Forest structural attributes as indicators and mediators of aboveground carbon storage and woody plant species richness in natural forests

• Tree carbon and species richness vary across six natural forest types in China. • Forest structure is a strong predictor of tree carbon and woody species richness. • Topsoil carbon is mainly shaped by environmental rather than structural variables. • Forest structure mediates the synergy between carbon storage and biodiversity. • Structural metrics can serve as indicators for multifunctional forest management. Understanding how forest structural attributes influence key ecosystem properties is essential for sustainable forest management. However, empirical evidence remains limited on whether forest structure can reliably indicate both carbon storage and biodiversity across diverse natural forest types. In this study, we examined six large forest dynamics plots representing major forest types in China to assess how forest structure and environmental conditions influence carbon storage in trees and woody plant species richness. Carbon storage in trees was estimated based on tree biomass, and woody species richness was derived from full tree inventories. We characterized forest structure using variation in tree diameter and height, stand basal area, and stem density. Our results show that forest structural complexity is a strong and consistent predictor of both carbon storage in trees and woody plant species richness across forest types. In contrast, topsoil carbon storage was primarily influenced by edaphic and environmental variables, with little association to forest structure. Moreover, we found that structural attributes not only independently influenced carbon and richness, but also mediated the positive relationship between them. These findings highlight forest structure as a robust, measurable, and management-relevant indicator of aboveground ecosystem functions and biodiversity. By identifying structural metrics that are sensitive to management and remotely observable, this study provides a basis for monitoring forest multifunctionality and integrating biodiversity and carbon goals into restoration and conservation planning across natural forest landscapes.