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In a community, due to the different characteristics of each species, their contributions to community beta diversity may vary. Quantifying the contribution of each species to overall beta diversity (SCBD) is essential for explaining the patterns of beta diversity. However, there is currently limited research linking SCBD with species functional traits, and how species functional traits influence SCBD remains unclear. This study is based on tree census data, species functional traits, and environmental variables from a 15 ha permanent monitoring plot in a tropical karst rainforest in south China. By calculating species-specific SCBD based on abundance and presence–absence data, as well as functional distinctiveness and species ecological niche characteristics (niche position and niche width), we applied structural equation modeling (SEM) to analyze how functional traits, distinctiveness, and niche characteristics jointly influence SCBD. The results revealed that SCBD based on abundance is positively correlated with occupancy and abundance, whereas SCBD based on presence–absence data exhibits a hump-shaped relationship with occupancy and abundance. Species ecological niche characteristics directly influence SCBD, with species occupying central ecological niches having a negative effect on SCBD and niche width having a positive effect. Functional traits and functional distinctiveness indirectly impact SCBD through their influence on species ecological niche characteristics. SEM models based on the presence–absence data provide higher explanatory power. In summary, in the seasonal rainforest communities of northern tropical karst regions in China, the combined effects of species’ functional traits, functional distinctiveness, and ecological niche characteristics determine SCBD. This not only contributes to a deeper understanding of how species traits influence β-diversity, making SCBD a more applicable tool for biodiversity conservation, but also allows for the development of more effective biodiversity protection strategies by elucidating the link between SCBD and ecosystem multifunctionality.

Lianas are a crucial component of karst seasonal rainforests, yet research on them has predominantly focused on non-karst regions. Consequently, their abundance and species richness remain relatively understudied within karst ecosystems. We aimed to document the abundance and species richness of lianas and investigate their relationships with abiotic and biotic factors, based on data from a fully mapped 15 ha plot in a karst seasonal rainforest of Nonggang (SW China). Structural equation models (SEMs) were employed to estimate the path coefficients and variation of dependent variables, enabling a comprehensive analysis of the factors affecting the abundance and species richness of liana. Within the 15 ha plot, a total of 23,819 lianas were identified, encompassing 113 species from 34 families. These lianas constituted 24.16% of the total woody plant density and 33.44% of the species present, but only 4.32% of the total woody plant basal area. Lianas are primarily influenced by abiotic factors, especially elevation and phosphorus (P), with less impact from biotic factors. Our findings reveal that lianas, despite constituting a relatively small percentage of the total woody plant basal area, significantly contribute to the density and diversity of the forest. Notably, abiotic factors such as elevation and phosphorus availability predominantly shape the distribution and richness of lianas, highlighting the importance of these environmental variables. The findings offer valuable insights for future liana studies and the preservation of karst forests’ biodiversity.

Rural agricultural activity generates cropland, secondary vegetation and straggling primary forest and can modify the soil seed bank (SSB), potentially impacting the restoration of preferred species. The interaction between vegetation and seed banks during the recovery process is dependent on management practices and recovery pathways. This study was carried out in Guilin of southwest China to assess the variation in plant diversity and species composition of both aboveground and soil seed banks across three typical vegetation types with different human interventions: orchard, bamboo shrub and primary forest. The results show that there were significant differences in the species composition and diversity of aboveground vegetation and SSB, as well as in soil properties among three typical vegetation types. The primary forest had the highest aboveground species diversity, while the orchard had the highest species diversity and seed density of SSB. In addition, principal component analysis (PCA) and canonical correspondence analyses (CCAs) showed that the species composition and plant life forms of the three typical vegetation types were significantly influenced by soil properties. Based on these findings, the characteristics of aboveground vegetation and the soil seed bank and their correlations with soil properties are expected to drastically change with human intervention. These results imply that unsustainable land use has greatly impacted soil properties, and consequently, the aboveground vegetation and SSB. Nevertheless, vegetation will recover quickly after farming is abandoned. The successful restoration of fragmented ecosystems requires the addition of seeds and seedlings of target species, especially perennial woody plants from the relevant natural ecosystems, to accelerate succession from bamboo shrub to forest.