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Soil bacterial communities of different natural forest types in Northeast China

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Abstract

Background and aims

The types of natural forests have long been suggested to shape below-ground microbial communities in forest ecosystem. However, detailed information on the impressionable bacterial groups and the potential mechanisms of these influences are still missing. The present study aims to deepen the current understanding on the soil microbial communities under four typical forest types in Northeast Asia, and to reveal the environmental factors driving the abundance, diversity and composition of soil bacterial communities.

Methods

Four forest types from Changbai Nature Reserve, representing mixed conifer-broadleaf forest and its natural secondary forest, evergreen coniferous forest, and deciduous coniferous forest were selected for this study. Namely, Broadleaf-Korean pine mixed forest (BLKP), secondary Poplar-Birch forest (PB), Spruce-Fir forest (SF), and Larch forest (LA), respectively. Soil bacterial community was analyzed using bar-coded pyrosequencing. Nonmetric multidimensional scaling (NMDS) was used to illustrate the clustering of different samples based on both Bray-Curtis distances and UniFrac distances. The relationship between environmental variables and the overall community structure was analyzed using the Mantel test.

Results

The two mixed conifer-broadleaf forests (BLKP and PB) displayed higher total soil nutrients (organic carbon, nitrogen, and phosphorus) and soil pH, but a lower C/N ratio as compared to the two coniferous forests (SF and LA). The mixed conifer-broadleaf forests had higher alpha-diversity and had distinct bacterial communities from the coniferous forests. Soil texture and pH were found as the principle factors for shaping soil bacterial diversity and community composition. The two mixed conifer-broadleaf forests were associated with higher proportion of Acidobacteria, Verrucomicrobia, Bacteroidetes, and Chloroflexi. While the SF and LA forests were dominated by Proteobacteria and Gemmatimonadetes.

Conclusions

Different natural forest type each selects for distinct microbial communities beneath them, with mixed conifer-broadleaf forests being associated with the low-activity bacterial groups, and the coniferous forests being dominated by the so-called high-activity members. The differentiation of soil bacterial communities in natural forests are presumably mediated by the differentiation in terms of soil properties, and could be partially explained by the copiotroph/oligotroph ecological classification model and non-random co-occurrence patterns.

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Acknowledgments

This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDB15010302), State Key Laboratory of Forest and Soil Ecology, Chinese Academy of Sciences (Grant No. LFSE2013-14) and State Key Laboratory of Genetic Resources and Evolution,Chinese Academy of Sciences (Grant No. GREKF12-12). We thank Prof. Larry Forney from Department of Biological Sciences, University of Idaho, USA for his kind review and valuable suggestions on the manuscript; our field crew from the Changbai Mountain National Station of Forest Ecosystem Observation and Research for their help collecting the soil cores; Dr. Suresh Iyer and the other researchers of the Institute for Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, USA for technical assistance with 454 pyrosequencing analysis; Dr. Hongbo He and Dr. Hongtu Xie from Institute of Applied Ecology, Chinese Academy of Sciences for helpful discussions.

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Authors and Affiliations

  1. State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110164, China

    Hui Li, Xugao Wang, Zhanqing Hao, Lisha Zhou & Yong Jiang

  2. State Key Laboratory of Genetic Resources and Evolution, Computational Biology and Medical Ecology Lab, Kunming Institute of Zoology,Chinese Academy of Sciences, Kunming, 650223, China

    Dandan Ye, Ping Dong & Zhanshan (Sam) Ma

  3. Institute for Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID, 83844, USA

    Matthew Lee Settles

  4. International Max Planck Research School for Evolutionary Biology, 24306, Plön, Germany

    Jun Wang

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  1. Hui Li
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  2. Dandan Ye
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  5. Jun Wang
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Correspondence to Zhanshan (Sam) Ma.

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Fig. S1

Rarefaction curves indicating the observed number of operational taxonomic units (OTUs) at a genetic distance of 3 % in each forest type (a) and individual soil sample (b) (DOC 246 kb)

Fig.S2

Non-metric multi-dimensional scaling (NMDS) plot of the bacterial communities based on weighted UniFrac index (DOC 78 kb)

Fig. S3

Composition of different phyla and sub-groups of Proteobacteria based on classification of partial 16S rRNA sequences of bacteria in soils from different forest types: (a) Alphaproteobacteria; (b) Gammaproteobacteria; (c) Verrucomicrobia; (d) Betaproteobacteria; (e) Acidobacteria (DOC 77.5 kb)

Fig. S4

Double hierarchal dendrogram (heatmap) to evaluate bacterial distribution of the top 101 abundant families among the 137 soil samples. Heatmap figure was drawn with R package pheatmap (Kolde R 2012). Clustering in the Y-axis is indicative of abundance, not phylogenetic similarity. The heatmap depicts the relative percentage of each bacteria (variables clustering on Y-axis) within each soil samples (X-axis clustering). The relative abundances for bacterial family are normalized and indicated by color intensity with the legend indicated at the top right corner. The heatmap demonstrates that each soil microenvironment supported a distinct bacterial community. The families affiliated with Alphaproteobacteria, representing by Bradyrhizobiaceae, an unclassified-Rhizobiales, Acetobacteraceae and Caulobacteraceae, were significantly predominant in coniferous forests (covered by red and orange color) compared with mixed conifer-broadleaf forests (mainly covered by blue color). The opposite is true for several subdivisions of Acidobacteria, with unclassified-Gp6, −Gp4, and -Gp7 exhibiting significant higher proportions in mixed conifer-broadleaf forests (shown by the coverage of red to orange color). The unclassified-Spartobacteria_genera_incertae_sedis was the second abundant families across all soil samples, and was significantly associated with mixed conifer-broadleaf forests. The less predominant families Chitinophagaceae (originated from Sphingobacteriales in Bacteroidetes) and an unclassified-Burkholderiales also showed a higher proportion in mixed conifer-broadleaf forests, while Gemmatimonadaceae (belongs to Gemmatimonadales) showed an opposite pattern. The distribution of the other dominant families did not vary significantly among different forest types (DOC 558 kb)

Table S1

Shown are significant (P < 0.05) Spearman’s rank correlation coefficients between soil edaphic factors (DOC 44.5 kb)

Table S2

Relative abundances of rare phyla (<4 % of all classified sequences). Significantly different (ANOVA, P < 0.05, Tukey’s HSD post-hoc analysis) groups are denoted with different letters (i.e., a, b) (DOC 40.5 kb)

Table S3

Relative abundances of taxonomic groups within the phylum Acidobacteria, Verrucomicrobia and within sub-groups of proteobacteria in the analyzed forest soils. Significantly different (ANOVA, P < 0.05, Tukey’s HSD post-hoc analysis) groups are denoted with different letters (i.e., a, b) (DOC 83.5 kb)

Table S4

Spearman’s rank correlations between the relative abundances of the most abundant sub-groups of Acidobacteria and the soil properties (environmental parameters) for the full forest soil samples (DOC 38.5 kb)

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Li, H., Ye, D., Wang, X. et al. Soil bacterial communities of different natural forest types in Northeast China. Plant Soil 383, 203–216 (2014). https://doi.org/10.1007/s11104-014-2165-y

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