Leaf photosynthetic pigment as a predictor of leaf maximum carboxylation rate in a farmland ecosystem.

The leaf maximum rate of carboxylation (V) is a key parameter of plant photosynthetic capacity. The accurate estimation of V is crucial for correctly predicting the carbon flux in the terrestrial carbon cycle. V is correlated with plant traits including leaf nitrogen (N) and leaf photosynthetic pigments. Proxies for leaf chlorophyll (Chl) and carotenoid contents (Car) need to be explored in different ecosystems. In this study, we evaluated the relationship between leaf maximum rate of carboxylation (scaled to 25°C; V) and both leaf N and photosynthetic pigments (Chl and Car) in winter wheat in a farmland ecosystem. Our results showed that V followed the same trends as leaf Chl. However, leaf N showed smaller dynamic changes before the flowering stage, and there were smaller seasonal variations in leaf Car. The correlation between leaf V and leaf Chl was the strongest, followed by leaf Car and leaf N (R = 0.69, R = 0.47 and R= 0.36, respectively). The random forest regression analysis also showed that leaf Chl and leaf Car were more important than leaf N for V. The correlation between leaf V and N can be weaker since nitrogen allocation is dynamic. The estimation accuracy of the V model based on N, Chl, and Car (R= 0.75) was only 0.05 higher than that of the V model based on Chl and Car (R= 0.70). However, the estimation accuracy of the V model based on Chl and Car (R= 0.70) was 0.34 higher than that of the V model based on N (R= 0.36). These results highlight that leaf photosynthetic pigments can be a predictor for estimating V, expanding a new way to estimate spatially continuous V on a regional scale, and to improve model simulation accuracy.