Parameters of one-variable tree volume model.

Forest productivity reflects forest growth quality and forms the basis for achieving forest service functions. The relationships between forest productivity and stand structure has been extensively studied, but it is still unclear whether environmental factors affect the relationship and how their relationships vary under the influence of stand type and environmental factors. A fixed monitoring dataset from 972 plots of natural mixed forests (including coniferous, broad-leaved, and coniferous and broad-leaved mixed forests) in Zhejiang Province was used. We analyzed the relationship between stand structure diversity (composition diversity and size differentiation diversity) and productivity in the different forest types and their influencing factors. Species richness, coefficient of the diameter at breast height (DBH) variation, and the DBH Shannon‒Wiener index were significantly positively correlated with productivity (P < 0.01). Environmental factors such as terrain and meteorology were associated with stand productivity and structure diversity. Considering the effects of environmental factors and stand density, it was evident that stand density was the primary direct factor influencing coniferous forest productivity ( = 0.635), and terrain exerted a substantial indirect effect on productivity through stand density ( = 0.202). In broad-leaved forests, topography ( = −0.161), size differentiation diversity ( = −0.519), and stand density ( = 0.954) were the primary factors influencing productivity, with climate exerting a significant indirect effect via stand density and size differentiation diversity. In coniferous and broad-leaved mixed forests, stand density ( = 0.862), size differentiation diversity ( = −0.424), and composition diversity ( = 0.260) were all significantly correlated with productivity. The effect of structure diversity on productivity in natural broad-leaved mixed forests in Zhejiang Province was modulated by environmental factors and stand density. Our research deepens understandings of the factors driving productivity in natural broad-leaved mixed forests and offers a theoretical foundation for sustainable development.