In the photosynthesis model,the photosynthetic capacity of plants is typically characterized by the maximum carbon assimilation rate (A_max),apparent quantum yield (AQY),maximum carboxylation rate (V_cmax),and maximum electron transfer rate (J_max). The mechanisms by which leaf traits influence photosynthetic capacity parameters of different types of plants at the interspecific scale remain unclear. In this study,we used a Li-6800 portable photosynthesis analyzer to measure the light response curves and carbon dioxide response curves of 26 woody plants in Tongluo Mountain during the peak growing season. Four photosynthetic capacity parameters (i.e.,A_max,AQY,V_cmax, and J_max) were further calculated,and eight leaf traits,including leaf nitrogen content per area (N_area),leaf carbon content per area (C_area),ratio of leaf carbon to nitrogen content (C ∶ N),chlorophyll content (Chl),leaf relative water content (LRWC),leaf mass per area (LMA),leaf thickness (L_t),and leaf dry matter content (LDMC) were simultaneously measured. These measurements aimed to explore the interspecific relationships between photosynthetic capacity parameters and leaf traits of woody plants in Tongluo Mountain. The results showed that the variation ranges of A_max,AQY,V_cmax,and J_max of 26 woody plants were 3.35-18.85 μmol m^-2 s^-1,0.009-0.066 mol/mol,10.05-81.89 μmol m^-2 s^-1,and 33.45-140.92 μmol m^-2 s^-1,respectively. The average inter-species variation coefficient of photosynthetic capacity parameters was 47.7%,and the degree of interspecific variation was higher than the average inter-species variation coefficient of 26.9% for leaf traits. There was no significant difference in leaf photosynthetic capacity between trees and shrubs,while deciduous plants had significantly higher photosynthetic capacity than evergreen plants. The photosynthetic capacity parameters were significantly positively correlated with N_area and LRWC,and significantly negatively correlated with C ∶ N. N_area was the best leaf trait for estimating plant photosynthetic capacity,but in evergreen plants,N_area's predictive ability for the four photosynthetic capacity parameters was lower than LRWC. N_area mainly indirectly affected AQY,V_cmax,and J_max by directly affecting V_cmax,while LRWC indirectly affected AQY and A_max by directly affecting V_cmax and J_max. Overall,the multiple linear regression model based on N_area,LRWC,and C ∶ N showed a higher coefficient of determination than any single leaf trait prediction model. Under all plant type conditions,its coefficient of determination was above 0.7,indicating its good predictive ability. The results of this study will provide a theoretical basis for improving the estimation model of photosynthetic capacity of evergreen deciduous broad-leaved forest plants in subtropical regions.