Forest productivity (increment of above-ground biomass) is determined by biodiversity but also by stand structure attributes. However, the relative strengths of these drivers in determining productivity remain controversial in subtropical forests. In this study, we analyzed a tree growth data from 500 plots with in a 20 ha mature subtropical forest in eastern China. We used spatial simultaneous autoregressive error models to examine the effects of diversity variables (species richness, evenness, and composition), stand structural attributes (stand density, tree size range and diversity), environmental factors (topography and soil), and initial above-ground biomass (AGB) on productivity. We also applied structural equation models to quantify the relative importance of diversity, stand structure, environmental factors, and initial AGB in determining forest productivity. Our results showed that stand structure together with diversity and initial AGB governed forest productivity. Tree size diversity (DBH Shannon’s diversity index) had the largest positive effect on forest productivity. These results provide new evidence that structural explanatory variables have greater contributions to productivity for mature subtropical forests, strongly supporting the niche complementarity hypothesis. Our work highlights the importance of tree size diversity in promoting high forest productivity, and suggests that regulating and conserving complexity of forest stand structure should be among the most important goals in subtropical forest management.

Woody plants are crucial components of forest ecosystems and play critical roles in regulating community succession and ecosystem function. Studying woody plant diversity and its influencing factors is thus important for understanding and protecting forest ecosystems. Quercus aliena var. acutiserrata is an important deciduous broadleaf species in the warm–temperate forest of central China. Multiple regression and structural equation modelling were used to discuss the effect of biotic and soil factors on tree species diversity across seven relative density gradients of Q. aliena var. acutiserrata trees in this zone. Our results showed that the following: (1) Species diversity showed significant decreasing trends with increasing relative density of Q. aliena var. acutiserrata. (2) As the relative density of the oak tree increased, some biotic factors (canopy density, and mean DBH) and soil factors (Soil SOC, AP, and AK) all showed significantly increasing trends, whereas the DBH variation (CVD) and soil pH displayed decreasing trends. (3) Biotic factor (e.g., mean DBH, CVD, and competition interaction) had strong direct effect on species diversity, and soil factors exerted indirect roles on tree diversity via biotic factors. Our results provide insight into biodiversity protection and scientific management in this warm–temperate natural oak forest.

Net primary productivity (NPP) is a key indicator for assessing carbon fixation capacity. Understanding the mechanisms of carbon sequestration capacity of forest ecosystems is critical in the context of global climate change. Research on the influencing factors and driving mechanisms of NPP in forest areas of China is still insufficient, especially the lack of systematic analysis on the role of climate and phenology. Forest cover in China has been increasing in recent decades due to natural forest expansion and planted forests. It is significant to clarify the underlying drivers of the forest NPP in China. To address this issue, we collected annual NPP, biomass, phenology, temperature, and precipitation data in China from 2002 to 2021, then applied the general linear mixed effect model (GLMM) and Bayesian structural equation models to conduct a comprehensive analysis of the influencing factors of NPP. The results have shown that influencing factors all exert a significant positive influence on NPP through bivariate relationship analysis. The GLMM revealed that forest NPP was significantly positively affected by biomass, aridity index, temperature, and phenology. Among these, the aridity index (AI) (58.39%) and temperature (27.21%) were identified as having the highest contributions to NPP. The direct and indirect effects on NPP were evaluated using Bayesian structural equation models (SEMs), and the interactions between the factors and their comprehensive regulatory mechanisms on NPP were revealed. This study is crucial for understanding the impact of climate change on regulating forest carbon sequestration and providing strategies for effective forest management.

The mechanisms controlling plant growth are important to understand as they are key to forest carbon sequestration. Growth is species-specific and depends on mycorrhizal associations, resource availability, and neighbor competition. However, the difference in conspecific negative density dependence (CNDD) on growth between arbuscular mycorrhizal (AM) and ectomycorrhizal (EM) species across life stages needs exploration. Using data from a 20 ha warm temperate deciduous broad-leaved forest in Donglingshan, China, we measured growth of established individuals. Using linear mixed-effects models, we assessed the combined effects of neighbor density, soil factors, and light availability on growth across life stages and mycorrhizal types. We observed reduced growth with increasing conspecific density, but effects varied between AM and EM species and between saplings and trees. Conspecific neighbor density had stronger negative effects on AM than EM saplings. For mature trees, conspecific density had weaker negative effects on AM species and no significant effect on EM species. Additionally, soil factors promoted AM sapling growth, while light promoted EM sapling growth. For trees, light promoted growth in both AM and EM species, whereas soil factors inhibited EM tree growth. Conspecific crowding, light and soil act jointly on growth, with CNDD strength set by mycorrhizal type and life stage.