Understanding the impact of vertical canopy position on leaf spectra and traits in an evergreen broadleaved forest

Fangyuan Yu, Tawanda Gara, Juyu Lian, Wanhui Ye, Jian Shen, Tiejun Wang, Zhifeng Wu, Junjie Wang* (Corresponding Author)

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)
75 Downloads (Pure)

Abstract

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
Original languageEnglish
Article number5057
Number of pages18
JournalRemote sensing
Volume13
Issue number24
DOIs
Publication statusPublished - 13 Dec 2021

Keywords

  • ITC-ISI-JOURNAL-ARTICLE
  • ITC-GOLD

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