Structure complexity is the primary driver of functional diversity in the temperate forests of northeastern China

Background: Assessing functional diversity to identify its spatial patterns and drivers is an important step towards understanding the adaptive capacity of ecosystems to environmental change. However, until now, these mechanisms were poorly understood in the temperate forests of northeastern China, which prevented the development of new management methods aimed at increasing functional trait diversity and thus ecological resilience. Methods: In this study, we mapped functional diversity distributions using a Kriging Interpolation Method. A specific random forest model approach was adopted to test the importance ranking of 18 variables in explaining the spatial variation of functional diversity. Three piecewise structural equation models (pSEMs) with forest types as random effects were constructed for testing the direct effects of climate, and the indirect effects of stand structure on functional diversity across the large study region. Specific causal relationships in each forest type were also examined using 15 linear structural equation models. Results: Although environmental filtering by climate is important, stand structure explains most of the functional variation of the forest ecosystems in northeastern China. Our study thus only partially supports the stressdominance hypothesis. Several abundant species determine most of the functional diversity, which supports the mass ratio hypothesis. Conclusions: Our results suggest that forest management aimed at increasing structural complexity can contribute to increased functional diversity, especially regarding the mixing of coniferous and broad-leaved tree species.