Spectroscopy outperforms leaf trait relationships for predicting photosynthetic capacity across different forest types

doi:10.1111/nph.17579

	Spectroscopy outperforms leaf trait relationships for predicting photosynthetic capacity across different forest types
	Yan, Zhengbing ; Guo, Zhengfei ; Serbin, Shawn P.; Song, Guangqin ; Zhao, Yingyi ; Chen, Yang ; Wu, Shengbiao ; Wang, Jing ; Wang, Xin 2; Li, Jing 2,3; Wang, Bin 2,3; Wu, Yuntao 2,3; Su, Yanjun 2,3; Wang, Han 4,5; Rogers, Alistair 1; Liu, Lingli2,3 ; Wu, Jin
	2021
发表期刊	NEW PHYTOLOGIST
ISSN	0028-646X
卷号	232 期号:1 页码:134-147
摘要	Leaf trait relationships are widely used to predict ecosystem function in terrestrial biosphere models (TBMs), in which leaf maximum carboxylation capacity (V-c,V-max), an important trait for modelling photosynthesis, can be inferred from other easier-to-measure traits. However, whether trait-V-c,V-max relationships are robust across different forest types remains unclear. Here we used measurements of leaf traits, including one morphological trait (leaf mass per area), three biochemical traits (leaf water content, area-based leaf nitrogen content, and leaf chlorophyll content), one physiological trait (V-c,V-max), as well as leaf reflectance spectra, and explored their relationships within and across three contrasting forest types in China. We found weak and forest type-specific relationships between V-c,V-max and the four morphological and biochemical traits (R-2 <= 0.15), indicated by significantly changing slopes and intercepts across forest types. By contrast, reflectance spectroscopy effectively collapsed the differences in the trait-V-c,V-max relationships across three forest biomes into a single robust model for V-c,V-max (R-2 = 0.77), and also accurately estimated the four traits (R-2 = 0.75-0.94). These findings challenge the traditional use of the empirical trait-V-c,V-max relationships in TBMs for estimating terrestrial plant photosynthesis, but also highlight spectroscopy as an efficient alternative for characterising V-c,V-max and multitrait variability, with critical insights into ecosystem modelling and functional trait ecology.
关键词	gas exchange leaf hyperspectral reflectance maximum carboxylation capacity multitrait covariance partial least-squares regression (PLSR) plant functional traits vegetation spectroscopy
学科领域	Plant Sciences
DOI	10.1111/nph.17579
收录类别	SCI
语种	英语
WOS关键词	IMAGING SPECTROSCOPY ; PHYSIOLOGICAL TRAITS ; CO2 ASSIMILATION ; NITROGEN-CONTENT ; V-CMAX ; CANOPY ; PLANT ; REFLECTANCE ; VEGETATION ; TEMPERATE
WOS研究方向	Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号	WOS:000674041900001
出版者	WILEY
文献子类	Article
出版地	HOBOKEN
EISSN	1469-8137
资助机构	National Natural Science Foundation of China [31922090, 31901086] ; Research Grants Council Early Career Scheme [27306020] ; Seed Fund for Basic Research [201905159005] ; Division of Ecology and Biodiversity PDF research award ; Next-Generation Ecosystem Experiments (NGEE Tropics) project - Office of Biological and Environmental Research in the Department of Energy, Office of Science ; United States Department of Energy [DE-SC0012704]
作者邮箱	jinwu@hku.hk
作品OA属性	Green Submitted
引用统计	被引频次：14[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ibcas.ac.cn/handle/2S10CLM1/26334
专题	植被与环境变化国家重点实验室
作者单位	1.Univ Hong Kong, Sch Biol Sci, Div Ecol & Biodivers, Pokfulam Rd, Hong Kong, Peoples R China 2.Brookhaven Natl Lab, Environm & Climate Sci Dept, Upton, NY 11973 USA 3.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.Tsinghua Univ, Dept Earth Syst Sci, Key Lab Earth Syst Modelling, Minist Educ, Beijing 100084, Peoples R China 6.Tsinghua Univ, Joint Ctr Global Change Studies, Beijing 100084, Peoples R China
推荐引用方式 GB/T 7714	Yan, Zhengbing,Guo, Zhengfei,Serbin, Shawn P.,et al. Spectroscopy outperforms leaf trait relationships for predicting photosynthetic capacity across different forest types[J]. NEW PHYTOLOGIST,2021,232(1):134-147.
APA	Yan, Zhengbing.,Guo, Zhengfei.,Serbin, Shawn P..,Song, Guangqin.,Zhao, Yingyi.,...&Wu, Jin.(2021).Spectroscopy outperforms leaf trait relationships for predicting photosynthetic capacity across different forest types.NEW PHYTOLOGIST,232(1),134-147.
MLA	Yan, Zhengbing,et al."Spectroscopy outperforms leaf trait relationships for predicting photosynthetic capacity across different forest types".NEW PHYTOLOGIST 232.1(2021):134-147.

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