Temperature dependence of carbon metabolism in the leaves in sun and shade in a subtropical forest.

Rising temperatures pose a threat to the stability of climate regulation by carbon metabolism in subtropical forests. Although the effects of temperature on leaf carbon metabolism traits in sun-exposed leaves are well understood, there is limited knowledge about its impacts on shade leaves and the implications for ecosystem-climate feedbacks. In this study, we measured temperature response curves of photosynthesis and respiration for 62 woody species in summer (including both evergreen and deciduous species) and 20 evergreen species in winter. The aim was to uncover the temperature dependence of carbon metabolism in both sun and shade leaves in subtropical forests. Our findings reveal that shade had no significant effects on the mean optimum photosynthetic temperatures (T) or temperature range (T). However, there were decreases observed in mean stomatal conductance, mean area-based photosynthetic rates at T and 25 °C, as well as mean area-based dark respiration rates at 25 °C in both evergreen and deciduous species. Moreover, the respiration-temperature sensitivity (Q) of sun leaves was higher than that of shade leaves in winter, with the reverse being true in summer. Leaf economics spectrum traits, such as leaf mass per area, and leaf concentration of nitrogen and phosphorus across species, proved to be good predictors of T, T, mass-based photosynthetic rate at T, and mass-based photosynthetic and respiration rate at 25 °C. However, Q was poorly predicted by these leaf economics spectrum traits except for shade leaves in winter. Our results suggest that model estimates of carbon metabolism in multilayered subtropical forest canopies do not necessitate independent parameterization of T and T temperature responses in sun and shade leaves. Nevertheless, a deeper understanding and quantification of canopy variations in Q responses to temperature are necessary to confirm the generality of temperature-carbon metabolism trait responses and enhance ecosystem model estimates of carbon dynamics under future climate warming.