Abstract: The restoration of severely fragmented forests requires urgent guidance from succession theory. New theories and methods in plant functional ecology offer novel perspectives on the mechanisms that drive forest succession and productivity. Here, we established a restoration gradient of seven forest logging periods in temperate forests in China, and conducted systematic surveys on the leaf functional traits of all observed plant species, plant community structure, and soil properties. Inspired by the new concept of two-dimensional plant community traits (i.e., efficiency and quantity traits) and plant trait networks (PTNs), we explored the adaptation mechanisms of forest communities along a restoration succession and their relationship to productivity. Efficiency and quantity traits initially increased and then stabilized, whereas multi-trait relationships (MR) exhibited fluctuations, with community resource utilization efficiency increasing initially before stabilization. As expected, productivity is poorly explained by either efficiency or quantity traits alone but is substantially better explained by their joint consideration as two-dimensional community traits. Among these, the efficiency and quantity traits of leaf area and leaf dry weight can explain up to 43% of productivity. Furthermore, MR exhibit a time-lag effect on productivity. A structural equation model (SEM) with time-lag analysis showed that efficiency traits, quantity traits, MR, and soil properties explained 64% of the spatial variation in productivity during forest succession. Efficiency and quantity traits directly regulated productivity, whereas soil properties and MR indirectly regulated productivity. Our findings are the first to demonstrate the regulation mechanisms between forest succession and productivity from the framework of efficiency traits–quantity traits-MR, providing theoretical guidance and a reference for ecological restoration, and predicting the spatial variation of forest productivity, especially at small scale.

Key words: Forest, Succession, Productivity, Traits, Plant trait network