Please use this identifier to cite or link to this item: https://doi.org/10.1111/pce.14997
Title: Seasonal variation in the relationship between leaf chlorophyll content and photosynthetic capacity
Authors: Yu, Liyao 
Luo, Xiangzhong 
Croft, Holly
Rogers, Cheryl A
Chen, Jing M
Keywords: chlorophyll fluorescence
Jmax
light acclimation
optimality theory
Vcmax
Issue Date: 7-Jun-2024
Publisher: Wiley
Citation: Yu, Liyao, Luo, Xiangzhong, Croft, Holly, Rogers, Cheryl A, Chen, Jing M (2024-06-07). Seasonal variation in the relationship between leaf chlorophyll content and photosynthetic capacity. Plant, Cell & Environment. ScholarBank@NUS Repository. https://doi.org/10.1111/pce.14997
Abstract: Accurate estimation of photosynthesis is crucial for ecosystem carbon cycle modelling. Previous studies have established an empirical relationship between photosynthetic capacity (maximum carboxylation rate, Vcmax; maximum electron transport rate, Jmax) and leaf chlorophyll (Chl) content to infer global photosynthetic capacity. However, the basis for the Chl‐Vcmax relationship remains unclear, which is further evidenced by the temporal variations in the Chl‐Vcmax relationship. Using multiple years of observations of four deciduous tree species, we found that Vcmax and Jmax acclimate to photosynthetically active radiation faster (4–8 weeks) than Chl (10–12 weeks). This mismatch in temporal scales causes seasonality in the Vcmax‐Chl relationship. To account for the mismatch, we used a Chl fluorescence parameter (quantum yield of Photosystem II, Φ(II)) to tighten the relationship and found Φ(II) × Chl correlated with Vcmax and Jmax (r 2 = 0.74 and 0.72 respectively) better than only Chl (r 2 = 0.7 and 0.6 respectively). It indicates that Φ(II) accounts for the short‐ term adjustment of leaf photosynthetic capacity to light, which was not captured by Chl. Our study advances our understanding of the ecophysiological basis for the empirical Vcmax‐Chl relationship and how to better infer Vcmax from Chl and fluorescence, which guides large‐scale photosynthesis simulations using remote sensing.
Source Title: Plant, Cell & Environment
URI: https://scholarbank.nus.edu.sg/handle/10635/248754
ISSN: 0140-7791
1365-3040
DOI: 10.1111/pce.14997
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