Leaf trait variation and trade-offs among growth types of broadleaf plants in Xiao Hinggan Mountains

doi:10.17521/cjpe.2023.0137

Abstract

Abstract:

Aims Patterns of leaf trait variation and correlation have long been a key aspect in unraveling plant responses to climate change. However, the specifics of how these patterns of leaf structural traits and photosynthetic physiological characteristics align and differ across growth types of broadleaf plants remain unclear.

Methods This study focused on 18 dominant or common broadleaf species in a mixed broadleaf-Korean pine (Pinus koraiensis) forest. We measured four structural traits (leaf area (LA), leaf thickness (LT), leaf dry matter content (LDMC) and leaf mass per area (LMA)) and four photosynthetic physiological traits (leaf chlorophyll value (SPAD), intercellular CO₂ concentration (C_i), stomatal conductance (G_s) and net photosynthetic rate (P_n)). We analyzed the variation and correlations between structural and physiological traits across different growth types of broadleaf plants.

Important findings Leaf functional traits displayed variation ranges spanning from 7.73% to 74.54%. Interspecific differences accounted for the majority of variability for LA and LT, while growth type primarily drove variation in C_i, SPAD, LDMC, and LMA. G_s and P_n variation originate mainly from intraspecific differences. There were significant differences among growth types for all leaf traits. Specifically, herbs showed significantly higher LA, LT, and C_i compared to shrubs and trees, trees exhibited significantly elevated LMA, LDMC, SPAD, P_n, and G_s compared to shrubs and herbs. There were significant isometric relationships between P_n and LMA, LDMC among growth types, with slopes above 1. For SPAD versus LA, LT, LDMC, LMA, along with C_i versus LT, LDMC, LMA, slopes remained under 1, indicating allometric growth relationships. Herbs displayed a resource-acquisitive strategy, while trees adopted a relatively conservative strategy. Falling intermediate, shrubs struck a balance, possibly linked to the light levels across their habitats. Investigating trade-off and connections between leaf structure and photosynthetic physiology proves critical for understanding resource acquisition and allocation mechanism in plants.

Key words: functional trait, leaf photosynthetic characteristics, leaf structural traits, leaf economic spectrum

FAN Hong-Kun, ZENG Tao, JIN Guang-Ze, LIU Zhi-Li. Leaf trait variation and trade-offs among growth types of broadleaf plants in Xiao Hinggan Mountains[J]. Chin J Plant Ecol, 2024, 48(3): 364-376.

Add to citation manager EndNote|Ris|BibTeX

URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2023.0137

https://www.plant-ecology.com/EN/Y2024/V48/I3/364

Figures/Tables 7

Table 1 Statistical information of leaf area (LA), leaf thickness (LT), leaf chlorophyll value (SPAD), leaf dry matter content (LDMC), leaf mass per area (LMA), net photosynthetic rate (Pn), intercellular CO2 concentration (Ci), stomatal conductance (Gs) of 18 broadleaf plants in Xiao Hinggan Mountains

性状 Trait	极小值 Min	极大值 Max	中位数 Median	均值 Mean	标准差 SD	偏度 Skewness	峰度 Kurtosis	变异系数 ^KCV (%)
LA (cm²)	0.978	423.847	23.936	33.974	39.314	4.114	23.582	74.54
LT (10^-2 mm)	5.667	26.000	12.000	12.495	3.022	0.813	1.043	21.24
LMA (g·cm^-2)	0.001	0.010	0.004	0.004	0.002	1.026	0.860	35.03
LDMC (g·g^-1)	0.077	0.951	0.332	0.327	0.110	0.857	3.166	26.74
SPAD	13.900	56.250	40.500	39.041	6.210	-0.881	0.716	15.84
P_n (µmol·m^-2)	0.195	21.995	5.864	7.082	3.943	1.182	1.369	45.09
C_i (µmol·mol^-1)	232.922	393.615	324.072	325.852	26.829	-0.094	0.513	7.73
G_s (mol·m^-2·s^-1)	0.018	0.676	0.159	0.193	0.119	1.250	1.406	45.57

Fig. 1 Variance decomposition of variation in 8 leaf traits of 18 broadleaf plants in Xiao Hinggan Mountains. Ci, intercellular CO2 concentration; Gs, stomatal conductance; LA, leaf area; LDMC, leaf dry matter content; LMA, leaf mass per area; LT, leaf thickness; Pn, net photosynthetic rate; SPAD, leaf chlorophyll value.

Fig. 2 Variation of 8 leaf traits of 18 broadleaf plants among trees, shrubs and herbs in Xiao Hinggan Mountains. Different lowercase letters indicate that the leaf traits of different growth types are significantly different (p < 0.05). Ci, intercellular CO2 concentration; Gs, stomatal conductance; LA, leaf area; LDMC, leaf dry matter content; LMA, leaf mass per area; LT, leaf thickness; Pn, net photosynthetic rate; SPAD, leaf chlorophyll value. H, herb; S, shrub; T, tree.

Fig. 3 Correlation among 8 leaf traits of 18 broadleaf plants in Xiao Hinggan Mountains. Ci, intercellular CO2 concentration; Gs, stomatal conductance; LA, leaf area; LDMC, leaf dry matter content; LMA, leaf mass per area; LT, leaf thickness; Pn, net photosynthetic rate; SPAD, leaf chlorophyll value. ***, p < 0.001.

Fig. 4 Correlations between leaf traits of herb, shrub and tree broadleaf plants in Xiao Hinggan Mountains. If there is no significant correlation between traits (p > 0.05), lines are not displayed. Ci, intercellular CO2 concentration; Gs, stomatal conductance; LA, leaf area; LDMC, leaf dry matter content; LMA, leaf mass per area; LT, leaf thickness; Pn, net photosynthetic rate; SPAD, leaf chlorophyll value.

Fig. 5 Principal component (PC) analysis of structural traits, physiological traits and total traits among tree, shrub and herb broadleaf plants in Xiao Hinggan Mountains. A, Principal component analysis for structural traits. B, Principal component analysis for physiological traits. C, Principal component analysis for all traits (eight leaf traits). Ci, intercellular CO2 concentration; Gs, stomatal conductance; LA, leaf area; LDMC, leaf dry matter content; LMA, leaf mass per area; LT, leaf thickness; Pn, net photosynthetic rate; SPAD, leaf chlorophyll value. Color is used to distinguish three different growth types.

Fig. 6 Regression relationships among first principle component (PC1) of leaf structural traits, PC1 of physiological traits and PC1 of total traits among tree, shrub and herb broadleaf plants in Xiao Hinggan Mountains. A, Relationships between structural traits PC1 and physiological traits PC1. B, Relationships between structural traits PC1 and total traits PC1. C, Relationships between physiological traits PC1 and total traits PC1.

References 62

[1]	Albert CH, Thuiller W, Yoccoz NG, Soudant A, Boucher F, Saccone P, Lavorel S (2010). Intraspecific functional variability: extent, structure and sources of variation. Journal of Ecology, 98, 604-613.
[2]	Atkinson LJ, Campbell CD, Zaragoza-Castells J, Hurry V, Atkin OK (2010). Impact of growth temperature on scaling relationships linking photosynthetic metabolism to leaf functional traits. Functional Ecology, 24, 1181-1191.
[3]	Bolmgren K, Cowan PD (2008). Time-size tradeoffs: a phylogenetic comparative study of flowering time, plant height and seed mass in a north-temperate flora. Oikos, 117, 424-429.
[4]	Bolnick DI, Amarasekare P, Araújo MS, Bürger R, Levine JM, Novak M, Rudolf VHW, Schreiber SJ, Urban MC, Vasseur DA (2011). Why intraspecific trait variation matters in community ecology. Trends in Ecology & Evolution, 26, 183-192.
[5]	Bonan GB (2008). Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science, 320, 1444-1449.
[6]	Cirtain MC, Franklin SB, Pezeshki SR (2009). Effect of light intensity on Arundinaria gigantea growth and physiology. Castanea, 74, 236-246.
[7]	Croft H, Chen J, Luo X, Bartlett P, Chen B, Staebler RM (2017). Leaf chlorophyll content as a proxy for leaf photosynthetic capacity. Global Change Biology, 23, 3513-3524. DOI PMID
[8]	Cui EQ, Weng ES, Yan ER, Xia JY (2020). Robust leaf trait relationships across species under global environmental changes. Nature Communications, 11, 2999. DOI: 10.1038/s41467-020-16839-9.
[9]	Díaz S, Kattge J, Cornelissen JHC, Wright IJ, Lavorel S, Dray S, Reu B, Kleyer M, Wirth C, Colin Prentice I, Garnier E, Bönisch G, Westoby M, Poorter H, Reich PB, et al. (2016). The global spectrum of plant form and function. Nature, 529, 167-171.
[10]	Ghimire B, Riley WJ, Koven CD, Kattge J, Rogers A, Reich PB, Wright IJ (2017). A global trait-based approach to estimate leaf nitrogen functional allocation from observations. Ecological Applications, 27, 1421-1434. DOI PMID
[11]	Hasper TB, Dusenge ME, Breuer F, Uwizeye FK, Wallin G, Uddling J (2017). Stomatal CO₂ responsiveness and photosynthetic capacity of tropical woody species in relation to taxonomy and functional traits. Oecologia, 184, 43-57.
[12]	Hassiotou F, Renton M, Ludwig M, Evans JR, Veneklaas EJ (2010). Photosynthesis at an extreme end of the leaf trait spectrum: How does it relate to high leaf dry mass per area and associated structural parameters? Journal of Experimental Botany, 61, 3015-3028. DOI PMID
[13]	He P, Wright IJ, Zhu S, Onoda Y, Liu H, Li R, Liu X, Hua L, Oyanoghafo OO, Ye Q (2019). Leaf mechanical strength and photosynthetic capacity vary independently across 57 subtropical forest species with contrasting light requirements. New Phytologist, 223, 607-618. DOI PMID
[14]	Hikosaka K, Shigeno A (2009). The role of Rubisco and cell walls in the interspecific variation in photosynthetic capacity. Oecologia, 160, 443-451. DOI PMID
[15]	Huxley JD, White CT, Humphries HC, Weber SE, Spasojevic MJ (2023). Plant functional traits are dynamic predictors of ecosystem functioning in variable environments. Journal of Ecology, 111, 2597-2613.
[16]	Jackson BG, Peltzer DA, Wardle DA (2013). The within- species leaf economic spectrum does not predict leaf litter decomposability at either the within-species or whole community levels. Journal of Ecology, 101, 1409-1419.
[17]	Jumrani K, Bhatia VS, Pandey GP (2017). Impact of elevated temperatures on specific leaf weight, stomatal density, photosynthesis and chlorophyll fluorescence in soybean. Photosynthesis Research, 131, 333-350. DOI PMID
[18]	Kosová V, Hájek T, Hadincová V, Münzbergová Z (2022). The importance of ecophysiological traits in response of Festuca rubra to changing climate. Physiologia Plantarum, 174, e13608. DOI: 10.1111/ppl.13608.
[19]	Kvålseth TO (2017). Coefficient of variation: the second-order alternative. Journal of Applied Statistics, 44, 402-415.
[20]	Leigh A, Sevanto S, Close JD, Nicotra AB (2017). The influence of leaf size and shape on leaf thermal dynamics: Does theory hold up under natural conditions? Plant, Cell & Environment, 40, 237-248.
[21]	Li J, Chen X, Niklas KJ, Sun J, Wang Z, Zhong Q, Hu D, Cheng D (2022). A whole-plant economics spectrum including bark functional traits for 59 subtropical woody plant species. Journal of Ecology, 110, 248-261.
[22]	Liang X, Wang D, Ye Q, Zhang J, Liu M, Liu H, Yu K, Wang Y, Hou E, Zhong B, Xu L, Lv T, Peng S, Lu H, Sicard P, et al. (2023). Stomatal responses of terrestrial plants to global change. Nature Communications, 14, 2188. DOI: 10.1038/s41467-023-37934-7.
[23]	Liu C, Sack L, Li Y, Zhang J, Yu K, Zhang Q, He N, Yu G (2023). Relationships of stomatal morphology to the environment across plant communities. Nature Communications, 14, 6629. DOI: 10.1038/s41467-023-42136-2.
[24]	Liu H, Ye Q, Simpson KJ, Cui E, Xia J (2022). Can evolutionary history predict plant plastic responses to climate change? New Phytologist, 235, 1260-1271.
[25]	Liu LB, Xia HJ, Quan XH, Wang YQ (2023). Plant trait-based life strategies of overlapping species vary in different succession stages of subtropical forests, Eastern China. Frontiers in Ecology and Evolution, 10, 1103937. DOI: 10.3389/fevo.2022.1103937.
[26]	Liu RH, Bai JL, Bao H, Nong JL, Zhao JJ, Jiang Y, Liang SC, Li YJ (2020). Variation and correlation in functional traits of main woody plants in the Cyclobalanopsis glauca community in the karst hills of Guilin, southwest China. Chinese Journal of Plant Ecology, 44, 828-841.
	[刘润红, 白金连, 包含, 农娟丽, 赵佳佳, 姜勇, 梁士楚, 李月娟 (2020). 桂林岩溶石山青冈群落主要木本植物功能性状变异与关联. 植物生态学报, 44, 828-841.]
[27]	Liu Z, Hikosaka K, Li F, Jin G (2020). Variations in leaf economics spectrum traits for an evergreen coniferous species: tree size dominates over environment factors. Functional Ecology, 34, 458-467.
[28]	Lobry JR, Bel-Venner MC, Bogdziewicz M, Hacket-Pain A, Venner S (2023). The CV is dead, long live the CV! Methods in Ecology and Evolution, 14, 2780-2786.
[29]	Lü XT, Hu YY, Zhang HY, Wei HW, Hou SL, Yang GJ, Liu ZY, Wang XB (2018). Intraspecific variation drives community-level stoichiometric responses to nitrogen and water enrichment in a temperate steppe. Plant and Soil, 423, 307-315.
[30]	Luo T, Yu FY, Lian JY, Wang JJ, Shen J, Wu ZF, Ye WH (2022). Impact of canopy vertical height on leaf functional traits in a lower subtropical evergreen broad-leaved forest of Dinghushan. Biodiversity Science, 30, 4-17.
	[罗恬, 俞方圆, 练琚愉, 王俊杰, 申健, 吴志峰, 叶万辉 (2022). 冠层垂直高度对植物叶片功能性状的影响: 以鼎湖山南亚热带常绿阔叶林为例. 生物多样性, 30, 4-17.]
[31]	Martinez-Garcia JF, Rodriguez-Concepcion M (2023). Molecular mechanisms of shade tolerance in plants. New Phytologist, 239, 1190-1202. DOI PMID
[32]	McGill BJ, Enquist BJ, Weiher E, Westoby M (2006). Rebuilding community ecology from functional traits. Trends in Ecology & Evolution, 21, 178-185.
[33]	Meng TT, Ni J, Wang GH (2007). Plant functional traits, environments and ecosystem functioning. Chinese Journal of Plant Ecology (Chinese Version), 31, 150-165.
	[孟婷婷, 倪健, 王国宏 (2007). 植物功能性状与环境和生态系统功能. 植物生态学报, 31, 150-165.] DOI
[34]	Midolo G, De Frenne P, Hölzel N, Wellstein C (2019). Global patterns of intraspecific leaf trait responses to elevation. Global Change Biology, 25, 2485-2498. DOI PMID
[35]	Mouillot D, Graham NAJ, Villéger S, Mason NWH, Bellwood DR (2013). A functional approach reveals community responses to disturbances. Trends in Ecology & Evolution, 28, 167-177.
[36]	Münzbergová Z, Hadincová V, Skálová H, Vandvik V (2017). Genetic differentiation and plasticity interact along temperature and precipitation gradients to determine plant performance under climate change. Journal of Ecology, 105, 1358-1373.
[37]	Niklas KJ, Owens T, Reich PB, Cobb ED (2005). Nitrogen/ phosphorus leaf stoichiometry and the scaling of plant growth. Ecology Letters, 8, 636-642.
[38]	Osnas JLD, Katabuchi M, Kitajima K, Wright SJ, Reich PB, van Bael SA, Kraft NJB, Samaniego MJ, Pacala SW, Lichstein JW (2018). Divergent drivers of leaf trait variation within species, among species, and among functional groups. Proceedings of the National Academy of Sciences of the United States of America, 115, 5480-5485. DOI PMID
[39]	Pérez-Ramos IM, Matías L, Gómez-Aparicio L, Godoy Ó (2019). Functional traits and phenotypic plasticity modulate species coexistence across contrasting climatic conditions. Nature Communications, 10, 2555. DOI: 10.1038/s41467-019-10453-0.
[40]	Piao S, Ciais P, Friedlingstein P, Peylin P, Reichstein M, Luyssaert S, Margolis H, Fang J, Barr A, Chen A, Grelle A, Hollinger DY, Laurila T, Lindroth A, Richardson AD, Vesala T (2008). Net carbon dioxide losses of northern ecosystems in response to autumn warming. Nature, 451, 49-52.
[41]	Plourde BT, Boukili VK, Chazdon RL (2015). Radial changes in wood specific gravity of tropical trees: inter- and intraspecific variation during secondary succession. Functional Ecology, 29, 111-120.
[42]	Poorter L (1999). Growth responses of 15 rain-forest tree species to a light gradient: the relative importance of morphological and physiological traits. Functional Ecology, 13, 396-410.
[43]	Rawat M, Arunachalam K, Arunachalam A, Alatalo JM, Pandey R (2021). Assessment of leaf morphological, physiological, chemical and stoichiometry functional traits for understanding the functioning of Himalayan temperate forest ecosystem. Scientific Reports, 11, 23807. DOI: 10.1038/s41598-021-03235-6.
[44]	Rosas T, Mencuccini M, Barba J, Cochard H, Saura-Mas S, Martínez-Vilalta J (2019). Adjustments and coordination of hydraulic, leaf and stem traits along a water availability gradient. New Phytologist, 223, 632-646. DOI PMID
[45]	Rowe N, Speck T (2005). Plant growth forms: an ecological and evolutionary perspective. New Phytologist, 166, 61-72. PMID
[46]	Sassi R, Bond RR, Cairns A, Finlay DD, Guldenring D, Libretti G, Isola L, Vaglio M, Poeta R, Campana M, Cuccia C, Badilini F (2017). PDF-ECG in clinical practice: a model for long-term preservation of digital 12-lead ECG data. Journal of Electrocardiology, 50, 776-780. DOI PMID
[47]	Spicer ME, Mellor H, Carson WP (2020). Seeing beyond the trees: a comparison of tropical and temperate plant growth forms and their vertical distribution. Ecology, 101, e02974. DOI: 10.1002/ecy.2974.
[48]	Taylor SH, Franks PJ, Hulme SP, Spriggs E, Christin PA, Edwards EJ, Woodward FI, Osborne CP (2012). Photosynthetic pathway and ecological adaptation explain stomatal trait diversity amongst grasses. New Phytologist, 193, 387-396. DOI PMID
[49]	Thakur D, Hadincová V, Schnablová R, Synková H, Haisel D, Wilhelmová N, Dostálek T, Münzbergová Z (2023). Differential effect of climate of origin and cultivation climate on structural and biochemical plant traits. Functional Ecology, 37, 1436-1448.
[50]	Wang CS, Wang SP (2015). A review of research on responses of leaf traits to climate change. Chinese Journal of Plant Ecology, 39, 206-216.
	[王常顺, 汪诗平 (2015). 植物叶片性状对气候变化的响应研究进展. 植物生态学报, 39, 206-216.] DOI
[51]	Wang J, Zhu J, Ai XR, Yao L, Huang X, Wu ML, Zhu Q, Hong JF (2019). Effects of topography on leaf functional traits across plant life forms in Xingdou Mountain, Hubei, China. Chinese Journal of Plant Ecology, 43, 447-457. DOI
	[王进, 朱江, 艾训儒, 姚兰, 黄小, 吴漫玲, 朱强, 洪建峰 (2019). 湖北星斗山地形变化对不同生活型植物叶功能性状的影响. 植物生态学报, 43, 447-457.] DOI
[52]	Wang JL, Wen XF, Zhao FH, Fang QX, Yang XM (2012). Effects of doubled CO₂ concentration on leaf photosynthesis, transpiration and water use efficiency of eight crop species. Chinese Journal of Plant Ecology, 36, 438-446.
	[王建林, 温学发, 赵风华, 房全孝, 杨新民 (2012). CO₂浓度倍增对8种作物叶片光合作用、蒸腾作用和水分利用效率的影响. 植物生态学报, 36, 438-446.] DOI
[53]	Wang ZY, Chen XP, Cheng Y, Wang MT, Zhong QL, Li M, Cheng DL (2021). Leaf and fine root economics spectrum across 49 woody plant species in Wuyi Mountains. Chinese Journal of Plant Ecology, 45, 242-252.
	[王钊颖, 陈晓萍, 程英, 王满堂, 钟全林, 李曼, 程栋梁 (2021). 武夷山49种木本植物叶片与细根经济谱. 植物生态学报, 45, 242-252.]
[54]	Westerband AC, Funk JL, Barton KE (2021). Intraspecific trait variation in plants: a renewed focus on its role in ecological processes. Annals of Botany, 127, 397-410. DOI PMID
[55]	Westoby M, Falster DS, Moles AT, Vesk PA, Wright IJ (2002). Plant ecological strategies: some leading dimensions of variation between species. Annual Review of Ecology and Systematics, 33, 125-159.
[56]	Wright IJ, Ackerly DD, Bongers F, Harms KE, Ibarra- Manriquez G, Martinez-Ramos M, Mazer SJ, Muller- Landau HC, Paz H, Pitman NCA, Poorter L, Silman MR, Vriesendorp CF, Webb CO, Westoby M, et al. (2007). Relationships among ecologically important dimensions of plant trait variation in seven neotropical forests. Annals of Botany, 99, 1003-1015. DOI PMID
[57]	Wright IJ, Dong N, Maire V, Prentice IC, Westoby M, Díaz S, Gallagher RV, Jacobs BF, Kooyman R, Law EA, Leishman MR, Niinemets Ü, Reich PB, Sack L, Villar R, et al. (2017). Global climatic drivers of leaf size. Science, 357, 917-921. DOI PMID
[58]	Wright IJ, Reich PB, Westoby M, Ackerly DD, Baruch Z, Bongers F, Cavender-Bares J, Chapin T, Cornelissen JHC, Diemer M, Flexas J, Garnier E, Groom PK, Gulias J, Hikosaka K, et al. (2004). The worldwide leaf economics spectrum. Nature, 428, 821-827.
[59]	Xun YH, Di XY, Jin GZ (2020). Vertical variation and economic strategy of leaf trait of major tree species in a typical mixed broadleaved-Korean pine forest. Chinese Journal of Plant Ecology, 44, 730-741.
	[荀彦涵, 邸雪颖, 金光泽 (2020). 典型阔叶红松林主要树种叶性状的垂直变异及经济策略. 植物生态学报, 44, 730-741.]
[60]	Yan Z, Sardans J, Peñuelas J, Detto M, Smith NG, Wang H, Guo L, Hughes A, Guo Z, Lee CKF, Liu L, Wu J (2023). Global patterns and drivers of leaf photosynthetic capacity: the relative importance of environmental factors and evolutionary history. Global Ecology and Biogeography, 32, 668-682.
[61]	Ye ZP, Yu Q (2009). Mechanism model of stomatal conductance. Chinese Journal of Plant Ecology, 33, 772-782.
	[叶子飘, 于强 (2009). 植物气孔导度的机理模型. 植物生态学报, 33, 772-782.] DOI
[62]	Zheng SX, Shangguan ZP (2007). Photosynthetic characteristics and their relationships with leaf nitrogen content and leaf mass per area in different plant functional types. Acta Ecologica Sinica, 27, 171-181.
	[郑淑霞, 上官周平 (2007). 不同功能型植物光合特性及其与叶氮含量、比叶重的关系. 生态学报, 27, 171-181.]