Biomass allocation patterns of Loropetalum chinense

doi:10.17521/cjpe.2016.0217

Abstract

Abstract:

Aims Biomass is the most fundamental quantitative character of an ecosystem. Biomass allocation patterns reflect the strategies of plants to adapt various habitat conditions and play a vital role in evolution, biodiversity conservation and global carbon cycle. Loropetalum chinense shrub is one of the most dominant shrub types in subtropical China. The objectives of this study were to quantify the allometric relationships and the biomass allocation pattern among organs, and to investigate the effects of body size, shrub regeneration origin and site factors on allometry and biomass allocation.
Methods Individual samples of L. chinense were harvested from shrublands in subtropical China and were further divided into leaves, stems and roots. The allometric relationships between different organs were modeled with standard major axis (SMA) regression and the biomass allocation to different organs was quantified. The effects of body size, shrub regeneration origin and other habitat factors on allometry and allocation were examined using Pearson’s correlation analysis and multiple linear regressions.
Important findings The isometric scaling relationships between shoot and root changed to allometric relationships with increasing basal diameter. The scaling relationships between leaf and stem and between leaf and root were isometric for smaller diameter classes, while for larger diameter classes they were allometric. These relationships were significantly different among shrub regeneration origin types. The scaling relationships between different organs were not affected by habitat factors; while the coverage of shrub layer and slope affected biomass allocation due to their influences on the allometric relationships between different organs at the initial stage of growth. The mean dry mass ratios of leaf, stem, root and the mean root to shoot ratio were 0.11, 0.55, 0.34 and 0.65, respectively. With the increase of basal diameter class, stem mass ratio (0.50-0.64) increased, while leaf mass ratio (0.12-0.08) and root mass ratio (0.38-0.28) decreased, and consequently root to shoot ratio (0.91-0.43) also decreased. In secondary shrublands, the leaf mass ratio was 0.12 and the root mass ratio was 0.33, while these values were 0.07 and 0.36 respectively in natural shrublands. The ratio of aboveground allocation was significantly correlated to shrub layer coverage (r = 0.44, p < 0.05). Leaf mass ratio was significantly correlated to slope (r = -0.36, p < 0.05) and root mass ratio was significantly correlated to mean annual temperature (r = 0.34, p < 0.05). Results showed that with the increase of body size, the scaling relationships between different organs of L. chinense changed from isometric to allometric, and more biomass was allocated to aboveground part, and concretely, to stems. Human disturbance affected biomass allocation by its influences on the allometric relationships between different organs, and by increasing biomass allocation to leaves and decreasing allocation to roots. Reduced light resource promoted the biomass allocation to aboveground part, and higher slope resulted in decreased biomass allocation to leaves, while higher mean annual temperature promoted biomass allocation to roots. The variation in annual precipitation had no significant influences on biomass allocation. The biomass allocation strategies of L. chinense partially support the optimal partitioning theory.

http://jtp.cnki.net/bilingual/detail/html/ZWSB201701012

Key words: allometry, shrublands, subtropicalm zone, habitat factor, root/shoot ratio

Yang WANG, Wen-Ting XU, Gao-Ming XIONG, Jia-Xiang LI, Chang-Ming ZHAO, Zhi-Jun LU, Yue-Lin LI, Zong-Qiang XIE. Biomass allocation patterns of Loropetalum chinense[J]. Chin J Plant Ecol, 2017, 41(1): 105-114.

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URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2016.0217

https://www.plant-ecology.com/EN/Y2017/V41/I1/105

Figures/Tables 8

References 29

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径级 Diameter class	样本数 n	回归常数 Regression constant			尺度系数 Scaling coefficient			p	R²
径级 Diameter class	样本数 n	α	置信下限 Lower CI	置信上限 Upper CI	β	置信下限 Lower CI	置信上限 Upper CI	p	R²
地上-根 M_A-M_R
A	96	0.125	-0.090	0.341	0.945	0.846	1.057	<0.001	0.704
B	136	0.272	0.136	0.407	0.979	0.879	1.090	<0.001	0.601
C	63	0.355	0.186	0.524	0.927	0.750	1.147	<0.001	0.300
D	32	0.429	0.311	0.546	0.975	0.724	1.313	<0.001	0.343
叶-茎 M_L-M_S
A	96	-0.601	-0.774	-0.429	1.029	0.943	1.124	<0.001	0.815
B	136	-0.690	-0.826	-0.554	1.089	0.970	1.221	<0.001	0.546
C	63	-0.733	-0.876	-0.589	1.268	1.031	1.559	<0.001	0.339
D	32	-1.047	-1.168	-0.926	1.681	1.311	2.157	<0.001	0.545
叶-根 M_L-M_R
A	96	-0.556	-0.802	-0.311	0.983	0.870	1.110	<0.001	0.644
B	136	-0.446	-0.629	-0.262	1.096	0.963	1.247	<0.001	0.422
C	63	-0.332	-0.582	-0.082	1.226	0.969	1.551	0.002	0.141
D	32	-0.429	-0.657	-0.201	1.586	1.129	2.227	0.036	0.138

径级 Diameter class	样本数 n	回归常数 Regression constant			尺度系数 Scaling coefficient			p	R²
径级 Diameter class	样本数 n	α	置信下限 Lower CI	置信上限 Upper CI	β	置信下限 Lower CI	置信上限 Upper CI	p	R²
地上-根 M_A-M_R
A	96	0.125	-0.090	0.341	0.945	0.846	1.057	<0.001	0.704
B	136	0.272	0.136	0.407	0.979	0.879	1.090	<0.001	0.601
C	63	0.355	0.186	0.524	0.927	0.750	1.147	<0.001	0.300
D	32	0.429	0.311	0.546	0.975	0.724	1.313	<0.001	0.343
叶-茎 M_L-M_S
A	96	-0.601	-0.774	-0.429	1.029	0.943	1.124	<0.001	0.815
B	136	-0.690	-0.826	-0.554	1.089	0.970	1.221	<0.001	0.546
C	63	-0.733	-0.876	-0.589	1.268	1.031	1.559	<0.001	0.339
D	32	-1.047	-1.168	-0.926	1.681	1.311	2.157	<0.001	0.545
叶-根 M_L-M_R
A	96	-0.556	-0.802	-0.311	0.983	0.870	1.110	<0.001	0.644
B	136	-0.446	-0.629	-0.262	1.096	0.963	1.247	<0.001	0.422
C	63	-0.332	-0.582	-0.082	1.226	0.969	1.551	0.002	0.141
D	32	-0.429	-0.657	-0.201	1.586	1.129	2.227	0.036	0.138

起源 Origin	样本数 n	回归常数 Regression constant			尺度系数 Scaling coefficient			p	R²
起源 Origin	样本数 n	α	置信下限 Lower CI	置信上限 Upper CI	β	置信下限 Lower CI	置信上限 Upper CI	p	R²
地上-根 M_A-M_R
次生 Secondary	209	0.376	0.296	0.455	1.032	0.977	1.090	<0.001	0.840
原生 Primary	118	0.396	0.269	0.522	1.097	1.015	1.185	<0.001	0.822
叶-茎 M_L-M_S
次生 Secondary	209	-0.745	-0.809	-0.681	0.949	0.898	1.002	<0.001	0.840
原生 Primary	118	-1.049	-1.129	-0.970	0.876	0.819	0.937	<0.001	0.867
叶-根 M_L-M_R
次生 Secondary	209	-0.449	-0.549	-0.349	1.002	0.934	1.075	<0.001	0.735
原生 Primary	118	-0.726	-0.853	-0.600	0.983	0.902	1.072	<0.001	0.779

起源 Origin	样本数 n	回归常数 Regression constant			尺度系数 Scaling coefficient			p	R²
起源 Origin	样本数 n	α	置信下限 Lower CI	置信上限 Upper CI	β	置信下限 Lower CI	置信上限 Upper CI	p	R²
地上-根 M_A-M_R
次生 Secondary	209	0.376	0.296	0.455	1.032	0.977	1.090	<0.001	0.840
原生 Primary	118	0.396	0.269	0.522	1.097	1.015	1.185	<0.001	0.822
叶-茎 M_L-M_S
次生 Secondary	209	-0.745	-0.809	-0.681	0.949	0.898	1.002	<0.001	0.840
原生 Primary	118	-1.049	-1.129	-0.970	0.876	0.819	0.937	<0.001	0.867
叶-根 M_L-M_R
次生 Secondary	209	-0.449	-0.549	-0.349	1.002	0.934	1.075	<0.001	0.735
原生 Primary	118	-0.726	-0.853	-0.600	0.983	0.902	1.072	<0.001	0.779