Characterization of Soil Bacterial Communities in Different Vegetation Types on the Lava Plateau of Jingpo Lake

Abstract

To explore the interactions within the vegetation-soil-microorganism continuum on the Jingpo Lake lava platform, five vegetation types-grassland (GL), shrubland (SL), deciduous broad-leaved forest (DB), coniferous and broad-leaved mixed forest (CB), and coniferous forest (CF)-were examined. Significant differences in the soil physical and chemical properties were identified among these types (p < 0.05). The soil bacterial community structures also varied significantly (p < 0.05), with Actinobacteriota, Proteobacteria, and Acidobacteria as the dominant phyla, exhibiting notable genus-level differences (p < 0.05). The soil organic matter (SOM), available nitrogen (AN), total nitrogen (TN), and soil water content (SWC) were significantly correlated with the bacterial community structure (p < 0.05 or p < 0.01), acting as key determinants of the microbial community structure and function. PICRUSt2 functional predictions revealed significant variations in the metabolic functions of the soil bacterial communities across vegetation types, indicating distinct functional specializations. In conclusion, the Jingpo Lake lava plateau harbors abundant bacterial resources. When devising vegetation adaptation strategies, it is essential to take into account variations in the rhizosphere soil bacteria across different vegetation types. Furthermore, prioritizing the implementation of forest vegetation is crucial in the adaptive management of the lava plateau. This approach holds significant implications for studying the bacterial diversity in the lava plateau and exploring the cultivation and application of functional bacteria in extreme environments.

Keywords: PICRUSt2 functional prediction; lava platform; rhizosphere bacterial community; soil physical and chemical properties.

Figure 1

Study area of Jingpo Lake World Geopark, Heilongjiang Province, China.

Figure 2

Different letters indicate significant differences at the 0.05 level; Soil bacterial community composition in different vegetation types: (a) community composition of bacterial phyla in different vegetation types; (b) horizontal distribution of bacterial phyla in different vegetation types; (c) community composition of bacterial genera in different vegetation types; and (d) horizontal distribution of bacterial genera in different vegetation types. (*** p < 0.001), (** p < 0.01), and (* p < 0.05) indicate significant differences in abundance among soil microorganisms in the five vegetation types according to the Wilcoxon signed-rank test.

Figure 3

Different letters indicate significant differences at the 0.05 level; Predictions of soil bacterial community function for different vegetation types based on the KEGG database (reflecting the top 10 species with a relative abundance greater than 1%).

Figure 4

Integrated analysis of soil–microbe correlations using a heatmap to show FDR-corrected correlations between bacterial phyla (rows) and soil properties (columns). Colored circles indicate Pearson’s r values (blue: negative, red: positive; scale shown). Symbols denote significance: * p < 0.05, **p < 0.01, ***p < 0.001.

Figure 5

RDA analysis of soil physico-chemical properties and bacterial community composition based on phylum level. Ordination diagram showing the effect of environmental variables (red line, red arrows) on the sample locations (circles). RDA triplot with environmental factors (red arrows), microbial communities (blue dots), and vegetation types (green labels). Statistical significance of RDA axes: Axis 1 (p = 0.003) and Axis 2 (p = 0.021) after FDR correction. Abbreviations: BD, bulk density; SWC, soil water content; SOM, soil organic matter.

Figure 6

Correlation between soil bacterial community diversity and physico-chemical properties in different vegetation types.

Figure 7

Correlation between soil bacterial community functions and soil physico-chemical properties in different vegetation types. Symbols denote significance: * p < 0.05, **p < 0.01.