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Correlations between dominant vegetation type and composition and diversity of soil bacterial communities in a subtropical forest


Cui, Juyan (2023), Correlations between dominant vegetation type and composition and diversity of soil bacterial communities in a subtropical forest, Dryad, Dataset,


Single and mixed vegetation types have significant effects on soil parameters and the composition and diversity of soil bacterial communities. To understand the influence of different vegetation types on the structure of soil bacterial community across soil depth in a subtropical forest, we assessed the relative abundance of edaphic bacterial community and soil parameters, including pH, cation exchange capacity (CEC), and dissolved organic carbon (DOC) in Daiyun Mountain Nature Reserve in Fujian Province, southeastern China. The study area constitutes pine coniferous forest (CF) of pinus taiwanensis, broad-leaved forest (BF) of castanopsis fabri, and a mixed forest comprising CF and BF (MF). Quantitative PCR and Illumina sequencing of 16S rDNA were used to analyze the abundance, diversity, and composition of soil bacteria. The results showed that the pH, CEC and diversity of tree species are all associated with the composition of the bacterial community in the soil. It was found that CEC, soluble organic nitrogen (DON) and pH largely affected the structure of soil bacterial community in A horizon, whereas CEC, moisture content (MC) and organic phosphorus (OP) affected the structure of soil bacterial community in B horizon. We found that the dominant taxa in the CF and BF were Proteobacteria and Acidobacteria, respectively. The results of both mental and random forest (RF) analyses displayed groups according to vegetation types, indicating that the bacterial communities in the research site were significantly influenced by vegetation types in subtropical forests. The study highlights the ecological effects of forest management and elucidates the differences in the functional structure of soil bacterial communities under different vegetation types and soil depths.


The pH of the soil was measured using a glass electrode (Starter 300; Ohaus, USA). Samples were shaken for 30 min in a 1:2.5 soil: water solution (w/v), and soil moisture was assessed by oven drying until a constant mass was achieved. The ratio of soil carbon to nitrogen (C/N ratio) was determined using an elemental analyzer (Elementar Vario EL III; Elementar, Langenselbod, Germany). The soil suspension was first centrifuged at 4000 rpm for 10 minutes and filtered through Whatman 42 filter paper. Dissolved organic carbon (DOC) was determined using TOC-VCPH/CPN analyzer (Elementar Analysensystem GmbH, Germany) and exchangeable NH4+-N, NO3--N and soluble organic nitrogen (DON) were analyzed using a continuous flow analysis system (Skalar SAN++; Breda, Netherlands). Soil organic P (OP) was measured using cauterization by Carter et al. (2006). Soil cation exchange capacity (CEC) was determined using the ammonium acetate method (Fan et al., 2019). The data about micro 16s rDNA was sequenced on an Illumina HiSeq platform and 250-bp paired-end reads were generated by Novogeno Co., Ltd China.


Anhui Provincial Natural Science Foundation, Award: 2108085QC105

Natural Science Foundation of Fujian Province, Award: 2020J01397

Anhui Provincial WanJiang Scholarship, Award: 34000021120500 1000408