Biodiversity and ecosystem multifunctionality show contrasting recovery patterns across tropical forests with different logging histories

Globally, a growing proportion of logging‐disturbed tropical forest is recovering, holding great potential for biodiversity conservation and ecosystem functioning. However, how ecosystem multifunctionality (EMF) and its trait‐based predictors in these secondary forests differ from those in old‐growth forests remains unknown. Here, we investigated old‐growth forests and two types of secondary forests (following selective logging and clear‐cutting) in China's Hainan Tropical Rainforest National Park to examine how logging history affects EMF, its relationship with biodiversity, and its trait‐based predictors. After about half a century of recovery, species richness in logged forests approached levels comparable to or even exceeding that of old‐growth forests. However, they sustained significantly lower levels of EMF, with the lowest mean EMF observed in clear‐cut forests. Species richness was positively associated with EMF within all forest types, whereas the trait‐based predictors associated with EMF differed among forest types. Based on the structural equation models, the community‐weighted mean (CWM) of leaf area was the strongest predictor in old‐growth forests, potentially reflecting a greater contribution of selection‐related processes, whereas functional dispersion (FDis) was the strongest trait‐based predictor in selectively logged forests, suggesting a potential role of complementarity‐related processes. In clear‐cut forests, by contrast, neither CWM nor FDis was significantly associated with EMF, and species richness was the only significant predictor among the variables examined. Our study suggests that forests with different logging histories differ not only in EMF but also in the trait‐based predictors associated with it. These findings underscore the irreplaceable value of old‐growth forests and suggest that restoration assessments should integrate biodiversity, ecosystem multifunctionality and functional trait composition.