Understanding the Impact of Vertical Canopy Position on Leaf Spectra and Traits in an Evergreen Broadleaved Forest
文献类型: 外文期刊
第一作者: Yu, Fangyuan
作者: Yu, Fangyuan;Wu, Zhifeng;Gara, Tawanda W.;Lian, Juyu;Ye, Wanhui;Lian, Juyu;Ye, Wanhui;Lian, Juyu;Ye, Wanhui;Lian, Juyu;Ye, Wanhui;Shen, Jian;Wang, Tiejun;Wang, Junjie
作者机构:
关键词: canopy layer; hyperspectral; tower crane; tree species; leaf traits
期刊名称:REMOTE SENSING ( 影响因子:5.349; 五年影响因子:5.786 )
ISSN:
年卷期: 2021 年 13 卷 24 期
页码:
收录情况: SCI
摘要: Little attention has been paid to the impact of vertical canopy position on the leaf spectral properties of tall trees, and few studies have explored the ability of leaf spectra to characterize the variation of leaf traits across different canopy positions. Using a tower crane, we collected leaf samples from three canopy layers (lower, middle, and upper) and measured eight leaf traits (equivalent water thickness, specific leaf area, leaf carbon content, leaf nitrogen content, leaf phosphorus content, leaf chlorophyll content, flavonoid, and nitrogen balance index) in a subtropical evergreen broadleaved forest. We evaluated the variability of leaf traits and leaf spectral properties, as well as the ability of leaf spectra to track the variation of leaf traits among three canopy layers for six species within the entire reflectance spectrum. The results showed that the eight leaf traits that were moderately or highly correlated with each other showed significant differences along the vertical canopy profile. The three canopy layers of leaf spectra showed contrasting patterns for light-demanding (Castanopsis chinensis, Castanopsis fissa, Schima superba, and Machilus chinensis) and shade-tolerant species (Cryptocarya chinensis and Cryptocarya concinna) along the vertical canopy profile. The spectra at the lower and upper canopy layers were more sensitive than the middle layer for tracking the variation of leaf chlorophyll and flavonoid content. Our results revealed that it is important to choose an appropriate canopy layer for the field sampling of tall trees, and we suggest that flavonoid is an important leaf trait that can be used for mapping and monitoring plant growth with hyperspectral remote sensing.
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