Dongxing Li

Forest biomass accumulation is fundamental to ecosystem stability, material cycling, and energy flow, and pit lays a crucial role in the carbon cycle. Understanding the factors influencing aboveground biomass (AGB) is essential for exploring ecosystem functioning mechanisms, restoring degraded forests, and estimating carbon balance in forest communities. Tropical karst seasonal rainforests are species-rich and heterogeneous, yet the impact mechanisms of biotic and abiotic factors on AGB remain incompletely understood. Based on the survey data of a 15 ha monitoring plot in a karst seasonal rainforest in Southern China, this study explores the distribution characteristics of AGB and its intrinsic correlation with different influencing factors. The results show that the average AGB of the plot is 125.7 Mg/ha, with notable variations among habitats, peaking in hillside habitats. Trees with medium and large diameters at breast height (DBH ≥ 10 cm) account for 83.94% of the aboveground biomass (AGB) and are its primary contributors; dominant tree species exhibit higher AGB values. Both biotic and abiotic elements substantially influence AGB, with biotic factors exhibiting the largest influence. Among abiotic factors, topographic factors have a strong direct or indirect influence on AGB, while soil physicochemical properties have the smallest indirect impact. This research provides a comprehensive understanding of AGB distribution and its influencing factors in tropical karst forests (KFs), contributing to the management of carbon sinks in these ecosystems.

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.

Habenaria dentata has medicinal and ornamental value, but the number of wild populations is decreasing dramatically. Thus, conducting research on its genetic diversity and structure is necessary to provide a basis for its conservation. This study aimed to explore the genetic diversity of the wild plant H. dentata and protect and optimize its wild resources. The genetic diversity of 133 samples from six wild populations of H. dentata was analyzed using Inter Simple Sequence Repeat molecular markers to provide a scientific basis for the screening of improved germplasm resources. The results showed that the average number of alleles was 1.765, the average number of effective alleles was 1.424, the average Nei’s gene diversity index was 0.252, the average Shannon diversity index was 0.381, and the average percentage of polymorphic loci was 76.499%. The variation within the populations was 77.34%, and the variation between the populations was 22.66%. The gene flow was 1.705, which was greater than 1. The results of the cluster analysis showed that the six populations were mainly divided into four clusters and were not classified according to their geographical location. There was no significant correlation between the geographical location and genetic distance between the populations (r = 0.557, p > 0.05). The genetic diversity of H. dentata is high. Among the six wild populations, the genetic diversity of the Mulun population was the highest and this population can be used as a key protection unit. The study on the genetic diversity of H. dentata can not only reveal the reasons for the decrease in the number of individuals in the population to a certain extent, and put forward the protection strategy, but also provide a scientific basis for the breeding of excellent seed resources.

In order to explore the genetic diversity of the extremely small population wild plant Habenaria dentata and protect and optimize its wild resources. The genetic diversity of 133 samples from 6 wild populations of H.dentata was analyzed by ISSR molecular marker technique to provide a scientific basis for the screening of improved germplasm resources. The results show that the average number of alleles (Na) was 1.765, the average number of effective alleles (Ne) was 1.424, the average Nei 's gene diversity index (He) was 0.252, the average Shannon information diversity index (I) was 0.381, and the average percentage of polymorphic loci (PPL) was 76.499%. The variation within populations was 77.34%, and the variation between populations was 22.66%. Gene flow (Nm) was 1.705 8, greater than 1. The results of cluster analysis showed that the six populations were mainly divided into four branches and not classified according to geographical location. There was no significant correlation between geographical location and genetic distance between populations (r=0.557, P>0.05). The genetic diversity of H.dentata is high. Among the six wild populations, the genetic diversity of Mulun population is the highest and this population can be used as a key protection unit.