7种木本植物的分支指数与代谢指数

doi:10.3724/SP.J.1258.2014.00055

摘要/Abstract

摘要：

West、Brown和Enquist提出的植物分形网络模型(简称WBE模型)认为: 植物的分支指数(1/a, 1/b)决定植物的代谢指数, 当分支指数1/a、1/b分别为理论值2.0、3.0时, 代谢速率与个体大小的3/4次幂成正比, 但是恒定的3/4代谢指数并不能全面地反映植物的代谢情况。基于分支指数的协同变化, Price、Enquist和Savage对WBE模型进行扩展, 提出植物分支参数协同变化模型(简称PES模型)。该文借助于PES模型分析了7种木本植物的分支指数和代谢指数。结果表明: 物种间叶面积与叶生物量呈异速生长关系, 基于叶面积得到的分支指数1/a和代谢指数θ在物种间无显著差异, 基于叶生物量得到的分支指数1/a、1/b和代谢指数θ在物种间均存在显著差异, 但基于叶面积和叶生物量分别拟合出的整体分支指数1/a、1/b和代谢指数θ与理论值均无显著差异, 且用叶面积作为代谢速率的替代指标比用叶生物量分析得出的代谢指数与理论值更接近。今后研究应当关注植物叶面积与叶生物量的异速生长关系对植物代谢速率及相关功能特性的影响。

关键词: 异速生长, 分支指数, 叶面积, PES模型, WBE模型

Abstract:

Aims The fractal-like network model of plants (the WBE model) considers that the branching exponents 1/a and 1/b determine the metabolic exponent θ in plants. However, the constant 3/4 metabolic exponent does not completely reflect the plant metabolic scaling. Price, Enquist and Savage extended the WBE model by assuming that branching exponents are not constant but covary with each other, and developed the branching traits covariation model of plants (the PES model). In this paper, we study and compare branching exponents and metabolic exponents in seven woody plants based on leaf area and leaf biomass by using the PES model.
Methods To test the PES model, data on leaf area and leaf biomass of seven woody species were used to determine the values of branching and metabolic exponents. Standardized major axis (SMA) regression protocols were used to determine the numerical values of scaling exponents and normalization constants for each species and across the seven species using the software SMATR. Furthermore, test of a common slope across all species and comparisons between the estimated values and theoretical values proposed by the WBE model were also performed by using the SMATR. Specifically, if the value of p exceeds a critical level, then it is considered that there would be no significant differences among the groups compared and that a common slope can be determined; if the value of p is below the critical level, then it would indicate that the estimated value would be significantly different from the theoretical value.
Important findings Significant allometric relationships between leaf area and leaf biomass were verified within and across species. Specifically, leaf area scaled as 0.86-power of leaf biomass across the entire data sets. Therefore, values of branching and metabolic exponents were determined by using leaf biomass and leaf area separately. Values of the branching exponent 1/a and the metabolic exponent θ based on leaf area were statistically indistinguishable among the seven woody species. On the contrary, values of the branching exponents 1/a and 1/b and the metabolic exponent θ based on leaf biomass differed significantly among the seven woody species. Values of the branching exponents and the metabolic exponent estimated from both leaf area and leaf biomass across the entire data set were all statistically indistinguishable from the theoretical values. Furthermore, compared with the value of metabolic exponent based on leaf biomass, the value of metabolic exponent based on leaf area was statistically more comparable to the theoretical value. The effect of allometric relationship between leaf area and leaf biomass on metabolic rate and relative functional traits of plants should be paid more attention in future research.

Key words: allometry, branching exponent, leaf area, PES model, WBE model

马玉珠,程栋梁,钟全林,靳冰洁,林江铭,卢宏典,郭炳桥. 7种木本植物的分支指数与代谢指数. 植物生态学报, 2014, 38(6): 599-607. DOI: 10.3724/SP.J.1258.2014.00055

MA Yu-Zhu,CHENG Dong-Liang,ZHONG Quan-Lin,JIN Bing-Jie,LIN Jiang-Ming,LU Hong-Dian,GUO Bing-Qiao. Branching and metabolic exponents in seven woody plants. Chinese Journal of Plant Ecology, 2014, 38(6): 599-607. DOI: 10.3724/SP.J.1258.2014.00055

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.plant-ecology.com/CN/10.3724/SP.J.1258.2014.00055

https://www.plant-ecology.com/CN/Y2014/V38/I6/599

图/表 7

参考文献 33

[1]	Ackerly DD, Knight CA, Weiss SB, Barton K, Starmer KP (2002). Leaf size, specific leaf area and microhabitat distribution of chaparral woody plants: contrasting patterns in species level and community level analyses. Oecologia, 130, 449-457. URL PMID
[2]	Bentley LP, Stegen JC, Savage VM, Smith DD, von Allmen EI, Sperry JS, Reich PB, Enquist BJ (2013). An empirical assessment of tree branching networks and implications for plant allometric scaling models. Ecology Letters, 16, 1069-1078. URL PMID
[3]	Brown JH, Gillooly JF, Allen AP, Savage VM, West GB (2004). Toward a metabolic theory of ecology. Ecology, 85, 1771-1789. DOI URL
[4]	Cheng DL, Li T, Zhong QL, Wang GX (2010). Scaling relationship between tree respiration rates and biomass. Biology Letters, 6, 715-717. URL PMID
[5]	Deng JM, Wang GX, Wei XP (2006). The advance of metabolic regulation studies for macroscopical ecology processes. Acta Ecologica Sinica, 26, 3413-3423. (in Chinese with English abstract)
	[ 邓建明, 王根轩, 魏小平 (2006). 宏观生态过程的代谢调控研究进展. 生态学报, 26, 3413-3423.]
[6]	Enquist BJ, Allen AP, Brown JH, Gillooly JF, Kerkhoff AJ, Niklas KJ, Price CA, West GB (2007). Biological scaling: Does the exception prove the rule? Nature, 445, E9-E10. URL PMID
[7]	Enquist BJ, Brown JH, West GB (1998). Allometric scaling of plant energetics and population density. Nature, 395, 163-165. DOI URL
[8]	Enquist BJ, Niklas KJ (2002). Global allocation rules for patterns of biomass partitioning in seed plants. Science, 295, 1517-1520. DOI URL PMID
[9]	Enquist BJ, West GB, Charnov EL, Brown JH (1999). Allometric scaling of production and life-history variation in vascular plants. Nature, 401, 907-911. DOI URL
[10]	Falster DS, Warton DI, Wright IJ (2003). (S)MATR: Standardised major axis tests and routines. http://www.bio.mq.edu.au/ecology/SMATR. Cited 2013-05-09.
[11]	Glazier DS (2005). Beyond the ‘3/4-power law’: variation in the intra-and interspecific scaling of metabolic rate in animals. Biological Reviews, 80, 611-662. URL PMID
[12]	Glazier DS (2006). The 3/4-power law is not universal: evolution of isometric, ontogenetic metabolic scaling in pelagic animals. BioScience, 56, 325-332. DOI URL
[13]	Glazier DS (2010). A unifying explanation for diverse metabolic scaling in animals and plants. Biological Reviews, 85, 111-138. DOI URL PMID
[14]	Koontz TL, Petroff A, West GB, Brown JH (2009). Scaling relations for a functionally two-dimensional plant: Chamaesyce setiloba (Euphorbiaceae). American Journal of Botany, 96, 877-884. DOI URL PMID
[15]	Li HT, Han XG, Wu JG (2005). Lack of evidence for 3/4 scaling of metabolism in terrestrial plants. Journal of Integrative Plant Biology, 47, 1173-1183. DOI URL
[16]	Mäkelä A, Valentine HT (2006). Crown ratio influences allometric scaling in trees. Ecology, 87, 2967-2972. URL PMID
[17]	Martin JG, Kloeppel BD, Schaefer TL, Kimbler DL, McNulty SG (1998). Aboveground biomass and nitrogen allocation of ten deciduous southern Appalachian tree species. Canadian Journal of Forest Research, 28, 1648-1659. DOI URL
[18]	Mori S, Yamaji K, Ishida A, Prokushkin SG, Masyagina OV, Hagihara A, Hoque ATMR, Suwa R, Osawa A, Nishizono T, Ueda T, Kinjo M, Miyagi T, Kajimoto T, Koike T, Matsuura Y, Toma T, Zyryanova OA, Abaimov AP, Awaya Y, Araki MG, Kawasaki T, Chiba Y, Umari M (2010). Mixed-power scaling of whole-plant respiration from seedings to giant trees. Proceedings of the National Academy of Sciences of the United States of America, 107, 1447-1451. URL PMID
[19]	Niklas KJ, Cobb ED (2008). Evidence for “diminishing returns” from the scaling of stem diameter and specific leaf area. American Journal of Botany, 95, 549-557. DOI URL PMID
[20]	Niklas KJ, Cobb ED, Niinemets Ü, Reich PB, Sellin A, Shipley B, Wright IJ (2007). “Diminishing returns” in the scaling of functional leaf traits across and within species groups. Proceedings of the National Academy of Sciences of the United States of America, 104, 8891-8896. DOI URL PMID
[21]	Niklas KJ, Enquist BJ (2001). Invariant scaling relationships for interspecific plant biomass production rates and body size. Proceeding of the National Academy of Sciences of the United States of America, 98, 2922-2927.
[22]	Pan S, Liu C, Zhang WP, Xu SS, Wang N, Li Y, Gao J, Wang Y, Wang GX (2013). The scaling relationships between leaf mass and leaf area of vascular plant species change with altitude. PLoS ONE, 8, e76872. DOI URL PMID
[23]	Peng YH, Niklas KJ, Reich PB, Sun SC (2010). Ontogenetic shift in the scaling of dark respiration with whole-plant mass in seven shrub species. Functional Ecology, 24, 502-512. DOI URL
[24]	Price CA, Enquist BJ, Savage VM (2007). A general model for allometric covariation in botanical form and function. Proceedings of the National Academy of Sciences of the United States of America, 104, 13204-13209. DOI URL PMID
[25]	Price CA, Ogle K, White EP, Weitz JS (2009). Evaluating scaling models in biology using hierarchical Bayesian approaches. Ecology Letters, 12, 641-651. DOI URL PMID
[26]	Reich PB, Tjoelker MG, Machado JL, Oleksyn J (2006). Universal scaling of respiratory metabolism, size and nitrogen in plants. Nature, 439, 457-461. DOI URL PMID
[27]	Savage VM, Deeds EJ, Fontana W (2008). Sizing up allometric scaling theory. PLoS Computational Biology, 4, e1000171. URL PMID
[28]	Wang JF, Feng YL (2004). The effect of light intensity on biomass allocation, leaf morphology and relative growth rate of two invasive plants. Acta Phytoecologica Sinica, 28, 781-786. (in Chinese with English abstract)
	[ 王俊峰, 冯玉龙 (2004). 光强对两种入侵植物生物量分配、叶片形态和相对生长速率的影响. 植物生态学报, 28, 781-786.]
[29]	Warton DI, Wright IJ, Falster DS, Westoby M (2006). Bivariate line-fitting methods for allometry. Biological Reviews, 81, 259-291. DOI URL PMID
[30]	West GB, Brown JH, Enquist BJ (1997). A general model for the origin of allometric scaling laws in biology. Science, 276, 122-126. URL PMID
[31]	West GB, Brown JH, Enquist BJ (1999a). A general model for the structure and allometry of plant vascular systems. Nature, 400, 664-667. DOI URL
[32]	West GB, Brown JH, Enquist BJ (1999b). The fourth dimension of life: fractal geometry and allometric scaling of organisms. Science, 284, 1677-1679. URL PMID
[33]	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, Lamont BB, Lee T, Lee W, Lusk C, Midgley JJ, Navas ML, Niinemets Ü, Oleksyn J, Osada N, Poorter H, Poot P, Prior L, Pyankov VI, Roumet C, Thomas SC, Tjoelker MG, Veneklaas EJ, Villar R (2004). The worldwide leaf economics spectrum. Nature, 428, 821-827. URL PMID

编辑推荐 0

Metrics

阅读次数

全文

3675

HTML			PDF

最新录用	在线预览	正式出版	最新录用	在线预览	正式出版
0	0	172	0	0	3503

来源	本网站	其他网站

次数	535	3140
比例	15%	85%

摘要

1334

最新录用	在线预览	正式出版

0	0	1334

来源	本网站	其他网站

次数	448	886
比例	34%	66%

物种 Species	数量 n	胸径范围 DBH range (cm)	树高范围 Tree height range (m)	地上生物量范围 Aboveground biomass range (kg)	茎生物量范围 Stem biomass range (kg)	叶生物量范围 Leaf biomass range (kg)	叶面积范围 Leaf area range (m²)
Acer rubrum	11	6-52	10-34	11-2 387	9-1 801	0.4-22.4	6-311
Betula lenta	10	8-40	13-28	15-1 520	14-979	0.2-18.6	10-309
北美鹅掌楸 Liriodendron tulipifera	10	10-56	14-40	27-2 256	24-1 982	0.8-16.7	16-266
Oxydendrum arboreum	8	4-35	5-21	2-416	2-329	0.2-4.4	5-71
Quercus alba	10	7-63	8-32	10-2 740	6-2 343	0.7-43.8	16-443
Quercus prinus	10	11-58	12-30	27-2 990	22-2 614	1.1-28.2	15-289
Quercus rubra	9	20-52	12-29	24-1 750	22-1 340	0.8-40.7	11-444

物种 Species	数量 n	胸径范围 DBH range (cm)	树高范围 Tree height range (m)	地上生物量范围 Aboveground biomass range (kg)	茎生物量范围 Stem biomass range (kg)	叶生物量范围 Leaf biomass range (kg)	叶面积范围 Leaf area range (m²)
Acer rubrum	11	6-52	10-34	11-2 387	9-1 801	0.4-22.4	6-311
Betula lenta	10	8-40	13-28	15-1 520	14-979	0.2-18.6	10-309
北美鹅掌楸 Liriodendron tulipifera	10	10-56	14-40	27-2 256	24-1 982	0.8-16.7	16-266
Oxydendrum arboreum	8	4-35	5-21	2-416	2-329	0.2-4.4	5-71
Quercus alba	10	7-63	8-32	10-2 740	6-2 343	0.7-43.8	16-443
Quercus prinus	10	11-58	12-30	27-2 990	22-2 614	1.1-28.2	15-289
Quercus rubra	9	20-52	12-29	24-1 750	22-1 340	0.8-40.7	11-444

物种 Species	n	叶面积∝叶生物量 Leaf area ∝leaf biomass			地上生物量∝茎生物量 Aboveground biomass ∝stem biomass
物种 Species	n	斜率(95%置信区间) Slope (95% CI )	R²	p__1.0	斜率(95%置信区间) Slope (95% CI )	R²	p__1.0
Acer rubrum	11	0.99^a (0.92, 1.07)	0.989^**	0.756	1.01 (0.98, 1.03)	0.999^**	0.637
Betula lenta	10	0.76^c (0.66, 0.88)	0.968^**	0.002	1.06 (1.02, 1.10)	0.998^**	0.011
北美鹅掌楸 Liriodendron tulipifera	10	0.96^a (0.87, 1.06)	0.986^**	0.365	0.99 (0.96, 1.02)	0.999^**	0.416
Oxydendrum arboreum	8	0.84^ab (0.65, 1.07)	0.937^**	0.129	0.98 (0.94, 1.02)	0.998^**	0.216
Quercus alba	10	0.83^bc (0.75, 0.93)	0.983^**	0.004	0.97 (0.92, 1.01)	0.997^**	0.134
Quercus prinus	10	0.92^ab (0.79, 1.08)	0.962^**	0.274	1.02 (0.95, 1.10)	0.992^**	0.580
Quercus rubra	9	0.93^ab (0.87, 0.99)	0.995^**	0.030	1.01 (0.96, 1.07)	0.996^**	0.637
全部 All	68	0.86 (0.80, 0.92)	0.916^**	<0.001	1.00 (0.98, 1.01)	0.996^**	0.786

物种 Species	n	叶面积∝叶生物量 Leaf area ∝leaf biomass			地上生物量∝茎生物量 Aboveground biomass ∝stem biomass
物种 Species	n	斜率(95%置信区间) Slope (95% CI )	R²	p__1.0	斜率(95%置信区间) Slope (95% CI )	R²	p__1.0
Acer rubrum	11	0.99^a (0.92, 1.07)	0.989^**	0.756	1.01 (0.98, 1.03)	0.999^**	0.637
Betula lenta	10	0.76^c (0.66, 0.88)	0.968^**	0.002	1.06 (1.02, 1.10)	0.998^**	0.011
北美鹅掌楸 Liriodendron tulipifera	10	0.96^a (0.87, 1.06)	0.986^**	0.365	0.99 (0.96, 1.02)	0.999^**	0.416
Oxydendrum arboreum	8	0.84^ab (0.65, 1.07)	0.937^**	0.129	0.98 (0.94, 1.02)	0.998^**	0.216
Quercus alba	10	0.83^bc (0.75, 0.93)	0.983^**	0.004	0.97 (0.92, 1.01)	0.997^**	0.134
Quercus prinus	10	0.92^ab (0.79, 1.08)	0.962^**	0.274	1.02 (0.95, 1.10)	0.992^**	0.580
Quercus rubra	9	0.93^ab (0.87, 0.99)	0.995^**	0.030	1.01 (0.96, 1.07)	0.996^**	0.637
全部 All	68	0.86 (0.80, 0.92)	0.916^**	<0.001	1.00 (0.98, 1.01)	0.996^**	0.786

物种 Species	估测值 Estimated values						计算值 Calculated values
	叶面积∝胸径 Leaf area ∝DBH		叶面积∝树高 Leaf area ∝height		叶面积∝地上生物量 Leaf area ∝aboveground biomass		1/(2a+b)
	分支半径指数1/a (95%置信区间) Branching radius exponent 1/a (95% CI)	p__2.0	分支长度指数1/b (95%置信区间) Branching length exponent 1/b (95% CI)	p__3.0	代谢指数θ (95%置信区间) Metabolic exponent θ (95% CI)	p__0.75	代谢指数θ (95%置信区间) Metabolic exponent θ (95% CI)
Acer rubrum	1.82 (1.52, 2.17)	0.257	3.31^ab (2.51, 4.38)	0.446	0.70 (0.58, 0.86)	0.500	0.71 (0.58, 0.87)
Betula lenta	2.04 (1.76, 2.37)	0.753	4.75^a (3.53, 6.39)	0.007	0.74 (0.66, 0.84)	0.888	0.84 (0.70, 1.00)
北美鹅掌楸 Liriodendron tulipifera	2.03 (1.50, 2.75)	0.919	3.24^ab (2.21, 4.74)	0.664	0.77 (0.55, 1.06)	0.880	0.77 (0.56, 1.07)
Oxydendrum arboreum	1.32 (1.07, 1.64)	0.003	1.86^c (1.21, 2.88)	0.036	0.51 (0.40, 0.64)	0.006	0.49 (0.37, 0.64)
Quercus alba	1.65 (1.01, 2.70)	0.412	2.57^bc (1.62, 4.07)	0.470	0.63 (0.41, 0.97)	0.381	0.62 (0.38, 1.01)
Quercus prinus	2.23 (1.62, 3.08)	0.467	3.95^ab (2.39, 6.54)	0.257	0.76 (0.57, 1.02)	0.906	0.87 (0.60, 1.25)
Quercus rubra	2.27 (1.69, 3.04)	0.346	3.85^ab (2.17, 6.84)	0.357	0.86 (0.61, 1.19)	0.390	0.88 (0.61, 1.24)
全部 All	1.87 (1.69, 2.07)	0.190	2.98 (2.57, 3.45)	0.916	0.70 (0.64, 0.77)	0.188	0.71 (0.63, 0.80)