Journal of Plant Ecology ›› 2017, Vol. 10 ›› Issue (1): 136-145.

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### Crown and leaf traits as predictors of subtropical tree sapling growth rates

Ying Li1,*, Wenzel Kröber2, Helge Bruelheide2,3, Werner Härdtle1 and Goddert von Oheimb4

1. 1 Faculty of Sustainability, Leuphana University Lüeburg, Institute of Ecology, Scharnhorststraße 1, D-21335 Lüeburg, Germany; 2 Martin Luther University Halle Wittenberg, Institute of Biology/Geobotany and Botanical Garden, Am Kirchtor 1, D-06108 Halle, Germany; 3 German Centre of Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, D-04103 Leipzig, Germany; 4 Faculty of Environmental Sciences, Technische Universität Dresden, Institute of General Ecology and Environmental Protection, Pienner Straße 7, D-01735 Tharandt, Germany
• 收稿日期:2015-07-22 接受日期:2016-05-04 出版日期:2017-02-04 发布日期:2017-01-30

### Crown and leaf traits as predictors of subtropical tree sapling growth rates

Ying Li1,*, Wenzel Kröber2, Helge Bruelheide2,3, Werner Härdtle1 and Goddert von Oheimb4

1. 1 Faculty of Sustainability, Leuphana University Lüeburg, Institute of Ecology, Scharnhorststraße 1, D-21335 Lüeburg, Germany; 2 Martin Luther University Halle Wittenberg, Institute of Biology/Geobotany and Botanical Garden, Am Kirchtor 1, D-06108 Halle, Germany; 3 German Centre of Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, D-04103 Leipzig, Germany; 4 Faculty of Environmental Sciences, Technische Universität Dresden, Institute of General Ecology and Environmental Protection, Pienner Straße 7, D-01735 Tharandt, Germany
• Received:2015-07-22 Accepted:2016-05-04 Online:2017-02-04 Published:2017-01-30
• Contact: Li, Ying

Methods Our study was conducted in a large-scale forest Biodiversity and Ecosystem Functioning experiment in China (BEF-China), located in a mountainous region in Jiangxi Province. We related 17 functional traits (two crown dimension and three crown structure traits; six physiological and six morphological leaf traits) to the mean annual growth rate of wood volume of young trees of the studied species. Interrelationships between crown and leaf traits were analyzed using principal component analysis. Simple linear regression analysis was used to test the effect of each trait separately. We used multiple regression analysis to establish the relationship of growth rate to each set of traits (crown traits, physiological and morphological leaf traits) and to the combination of all types of traits. The coefficients of determination (R 2 adj) of the best multiple regression models were compared to determine the relative explanatory power of crown and leaf traits and a combination of both.
Important findings The species-specific growth rates were not related to any of the single crown traits, but were related positively to leaf stomatal conductance and leaf water potential individually, and negatively to leaf toughness, with approximately 13% variance explained by each of the traits. Combinations of different crown traits did not significantly explain the species-specific growth rates, whereas combinations of either physiological or morphological leaf traits explained 24% and 31%, respectively. A combination of both crown and leaf traits explained 42% of variance in species-specific growth rates. We concluded that sets of traits related to carbon assimilation at the leaf-level and to overall amount of leaves exposed at the crown-level jointly explained species-specific growth rates better than either set of traits alone.

Abstract: Aims Growth rates of plants are driven by factors that influence the amount of resources captured and the efficiency of resource use. In trees, the amount of light captured and the efficiency of light use strongly depends on crown characteristics and leaf traits. Although theory predicts that both crown and leaf traits affect tree growth, few studies have yet to integrate these two types of traits to explain species-specific growth rates. Using 37 broad-leaved tree species of subtropical forests in SE China, we investigated how interspecific differences in wood volume growth rates were affected by crown and leaf traits. We tested the hypotheses that (i) larger crown dimensions promote growth rates, (ii) species-specific growth rates are positively related to leaf stomatal conductance, leaf water potential and leaf chemical components, and negatively related to leaf C/N and leaf toughness and (iii) the two sets of traits better explain growth rates in combination than either alone.
Methods Our study was conducted in a large-scale forest Biodiversity and Ecosystem Functioning experiment in China (BEF-China), located in a mountainous region in Jiangxi Province. We related 17 functional traits (two crown dimension and three crown structure traits; six physiological and six morphological leaf traits) to the mean annual growth rate of wood volume of young trees of the studied species. Interrelationships between crown and leaf traits were analyzed using principal component analysis. Simple linear regression analysis was used to test the effect of each trait separately. We used multiple regression analysis to establish the relationship of growth rate to each set of traits (crown traits, physiological and morphological leaf traits) and to the combination of all types of traits. The coefficients of determination (R 2 adj) of the best multiple regression models were compared to determine the relative explanatory power of crown and leaf traits and a combination of both.
Important findings The species-specific growth rates were not related to any of the single crown traits, but were related positively to leaf stomatal conductance and leaf water potential individually, and negatively to leaf toughness, with approximately 13% variance explained by each of the traits. Combinations of different crown traits did not significantly explain the species-specific growth rates, whereas combinations of either physiological or morphological leaf traits explained 24% and 31%, respectively. A combination of both crown and leaf traits explained 42% of variance in species-specific growth rates. We concluded that sets of traits related to carbon assimilation at the leaf-level and to overall amount of leaves exposed at the crown-level jointly explained species-specific growth rates better than either set of traits alone.