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Prediction of photosynthetic light‐response curves using traits of the leaf economics spectrum for 75 woody species: effects of leaf habit and sun–shade dichotomy
Author(s) -
Chen Xiaoping,
Sun Jun,
Lyu Min,
Wang Mantang,
Hu Dandan,
Zhong Quanlin,
Cheng Dongliang
Publication year - 2021
Publication title -
american journal of botany
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.218
H-Index - 151
eISSN - 1537-2197
pISSN - 0002-9122
DOI - 10.1002/ajb2.1629
Subject(s) - evergreen , biology , canopy , deciduous , botany , habit , allometry , leaf size , leaf area index , photosynthetic capacity , photosynthesis , horticulture , ecology , psychology , psychotherapist
Premise Photosynthetic light‐response (PLR) curves for leaves are important components of models related to carbon fixation in forest ecosystems, linking the Mitscherlich equation and Michaelis–Menten equation to traits of the leaf economics spectrum (LES). However, models do not consider changes in leaf habits (i.e., evergreen and deciduous) and within‐canopy shading variation in these PLR curves. Methods Here, we measured the PLR curves in sun and shade leaves of 44 evergreen and 31 deciduous species to examine the relationships between variables of the Mitscherlich equation and Michaelis–Menten equation, leaf nitrogen (N) and phosphorus (P) content, and leaf mass per area (LMA). Results Small changes were caused by different leaf habits and shade variations in relationships linking variables of the two equations to leaf N and P content and LMA. Values of the scaling exponents for PLR curve parameters did not differ regardless of canopy position and leaf habit ( P > 0.05). The PLR curves in species with different leaf habits (i.e., evergreen and deciduous) at different canopy positions could be predicted using the general allometric relations between leaf traits and PLR parameters in the two equations. For photosynthetic photon flux densities from 0 to 2000 μmol m ‐2 s ‐1 , approximately 71% (Mitscherlich equation) and 70% (Michaelis–Menten equation) of the net assimilation rates could be predicted. Conclusions These findings indicate that leaf net assimilation rates can be predicted through the large available data for LES traits. Incorporation of values for these traits available in the LES databases into ecosystem models of forest productivity and carbon fixation warrants further investigation.