Landform and lithospheric development contribute to the assembly of mountain floras in China.

Although it is well documented that mountains tend to exhibit high biodiversity, how geological processes affect the assemblage of montane floras is a matter of ongoing research. Here, we explore landform-specific differences among montane floras based on a dataset comprising 17,576 angiosperm species representing 140 Chinese mountain floras, which we define as the collection of all angiosperm species growing on a specific mountain. Our results show that igneous bedrock (granitic and karst-granitic landforms) is correlated with higher species richness and phylogenetic overdispersion, while the opposite is true for sedimentary bedrock (karst, Danxia, and desert landforms), which is correlated with phylogenetic clustering. Furthermore, we show that landform type was the primary determinant of the assembly of evolutionarily older species within floras, while climate was a greater determinant for younger species. Our study indicates that landform type not only affects montane species richness, but also contributes to the composition of montane floras. To explain the assembly and differentiation of mountain floras, we propose the 'floristic geo-lithology hypothesis', which highlights the role of bedrock and landform processes in montane floristic assembly and provides insights for future research on speciation, migration, and biodiversity in montane regions.

[HPLC fingerprint of liuwei dihuang soft capsule].

In order to establish HPLC fingerprint of Liuwei Dihuang soft capsule, and to provide certain reference for an quality control of it, the HPLC method was performed on an Agilent C18 (4.6 mm x 250 mm, 5 µm) column with acetonitrile-0.02% trifluoroacetic acid as mobile phase, gradient elution volume flow of 1.0 mL x min(-1), column temperature was 30 degrees C, detection wavelength: 0-60 min, 238 nm, 60-70 min, 210 nm. The software for chromatographic fingerprint was applied to analysis different batches of Liuwei Dihuang soft capsule samples. Sixteen mutual peaks were selected as the fingerprint peaks in 12 samples with loganin as the reference peak, and all of the detected peaks were separated effectively. Cluster analysis (HCA) and similarity analysis (SA) were done based on data of 12 samples clustering analysis of 12 batches of samples were divided into 2 categories. Including 7 for the first class, the rest was second, similarities calculated by SA were all above 0.92, indicating a good similarity between the reference and twelve batches of samples, also, the analysis results of HCA and SA basically the same. This method is simple with good precision, repeatability and stability, and provides the basis for Liuwei Dihuang soft capsule quality control.