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

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

© 2021 The Authors. New Phytologist © 2021 New Phytologist Foundation.

Détails bibliographiques
Publié dans:The New phytologist. - 1984. - 232(2021), 1 vom: 24. Okt., Seite 134-147
Auteur principal: Yan, Zhengbing (Auteur)
Autres auteurs: Guo, Zhengfei, Serbin, Shawn P, Song, Guangqin, Zhao, Yingyi, Chen, Yang, Wu, Shengbiao, Wang, Jing, Wang, Xin, Li, Jing, Wang, Bin, Wu, Yuntao, Su, Yanjun, Wang, Han, Rogers, Alistair, Liu, Lingli, Wu, Jin
Format: Article en ligne
Langue:English
Publié: 2021
Accès à la collection:The New phytologist
Sujets:Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. gas exchange leaf hyperspectral reflectance maximum carboxylation capacity multitrait covariance partial least-squares regression (PLSR) plant functional traits vegetation spectroscopy plus... Chlorophyll 1406-65-1 Nitrogen N762921K75
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100 1 |a Yan, Zhengbing  |e verfasserin  |4 aut 
245 1 0 |a Spectroscopy outperforms leaf trait relationships for predicting photosynthetic capacity across different forest types 
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500 |a Date Completed 09.09.2021 
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500 |a Citation Status MEDLINE 
520 |a © 2021 The Authors. New Phytologist © 2021 New Phytologist Foundation. 
520 |a Leaf trait relationships are widely used to predict ecosystem function in terrestrial biosphere models (TBMs), in which leaf maximum carboxylation capacity (Vc,max ), an important trait for modelling photosynthesis, can be inferred from other easier-to-measure traits. However, whether trait-Vc,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 (Vc,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 Vc,max and the four morphological and biochemical traits (R2  ≤ 0.15), indicated by significantly changing slopes and intercepts across forest types. By contrast, reflectance spectroscopy effectively collapsed the differences in the trait-Vc,max relationships across three forest biomes into a single robust model for Vc,max (R2  = 0.77), and also accurately estimated the four traits (R2  = 0.75-0.94). These findings challenge the traditional use of the empirical trait-Vc,max relationships in TBMs for estimating terrestrial plant photosynthesis, but also highlight spectroscopy as an efficient alternative for characterising Vc,max and multitrait variability, with critical insights into ecosystem modelling and functional trait ecology 
650 4 |a Journal Article 
650 4 |a Research Support, Non-U.S. Gov't 
650 4 |a Research Support, U.S. Gov't, Non-P.H.S. 
650 4 |a gas exchange 
650 4 |a leaf hyperspectral reflectance 
650 4 |a maximum carboxylation capacity 
650 4 |a multitrait covariance 
650 4 |a partial least-squares regression (PLSR) 
650 4 |a plant functional traits 
650 4 |a vegetation spectroscopy 
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700 1 |a Guo, Zhengfei  |e verfasserin  |4 aut 
700 1 |a Serbin, Shawn P  |e verfasserin  |4 aut 
700 1 |a Song, Guangqin  |e verfasserin  |4 aut 
700 1 |a Zhao, Yingyi  |e verfasserin  |4 aut 
700 1 |a Chen, Yang  |e verfasserin  |4 aut 
700 1 |a Wu, Shengbiao  |e verfasserin  |4 aut 
700 1 |a Wang, Jing  |e verfasserin  |4 aut 
700 1 |a Wang, Xin  |e verfasserin  |4 aut 
700 1 |a Li, Jing  |e verfasserin  |4 aut 
700 1 |a Wang, Bin  |e verfasserin  |4 aut 
700 1 |a Wu, Yuntao  |e verfasserin  |4 aut 
700 1 |a Su, Yanjun  |e verfasserin  |4 aut 
700 1 |a Wang, Han  |e verfasserin  |4 aut 
700 1 |a Rogers, Alistair  |e verfasserin  |4 aut 
700 1 |a Liu, Lingli  |e verfasserin  |4 aut 
700 1 |a Wu, Jin  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t The New phytologist  |d 1984  |g 232(2021), 1 vom: 24. Okt., Seite 134-147  |w (DE-627)NLM09818248X  |x 1469-8137  |7 nnas 
773 1 8 |g volume:232  |g year:2021  |g number:1  |g day:24  |g month:10  |g pages:134-147 
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