Remote Sensing Inversion of Leaf Maximum Carboxylation Rate Based on a Mechanistic Photosynthetic Model

Abstract

The maximum carboxylation rate ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{\mathrm {cmax}}$ </tex-math></inline-formula> ) of a leaf is a rate-limiting step in photosynthesis. A quantitative spatial distribution of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{\mathrm {cmax}}$ </tex-math></inline-formula> is necessary to predictively understand forest gross primary production (GPP). In this study, we propose a new method that combines hyperspectral data with the Farquhar photosynthetic mechanistic model to estimate <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{\mathrm {cmax}}$ </tex-math></inline-formula> . First, the photochemical reflectance index (PRI) of a leaf was calculated, and then a model of PRI and sunlit leaf light-use efficiency (LUE) was constructed to estimate sunlit leaf LUE. Next, sunlit leaf LUE and absorbed photosynthetically active radiation (APAR) were used to estimate the GPP of the sunlit leaf. Finally, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{\mathrm {cmax}}$ </tex-math></inline-formula> was deduced based on the Farquhar mechanistic model by using the GPP of sunlit leaves, and differences in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{\mathrm {cmax}}$ </tex-math></inline-formula> were analyzed across various types of vegetation. The results showed that the coefficient of determination between <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{\mathrm {cmax}}$ </tex-math></inline-formula> estimated using the mechanistic model and the mean <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{\mathrm {cmax}}$ </tex-math></inline-formula> measured at the sampling sites was 0.82, with a root mean square error of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4.27~\mu $ </tex-math></inline-formula> mol <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${}\cdot {}\text{m}^{\mathrm {-2}} {}\cdot {}\text{s}^{\mathrm {-1}}$ </tex-math></inline-formula> . Using a forest-type map of the Mao’er Mountain region as a reference, statistical analysis showed that coniferous forest showed the highest <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{\mathrm {cmax}}$ </tex-math></inline-formula> , followed by coniferous–broadleaf mixed forest, while broad-leaved forest showed the lowest <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{\mathrm {cmax}}$ </tex-math></inline-formula> . The proposed method can generate regional <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$V_{\mathrm {cmax}}$ </tex-math></inline-formula> distribution maps efficiently.