 1398. doi: 10.3732/ajb.0800237
	Morris H, Plavcová L, Cvecko P, et al. A global analysis of parenchyma tissue fractions in secondary xylem of seed plants. New Phytologist, 2016, 209 (4): 1553- 1565. doi: 10.1111/nph.13737
	Poorter L, McDonald I, Alarcón A, et al. The importance of wood traits and hydraulic conductance for the performance and life history strategies of 42 rainforest tree species. New Phytologist, 2010, 185 (2): 481- 492. doi: 10.1111/j.1469-8137.2009.03092.x
	Pratt R B, Jacobsen A L, Ewers F W, et al. Relationships among xylem transport, biomechanics and storage in stems and roots of nine Rhamnaceae species of the California chaparral. New Phytologist, 2007, 174 (4): 787- 798. doi: 10.1111/j.1469-8137.2007.02061.x
	Preston K A, Cornwell W K, DeNoyer J L. Wood density and vessel traits as distinct correlates of ecological strategy in 51 California coast range angiosperms. New Phytologist, 2006, 170 (4): 807- 818. doi: 10.1111/j.1469-8137.2006.01712.x
	Santiago L S, De Guzman M E, Baraloto C, et al. Coordination and trade-offs among hydraulic safety, efficiency and drought avoidance traits in Amazonian rainforest canopy tree species. New Phytologist, 2018, 218 (3): 1015- 1024. doi: 10.1111/nph.15058
	Tyree M T, Zimmermann M H. Xylem structure and the ascent of sap. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002.
	Veech J A. A probabilistic model for analysing species co‐occurrence. Global Ecology and Biogeography, 2013, 22 (2): 252- 260. doi: 10.1111/j.1466-8238.2012.00789.x
	Wang Y Q, Ni M Y, Zeng W H, et al. Co-ordination between leaf biomechanical resistance and hydraulic safety across 30 sub-tropical woody species. Annals of Botany, 2021, 128 (2): 183- 191. doi: 10.1093/aob/mcab055
	Wheeler J K, Sperry J S, Hacke U G, et al. 2005. Inter‐vessel pitting and cavitation in woody Rosaceae and other vesselled plants: a basis for a safety versus efficiency trade‐off in xylem transport. Plant, Cell and Environment, 28(6): 800−812.
	Wright I J, Ackerly D D, Bongers F, et al. Relationships among ecologically important dimensions of plant trait variation in seven Neotropical forests. Annals of Botany, 2007, 99 (5): 1003- 1015. doi: 10.1093/aob/mcl066
	Wright I J, Reich P B, Westoby M, et al. The worldwide leaf economics spectrum. Nature, 2004, 428, 821- 827. doi: 10.1038/nature02403
	Zheng J M, Martínez-Cabrera H I. Wood anatomical correlates with theoretical conductivity and wood density across China: evolutionary evidence of the functional differentiation of axial and radial parenchyma. Annals of Botany, 2013, 112 (5): 927- 935. doi: 10.1093/aob/mct153
	Ziemińska K, Butler D W, Gleason S M, et al. Fibre wall and lumen fractions drive wood density variation across 24 Australian angiosperms. AoB Plants, 2013, 5, plt046.

性状 Trait	平均值±标准差 Mean±SD	变异系数 CV（%）	最大值 Max	最小值 Min
LA/cm²	38.4±17.9	46.7	68.7	14.2
WD/(g·cm^?3)	0.59±0.09	15.8	0.75	0.41
RWC_tlp(%)	89.0±3.3	3.7	92.8	81.7
E	0.18±0.07	37.9	0.32	0.10
VD/(N·mm^?2)	249.7±157.0	62.9	628.4	97.9
HVD/(μm)	31.0±5.4	17.5	39.9	19.2
MaVD/(μm)	45.9±8.0	17.5	54.1	28.8
MVD/(μm)	27.5±4.9	17.9	36.6	17.6
VF(%)	14.1±4.0	28.2	21.4	7.6
RPF(%)	15.9±5.2	33.0	26.0	8.9
APF(%)	10.3±3.7	35.9	13.5	4.1
PF(%)	26.1±4.4	16.9	33.7	21.4
FF(%)	59.8±5.4	9.0	68.2	53.3
FLA/μm²	68.7±24.4	35.5	96.9	18.0
FLD/μm	8.9±2.0	22.1	11.0	4.6
FWA/μm²	47.5±11.8	24.9	65.0	29.1
FWT/μm	1.5±0.43	28.6	2.2	0.86
RFL/(μm·μm^?1)	0.22±0.14	62.6	0.54	0.10
RFF(%)	44.8±13.6	30.4	72.8	28.4
PFW(%)	26.3±6.2	23.7	38.8	19.4
PFL(%)	33.5±10.2	30.4	48.8	14.5

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